action research conclusion

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Action Research: What it is, Stages & Examples

The best way to get things accomplished is to do it yourself. This statement is utilized in corporations, community projects, and national governments. These organizations are relying on action research to cope with their continuously changing and unstable environments as they function in a more interdependent world.

In practical educational contexts, this involves using systematic inquiry and reflective practice to address real-world challenges, improve teaching and learning, enhance student engagement, and drive positive changes within the educational system.

This post outlines the definition of action research, its stages, and some examples.

Content Index

What is action research?

Stages of action research, the steps to conducting action research, examples of action research, advantages and disadvantages of action research.

Action research is a strategy that tries to find realistic solutions to organizations’ difficulties and issues. It is similar to applied research.

Action research refers basically learning by doing. First, a problem is identified, then some actions are taken to address it, then how well the efforts worked are measured, and if the results are not satisfactory, the steps are applied again.

It can be put into three different groups:

• Positivist: This type of research is also called “classical action research.” It considers research a social experiment. This research is used to test theories in the actual world.
• Interpretive: This kind of research is called “contemporary action research.” It thinks that business reality is socially made, and when doing this research, it focuses on the details of local and organizational factors.
• Critical: This action research cycle takes a critical reflection approach to corporate systems and tries to enhance them.

All research is about learning new things. Collaborative action research contributes knowledge based on investigations in particular and frequently useful circumstances. It starts with identifying a problem. After that, the research process is followed by the below stages:

Stage 1: Plan

For an action research project to go well, the researcher needs to plan it well. After coming up with an educational research topic or question after a research study, the first step is to develop an action plan to guide the research process. The research design aims to address the study’s question. The research strategy outlines what to undertake, when, and how.

Stage 2: Act

The next step is implementing the plan and gathering data. At this point, the researcher must select how to collect and organize research data . The researcher also needs to examine all tools and equipment before collecting data to ensure they are relevant, valid, and comprehensive.

Stage 3: Observe

Data observation is vital to any investigation. The action researcher needs to review the project’s goals and expectations before data observation. This is the final step before drawing conclusions and taking action.

Different kinds of graphs, charts, and networks can be used to represent the data. It assists in making judgments or progressing to the next stage of observing.

Stage 4: Reflect

This step involves applying a prospective solution and observing the results. It’s essential to see if the possible solution found through research can really solve the problem being studied.

The researcher must explore alternative ideas when the action research project’s solutions fail to solve the problem.

Action research is a systematic approach researchers, educators, and practitioners use to identify and address problems or challenges within a specific context. It involves a cyclical process of planning, implementing, reflecting, and adjusting actions based on the data collected. Here are the general steps involved in conducting an action research process:

Identify the action research question or problem

Clearly define the issue or problem you want to address through your research. It should be specific, actionable, and relevant to your working context.

Review existing knowledge

Conduct a literature review to understand what research has already been done on the topic. This will help you gain insights, identify gaps, and inform your research design.

Plan the research

Develop a research plan outlining your study’s objectives, methods, data collection tools, and timeline. Determine the scope of your research and the participants or stakeholders involved.

Collect data

Implement your research plan by collecting relevant data. This can involve various methods such as surveys, interviews, observations, document analysis, or focus groups. Ensure that your data collection methods align with your research objectives and allow you to gather the necessary information.

Analyze the data

Once you have collected the data, analyze it using appropriate qualitative or quantitative techniques. Look for patterns, themes, or trends in the data that can help you understand the problem better.

Reflect on the findings

Reflect on the analyzed data and interpret the results in the context of your research question. Consider the implications and possible solutions that emerge from the data analysis. This reflection phase is crucial for generating insights and understanding the underlying factors contributing to the problem.

Develop an action plan

Based on your analysis and reflection, develop an action plan that outlines the steps you will take to address the identified problem. The plan should be specific, measurable, achievable, relevant, and time-bound (SMART goals). Consider involving relevant stakeholders in planning to ensure their buy-in and support.

Implement the action plan

Put your action plan into practice by implementing the identified strategies or interventions. This may involve making changes to existing practices, introducing new approaches, or testing alternative solutions. Document the implementation process and any modifications made along the way.

Evaluate and monitor progress

Continuously monitor and evaluate the impact of your actions. Collect additional data, assess the effectiveness of the interventions, and measure progress towards your goals. This evaluation will help you determine if your actions have the desired effects and inform any necessary adjustments.

Reflect and iterate

Reflect on the outcomes of your actions and the evaluation results. Consider what worked well, what did not, and why. Use this information to refine your approach, make necessary adjustments, and plan for the next cycle of action research if needed.

Remember that participatory action research is an iterative process, and multiple cycles may be required to achieve significant improvements or solutions to the identified problem. Each cycle builds on the insights gained from the previous one, fostering continuous learning and improvement.

Explore Insightfully Contextual Inquiry in Qualitative Research

Here are two real-life examples of action research.

Action research initiatives are frequently situation-specific. Still, other researchers can adapt the techniques. The example is from a researcher’s (Franklin, 1994) report about a project encouraging nature tourism in the Caribbean.

In 1991, this was launched to study how nature tourism may be implemented on the four Windward Islands in the Caribbean: St. Lucia, Grenada, Dominica, and St. Vincent.

For environmental protection, a government-led action study determined that the consultation process needs to involve numerous stakeholders, including commercial enterprises.

First, two researchers undertook the study and held search conferences on each island. The search conferences resulted in suggestions and action plans for local community nature tourism sub-projects.

Several islands formed advisory groups and launched national awareness and community projects. Regional project meetings were held to discuss experiences, self-evaluations, and strategies. Creating a documentary about a local initiative helped build community. And the study was a success, leading to a number of changes in the area.

Lau and Hayward (1997) employed action research to analyze Internet-based collaborative work groups.

Over two years, the researchers facilitated three action research problem -solving cycles with 15 teachers, project personnel, and 25 health practitioners from diverse areas. The goal was to see how Internet-based communications might affect their virtual workgroup.

First, expectations were defined, technology was provided, and a bespoke workgroup system was developed. Participants suggested shorter, more dispersed training sessions with project-specific instructions.

The second phase saw the system’s complete deployment. The final cycle witnessed system stability and virtual group formation. The key lesson was that the learning curve was poorly misjudged, with frustrations only marginally met by phone-based technical help. According to the researchers, the absence of high-quality online material about community healthcare was harmful.

Role clarity, connection building, knowledge sharing, resource assistance, and experiential learning are vital for virtual group growth. More study is required on how group support systems might assist groups in engaging with their external environment and boost group members’ learning. 

Action research has both good and bad points.

• It is very flexible, so researchers can change their analyses to fit their needs and make individual changes.
• It offers a quick and easy way to solve problems that have been going on for a long time instead of complicated, long-term solutions based on complex facts.
• If It is done right, it can be very powerful because it can lead to social change and give people the tools to make that change in ways that are important to their communities.

Disadvantages

• These studies have a hard time being generalized and are hard to repeat because they are so flexible. Because the researcher has the power to draw conclusions, they are often not thought to be theoretically sound.
• Setting up an action study in an ethical way can be hard. People may feel like they have to take part or take part in a certain way.
• It is prone to research errors like selection bias , social desirability bias, and other cognitive biases.

LEARN ABOUT: Self-Selection Bias

This post discusses how action research generates knowledge, its steps, and real-life examples. It is very applicable to the field of research and has a high level of relevance. We can only state that the purpose of this research is to comprehend an issue and find a solution to it.

At QuestionPro, we give researchers tools for collecting data, like our survey software, and a library of insights for any long-term study. Go to the Insight Hub if you want to see a demo or learn more about it.

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Frequently Asked Questions(FAQ’s)

Action research is a systematic approach to inquiry that involves identifying a problem or challenge in a practical context, implementing interventions or changes, collecting and analyzing data, and using the findings to inform decision-making and drive positive change.

Action research can be conducted by various individuals or groups, including teachers, administrators, researchers, and educational practitioners. It is often carried out by those directly involved in the educational setting where the research takes place.

The steps of action research typically include identifying a problem, reviewing relevant literature, designing interventions or changes, collecting and analyzing data, reflecting on findings, and implementing improvements based on the results.

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How to Write a Conclusion for Research Papers (with Examples)

The conclusion of a research paper is a crucial section that plays a significant role in the overall impact and effectiveness of your research paper. However, this is also the section that typically receives less attention compared to the introduction and the body of the paper. The conclusion serves to provide a concise summary of the key findings, their significance, their implications, and a sense of closure to the study. Discussing how can the findings be applied in real-world scenarios or inform policy, practice, or decision-making is especially valuable to practitioners and policymakers. The research paper conclusion also provides researchers with clear insights and valuable information for their own work, which they can then build on and contribute to the advancement of knowledge in the field.

The research paper conclusion should explain the significance of your findings within the broader context of your field. It restates how your results contribute to the existing body of knowledge and whether they confirm or challenge existing theories or hypotheses. Also, by identifying unanswered questions or areas requiring further investigation, your awareness of the broader research landscape can be demonstrated.

Remember to tailor the research paper conclusion to the specific needs and interests of your intended audience, which may include researchers, practitioners, policymakers, or a combination of these.

Table of Contents

What is a conclusion in a research paper, summarizing conclusion, editorial conclusion, externalizing conclusion, importance of a good research paper conclusion, how to write a conclusion for your research paper, research paper conclusion examples.

• How to write a research paper conclusion with Paperpal? 

Frequently Asked Questions

A conclusion in a research paper is the final section where you summarize and wrap up your research, presenting the key findings and insights derived from your study. The research paper conclusion is not the place to introduce new information or data that was not discussed in the main body of the paper. When working on how to conclude a research paper, remember to stick to summarizing and interpreting existing content. The research paper conclusion serves the following purposes: 1

• Warn readers of the possible consequences of not attending to the problem.
• Recommend specific course(s) of action.
• Restate key ideas to drive home the ultimate point of your research paper.
• Provide a “take-home” message that you want the readers to remember about your study.

Types of conclusions for research papers

In research papers, the conclusion provides closure to the reader. The type of research paper conclusion you choose depends on the nature of your study, your goals, and your target audience. I provide you with three common types of conclusions:

A summarizing conclusion is the most common type of conclusion in research papers. It involves summarizing the main points, reiterating the research question, and restating the significance of the findings. This common type of research paper conclusion is used across different disciplines.

An editorial conclusion is less common but can be used in research papers that are focused on proposing or advocating for a particular viewpoint or policy. It involves presenting a strong editorial or opinion based on the research findings and offering recommendations or calls to action.

An externalizing conclusion is a type of conclusion that extends the research beyond the scope of the paper by suggesting potential future research directions or discussing the broader implications of the findings. This type of conclusion is often used in more theoretical or exploratory research papers.

Align your conclusion’s tone with the rest of your research paper. Start Writing with Paperpal Now!  

The conclusion in a research paper serves several important purposes:

• Offers Implications and Recommendations : Your research paper conclusion is an excellent place to discuss the broader implications of your research and suggest potential areas for further study. It’s also an opportunity to offer practical recommendations based on your findings.
• Provides Closure : A good research paper conclusion provides a sense of closure to your paper. It should leave the reader with a feeling that they have reached the end of a well-structured and thought-provoking research project.
• Leaves a Lasting Impression : Writing a well-crafted research paper conclusion leaves a lasting impression on your readers. It’s your final opportunity to leave them with a new idea, a call to action, or a memorable quote.

Writing a strong conclusion for your research paper is essential to leave a lasting impression on your readers. Here’s a step-by-step process to help you create and know what to put in the conclusion of a research paper: 2

• Research Statement : Begin your research paper conclusion by restating your research statement. This reminds the reader of the main point you’ve been trying to prove throughout your paper. Keep it concise and clear.
• Key Points : Summarize the main arguments and key points you’ve made in your paper. Avoid introducing new information in the research paper conclusion. Instead, provide a concise overview of what you’ve discussed in the body of your paper.
• Address the Research Questions : If your research paper is based on specific research questions or hypotheses, briefly address whether you’ve answered them or achieved your research goals. Discuss the significance of your findings in this context.
• Significance : Highlight the importance of your research and its relevance in the broader context. Explain why your findings matter and how they contribute to the existing knowledge in your field.
• Implications : Explore the practical or theoretical implications of your research. How might your findings impact future research, policy, or real-world applications? Consider the “so what?” question.
• Future Research : Offer suggestions for future research in your area. What questions or aspects remain unanswered or warrant further investigation? This shows that your work opens the door for future exploration.
• Closing Thought : Conclude your research paper conclusion with a thought-provoking or memorable statement. This can leave a lasting impression on your readers and wrap up your paper effectively. Avoid introducing new information or arguments here.
• Proofread and Revise : Carefully proofread your conclusion for grammar, spelling, and clarity. Ensure that your ideas flow smoothly and that your conclusion is coherent and well-structured.

Write your research paper conclusion 2x faster with Paperpal. Try it now!

Remember that a well-crafted research paper conclusion is a reflection of the strength of your research and your ability to communicate its significance effectively. It should leave a lasting impression on your readers and tie together all the threads of your paper. Now you know how to start the conclusion of a research paper and what elements to include to make it impactful, let’s look at a research paper conclusion sample.

How to write a research paper conclusion with Paperpal?

A research paper conclusion is not just a summary of your study, but a synthesis of the key findings that ties the research together and places it in a broader context. A research paper conclusion should be concise, typically around one paragraph in length. However, some complex topics may require a longer conclusion to ensure the reader is left with a clear understanding of the study’s significance. Paperpal, an AI writing assistant trusted by over 800,000 academics globally, can help you write a well-structured conclusion for your research paper. 

• Sign Up or Log In: Create a new Paperpal account or login with your details.  
• Navigate to Features : Once logged in, head over to the features’ side navigation pane. Click on Templates and you’ll find a suite of generative AI features to help you write better, faster.  
• Generate an outline: Under Templates, select ‘Outlines’. Choose ‘Research article’ as your document type.  
• Select your section: Since you’re focusing on the conclusion, select this section when prompted.  
• Choose your field of study: Identifying your field of study allows Paperpal to provide more targeted suggestions, ensuring the relevance of your conclusion to your specific area of research. 
• Provide a brief description of your study: Enter details about your research topic and findings. This information helps Paperpal generate a tailored outline that aligns with your paper’s content. 
• Generate the conclusion outline: After entering all necessary details, click on ‘generate’. Paperpal will then create a structured outline for your conclusion, to help you start writing and build upon the outline.  
• Write your conclusion: Use the generated outline to build your conclusion. The outline serves as a guide, ensuring you cover all critical aspects of a strong conclusion, from summarizing key findings to highlighting the research’s implications. 
• Refine and enhance: Paperpal’s ‘Make Academic’ feature can be particularly useful in the final stages. Select any paragraph of your conclusion and use this feature to elevate the academic tone, ensuring your writing is aligned to the academic journal standards. 

By following these steps, Paperpal not only simplifies the process of writing a research paper conclusion but also ensures it is impactful, concise, and aligned with academic standards. Sign up with Paperpal today and write your research paper conclusion 2x faster .  

The research paper conclusion is a crucial part of your paper as it provides the final opportunity to leave a strong impression on your readers. In the research paper conclusion, summarize the main points of your research paper by restating your research statement, highlighting the most important findings, addressing the research questions or objectives, explaining the broader context of the study, discussing the significance of your findings, providing recommendations if applicable, and emphasizing the takeaway message. The main purpose of the conclusion is to remind the reader of the main point or argument of your paper and to provide a clear and concise summary of the key findings and their implications. All these elements should feature on your list of what to put in the conclusion of a research paper to create a strong final statement for your work.

A strong conclusion is a critical component of a research paper, as it provides an opportunity to wrap up your arguments, reiterate your main points, and leave a lasting impression on your readers. Here are the key elements of a strong research paper conclusion: 1. Conciseness : A research paper conclusion should be concise and to the point. It should not introduce new information or ideas that were not discussed in the body of the paper. 2. Summarization : The research paper conclusion should be comprehensive enough to give the reader a clear understanding of the research’s main contributions. 3 . Relevance : Ensure that the information included in the research paper conclusion is directly relevant to the research paper’s main topic and objectives; avoid unnecessary details. 4 . Connection to the Introduction : A well-structured research paper conclusion often revisits the key points made in the introduction and shows how the research has addressed the initial questions or objectives. 5. Emphasis : Highlight the significance and implications of your research. Why is your study important? What are the broader implications or applications of your findings? 6 . Call to Action : Include a call to action or a recommendation for future research or action based on your findings.

The length of a research paper conclusion can vary depending on several factors, including the overall length of the paper, the complexity of the research, and the specific journal requirements. While there is no strict rule for the length of a conclusion, but it’s generally advisable to keep it relatively short. A typical research paper conclusion might be around 5-10% of the paper’s total length. For example, if your paper is 10 pages long, the conclusion might be roughly half a page to one page in length.

In general, you do not need to include citations in the research paper conclusion. Citations are typically reserved for the body of the paper to support your arguments and provide evidence for your claims. However, there may be some exceptions to this rule: 1. If you are drawing a direct quote or paraphrasing a specific source in your research paper conclusion, you should include a citation to give proper credit to the original author. 2. If your conclusion refers to or discusses specific research, data, or sources that are crucial to the overall argument, citations can be included to reinforce your conclusion’s validity.

The conclusion of a research paper serves several important purposes: 1. Summarize the Key Points 2. Reinforce the Main Argument 3. Provide Closure 4. Offer Insights or Implications 5. Engage the Reader. 6. Reflect on Limitations

Remember that the primary purpose of the research paper conclusion is to leave a lasting impression on the reader, reinforcing the key points and providing closure to your research. It’s often the last part of the paper that the reader will see, so it should be strong and well-crafted.

• Makar, G., Foltz, C., Lendner, M., & Vaccaro, A. R. (2018). How to write effective discussion and conclusion sections. Clinical spine surgery, 31(8), 345-346.
• Bunton, D. (2005). The structure of PhD conclusion chapters.  Journal of English for academic purposes ,  4 (3), 207-224.

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education, community-building and change

What is action research and how do we do it?

In this article, we explore the development of some different traditions of action research and provide an introductory guide to the literature.

Contents : what is action research ·  origins · the decline and rediscovery of action research · undertaking action research · conclusion · further reading · how to cite this article . see, also: research for practice ., what is action research.

In the literature, discussion of action research tends to fall into two distinctive camps. The British tradition – especially that linked to education – tends to view action research as research-oriented toward the enhancement of direct practice. For example, Carr and Kemmis provide a classic definition:

Action research is simply a form of self-reflective enquiry undertaken by participants in social situations in order to improve the rationality and justice of their own practices, their understanding of these practices, and the situations in which the practices are carried out (Carr and Kemmis 1986: 162).

Many people are drawn to this understanding of action research because it is firmly located in the realm of the practitioner – it is tied to self-reflection. As a way of working it is very close to the notion of reflective practice coined by Donald Schön (1983).

The second tradition, perhaps more widely approached within the social welfare field – and most certainly the broader understanding in the USA is of action research as ‘the systematic collection of information that is designed to bring about social change’ (Bogdan and Biklen 1992: 223). Bogdan and Biklen continue by saying that its practitioners marshal evidence or data to expose unjust practices or environmental dangers and recommend actions for change. In many respects, for them, it is linked into traditions of citizen’s action and community organizing. The practitioner is actively involved in the cause for which the research is conducted. For others, it is such commitment is a necessary part of being a practitioner or member of a community of practice. Thus, various projects designed to enhance practice within youth work, for example, such as the detached work reported on by Goetschius and Tash (1967) could be talked of as action research.

Kurt Lewin is generally credited as the person who coined the term ‘action research’:

The research needed for social practice can best be characterized as research for social management or social engineering. It is a type of action-research, a comparative research on the conditions and effects of various forms of social action, and research leading to social action. Research that produces nothing but books will not suffice (Lewin 1946, reproduced in Lewin 1948: 202-3)

His approach involves a spiral of steps, ‘each of which is composed of a circle of planning, action and fact-finding about the result of the action’ ( ibid. : 206). The basic cycle involves the following:

This is how Lewin describes the initial cycle:

The first step then is to examine the idea carefully in the light of the means available. Frequently more fact-finding about the situation is required. If this first period of planning is successful, two items emerge: namely, “an overall plan” of how to reach the objective and secondly, a decision in regard to the first step of action. Usually this planning has also somewhat modified the original idea. ( ibid. : 205)

The next step is ‘composed of a circle of planning, executing, and reconnaissance or fact-finding for the purpose of evaluating the results of the second step, and preparing the rational basis for planning the third step, and for perhaps modifying again the overall plan’ ( ibid. : 206). What we can see here is an approach to research that is oriented to problem-solving in social and organizational settings, and that has a form that parallels Dewey’s conception of learning from experience.

The approach, as presented, does take a fairly sequential form – and it is open to a literal interpretation. Following it can lead to practice that is ‘correct’ rather than ‘good’ – as we will see. It can also be argued that the model itself places insufficient emphasis on analysis at key points. Elliott (1991: 70), for example, believed that the basic model allows those who use it to assume that the ‘general idea’ can be fixed in advance, ‘that “reconnaissance” is merely fact-finding, and that “implementation” is a fairly straightforward process’. As might be expected there was some questioning as to whether this was ‘real’ research. There were questions around action research’s partisan nature – the fact that it served particular causes.

The decline and rediscovery of action research

Action research did suffer a decline in favour during the 1960s because of its association with radical political activism (Stringer 2007: 9). There were, and are, questions concerning its rigour, and the training of those undertaking it. However, as Bogdan and Biklen (1992: 223) point out, research is a frame of mind – ‘a perspective that people take toward objects and activities’. Once we have satisfied ourselves that the collection of information is systematic and that any interpretations made have a proper regard for satisfying truth claims, then much of the critique aimed at action research disappears. In some of Lewin’s earlier work on action research (e.g. Lewin and Grabbe 1945), there was a tension between providing a rational basis for change through research, and the recognition that individuals are constrained in their ability to change by their cultural and social perceptions, and the systems of which they are a part. Having ‘correct knowledge’ does not of itself lead to change, attention also needs to be paid to the ‘matrix of cultural and psychic forces’ through which the subject is constituted (Winter 1987: 48).

Subsequently, action research has gained a significant foothold both within the realm of community-based, and participatory action research; and as a form of practice-oriented to the improvement of educative encounters (e.g. Carr and Kemmis 1986).

Exhibit 1: Stringer on community-based action research

A fundamental premise of community-based action research is that it commences with an interest in the problems of a group, a community, or an organization. Its purpose is to assist people in extending their understanding of their situation and thus resolving problems that confront them….

Community-based action research is always enacted through an explicit set of social values. In modern, democratic social contexts, it is seen as a process of inquiry that has the following characteristics:

• It is democratic , enabling the participation of all people.

• It is equitable , acknowledging people’s equality of worth.

• It is liberating , providing freedom from oppressive, debilitating conditions.

• It is life enhancing , enabling the expression of people’s full human potential.

(Stringer 1999: 9-10)

Undertaking action research

As Thomas (2017: 154) put it, the central aim is change, ‘and the emphasis is on problem-solving in whatever way is appropriate’. It can be seen as a conversation rather more than a technique (McNiff et. al. ). It is about people ‘thinking for themselves and making their own choices, asking themselves what they should do and accepting the consequences of their own actions’ (Thomas 2009: 113).

The action research process works through three basic phases:

Look -building a picture and gathering information. When evaluating we define and describe the problem to be investigated and the context in which it is set. We also describe what all the participants (educators, group members, managers etc.) have been doing.

Think – interpreting and explaining. When evaluating we analyse and interpret the situation. We reflect on what participants have been doing. We look at areas of success and any deficiencies, issues or problems.

Act – resolving issues and problems. In evaluation we judge the worth, effectiveness, appropriateness, and outcomes of those activities. We act to formulate solutions to any problems. (Stringer 1999: 18; 43-44;160)

The use of action research to deepen and develop classroom practice has grown into a strong tradition of practice (one of the first examples being the work of Stephen Corey in 1949). For some, there is an insistence that action research must be collaborative and entail groupwork.

Action research is a form of collective self-reflective enquiry undertaken by participants in social situations in order to improve the rationality and justice of their own social or educational practices, as well as their understanding of those practices and the situations in which the practices are carried out… The approach is only action research when it is collaborative, though it is important to realise that action research of the group is achieved through the critically examined action of individual group members. (Kemmis and McTaggart 1988: 5-6)

Just why it must be collective is open to some question and debate (Webb 1996), but there is an important point here concerning the commitments and orientations of those involved in action research.

One of the legacies Kurt Lewin left us is the ‘action research spiral’ – and with it there is the danger that action research becomes little more than a procedure. It is a mistake, according to McTaggart (1996: 248) to think that following the action research spiral constitutes ‘doing action research’. He continues, ‘Action research is not a ‘method’ or a ‘procedure’ for research but a series of commitments to observe and problematize through practice a series of principles for conducting social enquiry’. It is his argument that Lewin has been misunderstood or, rather, misused. When set in historical context, while Lewin does talk about action research as a method, he is stressing a contrast between this form of interpretative practice and more traditional empirical-analytic research. The notion of a spiral may be a useful teaching device – but it is all too easy to slip into using it as the template for practice (McTaggart 1996: 249).

Further reading

This select, annotated bibliography has been designed to give a flavour of the possibilities of action research and includes some useful guides to practice. As ever, if you have suggestions about areas or specific texts for inclusion, I’d like to hear from you.

Explorations of action research

Atweh, B., Kemmis, S. and Weeks, P. (eds.) (1998) Action Research in Practice: Partnership for Social Justice in Education, London: Routledge. Presents a collection of stories from action research projects in schools and a university. The book begins with theme chapters discussing action research, social justice and partnerships in research. The case study chapters cover topics such as: school environment – how to make a school a healthier place to be; parents – how to involve them more in decision-making; students as action researchers; gender – how to promote gender equity in schools; writing up action research projects.

Carr, W. and Kemmis, S. (1986) Becoming Critical. Education, knowledge and action research , Lewes: Falmer. Influential book that provides a good account of ‘action research’ in education. Chapters on teachers, researchers and curriculum; the natural scientific view of educational theory and practice; the interpretative view of educational theory and practice; theory and practice – redefining the problem; a critical approach to theory and practice; towards a critical educational science; action research as critical education science; educational research, educational reform and the role of the profession.

Carson, T. R. and Sumara, D. J. (ed.) (1997) Action Research as a Living Practice , New York: Peter Lang. 140 pages. Book draws on a wide range of sources to develop an understanding of action research. Explores action research as a lived practice, ‘that asks the researcher to not only investigate the subject at hand but, as well, to provide some account of the way in which the investigation both shapes and is shaped by the investigator.

Dadds, M. (1995) Passionate Enquiry and School Development. A story about action research , London: Falmer. 192 + ix pages. Examines three action research studies undertaken by a teacher and how they related to work in school – how she did the research, the problems she experienced, her feelings, the impact on her feelings and ideas, and some of the outcomes. In his introduction, John Elliot comments that the book is ‘the most readable, thoughtful, and detailed study of the potential of action-research in professional education that I have read’.

Ghaye, T. and Wakefield, P. (eds.) CARN Critical Conversations. Book one: the role of the self in action , Bournemouth: Hyde Publications. 146 + xiii pages. Collection of five pieces from the Classroom Action Research Network. Chapters on: dialectical forms; graduate medical education – research’s outer limits; democratic education; managing action research; writing up.

McNiff, J. (1993) Teaching as Learning: An Action Research Approach , London: Routledge. Argues that educational knowledge is created by individual teachers as they attempt to express their own values in their professional lives. Sets out familiar action research model: identifying a problem, devising, implementing and evaluating a solution and modifying practice. Includes advice on how working in this way can aid the professional development of action researcher and practitioner.

Quigley, B. A. and Kuhne, G. W. (eds.) (1997) Creating Practical Knowledge Through Action Research, San Fransisco: Jossey Bass. Guide to action research that outlines the action research process, provides a project planner, and presents examples to show how action research can yield improvements in six different settings, including a hospital, a university and a literacy education program.

Plummer, G. and Edwards, G. (eds.) CARN Critical Conversations. Book two: dimensions of action research – people, practice and power , Bournemouth: Hyde Publications. 142 + xvii pages. Collection of five pieces from the Classroom Action Research Network. Chapters on: exchanging letters and collaborative research; diary writing; personal and professional learning – on teaching and self-knowledge; anti-racist approaches; psychodynamic group theory in action research.

Whyte, W. F. (ed.) (1991) Participatory Action Research , Newbury Park: Sage. 247 pages. Chapters explore the development of participatory action research and its relation with action science and examine its usages in various agricultural and industrial settings

Zuber-Skerritt, O. (ed.) (1996) New Directions in Action Research , London; Falmer Press. 266 + xii pages. A useful collection that explores principles and procedures for critical action research; problems and suggested solutions; and postmodernism and critical action research.

Action research guides

Coghlan, D. and Brannick, D. (2000) Doing Action Research in your own Organization, London: Sage. 128 pages. Popular introduction. Part one covers the basics of action research including the action research cycle, the role of the ‘insider’ action researcher and the complexities of undertaking action research within your own organisation. Part two looks at the implementation of the action research project (including managing internal politics and the ethics and politics of action research). New edition due late 2004.

Elliot, J. (1991) Action Research for Educational Change , Buckingham: Open University Press. 163 + x pages Collection of various articles written by Elliot in which he develops his own particular interpretation of action research as a form of teacher professional development. In some ways close to a form of ‘reflective practice’. Chapter 6, ‘A practical guide to action research’ – builds a staged model on Lewin’s work and on developments by writers such as Kemmis.

Johnson, A. P. (2007) A short guide to action research 3e. Allyn and Bacon. Popular step by step guide for master’s work.

Macintyre, C. (2002) The Art of the Action Research in the Classroom , London: David Fulton. 138 pages. Includes sections on action research, the role of literature, formulating a research question, gathering data, analysing data and writing a dissertation. Useful and readable guide for students.

McNiff, J., Whitehead, J., Lomax, P. (2003) You and Your Action Research Project , London: Routledge. Practical guidance on doing an action research project.Takes the practitioner-researcher through the various stages of a project. Each section of the book is supported by case studies

Stringer, E. T. (2007) Action Research: A handbook for practitioners 3e , Newbury Park, ca.: Sage. 304 pages. Sets community-based action research in context and develops a model. Chapters on information gathering, interpretation, resolving issues; legitimacy etc. See, also Stringer’s (2003) Action Research in Education , Prentice-Hall.

Winter, R. (1989) Learning From Experience. Principles and practice in action research , Lewes: Falmer Press. 200 + 10 pages. Introduces the idea of action research; the basic process; theoretical issues; and provides six principles for the conduct of action research. Includes examples of action research. Further chapters on from principles to practice; the learner’s experience; and research topics and personal interests.

Action research in informal education

Usher, R., Bryant, I. and Johnston, R. (1997) Adult Education and the Postmodern Challenge. Learning beyond the limits , London: Routledge. 248 + xvi pages. Has some interesting chapters that relate to action research: on reflective practice; changing paradigms and traditions of research; new approaches to research; writing and learning about research.

Other references

Bogdan, R. and Biklen, S. K. (1992) Qualitative Research For Education , Boston: Allyn and Bacon.

Goetschius, G. and Tash, J. (1967) Working with the Unattached , London: Routledge and Kegan Paul.

McTaggart, R. (1996) ‘Issues for participatory action researchers’ in O. Zuber-Skerritt (ed.) New Directions in Action Research , London: Falmer Press.

McNiff, J., Lomax, P. and Whitehead, J. (2003) You and Your Action Research Project 2e. London: Routledge.

Thomas, G. (2017). How to do your Research Project. A guide for students in education and applied social sciences . 3e. London: Sage.

Acknowledgements : spiral by Michèle C. | flickr ccbyncnd2 licence

How to cite this article : Smith, M. K. (1996; 2001, 2007, 2017) What is action research and how do we do it?’, The encyclopedia of pedagogy and informal education. [ https://infed.org/mobi/action-research/ . Retrieved: insert date] .

© Mark K. Smith 1996; 2001, 2007, 2017

Last Updated on December 7, 2020 by infed.org

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Writing a Research Paper Conclusion | Step-by-Step Guide

Published on October 30, 2022 by Jack Caulfield . Revised on April 13, 2023.

• Restate the problem statement addressed in the paper
• Summarize your overall arguments or findings
• Suggest the key takeaways from your paper

The content of the conclusion varies depending on whether your paper presents the results of original empirical research or constructs an argument through engagement with sources .

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Table of contents

Step 1: restate the problem, step 2: sum up the paper, step 3: discuss the implications, research paper conclusion examples, frequently asked questions about research paper conclusions.

The first task of your conclusion is to remind the reader of your research problem . You will have discussed this problem in depth throughout the body, but now the point is to zoom back out from the details to the bigger picture.

While you are restating a problem you’ve already introduced, you should avoid phrasing it identically to how it appeared in the introduction . Ideally, you’ll find a novel way to circle back to the problem from the more detailed ideas discussed in the body.

For example, an argumentative paper advocating new measures to reduce the environmental impact of agriculture might restate its problem as follows:

Meanwhile, an empirical paper studying the relationship of Instagram use with body image issues might present its problem like this:

“In conclusion …”

Avoid starting your conclusion with phrases like “In conclusion” or “To conclude,” as this can come across as too obvious and make your writing seem unsophisticated. The content and placement of your conclusion should make its function clear without the need for additional signposting.

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Having zoomed back in on the problem, it’s time to summarize how the body of the paper went about addressing it, and what conclusions this approach led to.

Depending on the nature of your research paper, this might mean restating your thesis and arguments, or summarizing your overall findings.

Argumentative paper: Restate your thesis and arguments

In an argumentative paper, you will have presented a thesis statement in your introduction, expressing the overall claim your paper argues for. In the conclusion, you should restate the thesis and show how it has been developed through the body of the paper.

Briefly summarize the key arguments made in the body, showing how each of them contributes to proving your thesis. You may also mention any counterarguments you addressed, emphasizing why your thesis holds up against them, particularly if your argument is a controversial one.

Don’t go into the details of your evidence or present new ideas; focus on outlining in broad strokes the argument you have made.

Empirical paper: Summarize your findings

In an empirical paper, this is the time to summarize your key findings. Don’t go into great detail here (you will have presented your in-depth results and discussion already), but do clearly express the answers to the research questions you investigated.

Describe your main findings, even if they weren’t necessarily the ones you expected or hoped for, and explain the overall conclusion they led you to.

Having summed up your key arguments or findings, the conclusion ends by considering the broader implications of your research. This means expressing the key takeaways, practical or theoretical, from your paper—often in the form of a call for action or suggestions for future research.

Argumentative paper: Strong closing statement

An argumentative paper generally ends with a strong closing statement. In the case of a practical argument, make a call for action: What actions do you think should be taken by the people or organizations concerned in response to your argument?

If your topic is more theoretical and unsuitable for a call for action, your closing statement should express the significance of your argument—for example, in proposing a new understanding of a topic or laying the groundwork for future research.

Empirical paper: Future research directions

In a more empirical paper, you can close by either making recommendations for practice (for example, in clinical or policy papers), or suggesting directions for future research.

Whatever the scope of your own research, there will always be room for further investigation of related topics, and you’ll often discover new questions and problems during the research process .

Finish your paper on a forward-looking note by suggesting how you or other researchers might build on this topic in the future and address any limitations of the current paper.

Full examples of research paper conclusions are shown in the tabs below: one for an argumentative paper, the other for an empirical paper.

• Argumentative paper
• Empirical paper

While the role of cattle in climate change is by now common knowledge, countries like the Netherlands continually fail to confront this issue with the urgency it deserves. The evidence is clear: To create a truly futureproof agricultural sector, Dutch farmers must be incentivized to transition from livestock farming to sustainable vegetable farming. As well as dramatically lowering emissions, plant-based agriculture, if approached in the right way, can produce more food with less land, providing opportunities for nature regeneration areas that will themselves contribute to climate targets. Although this approach would have economic ramifications, from a long-term perspective, it would represent a significant step towards a more sustainable and resilient national economy. Transitioning to sustainable vegetable farming will make the Netherlands greener and healthier, setting an example for other European governments. Farmers, policymakers, and consumers must focus on the future, not just on their own short-term interests, and work to implement this transition now.

As social media becomes increasingly central to young people’s everyday lives, it is important to understand how different platforms affect their developing self-conception. By testing the effect of daily Instagram use among teenage girls, this study established that highly visual social media does indeed have a significant effect on body image concerns, with a strong correlation between the amount of time spent on the platform and participants’ self-reported dissatisfaction with their appearance. However, the strength of this effect was moderated by pre-test self-esteem ratings: Participants with higher self-esteem were less likely to experience an increase in body image concerns after using Instagram. This suggests that, while Instagram does impact body image, it is also important to consider the wider social and psychological context in which this usage occurs: Teenagers who are already predisposed to self-esteem issues may be at greater risk of experiencing negative effects. Future research into Instagram and other highly visual social media should focus on establishing a clearer picture of how self-esteem and related constructs influence young people’s experiences of these platforms. Furthermore, while this experiment measured Instagram usage in terms of time spent on the platform, observational studies are required to gain more insight into different patterns of usage—to investigate, for instance, whether active posting is associated with different effects than passive consumption of social media content.

If you’re unsure about the conclusion, it can be helpful to ask a friend or fellow student to read your conclusion and summarize the main takeaways.

• Do they understand from your conclusion what your research was about?
• Are they able to summarize the implications of your findings?
• Can they answer your research question based on your conclusion?

You can also get an expert to proofread and feedback your paper with a paper editing service .

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The conclusion of a research paper has several key elements you should make sure to include:

• A restatement of the research problem
• A summary of your key arguments and/or findings
• A short discussion of the implications of your research

No, it’s not appropriate to present new arguments or evidence in the conclusion . While you might be tempted to save a striking argument for last, research papers follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the results and discussion sections if you are following a scientific structure). The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

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Action Research: Steps, Benefits, and Tips

Introduction

History of action research, what is the definition of action research, types of action research, conducting action research.

Action research stands as a unique approach in the realm of qualitative inquiry in social science research. Rooted in real-world problems, it seeks not just to understand but also to act, bringing about positive change in specific contexts. Often distinguished by its collaborative nature, the action research process goes beyond traditional research paradigms by emphasizing the involvement of those being studied in resolving social conflicts and effecting positive change.

The value of action research lies not just in its outcomes, but also in the process itself, where stakeholders become active participants rather than mere subjects. In this article, we'll examine action research in depth, shedding light on its history, principles, and types of action research.

Tracing its roots back to the mid-20th century, Kurt Lewin developed classical action research as a response to traditional research methods in the social sciences that often sidelined the very communities they studied. Proponents of action research championed the idea that research should not just be an observational exercise but an actionable one that involves devising practical solutions. Advocates believed in the idea of research leading to immediate social action, emphasizing the importance of involving the community in the process.

Applications for action research

Over the years, action research has evolved and diversified. From its early applications in social psychology and organizational development, it has branched out into various fields such as education, healthcare, and community development, informing questions around improving schools, minority problems, and more. This growth wasn't just in application, but also in its methodologies.

How is action research different?

Like all research methodologies, effective action research generates knowledge. However, action research stands apart in its commitment to instigate tangible change. Traditional research often places emphasis on passive observation , employing data collection methods primarily to contribute to broader theoretical frameworks . In contrast, action research is inherently proactive, intertwining the acts of observing and acting.

The primary goal isn't just to understand a problem but to solve or alleviate it. Action researchers partner closely with communities, ensuring that the research process directly benefits those involved. This collaboration often leads to immediate interventions, tweaks, or solutions applied in real-time, marking a departure from other forms of research that might wait until the end of a study to make recommendations.

This proactive, change-driven nature makes action research particularly impactful in settings where immediate change is not just beneficial but essential.

Action research is best understood as a systematic approach to cooperative inquiry. Unlike traditional research methodologies that might primarily focus on generating knowledge, action research emphasizes producing actionable solutions for pressing real-world challenges.

This form of research undertakes a cyclic and reflective journey, typically cycling through stages of planning , acting, observing, and reflecting. A defining characteristic of action research is the collaborative spirit it embodies, often dissolving the rigid distinction between the researcher and the researched, leading to mutual learning and shared outcomes.

Advantages of action research

One of the foremost benefits of action research is the immediacy of its application. Since the research is embedded within real-world issues, any findings or solutions derived can often be integrated straightaway, catalyzing prompt improvements within the concerned community or organization. This immediacy is coupled with the empowering nature of the methodology. Participants aren't mere subjects; they actively shape the research process, giving them a tangible sense of ownership over both the research journey and its eventual outcomes.

Moreover, the inherent adaptability of action research allows researchers to tweak their approaches responsively based on live feedback. This ensures the research remains rooted in the evolving context, capturing the nuances of the situation and making any necessary adjustments. Lastly, this form of research tends to offer a comprehensive understanding of the issue at hand, harmonizing socially constructed theoretical knowledge with hands-on insights, leading to a richer, more textured understanding.

Disadvantages of action research

Like any methodology, action research isn't devoid of challenges. Its iterative nature, while beneficial, can extend timelines. Researchers might find themselves engaged in multiple cycles of observation, reflection, and action before arriving at a satisfactory conclusion. The intimate involvement of the researcher with the research participants, although crucial for collaboration, opens doors to potential conflicts. Through collaborative problem solving, disagreements can lead to richer and more nuanced solutions, but it can take considerable time and effort.

Another limitation stems from its focus on a specific context: results derived from a particular action research project might not always resonate or be applicable in a different context or with a different group. Lastly, the depth of collaboration this methodology demands means all stakeholders need to be deeply invested, and such a level of commitment might not always be feasible.

Examples of action research

To illustrate, let's consider a few scenarios. Imagine a classroom where a teacher observes dwindling student participation. Instead of sticking to conventional methods, the teacher experiments with introducing group-based activities. As the outcomes unfold, the teacher continually refines the approach based on student feedback, eventually leading to a teaching strategy that rejuvenates student engagement.

In a healthcare context, hospital staff who recognize growing patient anxiety related to certain procedures might innovate by introducing a new patient-informing protocol. As they study the effects of this change, they could, through iterations, sculpt a procedure that diminishes patient anxiety.

Similarly, in the realm of community development, a community grappling with the absence of child-friendly public spaces might collaborate with local authorities to conceptualize a park. As they monitor its utilization and societal impact, continual feedback could refine the park's infrastructure and design.

Contemporary action research, while grounded in the core principles of collaboration, reflection, and change, has seen various adaptations tailored to the specific needs of different contexts and fields. These adaptations have led to the emergence of distinct types of action research, each with its unique emphasis and approach.

Collaborative action research

Collaborative action research emphasizes the joint efforts of professionals, often from the same field, working together to address common concerns or challenges. In this approach, there's a strong emphasis on shared responsibility, mutual respect, and co-learning. For example, a group of classroom teachers might collaboratively investigate methods to improve student literacy, pooling their expertise and resources to devise, implement, and refine strategies for improving teaching.

Participatory action research

Participatory action research (PAR) goes a step further in dissolving the barriers between the researcher and the researched. It actively involves community members or stakeholders not just as participants, but as equal partners in the entire research process. PAR is deeply democratic and seeks to empower participants, fostering a sense of agency and ownership. For instance, a participatory research project might involve local residents in studying and addressing community health concerns, ensuring that the research process and outcomes are both informed by and beneficial to the community itself.

Educational action research

Educational action research is tailored specifically to practical educational contexts. Here, educators take on the dual role of teacher and researcher, seeking to improve teaching practices, curricula, classroom dynamics, or educational evaluation. This type of research is cyclical, with educators implementing changes, observing outcomes, and reflecting on results to continually enhance the educational experience. An example might be a teacher studying the impact of technology integration in her classroom, adjusting strategies based on student feedback and learning outcomes.

Community-based action research

Another noteworthy type is community-based action research, which focuses primarily on community development and well-being. Rooted in the principles of social justice, this approach emphasizes the collective power of community members to identify, study, and address their challenges. It's particularly powerful in grassroots movements and local development projects where community insights and collaboration drive meaningful, sustainable change.

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Engaging in action research is both an enlightening and transformative journey, rooted in practicality yet deeply connected to theory. For those embarking on this path, understanding the essentials of an action research study and the significance of a research cycle is paramount.

Understanding the action research cycle

At the heart of action research is its cycle, a structured yet adaptable framework guiding the research. This cycle embodies the iterative nature of action research, emphasizing that learning and change evolve through repetition and reflection.

The typical stages include:

• Identifying a problem : This is the starting point where the action researcher pinpoints a pressing issue or challenge that demands attention.
• Planning : Here, the researcher devises an action research strategy aimed at addressing the identified problem. In action research, network resources, participant consultation, and the literature review are core components in planning.
• Action : The planned strategies are then implemented in this stage. This 'action' phase is where theoretical knowledge meets practical application.
• Observation : Post-implementation, the researcher observes the outcomes and effects of the action. This stage ensures that the research remains grounded in the real-world context.
• Critical reflection : This part of the cycle involves analyzing the observed results to draw conclusions about their effectiveness and identify areas for improvement.
• Revision : Based on the insights from reflection, the initial plan is revised, marking the beginning of another cycle.

Rigorous research and iteration

It's essential to understand that while action research is deeply practical, it doesn't sacrifice rigor . The cyclical process ensures that the research remains thorough and robust. Each iteration of the cycle in an action research project refines the approach, drawing it closer to an effective solution.

The role of the action researcher

The action researcher stands at the nexus of theory and practice. Not just an observer, the researcher actively engages with the study's participants, collaboratively navigating through the research cycle by conducting interviews, participant observations, and member checking . This close involvement ensures that the study remains relevant, timely, and responsive.

Drawing conclusions and informing theory

As the research progresses through multiple iterations of data collection and data analysis , drawing conclusions becomes an integral aspect. These conclusions, while immediately beneficial in addressing the practical issue at hand, also serve a broader purpose. They inform theory, enriching the academic discourse and providing valuable insights for future research.

Identifying actionable insights

Keep in mind that action research should facilitate implications for professional practice as well as space for systematic inquiry. As you draw conclusions about the knowledge generated from action research, consider how this knowledge can create new forms of solutions to the pressing concern you set out to address.

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Action research.

• Getting Started
• Action Research by Groups
• The Teacher Action Researcher
• Bibliography & Additional Resources

Education Liaison Librarian

What is Action Research?

Action research involves a systematic process of examining the evidence. The results of this type of research are practical, relevant, and can inform theory. Action research is different than other forms of research as there is less concern for universality of findings, and more value is placed on the relevance of the findings to the researcher and the local collaborators.

Riel, M. (2020). Understanding action research. Center For Collaborative Action Research, Pepperdine University.  Retrieved January 31, 2021 from the Center for Collaborative Action Research.  https://www.actionresearchtutorials.org/  

-----------------------------------

The short video below by John Spencer provides a quick overview of Action Research.

How is Action Research different?

This chart demonstrates the difference between traditional research and action research. Traditional research is a means to an end - the conclusion. They start with a theory, statistical analysis is critical and the researcher does not insert herself into the research.

Action research is often practiced by practitioners like teachers and librarians who remain in the middle of the research process. They are looking for ways to improve the specific situation for their clientele or students. Statistics may be collected but they are not the point of the research.

Adapted from: Mc Millan, J. H. & Wergin. J. F. (1998). Understanding and evaluating educational research. Prentice-Hall, Inc.

Teacher Action Research

According to Paul Gorski, Action Research for educators meets the following qualifications:

• a non-traditional and community-based form of educational evaluation;
• carried out by educators, not outside researchers or evaluators;
• focused on improving teaching and learning, but also social and environmental factors that affect the nature and success of teaching and learning;
• formative, not summative--an on-going process of evaluation, recommendation, practice, reflection, and reevaluation; and
• change-oriented, and undertaken with the assumption that change is needed in a given context

Gorski, P. C. (1995-2018). Teacher Action Research . Critical Multicultural Pavilion. Retrieved October 6, 2018 from https://www.edchange.org/multicultural/tar.html

• Next: Action Research by Groups >>
• Last Updated: Mar 12, 2024 3:14 PM
• URL: https://guides.library.ucmo.edu/actionresearch

Research Design in Business and Management pp 117–139 Cite as

Action Research Design

• Stefan Hunziker 3 &
• Michael Blankenagel 3  
• First Online: 10 November 2021

2948 Accesses

This chapter addresses the peculiarities, characteristics, and major fallacies of action research design. This research design is a change-oriented approach. Its central assumption is that complex social processes can best be studied by introducing change into these processes and observing their effects. The fundamental basis for action research is taking actions to address organizational problems and their associated unsatisfactory conditions. Also, researchers find relevant information on how to write an action research paper and learn about typical methodologies used for this research design. The chapter closes with referring to overlapping and adjacent research designs.

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1 What is Action Research for Classroom Teachers?

ESSENTIAL QUESTIONS

• What is the nature of action research?
• How does action research develop in the classroom?
• What models of action research work best for your classroom?
• What are the epistemological, ontological, theoretical underpinnings of action research?

Educational research provides a vast landscape of knowledge on topics related to teaching and learning, curriculum and assessment, students’ cognitive and affective needs, cultural and socio-economic factors of schools, and many other factors considered viable to improving schools. Educational stakeholders rely on research to make informed decisions that ultimately affect the quality of schooling for their students. Accordingly, the purpose of educational research is to engage in disciplined inquiry to generate knowledge on topics significant to the students, teachers, administrators, schools, and other educational stakeholders. Just as the topics of educational research vary, so do the approaches to conducting educational research in the classroom. Your approach to research will be shaped by your context, your professional identity, and paradigm (set of beliefs and assumptions that guide your inquiry). These will all be key factors in how you generate knowledge related to your work as an educator.

Action research is an approach to educational research that is commonly used by educational practitioners and professionals to examine, and ultimately improve, their pedagogy and practice. In this way, action research represents an extension of the reflection and critical self-reflection that an educator employs on a daily basis in their classroom. When students are actively engaged in learning, the classroom can be dynamic and uncertain, demanding the constant attention of the educator. Considering these demands, educators are often only able to engage in reflection that is fleeting, and for the purpose of accommodation, modification, or formative assessment. Action research offers one path to more deliberate, substantial, and critical reflection that can be documented and analyzed to improve an educator’s practice.

Purpose of Action Research

As one of many approaches to educational research, it is important to distinguish the potential purposes of action research in the classroom. This book focuses on action research as a method to enable and support educators in pursuing effective pedagogical practices by transforming the quality of teaching decisions and actions, to subsequently enhance student engagement and learning. Being mindful of this purpose, the following aspects of action research are important to consider as you contemplate and engage with action research methodology in your classroom:

• Action research is a process for improving educational practice. Its methods involve action, evaluation, and reflection. It is a process to gather evidence to implement change in practices.
• Action research is participative and collaborative. It is undertaken by individuals with a common purpose.
• Action research is situation and context-based.
• Action research develops reflection practices based on the interpretations made by participants.
• Knowledge is created through action and application.
• Action research can be based in problem-solving, if the solution to the problem results in the improvement of practice.
• Action research is iterative; plans are created, implemented, revised, then implemented, lending itself to an ongoing process of reflection and revision.
• In action research, findings emerge as action develops and takes place; however, they are not conclusive or absolute, but ongoing (Koshy, 2010, pgs. 1-2).

In thinking about the purpose of action research, it is helpful to situate action research as a distinct paradigm of educational research. I like to think about action research as part of the larger concept of living knowledge. Living knowledge has been characterized as “a quest for life, to understand life and to create… knowledge which is valid for the people with whom I work and for myself” (Swantz, in Reason & Bradbury, 2001, pg. 1). Why should educators care about living knowledge as part of educational research? As mentioned above, action research is meant “to produce practical knowledge that is useful to people in the everyday conduct of their lives and to see that action research is about working towards practical outcomes” (Koshy, 2010, pg. 2). However, it is also about:

creating new forms of understanding, since action without reflection and understanding is blind, just as theory without action is meaningless. The participatory nature of action research makes it only possible with, for and by persons and communities, ideally involving all stakeholders both in the questioning and sense making that informs the research, and in the action, which is its focus. (Reason & Bradbury, 2001, pg. 2)

In an effort to further situate action research as living knowledge, Jean McNiff reminds us that “there is no such ‘thing’ as ‘action research’” (2013, pg. 24). In other words, action research is not static or finished, it defines itself as it proceeds. McNiff’s reminder characterizes action research as action-oriented, and a process that individuals go through to make their learning public to explain how it informs their practice. Action research does not derive its meaning from an abstract idea, or a self-contained discovery – action research’s meaning stems from the way educators negotiate the problems and successes of living and working in the classroom, school, and community.

While we can debate the idea of action research, there are people who are action researchers, and they use the idea of action research to develop principles and theories to guide their practice. Action research, then, refers to an organization of principles that guide action researchers as they act on shared beliefs, commitments, and expectations in their inquiry.

Reflection and the Process of Action Research

When an individual engages in reflection on their actions or experiences, it is typically for the purpose of better understanding those experiences, or the consequences of those actions to improve related action and experiences in the future. Reflection in this way develops knowledge around these actions and experiences to help us better regulate those actions in the future. The reflective process generates new knowledge regularly for classroom teachers and informs their classroom actions.

Unfortunately, the knowledge generated by educators through the reflective process is not always prioritized among the other sources of knowledge educators are expected to utilize in the classroom. Educators are expected to draw upon formal types of knowledge, such as textbooks, content standards, teaching standards, district curriculum and behavioral programs, etc., to gain new knowledge and make decisions in the classroom. While these forms of knowledge are important, the reflective knowledge that educators generate through their pedagogy is the amalgamation of these types of knowledge enacted in the classroom. Therefore, reflective knowledge is uniquely developed based on the action and implementation of an educator’s pedagogy in the classroom. Action research offers a way to formalize the knowledge generated by educators so that it can be utilized and disseminated throughout the teaching profession.

Research is concerned with the generation of knowledge, and typically creating knowledge related to a concept, idea, phenomenon, or topic. Action research generates knowledge around inquiry in practical educational contexts. Action research allows educators to learn through their actions with the purpose of developing personally or professionally. Due to its participatory nature, the process of action research is also distinct in educational research. There are many models for how the action research process takes shape. I will share a few of those here. Each model utilizes the following processes to some extent:

• Plan a change;
• Take action to enact the change;
• Observe the process and consequences of the change;
• Reflect on the process and consequences;
• Act, observe, & reflect again and so on.

Figure 1.1 Basic action research cycle

There are many other models that supplement the basic process of action research with other aspects of the research process to consider. For example, figure 1.2 illustrates a spiral model of action research proposed by Kemmis and McTaggart (2004). The spiral model emphasizes the cyclical process that moves beyond the initial plan for change. The spiral model also emphasizes revisiting the initial plan and revising based on the initial cycle of research:

Figure 1.2 Interpretation of action research spiral, Kemmis and McTaggart (2004, p. 595)

Other models of action research reorganize the process to emphasize the distinct ways knowledge takes shape in the reflection process. O’Leary’s (2004, p. 141) model, for example, recognizes that the research may take shape in the classroom as knowledge emerges from the teacher’s observations. O’Leary highlights the need for action research to be focused on situational understanding and implementation of action, initiated organically from real-time issues:

Figure 1.3 Interpretation of O’Leary’s cycles of research, O’Leary (2000, p. 141)

Lastly, Macintyre’s (2000, p. 1) model, offers a different characterization of the action research process. Macintyre emphasizes a messier process of research with the initial reflections and conclusions as the benchmarks for guiding the research process. Macintyre emphasizes the flexibility in planning, acting, and observing stages to allow the process to be naturalistic. Our interpretation of Macintyre process is below:

Figure 1.4 Interpretation of the action research cycle, Macintyre (2000, p. 1)

We believe it is important to prioritize the flexibility of the process, and encourage you to only use these models as basic guides for your process. Your process may look similar, or you may diverge from these models as you better understand your students, context, and data.

Definitions of Action Research and Examples

At this point, it may be helpful for readers to have a working definition of action research and some examples to illustrate the methodology in the classroom. Bassey (1998, p. 93) offers a very practical definition and describes “action research as an inquiry which is carried out in order to understand, to evaluate and then to change, in order to improve educational practice.” Cohen and Manion (1994, p. 192) situate action research differently, and describe action research as emergent, writing:

essentially an on-the-spot procedure designed to deal with a concrete problem located in an immediate situation. This means that ideally, the step-by-step process is constantly monitored over varying periods of time and by a variety of mechanisms (questionnaires, diaries, interviews and case studies, for example) so that the ensuing feedback may be translated into modifications, adjustment, directional changes, redefinitions, as necessary, so as to bring about lasting benefit to the ongoing process itself rather than to some future occasion.

Lastly, Koshy (2010, p. 9) describes action research as:

a constructive inquiry, during which the researcher constructs his or her knowledge of specific issues through planning, acting, evaluating, refining and learning from the experience. It is a continuous learning process in which the researcher learns and also shares the newly generated knowledge with those who may benefit from it.

These definitions highlight the distinct features of action research and emphasize the purposeful intent of action researchers to improve, refine, reform, and problem-solve issues in their educational context. To better understand the distinctness of action research, these are some examples of action research topics:

Examples of Action Research Topics

• Flexible seating in 4th grade classroom to increase effective collaborative learning.
• Structured homework protocols for increasing student achievement.
• Developing a system of formative feedback for 8th grade writing.
• Using music to stimulate creative writing.
• Weekly brown bag lunch sessions to improve responses to PD from staff.
• Using exercise balls as chairs for better classroom management.

Action Research in Theory

Action research-based inquiry in educational contexts and classrooms involves distinct participants – students, teachers, and other educational stakeholders within the system. All of these participants are engaged in activities to benefit the students, and subsequently society as a whole. Action research contributes to these activities and potentially enhances the participants’ roles in the education system. Participants’ roles are enhanced based on two underlying principles:

• communities, schools, and classrooms are sites of socially mediated actions, and action research provides a greater understanding of self and new knowledge of how to negotiate these socially mediated environments;
• communities, schools, and classrooms are part of social systems in which humans interact with many cultural tools, and action research provides a basis to construct and analyze these interactions.

In our quest for knowledge and understanding, we have consistently analyzed human experience over time and have distinguished between types of reality. Humans have constantly sought “facts” and “truth” about reality that can be empirically demonstrated or observed.

Social systems are based on beliefs, and generally, beliefs about what will benefit the greatest amount of people in that society. Beliefs, and more specifically the rationale or support for beliefs, are not always easy to demonstrate or observe as part of our reality. Take the example of an English Language Arts teacher who prioritizes argumentative writing in her class. She believes that argumentative writing demonstrates the mechanics of writing best among types of writing, while also providing students a skill they will need as citizens and professionals. While we can observe the students writing, and we can assess their ability to develop a written argument, it is difficult to observe the students’ understanding of argumentative writing and its purpose in their future. This relates to the teacher’s beliefs about argumentative writing; we cannot observe the real value of the teaching of argumentative writing. The teacher’s rationale and beliefs about teaching argumentative writing are bound to the social system and the skills their students will need to be active parts of that system. Therefore, our goal through action research is to demonstrate the best ways to teach argumentative writing to help all participants understand its value as part of a social system.

The knowledge that is conveyed in a classroom is bound to, and justified by, a social system. A postmodernist approach to understanding our world seeks knowledge within a social system, which is directly opposed to the empirical or positivist approach which demands evidence based on logic or science as rationale for beliefs. Action research does not rely on a positivist viewpoint to develop evidence and conclusions as part of the research process. Action research offers a postmodernist stance to epistemology (theory of knowledge) and supports developing questions and new inquiries during the research process. In this way action research is an emergent process that allows beliefs and decisions to be negotiated as reality and meaning are being constructed in the socially mediated space of the classroom.

Theorizing Action Research for the Classroom

All research, at its core, is for the purpose of generating new knowledge and contributing to the knowledge base of educational research. Action researchers in the classroom want to explore methods of improving their pedagogy and practice. The starting place of their inquiry stems from their pedagogy and practice, so by nature the knowledge created from their inquiry is often contextually specific to their classroom, school, or community. Therefore, we should examine the theoretical underpinnings of action research for the classroom. It is important to connect action research conceptually to experience; for example, Levin and Greenwood (2001, p. 105) make these connections:

• Action research is context bound and addresses real life problems.
• Action research is inquiry where participants and researchers cogenerate knowledge through collaborative communicative processes in which all participants’ contributions are taken seriously.
• The meanings constructed in the inquiry process lead to social action or these reflections and action lead to the construction of new meanings.
• The credibility/validity of action research knowledge is measured according to whether the actions that arise from it solve problems (workability) and increase participants’ control over their own situation.

Educators who engage in action research will generate new knowledge and beliefs based on their experiences in the classroom. Let us emphasize that these are all important to you and your work, as both an educator and researcher. It is these experiences, beliefs, and theories that are often discounted when more official forms of knowledge (e.g., textbooks, curriculum standards, districts standards) are prioritized. These beliefs and theories based on experiences should be valued and explored further, and this is one of the primary purposes of action research in the classroom. These beliefs and theories should be valued because they were meaningful aspects of knowledge constructed from teachers’ experiences. Developing meaning and knowledge in this way forms the basis of constructivist ideology, just as teachers often try to get their students to construct their own meanings and understandings when experiencing new ideas.  

Classroom Teachers Constructing their Own Knowledge

Most of you are probably at least minimally familiar with constructivism, or the process of constructing knowledge. However, what is constructivism precisely, for the purposes of action research? Many scholars have theorized constructivism and have identified two key attributes (Koshy, 2010; von Glasersfeld, 1987):

• Knowledge is not passively received, but actively developed through an individual’s cognition;
• Human cognition is adaptive and finds purpose in organizing the new experiences of the world, instead of settling for absolute or objective truth.

Considering these two attributes, constructivism is distinct from conventional knowledge formation because people can develop a theory of knowledge that orders and organizes the world based on their experiences, instead of an objective or neutral reality. When individuals construct knowledge, there are interactions between an individual and their environment where communication, negotiation and meaning-making are collectively developing knowledge. For most educators, constructivism may be a natural inclination of their pedagogy. Action researchers have a similar relationship to constructivism because they are actively engaged in a process of constructing knowledge. However, their constructions may be more formal and based on the data they collect in the research process. Action researchers also are engaged in the meaning making process, making interpretations from their data. These aspects of the action research process situate them in the constructivist ideology. Just like constructivist educators, action researchers’ constructions of knowledge will be affected by their individual and professional ideas and values, as well as the ecological context in which they work (Biesta & Tedder, 2006). The relations between constructivist inquiry and action research is important, as Lincoln (2001, p. 130) states:

much of the epistemological, ontological, and axiological belief systems are the same or similar, and methodologically, constructivists and action researchers work in similar ways, relying on qualitative methods in face-to-face work, while buttressing information, data and background with quantitative method work when necessary or useful.

While there are many links between action research and educators in the classroom, constructivism offers the most familiar and practical threads to bind the beliefs of educators and action researchers.  

Epistemology, Ontology, and Action Research

It is also important for educators to consider the philosophical stances related to action research to better situate it with their beliefs and reality. When researchers make decisions about the methodology they intend to use, they will consider their ontological and epistemological stances. It is vital that researchers clearly distinguish their philosophical stances and understand the implications of their stance in the research process, especially when collecting and analyzing their data. In what follows, we will discuss ontological and epistemological stances in relation to action research methodology.

Ontology, or the theory of being, is concerned with the claims or assumptions we make about ourselves within our social reality – what do we think exists, what does it look like, what entities are involved and how do these entities interact with each other (Blaikie, 2007). In relation to the discussion of constructivism, generally action researchers would consider their educational reality as socially constructed. Social construction of reality happens when individuals interact in a social system. Meaningful construction of concepts and representations of reality develop through an individual’s interpretations of others’ actions. These interpretations become agreed upon by members of a social system and become part of social fabric, reproduced as knowledge and beliefs to develop assumptions about reality. Researchers develop meaningful constructions based on their experiences and through communication. Educators as action researchers will be examining the socially constructed reality of schools. In the United States, many of our concepts, knowledge, and beliefs about schooling have been socially constructed over the last hundred years. For example, a group of teachers may look at why fewer female students enroll in upper-level science courses at their school. This question deals directly with the social construction of gender and specifically what careers females have been conditioned to pursue. We know this is a social construction in some school social systems because in other parts of the world, or even the United States, there are schools that have more females enrolled in upper level science courses than male students. Therefore, the educators conducting the research have to recognize the socially constructed reality of their school and consider this reality throughout the research process. Action researchers will use methods of data collection that support their ontological stance and clarify their theoretical stance throughout the research process.

Koshy (2010, p. 23-24) offers another example of addressing the ontological challenges in the classroom:

A teacher who was concerned with increasing her pupils’ motivation and enthusiasm for learning decided to introduce learning diaries which the children could take home. They were invited to record their reactions to the day’s lessons and what they had learnt. The teacher reported in her field diary that the learning diaries stimulated the children’s interest in her lessons, increased their capacity to learn, and generally improved their level of participation in lessons. The challenge for the teacher here is in the analysis and interpretation of the multiplicity of factors accompanying the use of diaries. The diaries were taken home so the entries may have been influenced by discussions with parents. Another possibility is that children felt the need to please their teacher. Another possible influence was that their increased motivation was as a result of the difference in style of teaching which included more discussions in the classroom based on the entries in the dairies.

Here you can see the challenge for the action researcher is working in a social context with multiple factors, values, and experiences that were outside of the teacher’s control. The teacher was only responsible for introducing the diaries as a new style of learning. The students’ engagement and interactions with this new style of learning were all based upon their socially constructed notions of learning inside and outside of the classroom. A researcher with a positivist ontological stance would not consider these factors, and instead might simply conclude that the dairies increased motivation and interest in the topic, as a result of introducing the diaries as a learning strategy.

Epistemology, or the theory of knowledge, signifies a philosophical view of what counts as knowledge – it justifies what is possible to be known and what criteria distinguishes knowledge from beliefs (Blaikie, 1993). Positivist researchers, for example, consider knowledge to be certain and discovered through scientific processes. Action researchers collect data that is more subjective and examine personal experience, insights, and beliefs.

Action researchers utilize interpretation as a means for knowledge creation. Action researchers have many epistemologies to choose from as means of situating the types of knowledge they will generate by interpreting the data from their research. For example, Koro-Ljungberg et al., (2009) identified several common epistemologies in their article that examined epistemological awareness in qualitative educational research, such as: objectivism, subjectivism, constructionism, contextualism, social epistemology, feminist epistemology, idealism, naturalized epistemology, externalism, relativism, skepticism, and pluralism. All of these epistemological stances have implications for the research process, especially data collection and analysis. Please see the table on pages 689-90, linked below for a sketch of these potential implications:

Again, Koshy (2010, p. 24) provides an excellent example to illustrate the epistemological challenges within action research:

A teacher of 11-year-old children decided to carry out an action research project which involved a change in style in teaching mathematics. Instead of giving children mathematical tasks displaying the subject as abstract principles, she made links with other subjects which she believed would encourage children to see mathematics as a discipline that could improve their understanding of the environment and historic events. At the conclusion of the project, the teacher reported that applicable mathematics generated greater enthusiasm and understanding of the subject.

The educator/researcher engaged in action research-based inquiry to improve an aspect of her pedagogy. She generated knowledge that indicated she had improved her students’ understanding of mathematics by integrating it with other subjects – specifically in the social and ecological context of her classroom, school, and community. She valued constructivism and students generating their own understanding of mathematics based on related topics in other subjects. Action researchers working in a social context do not generate certain knowledge, but knowledge that emerges and can be observed and researched again, building upon their knowledge each time.

Researcher Positionality in Action Research

In this first chapter, we have discussed a lot about the role of experiences in sparking the research process in the classroom. Your experiences as an educator will shape how you approach action research in your classroom. Your experiences as a person in general will also shape how you create knowledge from your research process. In particular, your experiences will shape how you make meaning from your findings. It is important to be clear about your experiences when developing your methodology too. This is referred to as researcher positionality. Maher and Tetreault (1993, p. 118) define positionality as:

Gender, race, class, and other aspects of our identities are markers of relational positions rather than essential qualities. Knowledge is valid when it includes an acknowledgment of the knower’s specific position in any context, because changing contextual and relational factors are crucial for defining identities and our knowledge in any given situation.

By presenting your positionality in the research process, you are signifying the type of socially constructed, and other types of, knowledge you will be using to make sense of the data. As Maher and Tetreault explain, this increases the trustworthiness of your conclusions about the data. This would not be possible with a positivist ontology. We will discuss positionality more in chapter 6, but we wanted to connect it to the overall theoretical underpinnings of action research.

Advantages of Engaging in Action Research in the Classroom

In the following chapters, we will discuss how action research takes shape in your classroom, and we wanted to briefly summarize the key advantages to action research methodology over other types of research methodology. As Koshy (2010, p. 25) notes, action research provides useful methodology for school and classroom research because:

Advantages of Action Research for the Classroom

• research can be set within a specific context or situation;
• researchers can be participants – they don’t have to be distant and detached from the situation;
• it involves continuous evaluation and modifications can be made easily as the project progresses;
• there are opportunities for theory to emerge from the research rather than always follow a previously formulated theory;
• the study can lead to open-ended outcomes;
• through action research, a researcher can bring a story to life.

Action Research Copyright © by J. Spencer Clark; Suzanne Porath; Julie Thiele; and Morgan Jobe is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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What Is Action Research? | Definition & Examples

Published on 27 January 2023 by Tegan George . Revised on 21 April 2023.

Table of contents

Types of action research, action research models, examples of action research, action research vs. traditional research, advantages and disadvantages of action research, frequently asked questions about action research.

There are 2 common types of action research: participatory action research and practical action research.

• Participatory action research emphasises that participants should be members of the community being studied, empowering those directly affected by outcomes of said research. In this method, participants are effectively co-researchers, with their lived experiences considered formative to the research process.
• Practical action research focuses more on how research is conducted and is designed to address and solve specific issues.

Both types of action research are more focused on increasing the capacity and ability of future practitioners than contributing to a theoretical body of knowledge.

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Action research is often reflected in 3 action research models: operational (sometimes called technical), collaboration, and critical reflection.

• Operational (or technical) action research is usually visualised like a spiral following a series of steps, such as “planning → acting → observing → reflecting.”
• Collaboration action research is more community-based, focused on building a network of similar individuals (e.g., college professors in a given geographic area) and compiling learnings from iterated feedback cycles.
• Critical reflection action research serves to contextualise systemic processes that are already ongoing (e.g., working retroactively to analyse existing school systems by questioning why certain practices were put into place and developed the way they did).

Action research is often used in fields like education because of its iterative and flexible style.

After the information was collected, the students were asked where they thought ramps or other accessibility measures would be best utilised, and the suggestions were sent to school administrators. Example: Practical action research Science teachers at your city’s high school have been witnessing a year-over-year decline in standardised test scores in chemistry. In seeking the source of this issue, they studied how concepts are taught in depth, focusing on the methods, tools, and approaches used by each teacher.

Action research differs sharply from other types of research in that it seeks to produce actionable processes over the course of the research rather than contributing to existing knowledge or drawing conclusions from datasets. In this way, action research is formative , not summative , and is conducted in an ongoing, iterative way.

As such, action research is different in purpose, context, and significance and is a good fit for those seeking to implement systemic change.

Action research comes with advantages and disadvantages.

• Action research is highly adaptable , allowing researchers to mould their analysis to their individual needs and implement practical individual-level changes.
• Action research provides an immediate and actionable path forward for solving entrenched issues, rather than suggesting complicated, longer-term solutions rooted in complex data.
• Done correctly, action research can be very empowering , informing social change and allowing participants to effect that change in ways meaningful to their communities.

Disadvantages

• Due to their flexibility, action research studies are plagued by very limited generalisability  and are very difficult to replicate . They are often not considered theoretically rigorous due to the power the researcher holds in drawing conclusions.
• Action research can be complicated to structure in an ethical manner . Participants may feel pressured to participate or to participate in a certain way.
• Action research is at high risk for research biases such as selection bias , social desirability bias , or other types of cognitive biases .

Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon.

Action research is focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. It is less focused on contributing theoretical input, instead producing actionable input.

Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible.

A cycle of inquiry is another name for action research . It is usually visualized in a spiral shape following a series of steps, such as “planning → acting → observing → reflecting.”

Sources for this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2023, April 21). What Is Action Research? | Definition & Examples. Scribbr. Retrieved 25 March 2024, from https://www.scribbr.co.uk/research-methods/action-research-cycle/

Cohen, L., Manion, L., & Morrison, K. (2017). Research methods in education (8th edition). Routledge.

Naughton, G. M. (2001).  Action research (1st edition). Routledge.

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• PMC8240599.1 ; 2021 May 7
• ➤ PMC8240599.2; 2021 Jun 15

Application of action research in the field of healthcare: a scoping review protocol

1 UCD School of Nursing, Midwifery & Health Systems, University College Dublin, Dublin 4, Ireland

David Coghlan

2 Trinity Business School, University of Dublin, Trinity College, Dublin 2, Ireland

Áine Carroll

3 School of Medicine, University College Dublin, Dublin 4, Ireland

4 National Rehabilitation Hospital, Dun Laoghaire, Co Dublin, Ireland

Diarmuid Stokes

5 The Library, University College Dublin, Dublin 4, Ireland

Kinley Roberts

Geralyn hynes.

6 School of Nursing & Midwifery, University of Dublin, Trinity College, Dublin 2, Ireland

Associated Data

No data are associated with this article.

Version Changes

Revised. amendments from version 1.

We received feedback from two very helpful experts in the field of action research and action learning. There were a few minor changes that we made in the light of this feedback as seen hereunder. We see all action research as involving change, action, and reflection which is thus transformational and transformative in some way. We further elaborated slightly on the description of stage 5 to emphasise that there is no extant quality appraisal checklist for action research studies and that our findings will contribute to future development.  We justified our choice of action research framework on the basis that the framework by Coghlan and Shani (2018) expresses the essential relationships between context, quality of relationships, has a dual focus on the inquiry and implementation process as well as concern for the actionability and contribution to knowledge creation. These four factors comprise a comprehensive framework as they capture the core of action research and the complex cause-and-effect dynamics within each factor and between the factors. We interpret the explanatory definition of organisational context as described by Coghlan and Shani (2018) to include community healthcare context which is also seen as community care context in healthcare parlance. Therefore, our search will pick up CBPR. We have clarified that participative values are embodied within the relational component of the action research and added an additional reference. We have also justified the inclusion of a particular focus on measurement of the degree of participation as in some publications the inclusion of stakeholders in interviews and focus groups only, is taken as essentially constituting the entire spectrum of the core values of participation and inclusion of the quality of the co-researcher partnership.

Peer Review Summary

Background: Traditional research approaches are increasingly challenged in healthcare contexts as they produce abstract thinking rather than practical application. In this regard, action research is a growing area of popularity and interest, essentially because of its dual focus on theory and action. However, there is a need for action researchers not only to justify their research approach but also to demonstrate the quality of their empirical studies. Therefore, the authors set out to examine the current status of the quality of extant action research studies in healthcare to encourage improved scholarship in this area. The aim of this scoping review is to identify, explore and map the literature regarding the application of action research in either individual, group or organisational domains in any healthcare context.

Methods: The systematic scoping review will search the literature within the databases of CINAHL, PubMed and ABI/Inform within the recent five-year period to investigate the scientific evidence of the quality of action research studies in healthcare contexts. The review will be guided by Arksey and O'Malley’s five mandatory steps, which have been updated and published online by the Joanna Briggs Institute. The review will follow the PRISMA-ScR framework guidelines to ensure the standard of the methodological and reporting approaches are exemplary.

Conclusion: This paper outlines the protocol for an exploratory scoping review to systematically and comprehensively map out the evidence as to whether action research studies demonstrate explicitly how the essential factors of a comprehensive framework of action research are upheld. The review will summarise the evidence on the quality of current action research studies in healthcare. It is anticipated that the findings will inform future action researchers in designing studies to ensure the quality of the studies is upheld.

Introduction

The utility and versatility of action research has brought about an increase in the level of interest, application and usage of action research in a variety of healthcare contexts in the past 20 years as healthcare systems all over the world undergo transformative change. Part of this greater interest and usage relates to the fact that in this context of change, action research aims at both taking action in a particular system in response to particular forces, and therefore brings a change, and creating knowledge about that action that provides actionable knowledge for other health care organisations. Another possible explanation for the increased application of action research in healthcare is its participatory paradigm, which invites participants to be both embedded and reflexive in the creation of collaborative learning and of actionable knowledge where research is with, rather than on or for, people. Action research therefore attempts to link theory and practice, thinking and doing, achieving both practical and research objectives ( Casey & Coghlan, 2021 ), and therefore provides a means of improvement by narrowing the gap between researching and implementing.

A wide range of terms are used to describe action research approaches such that it is now considered as a family of approaches ( Casey et al. , 2018 ), the common approaches being appreciative inquiry, co-operative inquiry, collaborative research, participatory action research and, more recently, co-design to name a few. The action research process involves engagement in cycles of action and reflection and always involves two goals: to address a real issue and to contribute to science through the elaboration or development of theory. These are the dual imperatives of action research. The creation of actionable knowledge is the most rigorous test of knowledge creation. Action research embodies a set of principles and outlines definite steps on how to engage in the research process. These steps are cyclical and spiral in nature and iterative and some argue that two overlapping spirals of activity exist, where one spiral depicts the research activity and the other depicts the work interest ( Casey & Coghlan, 2021 ). This facilitates the researchers giving adequate consideration to their own learning and knowledge as well as to all the relevant issues prior to engaging in research activity. Thus the researchers are engaging in developmental reflexivity and adopt a critical stance on their role throughout the action research project ( Bradbury et al. , 2019 ). According to Reason & Bradbury (2008:4) action research “is a living, emergent process that cannot be predetermined but changes and develops as those who engage deepen their understanding of the issues to be addressed and develop their capacity as co-inquirers both individually and collectively’.

In one of his seminal articles on action research, Lewin (1947: 147-8) describes how action research begins and develops.

• Planned social action (intentional change) usually emerges from a more or less vague “idea”. An objective appears in the cloudy form of a dream or a wish, which can hardly be called a goal. To become real, to be able to steer action, something has to be developed which might be called a plan... It should be noted that the development of a general plan presupposes “fact-finding” … On the basis of this fact-finding the goal is somewhat altered…Accepting a plan does not mean that all further steps are fixed by a decision; only in regard to the first step should be the decision be final. After the first action is carried out, the second step should not follow automatically. Instead it should be investigated whether the effect of the first action was actually what was expected.

Keeping a regular check on how the inquiry process is unfolding and checking for the presence of any underlying assumptions with the group is essential ( Coughlan & Coghlan, 2002 ).

Participation as a core value in action research

Action research has its focus on generating solutions to practical problems and its ability to empower practitioners because of its emphasis on participation as a core strategy ( Reason, 1994 ) and implementation of action ( Meyer, 2000 ). Active participation in a research study can be more threatening than participation in the traditional designs and there are increasing calls for evidence of impact and outcome from participation and co-design ( Palmer, 2020 ). Participation in healthcare is rendered complex by the different lens through which different professional groups view and understand problems through different disciplinary lens while patients must engage with these against a hierarchical background. Participation has thus been described as a multivoiced process ( Hynes et al. , 2012 ) and embraces multiple ways of knowing-for-action ( Bradbury et al. , 2019 ). Indeed, there is an expectation that participation from participants and co-researchers increases involvement and commitment and sustainability of action research outcomes; however, the measurement of this has been inconsistent and almost absent. In some published accounts we have seen the inclusion of stakeholders in interviews and focus groups only, as essentially constituting the entire spectrum of the core values of participation and inclusion of the quality of the co-researcher partnership. Indeed, there is an expectation that participation from participants and co-researchers increases involvement and commitment and sustainability of action research outcomes; however, the measurement of this has been inconsistent and almost absent. For this reason we have opted to look at the degree of participation that is evidenced in the empirical studies using the ladder of citizen participation ( Arnstein, 1969 ), which although based on citizen participation in model cities in a department of housing and urban development, can form the basis for a more enlightened conversation about the type of participation evident in the selected studies. The ladder is organised into three major positions on citizen participation along a continuum of citizen control based on the concept of ability to exercise power. The ladder has eight rungs, with the bottom two rungs representing non-participation labelled as ‘therapy’ and ‘manipulation’. The middle section is labelled ‘degrees of tokenism’ and includes three rungs called ‘informing’, ‘consultation’ and ‘placation’ in ascending order. The higher rungs indicate three degrees of citizen power ranging from ‘partnership’ at the lower level, followed by ‘delegated power’, and ‘citizen control’ as the top rung of the ladder.

Indicating the quality of action research studies

Action researchers do not make claims “so much on the grounds of scientific rigour, as in terms of generating findings which are useful and relevant" ( Hart & Bond, 1995:13 ). Baskerville & Wood-Harper (1996:238) suggest that “where the change is successful, the evaluation must critically question whether the undertaken action, among the myriad routine and non-routine organisational actions, was the sole cause of success”. According to Waterman (1998:104) , “the validity of action research projects does not reside in their degree to effect change but in their attempt to improve people’s lives...through voluntary participation and cooperation”. According to Ellis & Kiely (2000:87) the validity of the research is based on the degree to which the research is useful and relevant in precipitating discussion about improvement. Morrison & Lilford (2001:441) suggest the search for knowledge can be considered scientific “if it leads to the development of theories that are explanatory: telling us why things happen as they do in that domain, comprehensively applying to the whole domain, and falsifiability: giving rise, via testable hypotheses, to empirical predictions whose persistent failure counts against the theory”. They conclude action research offers explanatory theories, and that these theories can be falsified. However, they attest these theories are context dependent and hence cannot be comprehensive.

Reason & Bradbury (2001) prefer to use the term quality rather than validity in action research as a means of expressing and judging rigour. They suggest the judge for quality action research be on the basis that it develops a praxis of relational knowledge and knowledge generation reflects co-operation between the researcher and participants. These authors also ask whether the research is guided by a reflexive concern for practical outcomes and whether the process of iterative reflection as part of the change process is readily apparent. Therefore, action research must acknowledge multiple realities and a plurality of knowing evident in the inclusion of various perspectives from the participants without attempting to find an agreed common perspective. The significance of the project is also an important aspect of quality criteria and whether the project results in new developments such as sustainable change. A framework that expresses these essential relationships between context, quality of relationships, has a dual focus on the inquiry and implementation process as well as concern for the actionability and contribution to knowledge creation was selected. Such a framework exists in the work of Shani & Pasmore (1985/2016) who suggest that the necessary evidence of the quality of their action research studies can be achieved by: i) demonstrating knowledge of the practical and academic context of the project; ii) creating participants as co-researchers; iii) enacting cycles of action and reflection as the project is being implemented and knowledge is being co-generated; and iv) generating outcomes that are both practical for the delivery of healthcare system in the project and robust for theory development about change in healthcare. A comprehensive framework of the action research process is presented by Coghlan & Shani (2018) in terms of four factors. These four factors comprise a comprehensive framework as they capture the core of action research and the complex cause-and-effect dynamics within each factor and between the factors.

• The context of the action research project refers to individual, organisational, environmental and research/consulting factors. Individual factors include ideas about the direction of the project and how collaboration can be assured. From an organisational perspective, the availability and use of resources influence of previous history, and the level of congruence between these impacts on the capability for participation. Environmental factors in the global and local economies provide the larger context in which action research takes place. An example of research factors which can have relevance relates to previous research experience and involvement a similar area or topic.
• The quality of relationship refers to trust, shared language, concern for each other and equality of influence between members and researchers.
• Refers to the dual focus on both the inquiry process and the implementation process as they are being undertaken.
• The dual outcomes of action research are some level of organisational improvement and learning and the creation of actionable knowledge.

These four factors will be used for the scoping review. A scoping review is the most appropriate approach to the literature as it provides an overview of studies, clarifying concepts or contextual information ( Pollack et al ., 2021 ) and it can be used to investigate research conduct ( Munn et al ., 2018 ; Tricco et al ., 2018 ). This aim of this scoping review is to explore whether action research studies demonstrate explicitly how the essential factors of a comprehensive framework of action research are upheld. This is a scoping protocol for this review. Our protocol includes information about the aims and objectives of the scoping review, inclusion and exclusion criteria, search strategy and data extraction.

The protocol for the scoping review is based on the work of Arksey & O' Malley (2005) . In addition, The Preferred Reporting Items for Systematic reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) ( Tricco et al ., 2018 ) will guide the process. This reporting guideline is consistent with the JBI guidance for scoping reviews, ( Tricco et al. , 2018 ). These steps are:

• Stage 1 : Identifying the research question

Stage 2: Identifying relevant studies

Stage 3: study selection, stage 4: charting the data.

• Stage 5: Collating, summarising and reporting results

Stage 1: Identifying the research question

The review aims to identify, explore and map the literature regarding the application of action research in either individual, group or organisational domains in any healthcare context.

Objectives . To identify the degree to which the core factors of a comprehensive framework of action research ( Coghlan & Shani, 2018 ) are manifestly addressed. The following are the key objectives of the scoping review:

• 1. To identify the degree to which knowledge of the practical and academic context are addressed.
• 2. To establish how the quality of co-researcher relationships was maintained.
• 3. To determine how the quality of the enactment of cycles of action and reflection in the present tense were implemented.
• 4. To identify how the dual outcomes of co-generated actionable knowledge are addressed.

Review question . How do researchers address the core factors of a comprehensive framework of action research in healthcare?

According to Peters et al. (2020b) , a scoping review question should include elements of the PCC mnemonic (population, concept, and context) and it will also inform inclusion and exclusion criteria and consequently the literature search strategy.

• Population - healthcare professionals and patients and clients who work or come into contact with health care in any context of primary, secondary or tertiary settings
• Concept - studies that use an action research approach in healthcare contexts.
• Context - any part of health service in any country that people (healthcare professionals and patients or clients) interact with.

Inclusion and exclusion criteria . The inclusion and exclusion criteria for study selection are summarised in Table 1 .

The research team will undertake a comprehensive search of the literature within the following databases:

• CINAHL - Nursing and Allied Health (CINAHL Plus)
• PubMed – Biomedical and life sciences database
• ABI/Inform (ProQuest) – Business database

Using the three terms of population, concept, context (PCC framework) an initial search will be deployed on CINAHL Plus. This will be followed by the use of search terms to identify key text words used to address the major concepts of population (healthcare professionals and patients), concept (action research studies in healthcare), and context (any part of health service that people interact with). Alternative terms for each of the concepts will also be included. Then each search strategy will be adapted for each database (PubMed and ABI/Inform) and specific Boolean operators, truncation markers, and MeSH headings where necessary will be used. The inclusion of the expertise of a research librarian is invaluable at an early stage of completing a scoping review ( McGowan et al. , 2020 ); the research team worked with the expert university librarian in designing and refining the search strategy and will be included as part of the research team. We noted that while the data bases CINAHL and ABI/Inform claim to include the Action Research Journal, this is not the case. Therefore, we plan to do a manual search of the Action Research Journal and also of Educational Action Research for the past 5 years in keeping with the timeframe of the search strategy for this protocol. Sample search terms for the PubMed database are outlined in Table 2 .

Key search concepts . The key search concepts for this study are ‘people in healthcare’ AND ‘action research’ AND ‘healthcare environment’.

Endnote 9 will be used to manage the identified studies from the three databases. All duplicates will be removed within Endnote 9. The process of screening the titles and abstracts will be undertaken by four members of the team and non-relevant studies based on the criteria will be removed with the assistance of Rayyan (an online open access screening software tool). To resolve any conflict regarding the difference of opinion and in the ‘undecided, category, one member from the other team will chair a discussion to reach a consensus agreement. To improve reliability of the reviewers, a short training programme on the use of Rayyan will be undertaken by all the researchers and a small percentage of the studies will be screened independently by each reviewer and then a comparison will be reviewed for consistency of decision-making between the members. The full text article review will be undertaken by the same researchers using the same iterative steps, with the researchers reviewing the full texts independently.

We will do a small pilot study to test the use of the criteria and these can be modified as the researchers become more familiar with a sample of the studies to determine if further information is required of if fields are not relevant and should be removed. Data will be extracted using specified criteria and evidence from this process will be presented in table format.

Four members of the research team will be involved in extracting the data using a charting table created by the researchers within Microsoft Excel 365 software, as suggested by Joanna Briggs Institute (JBI) ( Peters et al. , 2017 ). The extracted data will be selected and mapped according to the specified inclusion of evidence of the quality of the action research study. Using the elements identified in the PCC framework as a guide, the initial fields will include:

• Citation details (authors and year of publication)
• Study title
• Geographical location of study
• Study setting/context
• Methodology/design – Type of action research
• ▪ knowledge of the practical and academic context,
• ▪ quality of co-researcher relationships,
• ▪ quality of the enactment of cycles of action and reflection in the present tense,
• ▪ the dual outcomes of co-generated actionable knowledge.
• ▪ Citizen power (citizen control, delegated power, partnership)
• ▪ Tokenism (placation, consultation, informing)
• ▪ Non-participation (therapy, manipulation)

Stage 5: Collating, summarising and reporting the results

Data will be collected using Microsoft Excel 365 software to capture relevant information for each study by the same four members of the research team and it will be available to all members via a shared drive. Studies will be mapped according to their contextual setting, geographical location, and year of publication. All authors will discuss the data prior to analysis, which will be a descriptive analysis, as recommended by Peters et al. (2020a) . A narrative tabular report will be produced summarising the extracted data concerning the objectives and scoping review question. The PRISMA-ScR guidelines will be used for reporting the outcomes of the review ( Tricco et al. , 2018 ). Quality appraisal of the studies will not be conducted as there is no extant quality appraisal check list for action research studies. This review aims to explore how the core factors of a comprehensive framework of action research are addressed in each study and our findings will contribute to future development of such a check list for the application of action research principles in action research studies in general. The review will consist of analysis of the evidence of the quality of their action research on: i) demonstrating knowledge of the practical and academic context of the project; ii) creating participants as co-researchers; iii) enacting cycles of action and reflection in the present tense as the project is being implemented and knowledge is being co-generated; and iv) generating outcomes that are both practical for the delivery of healthcare system in the project and robust for theory development about change in healthcare. Full adherence to ethical procedures in disseminating information will be undertaken by the research team. The report will be presented both orally and through publications at national and international conferences.

Study status

At the time of publication of this protocol, preliminary database searches had commenced.

This scoping review protocol has been designed in line with the latest evidence. Action research studies were carried out in diverse healthcare settings and there are many ways of undertaking action research in healthcare that consider the research purpose, aims and theoretical underpinnings. However, there is a need demonstrate the quality of the action research studies by choosing a coherent theoretical guidance provided by scholars. This will enable the transformation and impact of action research in healthcare settings to be evaluated and thereby improve the quality of action research studies in healthcare. The results extracted from this scoping review will identify how the quality element is addressed in current empirical action research studies within a recent five-year period. Based on the outcome of the review knowledge gaps and deficits will be uncovered in relation to demonstrating adherence to quality criteria when undertaking action research studies. A Quality check list for action research studies may be generated similar in format to extant reporting criteria for qualitative and quantitative studies. Findings from the review will be shared widely with healthcare personnel both locally and nationally and also through presentations and publication of the review in an open-access journal.

Data availability

[version 2; peer review: 2 approved]

Funding Statement

The author(s) declared that no grants were involved in supporting this work.

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Reviewer response for version 2

Victor friedman.

1 Action Research Center for Social Justice, Max Stern Yezreel Valley College, Emek Yezreel, Israel

The changes to the article are sufficient.

Is the study design appropriate for the research question?

Is the rationale for, and objectives of, the study clearly described?

Are sufficient details of the methods provided to allow replication by others?

Are the datasets clearly presented in a useable and accessible format?

Not applicable

Reviewer Expertise:

Action research, organisational learning, social inclusion, conflict transformation, action science, field theory

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

UCD Nursing, Midwifery & Health Systems, Ireland

Many thanks for your considered response that has helped us to improve our publication.

Kind Regards

Reviewer response for version 1

This paper presents a protocol for a scoping literature review of how action research in health care deals with quality. It argues for the need for such a review, which promises to provide a deeper, more nuanced, and empirically based understanding of what quality actually means in action research in the health care field. The paper reviews a small sample of the literature on quality in action research and points to a variety of criteria/factors for evaluating/generating quality. For their scoping review, the authors choose “four factors” for quality as presented by Coghlan and Shani (2018). The paper then presents the research question, the methods to be used for (1) identifying and selecting relevant studies to be reviewed, (2) charting the data, and (3) collating, summarising and reporting the results.

The paper makes a convincing argument for the need for such a scoping review and prevents a very clear, systematic, and well though-out protocol that should generate very useful and important knowledge. 

At the same time, I question the authors choice of a single, pre-existing framework for quality (Coghlan & Shani,2018). After presenting a number of varying approaches to quality, they write, “a connection that integrates their different forms of expertise and different initial frameworks is needed in order to generate a third framework of the local situation.” However, the authors do not actually explain how these frameworks are integrated within the Coghlan and Shani (2018) model. It seems to me that some things are missing or need to be developed a bit more:

•  Making a specific reference to the issues of reflection/reflexivity, which are featured in the literature reviewed earlier in the paper. These are not the same processes, though they related, and are an important component of action research.
• The Coghlan & Shani (2018) framework is very heavily oriented towards action research in organizations. Making a specific reference to the issue of “community,” which is a central domain in health care but is missing from the “Context” part of the framework. It does appear in Table 2. Regarding Table 2, I would add “Community Based (Participatory Research (CBPR or CBR)” to “Concept” (studies that use an action research approach in healthcare contexts).
•  “Participation” appears as a separate category outside of the framework. However, participation is applied implied in the Coghlan and Shani (2018) model by “equality of influence between members and researchers” in the “quality of relationships” (factor 3). How does quality of relationships differ from participation? Perhaps participation cold be incorporated into the framework or the framework crafted to reduce redundancy.
• I suggest that the authors take a look at the quality choice-points for action oriented research for transformation suggested by the (Bradbury et al, 2020), https://journals.sagepub.com/doi/full/10.1177/1476750320904562 . )

To sum up, Coghlan & Shani (2018) provides a very good foundation on which to build the integrative model, but a bit more work needs to be done to make it integrative and more comprehensive.

There are also a number of editing issues:

•  The authors write: “Therefore, a connection that integrates their different forms of expertise and different initial frameworks is needed in order to generate a third framework of the local situation.”  What is meant by “third framework”? What were the first and second frameworks? 
• The very next sentence says  “Such a frame exists”.  This confuses a bit more since “framework” and “frame” are not the same
• The authors write: “Individual factors include ideas about the direction and collaboration can be assured.”  There is something missing in this sentence. I think it should say “ideas about how the…” but that’s up to the authors
• The authors write: “From an organisational perspective, the availability and use of resources influence of previous history, and the level of congruence between these impacts on the capability for participation.” There is something missing in this sentence as well. I think there needs to be a comma: “use of resources, influence of previous history and…"
• The authors write: “Based on the outcome of the review knowledge gaps and deficits will be uncovered in relation to demonstrating adherence to quality criteria when undertaking action research studies.” I think there is a missing comma and should read: Based on the outcome of the review, knowledge gaps…

Finally, I want to raise a thought I had about the relationship between action research and academic writing that may, or may not, be relevant to this project and the protocol. Understandably, the authors exclude research that lacks “information and descriptions on the core tenets of action research”. However, as an associate editor of the Acton Research Journal and a frequent reviewer of action research papers, I am often struck by the difference between doing action research and writing about it for academic journals. Unlike normal research, which can be planned and controlled to a high degree, action research, by its very nature as a participative process, is emergent and responsive to changing situations, rarely actually occurring according to “plan.” Sometimes I read manuscripts that are based on quite interesting and high quality action research, but this research is not framed or presented in a way that meets academic standards. Writing up action research for academic journals is often a post hoc reflective process that addresses the question “What did we learn from this project? What kind of knowledge did we produce?” In my experience, many manuscripts fail because they do not adequately frame a question, connect with the relevant literature, or adequately present the data to back up their claims. All of these problems have more to with writing than with the action research itself. In this respect, I believe that this project looks not so much at the quality of action research as the quality of action research as reflected in academic writing. I am not sure how important this distinction is, if at all, but I did want to put it on the table.

I wish the authors all the best in carrying out this important study.

action research, organisational learning, social inclusion, conflict transformation, action science, field theory

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Brendan McCormack

1 Centre for Person-Centred Practice Research, Queen Margaret University Edinburgh, Musselburgh, UK

Thanks for asking me to review this protocol. It is great to see this work happen and it is to be welcomed, as it is needed. Generally the protocol is really thorough and is very clear and should produce some good outcomes.

A couple of comments:

• The focus is interesting to me. You clearly set out what 'counts' as action research, which includes 'co-design work in healthcare' (much of which I struggle to see as research at all!) but don't include transformational and transformative research which is usually theoretically and philosophically robust. That seems odd!
• The databases to be searched don't include any educational or social science databases. Whilst I completely appreciate that health related publications in these databases are few, they are however places that health-focused action research gets published. I think these need to be included.
• The methods are clearly set out and are very thorough. However I found the stage 5 of the methods to be 'vague' and I am not completely sure what the processes are and how standardised they are. I think these could be further clarified.
• The dissemination ideas lack creativity and contemporary (non-academic publication focused) methods. These should be further considered.

Well done and I wish you luck with the project.

action research. participatory research. person-centred research. nursing and healthcare research

Action Research and Participatory Action Research

In action research the researchers co-learns with a stakeholder group. In participatory action research they take a more active role as a member of a community. Participatory action research is sometimes used when an organisation needs to solve a problem but no clear line of inquiry is indicated. Alongside this kind of flexibility, another advantage of these approaches is that research can be tailored to a specific context while focusing stakeholders, allowing unanticipated solutions to emerge. This might be done to personalise a learning experience, or promote social inclusion (Warschauer, 2003; Lewis & Sanderson, 2011; Kemmis et al. 2013). Conversely, this approach might be considered disadvantageous because it may limit the ability to make generalised claims or apply what has been found in new contexts.

Action Research: GO-GN Insights

Ada Czerwonogora used Action Research as part of a complex case study into reflective practice and the transformation of teaching through technological integration on behalf of the PRAXIS project:

“The project approach was based on Open Science and Open Educational Practices as foundational frameworks to face the challenges of critical Educational Action Research… I see as an advantage the multi-methods approach, to provide a deep understanding of the complex case. However, this could result in a more difficult methodology… I think the pros are far more than the cons.”

Jenni Hayman used an action research approach in face-to-face workshops and on a MOOCs to determine the usefulness of an awareness and support strategy designed to increase the use of OER among post-secondary educators:

“The method for my research was mixed method action research (MMAR) and it was defined by my institution as a requirement…I engaged in three cycles of research (a common practice for action research), each leading to more refined practices and greater participation. Although my personal tendency is toward qualitative methods, I found the requirement of a mixed method approach for my research extremely beneficial as a novice. I was required to learn and practice skills of both approaches and to learn how different types of data interact and combine to magnify insight. When qualitative and quantitative data agreed, this generated confidence for me that I was on the right path. When these data disagreed, I returned to the literature, and method descriptions to develop explanations and further refine my contexts and the contexts of my participants. Action research (similar to design based research) is grounded in practice and the design of experiences. It is personal and contextual and is therefore impossible to describe as objective or replicable. It is often used by educators to examine and improve some element of their teaching practice or the systems in which they work.”

Francisco Iniesto used action research within a Person-Centred Planning (PCP) perspective, designed to empower disabled learners to make their own choices and decisions by placing the individual at the centre of the planning process for improving accessibility in MOOCs:

“Learners were a useful source of data to explore the accessibility barriers and their solutions in using the technology and the learning designs they come up against when interacting with MOOCs. The data from the interviews helped to understand their motivations, the current accessibility barriers they have found, how they reacted to them, and their suggestions for desired solutions”.

Useful references for Action Research: Caruth (2018); Danermark et al. (2002); Freire (1994); Heron & Reason (1997); Ivankova (2015); Kemmis, McTaggart & Nixon (2013); Lewis & Sanderson (2011); Mertler (2014); Smith (1999). Warschauer (2003); Whyte, Greenwood & Lazes (1991)

Research Methods Handbook Copyright © 2020 by Rob Farrow; Francisco Iniesto; Martin Weller; and Rebecca Pitt is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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• Writing Tips

How to Conduct Action Research Effectively

4-minute read

• 20th April 2023

There are many ways to conduct research , and action research is a particularly useful method. If you’re wondering how you can conduct action research effectively, you’ve come to the right place! Check out our guide below.

What Is Action Research?

Action research is about more than just collecting data. It involves taking action, as the name suggests, based on the findings of the study. To conduct action research, you gather information and use it to enact some sort of change or improvement.

How To Conduct It Effectively

If you’re getting ready to do some action research yourself, take some time to prepare so that you end up with the best results. To set yourself up for success, follow these tips.

1.   Identify the Problem

Research aims to answer a question , fill a knowledge gap, or address an issue. Defining the problem clearly can help you come up with the most effective plan of action.

This isn’t always as straightforward as it may seem! Sometimes, the issue you’re initially looking into is actually the consequence of a deeper problem. For example, maybe lots of students in the same class are consistently receiving poor test grades. This could be due to many things, so to identify the problem, you might need to consider a variety of potential factors before narrowing in on your research plan.

2.   Plan To Collect the Most Relevant Data

Once you have a specific problem area to focus on, determine what kind of data will be most helpful for your study so you don’t waste time and resources gathering information you won’t end up using.

A key part of this step is making sure you have a reasonable source for the data and that it will be easy to collect . You should also have a system to keep it organized and recorded accurately.

3.   Examine Your Findings

Keeping your data organized, sort through it carefully , looking at one component at a time. Notice if any themes or patterns jump out from the numbers and make notes so you don’t lose track of them.

After doing this thoroughly, think about what variables you can change to generate more data. You may notice a strong connection between certain variables, but the underlying issue could still be elusive. By adjusting various factors, the root cause of the problem may start to reveal itself.

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Thinking about our example of students receiving poor grades, you might notice a correlation between poor performance and those who participate in extracurricular activities. The attributing factor(s), though, could be to do with the types of extracurricular activities, the number of them, or the day of the week they’re performed.

4.   Generate Action Ideas

Using your findings, come up with a list of potential actions that can be taken to solve the problem or make improvements. Write everything down, even ideas you’re not so sure about. Often, the most effective options pop up later on in the brainstorming process.

Next, pick out the most plausible and promising actions and try them out, one at a time. Be careful not to implement anything too permanent right away. Take note of how things change and what improvements are made. Once you’ve solidified the best plan of action, you can move on to making more permanent changes.

The Action Research Cycle

Once you’ve conducted action research effectively, you may notice other areas that could benefit from it. This is the beauty of action research – it’s ongoing and allows for constant improvement! Keep the cycle going by looking into more problem areas and using action research to address them.

Action research is a proactive and useful way of generating data about a problem and implementing changes to fix it. It’s often used in the classroom and other educational settings, so if you work in this field, action research could be particularly helpful to you.

If you’re writing a research paper , make sure you send your draft our way! Our editors will check it for spelling, grammar, referencing, and more. Try it out for free today.

Frequently Asked Questions

What is action research used for.

Action research is especially helpful in educational settings. It’s used as a problem-solving method to improve the learning environment for students.

What are the main types of research?

There are many research methods, with some of the most common being qualitative, deductive, action, exploratory, and quantitative.

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21 Action Research Examples (In Education)

Action research is an example of qualitative research . It refers to a wide range of evaluative or investigative methods designed to analyze professional practices and take action for improvement.

Commonly used in education, those practices could be related to instructional methods, classroom practices, or school organizational matters.

The creation of action research is attributed to Kurt Lewin , a German-American psychologist also considered to be the father of social psychology.

Gillis and Jackson (2002) offer a very concise definition of action research: “systematic collection and analysis of data for the purpose of taking action and making change” (p.264).

The methods of action research in education include:

• conducting in-class observations
• taking field notes
• surveying or interviewing teachers, administrators, or parents
• using audio and video recordings.

The goal is to identify problematic issues, test possible solutions, or simply carry-out continuous improvement.

There are several steps in action research : identify a problem, design a plan to resolve, implement the plan, evaluate effectiveness, reflect on results, make necessary adjustment and repeat the process.

Action Research Examples

• Digital literacy assessment and training: The school’s IT department conducts a survey on students’ digital literacy skills. Based on the results, a tailored training program is designed for different age groups.
• Library resources utilization study: The school librarian tracks the frequency and type of books checked out by students. The data is then used to curate a more relevant collection and organize reading programs.
• Extracurricular activities and student well-being: A team of teachers and counselors assess the impact of extracurricular activities on student mental health through surveys and interviews. Adjustments are made based on findings.
• Parent-teacher communication channels: The school evaluates the effectiveness of current communication tools (e.g., newsletters, apps) between teachers and parents. Feedback is used to implement a more streamlined system.
• Homework load evaluation: Teachers across grade levels assess the amount and effectiveness of homework given. Adjustments are made to ensure a balance between academic rigor and student well-being.
• Classroom environment and learning: A group of teachers collaborates to study the impact of classroom layouts and decorations on student engagement and comprehension. Changes are made based on the findings.
• Student feedback on curriculum content: High school students are surveyed about the relevance and applicability of their current curriculum. The feedback is then used to make necessary curriculum adjustments.
• Teacher mentoring and support: New teachers are paired with experienced mentors. Both parties provide feedback on the effectiveness of the mentoring program, leading to continuous improvements.
• Assessment of school transportation: The school board evaluates the efficiency and safety of school buses through surveys with students and parents. Necessary changes are implemented based on the results.
• Cultural sensitivity training: After conducting a survey on students’ cultural backgrounds and experiences, the school organizes workshops for teachers to promote a more inclusive classroom environment.
• Environmental initiatives and student involvement: The school’s eco-club assesses the school’s carbon footprint and waste management. They then collaborate with the administration to implement greener practices and raise environmental awareness.
• Working with parents through research: A school’s admin staff conduct focus group sessions with parents to identify top concerns.Those concerns will then be addressed and another session conducted at the end of the school year.
• Peer teaching observations and improvements: Kindergarten teachers observe other teachers handling class transition techniques to share best practices.
• PTA surveys and resultant action: The PTA of a district conducts a survey of members regarding their satisfaction with remote learning classes.The results will be presented to the school board for further action.
• Recording and reflecting: A school administrator takes video recordings of playground behavior and then plays them for the teachers. The teachers work together to formulate a list of 10 playground safety guidelines.
• Pre/post testing of interventions: A school board conducts a district wide evaluation of a STEM program by conducting a pre/post-test of students’ skills in computer programming.
• Focus groups of practitioners : The professional development needs of teachers are determined from structured focus group sessions with teachers and admin.
• School lunch research and intervention: A nutrition expert is hired to evaluate and improve the quality of school lunches.
• School nurse systematic checklist and improvements: The school nurse implements a bathroom cleaning checklist to monitor cleanliness after the results of a recent teacher survey revealed several issues.
• Wearable technologies for pedagogical improvements; Students wear accelerometers attached to their hips to gain a baseline measure of physical activity.The results will identify if any issues exist.
• School counselor reflective practice : The school counselor conducts a student survey on antisocial behavior and then plans a series of workshops for both teachers and parents.

Detailed Examples

1. cooperation and leadership.

A science teacher has noticed that her 9 th grade students do not cooperate with each other when doing group projects. There is a lot of arguing and battles over whose ideas will be followed.

So, she decides to implement a simple action research project on the matter. First, she conducts a structured observation of the students’ behavior during meetings. She also has the students respond to a short questionnaire regarding their notions of leadership.

She then designs a two-week course on group dynamics and leadership styles. The course involves learning about leadership concepts and practices . In another element of the short course, students randomly select a leadership style and then engage in a role-play with other students.

At the end of the two weeks, she has the students work on a group project and conducts the same structured observation as before. She also gives the students a slightly different questionnaire on leadership as it relates to the group.

She plans to analyze the results and present the findings at a teachers’ meeting at the end of the term.

2. Professional Development Needs

Two high-school teachers have been selected to participate in a 1-year project in a third-world country. The project goal is to improve the classroom effectiveness of local teachers. 

The two teachers arrive in the country and begin to plan their action research. First, they decide to conduct a survey of teachers in the nearby communities of the school they are assigned to.

The survey will assess their professional development needs by directly asking the teachers and administrators. After collecting the surveys, they analyze the results by grouping the teachers based on subject matter.

They discover that history and social science teachers would like professional development on integrating smartboards into classroom instruction. Math teachers would like to attend workshops on project-based learning, while chemistry teachers feel that they need equipment more than training.

The two teachers then get started on finding the necessary training experts for the workshops and applying for equipment grants for the science teachers.

3. Playground Accidents

The school nurse has noticed a lot of students coming in after having mild accidents on the playground. She’s not sure if this is just her perception or if there really is an unusual increase this year.  So, she starts pulling data from the records over the last two years. She chooses the months carefully and only selects data from the first three months of each school year.

She creates a chart to make the data more easily understood. Sure enough, there seems to have been a dramatic increase in accidents this year compared to the same period of time from the previous two years.

She shows the data to the principal and teachers at the next meeting. They all agree that a field observation of the playground is needed.

Those observations reveal that the kids are not having accidents on the playground equipment as originally suspected. It turns out that the kids are tripping on the new sod that was installed over the summer.

They examine the sod and observe small gaps between the slabs. Each gap is approximately 1.5 inches wide and nearly two inches deep. The kids are tripping on this gap as they run.

They then discuss possible solutions.

4. Differentiated Learning

Trying to use the same content, methods, and processes for all students is a recipe for failure. This is why modifying each lesson to be flexible is highly recommended. Differentiated learning allows the teacher to adjust their teaching strategy based on all the different personalities and learning styles they see in their classroom.

Of course, differentiated learning should undergo the same rigorous assessment that all teaching techniques go through. So, a third-grade social science teacher asks his students to take a simple quiz on the industrial revolution. Then, he applies differentiated learning to the lesson.

By creating several different learning stations in his classroom, he gives his students a chance to learn about the industrial revolution in a way that captures their interests. The different stations contain: short videos, fact cards, PowerPoints, mini-chapters, and role-plays.

At the end of the lesson, students get to choose how they demonstrate their knowledge. They can take a test, construct a PPT, give an oral presentation, or conduct a simulated TV interview with different characters.

During this last phase of the lesson, the teacher is able to assess if they demonstrate the necessary knowledge and have achieved the defined learning outcomes. This analysis will allow him to make further adjustments to future lessons.

5. Healthy Habits Program

While looking at obesity rates of students, the school board of a large city is shocked by the dramatic increase in the weight of their students over the last five years. After consulting with three companies that specialize in student physical health, they offer the companies an opportunity to prove their value.

So, the board randomly assigns each company to a group of schools. Starting in the next academic year, each company will implement their healthy habits program in 5 middle schools.

Preliminary data is collected at each school at the beginning of the school year. Each and every student is weighed, their resting heart rate, blood pressure and cholesterol are also measured.

After analyzing the data, it is found that the schools assigned to each of the three companies are relatively similar on all of these measures.

At the end of the year, data for students at each school will be collected again. A simple comparison of pre- and post-program measurements will be conducted. The company with the best outcomes will be selected to implement their program city-wide.

Action research is a great way to collect data on a specific issue, implement a change, and then evaluate the effects of that change. It is perhaps the most practical of all types of primary research .

Most likely, the results will be mixed. Some aspects of the change were effective, while other elements were not. That’s okay. This just means that additional modifications to the change plan need to be made, which is usually quite easy to do.

There are many methods that can be utilized, such as surveys, field observations , and program evaluations.

The beauty of action research is based in its utility and flexibility. Just about anyone in a school setting is capable of conducting action research and the information can be incredibly useful.

Aronson, E., & Patnoe, S. (1997). The jigsaw classroom: Building cooperation in the classroom (2nd ed.). New York: Addison Wesley Longman.

Gillis, A., & Jackson, W. (2002). Research Methods for Nurses: Methods and Interpretation . Philadelphia: F.A. Davis Company.

Lewin, K. (1946). Action research and minority problems. Journal of SocialIssues, 2 (4), 34-46.

Macdonald, C. (2012). Understanding participatory action research: A qualitative research methodology option. Canadian Journal of Action Research, 13 , 34-50. https://doi.org/10.33524/cjar.v13i2.37 Mertler, C. A. (2008). Action Research: Teachers as Researchers in the Classroom . London: Sage.

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Positive Punishment Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 25 Dissociation Examples (Psychology)
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ 15 Zone of Proximal Development Examples
• Dave Cornell (PhD) https://helpfulprofessor.com/author/dave-cornell-phd/ Perception Checking: 15 Examples and Definition

Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

• Chris Drew (PhD) #molongui-disabled-link 25 Positive Punishment Examples
• Chris Drew (PhD) #molongui-disabled-link 25 Dissociation Examples (Psychology)
• Chris Drew (PhD) #molongui-disabled-link 15 Zone of Proximal Development Examples
• Chris Drew (PhD) #molongui-disabled-link Perception Checking: 15 Examples and Definition

2 thoughts on “21 Action Research Examples (In Education)”

Where can I capture this article in a better user-friendly format, since I would like to provide it to my students in a Qualitative Methods course at the University of Prince Edward Island? It is a good article, however, it is visually disjointed in its current format. Thanks, Dr. Frank T. Lavandier

Hi Dr. Lavandier,

I’ve emailed you a word doc copy that you can use and edit with your class.

Best, Chris.

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Home » Research Paper Conclusion – Writing Guide and Examples

Research Paper Conclusion – Writing Guide and Examples

Table of Contents

Research Paper Conclusion

Definition:

A research paper conclusion is the final section of a research paper that summarizes the key findings, significance, and implications of the research. It is the writer’s opportunity to synthesize the information presented in the paper, draw conclusions, and make recommendations for future research or actions.

The conclusion should provide a clear and concise summary of the research paper, reiterating the research question or problem, the main results, and the significance of the findings. It should also discuss the limitations of the study and suggest areas for further research.

Parts of Research Paper Conclusion

The parts of a research paper conclusion typically include:

Restatement of the Thesis

The conclusion should begin by restating the thesis statement from the introduction in a different way. This helps to remind the reader of the main argument or purpose of the research.

Summary of Key Findings

The conclusion should summarize the main findings of the research, highlighting the most important results and conclusions. This section should be brief and to the point.

Implications and Significance

In this section, the researcher should explain the implications and significance of the research findings. This may include discussing the potential impact on the field or industry, highlighting new insights or knowledge gained, or pointing out areas for future research.

Limitations and Recommendations

It is important to acknowledge any limitations or weaknesses of the research and to make recommendations for how these could be addressed in future studies. This shows that the researcher is aware of the potential limitations of their work and is committed to improving the quality of research in their field.

Concluding Statement

The conclusion should end with a strong concluding statement that leaves a lasting impression on the reader. This could be a call to action, a recommendation for further research, or a final thought on the topic.

How to Write Research Paper Conclusion

Here are some steps you can follow to write an effective research paper conclusion:

• Restate the research problem or question: Begin by restating the research problem or question that you aimed to answer in your research. This will remind the reader of the purpose of your study.
• Summarize the main points: Summarize the key findings and results of your research. This can be done by highlighting the most important aspects of your research and the evidence that supports them.
• Discuss the implications: Discuss the implications of your findings for the research area and any potential applications of your research. You should also mention any limitations of your research that may affect the interpretation of your findings.
• Provide a conclusion : Provide a concise conclusion that summarizes the main points of your paper and emphasizes the significance of your research. This should be a strong and clear statement that leaves a lasting impression on the reader.
• Offer suggestions for future research: Lastly, offer suggestions for future research that could build on your findings and contribute to further advancements in the field.

Remember that the conclusion should be brief and to the point, while still effectively summarizing the key findings and implications of your research.

Example of Research Paper Conclusion

Here’s an example of a research paper conclusion:

Conclusion :

In conclusion, our study aimed to investigate the relationship between social media use and mental health among college students. Our findings suggest that there is a significant association between social media use and increased levels of anxiety and depression among college students. This highlights the need for increased awareness and education about the potential negative effects of social media use on mental health, particularly among college students.

Despite the limitations of our study, such as the small sample size and self-reported data, our findings have important implications for future research and practice. Future studies should aim to replicate our findings in larger, more diverse samples, and investigate the potential mechanisms underlying the association between social media use and mental health. In addition, interventions should be developed to promote healthy social media use among college students, such as mindfulness-based approaches and social media detox programs.

Overall, our study contributes to the growing body of research on the impact of social media on mental health, and highlights the importance of addressing this issue in the context of higher education. By raising awareness and promoting healthy social media use among college students, we can help to reduce the negative impact of social media on mental health and improve the well-being of young adults.

Purpose of Research Paper Conclusion

The purpose of a research paper conclusion is to provide a summary and synthesis of the key findings, significance, and implications of the research presented in the paper. The conclusion serves as the final opportunity for the writer to convey their message and leave a lasting impression on the reader.

The conclusion should restate the research problem or question, summarize the main results of the research, and explain their significance. It should also acknowledge the limitations of the study and suggest areas for future research or action.

Overall, the purpose of the conclusion is to provide a sense of closure to the research paper and to emphasize the importance of the research and its potential impact. It should leave the reader with a clear understanding of the main findings and why they matter. The conclusion serves as the writer’s opportunity to showcase their contribution to the field and to inspire further research and action.

When to Write Research Paper Conclusion

The conclusion of a research paper should be written after the body of the paper has been completed. It should not be written until the writer has thoroughly analyzed and interpreted their findings and has written a complete and cohesive discussion of the research.

Before writing the conclusion, the writer should review their research paper and consider the key points that they want to convey to the reader. They should also review the research question, hypotheses, and methodology to ensure that they have addressed all of the necessary components of the research.

Once the writer has a clear understanding of the main findings and their significance, they can begin writing the conclusion. The conclusion should be written in a clear and concise manner, and should reiterate the main points of the research while also providing insights and recommendations for future research or action.

Characteristics of Research Paper Conclusion

The characteristics of a research paper conclusion include:

• Clear and concise: The conclusion should be written in a clear and concise manner, summarizing the key findings and their significance.
• Comprehensive: The conclusion should address all of the main points of the research paper, including the research question or problem, the methodology, the main results, and their implications.
• Future-oriented : The conclusion should provide insights and recommendations for future research or action, based on the findings of the research.
• Impressive : The conclusion should leave a lasting impression on the reader, emphasizing the importance of the research and its potential impact.
• Objective : The conclusion should be based on the evidence presented in the research paper, and should avoid personal biases or opinions.
• Unique : The conclusion should be unique to the research paper and should not simply repeat information from the introduction or body of the paper.

Advantages of Research Paper Conclusion

The advantages of a research paper conclusion include:

• Summarizing the key findings : The conclusion provides a summary of the main findings of the research, making it easier for the reader to understand the key points of the study.
• Emphasizing the significance of the research: The conclusion emphasizes the importance of the research and its potential impact, making it more likely that readers will take the research seriously and consider its implications.
• Providing recommendations for future research or action : The conclusion suggests practical recommendations for future research or action, based on the findings of the study.
• Providing closure to the research paper : The conclusion provides a sense of closure to the research paper, tying together the different sections of the paper and leaving a lasting impression on the reader.
• Demonstrating the writer’s contribution to the field : The conclusion provides the writer with an opportunity to showcase their contribution to the field and to inspire further research and action.

Limitations of Research Paper Conclusion

While the conclusion of a research paper has many advantages, it also has some limitations that should be considered, including:

• I nability to address all aspects of the research: Due to the limited space available in the conclusion, it may not be possible to address all aspects of the research in detail.
• Subjectivity : While the conclusion should be objective, it may be influenced by the writer’s personal biases or opinions.
• Lack of new information: The conclusion should not introduce new information that has not been discussed in the body of the research paper.
• Lack of generalizability: The conclusions drawn from the research may not be applicable to other contexts or populations, limiting the generalizability of the study.
• Misinterpretation by the reader: The reader may misinterpret the conclusions drawn from the research, leading to a misunderstanding of the findings.

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Muhammad Hassan

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• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

The conclusion is intended to help the reader understand why your research should matter to them after they have finished reading the paper. A conclusion is not merely a summary of the main topics covered or a re-statement of your research problem, but a synthesis of key points and, if applicable, where you recommend new areas for future research. For most college-level research papers, one or two well-developed paragraphs is sufficient for a conclusion, although in some cases, more paragraphs may be required in summarizing key findings and their significance.

Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University.

Importance of a Good Conclusion

A well-written conclusion provides you with important opportunities to demonstrate to the reader your understanding of the research problem. These include:

• Presenting the last word on the issues you raised in your paper . Just as the introduction gives a first impression to your reader, the conclusion offers a chance to leave a lasting impression. Do this, for example, by highlighting key findings in your analysis that advance new understanding about the research problem, that are unusual or unexpected, or that have important implications applied to practice.
• Summarizing your thoughts and conveying the larger significance of your study . The conclusion is an opportunity to succinctly re-emphasize  the "So What?" question by placing the study within the context of how your research advances past research about the topic.
• Identifying how a gap in the literature has been addressed . The conclusion can be where you describe how a previously identified gap in the literature [described in your literature review section] has been filled by your research.
• Demonstrating the importance of your ideas . Don't be shy. The conclusion offers you the opportunity to elaborate on the impact and significance of your findings. This is particularly important if your study approached examining the research problem from an unusual or innovative perspective.
• Introducing possible new or expanded ways of thinking about the research problem . This does not refer to introducing new information [which should be avoided], but to offer new insight and creative approaches for framing or contextualizing the research problem based on the results of your study.

Bunton, David. “The Structure of PhD Conclusion Chapters.” Journal of English for Academic Purposes 4 (July 2005): 207–224; Conclusions. The Writing Center. University of North Carolina; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Conclusions. The Writing Lab and The OWL. Purdue University; Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Structure and Writing Style

I.  General Rules

The function of your paper's conclusion is to restate the main argument . It reminds the reader of the strengths of your main argument(s) and reiterates the most important evidence supporting those argument(s). Do this by stating clearly the context, background, and necessity of pursuing the research problem you investigated in relation to an issue, controversy, or a gap found in the literature. Make sure, however, that your conclusion is not simply a repetitive summary of the findings. This reduces the impact of the argument(s) you have developed in your essay.

When writing the conclusion to your paper, follow these general rules:

• Present your conclusions in clear, simple language. Re-state the purpose of your study, then describe how your findings differ or support those of other studies and why [i.e., what were the unique or new contributions your study made to the overall research about your topic?].
• Do not simply reiterate your findings or the discussion of your results. Provide a synthesis of arguments presented in the paper to show how these converge to address the research problem and the overall objectives of your study.
• Indicate opportunities for future research if you haven't already done so in the discussion section of your paper. Highlighting the need for further research provides the reader with evidence that you have an in-depth awareness of the research problem and that further investigations should take place.

Consider the following points to help ensure your conclusion is presented well:

• If the argument or purpose of your paper is complex, you may need to summarize the argument for your reader.
• If, prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the end of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration that returns the topic to the context provided by the introduction or within a new context that emerges from the data. 

The conclusion also provides a place for you to persuasively and succinctly restate the research problem, given that the reader has now been presented with all the information about the topic . Depending on the discipline you are writing in, the concluding paragraph may contain your reflections on the evidence presented. However, the nature of being introspective about the research you have conducted will depend on the topic and whether your professor wants you to express your observations in this way.

NOTE : If asked to think introspectively about the topics, do not delve into idle speculation. Being introspective means looking within yourself as an author to try and understand an issue more deeply, not to guess at possible outcomes or make up scenarios not supported by the evidence.

II.  Developing a Compelling Conclusion

Although an effective conclusion needs to be clear and succinct, it does not need to be written passively or lack a compelling narrative. Strategies to help you move beyond merely summarizing the key points of your research paper may include any of the following strategies:

• If your essay deals with a critical, contemporary problem, warn readers of the possible consequences of not attending to the problem proactively.
• Recommend a specific course or courses of action that, if adopted, could address a specific problem in practice or in the development of new knowledge.
• Cite a relevant quotation or expert opinion already noted in your paper in order to lend authority and support to the conclusion(s) you have reached [a good place to look is research from your literature review].
• Explain the consequences of your research in a way that elicits action or demonstrates urgency in seeking change.
• Restate a key statistic, fact, or visual image to emphasize the most important finding of your paper.
• If your discipline encourages personal reflection, illustrate your concluding point by drawing from your own life experiences.
• Return to an anecdote, an example, or a quotation that you presented in your introduction, but add further insight derived from the findings of your study; use your interpretation of results to recast it in new or important ways.
• Provide a "take-home" message in the form of a succinct, declarative statement that you want the reader to remember about your study.

III. Problems to Avoid

Failure to be concise Your conclusion section should be concise and to the point. Conclusions that are too lengthy often have unnecessary information in them. The conclusion is not the place for details about your methodology or results. Although you should give a summary of what was learned from your research, this summary should be relatively brief, since the emphasis in the conclusion is on the implications, evaluations, insights, and other forms of analysis that you make. Strategies for writing concisely can be found here .

Failure to comment on larger, more significant issues In the introduction, your task was to move from the general [the field of study] to the specific [the research problem]. However, in the conclusion, your task is to move from a specific discussion [your research problem] back to a general discussion [i.e., how your research contributes new understanding or fills an important gap in the literature]. In short, the conclusion is where you should place your research within a larger context [visualize your paper as an hourglass--start with a broad introduction and review of the literature, move to the specific analysis and discussion, conclude with a broad summary of the study's implications and significance].

Failure to reveal problems and negative results Negative aspects of the research process should never be ignored. These are problems, deficiencies, or challenges encountered during your study should be summarized as a way of qualifying your overall conclusions. If you encountered negative or unintended results [i.e., findings that are validated outside the research context in which they were generated], you must report them in the results section and discuss their implications in the discussion section of your paper. In the conclusion, use your summary of the negative results as an opportunity to explain their possible significance and/or how they may form the basis for future research.

Failure to provide a clear summary of what was learned In order to be able to discuss how your research fits within your field of study [and possibly the world at large], you need to summarize briefly and succinctly how it contributes to new knowledge or a new understanding about the research problem. This element of your conclusion may be only a few sentences long.

Failure to match the objectives of your research Often research objectives in the social sciences change while the research is being carried out. This is not a problem unless you forget to go back and refine the original objectives in your introduction. As these changes emerge they must be documented so that they accurately reflect what you were trying to accomplish in your research [not what you thought you might accomplish when you began].

Resist the urge to apologize If you've immersed yourself in studying the research problem, you presumably should know a good deal about it [perhaps even more than your professor!]. Nevertheless, by the time you have finished writing, you may be having some doubts about what you have produced. Repress those doubts! Don't undermine your authority by saying something like, "This is just one approach to examining this problem; there may be other, much better approaches that...." The overall tone of your conclusion should convey confidence to the reader.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Concluding Paragraphs. College Writing Center at Meramec. St. Louis Community College; Conclusions. The Writing Center. University of North Carolina; Conclusions. The Writing Lab and The OWL. Purdue University; Freedman, Leora  and Jerry Plotnick. Introductions and Conclusions. The Lab Report. University College Writing Centre. University of Toronto; Leibensperger, Summer. Draft Your Conclusion. Academic Center, the University of Houston-Victoria, 2003; Make Your Last Words Count. The Writer’s Handbook. Writing Center. University of Wisconsin Madison; Miquel, Fuster-Marquez and Carmen Gregori-Signes. “Chapter Six: ‘Last but Not Least:’ Writing the Conclusion of Your Paper.” In Writing an Applied Linguistics Thesis or Dissertation: A Guide to Presenting Empirical Research . John Bitchener, editor. (Basingstoke,UK: Palgrave Macmillan, 2010), pp. 93-105; Tips for Writing a Good Conclusion. Writing@CSU. Colorado State University; Kretchmer, Paul. Twelve Steps to Writing an Effective Conclusion. San Francisco Edit, 2003-2008; Writing Conclusions. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Writing: Considering Structure and Organization. Institute for Writing Rhetoric. Dartmouth College.

Writing Tip

Don't Belabor the Obvious!

Avoid phrases like "in conclusion...," "in summary...," or "in closing...." These phrases can be useful, even welcome, in oral presentations. But readers can see by the tell-tale section heading and number of pages remaining to read, when an essay is about to end. You'll irritate your readers if you belabor the obvious.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8.

Another Writing Tip

New Insight, Not New Information!

Don't surprise the reader with new information in your conclusion that was never referenced anywhere else in the paper and, as such, the conclusion rarely has citations to sources. If you have new information to present, add it to the discussion or other appropriate section of the paper. Note that, although no actual new information is introduced, the conclusion, along with the discussion section, is where you offer your most "original" contributions in the paper; the conclusion is where you describe the value of your research, demonstrate that you understand the material that you’ve presented, and locate your findings within the larger context of scholarship on the topic, including describing how your research contributes new insights or valuable insight to that scholarship.

Assan, Joseph. "Writing the Conclusion Chapter: The Good, the Bad and the Missing." Liverpool: Development Studies Association (2009): 1-8; Conclusions. The Writing Center. University of North Carolina.

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• Last Updated: Mar 26, 2024 10:40 AM
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200+ List of Topics for Action Research in the Classroom

In the dynamic landscape of education, teachers are continually seeking innovative ways to enhance their teaching practices and improve student outcomes. Action research in the classroom is a powerful tool that allows educators to investigate and address specific challenges, leading to positive changes in teaching methods and learning experiences. 

Selecting the right topics from the list of topics for action research in the classroom is crucial for ensuring meaningful insights and improvements. In this blog post, we will explore the significance of action research in the classroom, the criteria for selecting impactful topics, and provide an extensive list of potential research areas.

Understanding: What is Action Research

Table of Contents

Action research is a reflective process that empowers teachers to systematically investigate and analyze their own teaching practices. Unlike traditional research, action research is conducted by educators within their own classrooms, emphasizing a collaborative and participatory approach. 

This method enables teachers to identify challenges, implement interventions, and assess the effectiveness of their actions.

How to Select Topics From List of Topics for Action Research in the Classroom

Choosing the right topic is the first step in the action research process. The selected topic should align with classroom goals, address students’ needs, be feasible to implement, and have the potential for positive impact. Teachers should consider the following criteria when selecting action research topics:

• Alignment with Classroom Goals and Objectives: The chosen topic should directly contribute to the overall goals and objectives of the classroom. Whether it’s improving student engagement, enhancing learning outcomes, or fostering a positive classroom environment, the topic should align with the broader educational context.
• Relevance to Students’ Needs and Challenges: Effective action research addresses the specific needs and challenges faced by students. Teachers should identify areas where students may be struggling or where improvement is needed, ensuring that the research directly impacts the learning experiences of the students.
• Feasibility and Practicality: The feasibility of the research is crucial. Teachers must choose topics that are practical to implement within the constraints of the classroom setting. This includes considering available resources, time constraints, and the level of support from school administrators.
• Potential for Positive Impact: The ultimate goal of action research is to bring about positive change. Teachers should carefully assess the potential impact of their research, aiming for improvements in teaching methods, student performance, or overall classroom dynamics.

List of Topics for Action Research in the Classroom

• Impact of Mindfulness Practices on Student Focus
• The Effectiveness of Peer Tutoring in Mathematics
• Strategies for Encouraging Critical Thinking in History Classes
• Using Gamification to Enhance Learning in Science
• Investigating the Impact of Flexible Seating Arrangements
• Assessing the Benefits of Project-Based Learning in Language Arts
• The Influence of Classroom Decor on Student Motivation
• Examining the Use of Learning Stations for Differentiation
• Implementing Reflective Journals to Enhance Writing Skills
• Exploring the Impact of Flipped Classroom Models
• Analyzing the Effects of Homework on Student Performance
• The Role of Positive Reinforcement in Classroom Behavior
• Investigating the Impact of Classroom Libraries on Reading Proficiency
• Strategies for Fostering a Growth Mindset in Students
• Assessing the Benefits of Cross-Curricular Integration
• Using Technology to Enhance Vocabulary Acquisition
• The Impact of Outdoor Learning on Student Engagement
• Investigating the Relationship Between Attendance and Academic Success
• The Role of Parental Involvement in Homework Completion
• Assessing the Impact of Classroom Rituals on Community Building
• Strategies for Increasing Student Participation in Discussions
• Exploring the Influence of Classroom Lighting on Student Alertness
• Investigating the Impact of Daily Agendas on Time Management
• The Effectiveness of Socratic Seminars in Social Studies
• Analyzing the Use of Graphic Organizers for Concept Mapping
• Implementing Student-Led Conferences for Goal Setting
• Examining the Effects of Mind Mapping on Information Retention
• The Influence of Classroom Temperature on Academic Performance
• Investigating the Benefits of Cooperative Learning Strategies
• Strategies for Addressing Test Anxiety in Students
• Assessing the Impact of Positive Affirmations on Student Confidence
• The Use of Literature Circles to Enhance Reading Comprehension
• Exploring the Effects of Classroom Noise Levels on Concentration
• Investigating the Benefits of Cross-Grade Collaborations
• Analyzing the Impact of Goal Setting on Student Achievement
• Implementing Interactive Notebooks for Conceptual Understanding
• The Effectiveness of Response to Intervention (RTI) Programs
• Strategies for Integrating Social-Emotional Learning (SEL)
• Investigating the Impact of Classroom Discussions on Critical Thinking
• The Role of Brain Breaks in Enhancing Student Focus
• Assessing the Benefits of Inquiry-Based Learning in Science
• Exploring the Effects of Music on Studying and Retention
• Investigating the Use of Learning Contracts for Individualized Learning
• The Influence of Classroom Colors on Mood and Learning
• Strategies for Promoting Collaborative Problem-Solving
• Analyzing the Impact of Flexible Scheduling on Student Productivity
• The Effectiveness of Mindful Breathing Exercises on Stress Reduction
• Investigating the Benefits of Service Learning Projects
• The Role of Peer Assessment in Improving Writing Skills
• Exploring the Impact of Field Trips on Cultural Competency
• Assessing the Benefits of Personalized Learning Plans
• Strategies for Differentiating Instruction in Large Classrooms
• Investigating the Influence of Teacher-Student Relationships on Learning
• The Effectiveness of Vocabulary Games in Foreign Language Classes
• Analyzing the Impact of Classroom Discussions on Civic Engagement
• Implementing Goal-Setting Strategies for Test Preparation
• The Role of Classroom Celebrations in Building a Positive Environment
• Strategies for Enhancing Student Reflection and Metacognition
• Investigating the Effects of Positive Behavior Supports (PBS)
• The Influence of Classroom Humor on Student Engagement
• Assessing the Benefits of Student-Led Research Projects
• Exploring the Impact of Timed vs. Untimed Tests on Anxiety
• Investigating the Use of Educational Podcasts for Learning
• The Effectiveness of Debate Activities in Developing Persuasive Skills
• Analyzing the Impact of Mindful Walking Breaks on Concentration
• Strategies for Promoting Digital Citizenship in the Classroom
• The Role of Visualization Techniques in Mathematics Learning
• Assessing the Benefits of Classroom Agreements for Behavior
• Exploring the Effects of Goal-Setting in Physical Education
• Investigating the Influence of Classroom Seating Charts on Behavior
• The Effectiveness of Peer Editing in Improving Writing Skills
• Strategies for Integrating Cultural Competency in History Lessons
• Analyzing the Impact of Classroom Pets on Student Well-Being
• The Role of Morning Meetings in Building Classroom Community
• Investigating the Benefits of Using Learning Centers in Elementary Schools
• Exploring the Effects of Virtual Reality in Geography Education
• Assessing the Impact of Homework Choice on Student Motivation
• Strategies for Promoting Growth Mindset in Mathematics
• The Influence of Classroom Layout on Group Collaboration
• Investigating the Benefits of Mindful Listening Practices
• The Effectiveness of Using Real-World Examples in Science Lessons
• Analyzing the Impact of Student-Led Assessments on Accountability
• Exploring the Use of Learning Contracts for Student Responsibility
• Investigating the Benefits of Teaching Digital Literacy Skills
• Strategies for Implementing Peer Mentoring Programs
• The Role of Graphic Novels in Promoting Literacy
• Assessing the Impact of Flexible Grouping in Mathematics Classes
• The Effectiveness of Using Storytelling for Conceptual Understanding
• Investigating the Influence of Classroom Rituals on Attendance
• Exploring the Benefits of Mindfulness Practices in Physical Education
• Strategies for Integrating Social Justice Education in the Curriculum
• Analyzing the Impact of Goal-Setting on Homework Completion
• The Role of Classroom Mindfulness Activities in Stress Reduction
• Investigating the Benefits of Using Educational Apps for Vocabulary
• The Effectiveness of Using Drama in History Lessons
• Assessing the Impact of Classroom Routines on Time Management
• Exploring the Influence of Teacher-Student Rapport on Academic Achievement
• Strategies for Promoting Active Listening Skills in the Classroom
• Investigating the Benefits of Using Concept Mapping in Science
• The Role of Classroom Socratic Seminars in Developing Critical Thinking
• Assessing the Impact of Mindful Eating Practices on Student Focus
• Exploring the Effects of Flipped Learning in Physical Education
• Investigating the Benefits of Using Educational Games for Math Fluency
• The Effectiveness of Peer Assessment in Art Classes
• Strategies for Fostering Creativity in Science Education
• Analyzing the Impact of Morning Stretches on Student Alertness
• The Role of Classroom Discussions in Enhancing Social Studies Learning
• Investigating the Benefits of Using Augmented Reality in History Lessons
• Assessing the Impact of Growth Mindset Interventions on Test Anxiety
• Strategies for Incorporating Environmental Education in the Curriculum
• The Effectiveness of Using Conceptual Maps in Literature Analysis
• Exploring the Influence of Classroom Lighting on Reading Comprehension
• Investigating the Benefits of Using Learning Apps for Language Acquisition
• The Role of Classroom Experiments in Science Education
• Analyzing the Impact of Mindful Breathing Exercises on Test Performance
• Strategies for Promoting Collaborative Problem-Solving in Mathematics
• Assessing the Benefits of Mindfulness Practices in Physical Education
• Exploring the Effects of Flexible Seating on Student Collaboration
• Investigating the Influence of Homework Choice on Student Motivation
• The Effectiveness of Using Educational Podcasts for History Learning
• Strategies for Integrating Sustainability Education Across Subjects
• Analyzing the Impact of Mindful Writing Practices on Language Arts Skills
• The Role of Peer Teaching in Enhancing Understanding of Complex Concepts
• Investigating the Benefits of Using Digital Storytelling in Literature Classes
• The Effectiveness of Inquiry-Based Learning in Social Studies
• Assessing the Impact of Student-Led Book Clubs on Reading Engagement
• Strategies for Incorporating Financial Literacy in Mathematics Education
• Exploring the Influence of Classroom Decor on Science Interest
• Investigating the Benefits of Mindful Movement Breaks in the Classroom
• The Role of Reflection Journals in Developing Critical Thinking Skills
• Analyzing the Impact of Virtual Field Trips on Geography Learning
• Strategies for Promoting Inclusive Physical Education Practices
• Assessing the Benefits of Using Educational Board Games for Learning
• The Effectiveness of Mindfulness Practices in Foreign Language Classes
• Investigating the Influence of Classroom Rituals on Academic Rigor
• Exploring the Impact of Student-Led Conferences on Goal Setting
• The Role of Mindful Listening Practices in Improving Communication Skills
• Investigating the Benefits of Using Educational Apps for Science Exploration
• Analyzing the Effectiveness of Socratic Seminars in Philosophy Classes
• Strategies for Promoting Gender Equity in STEM Education
• Assessing the Impact of Classroom Celebrations on Student Well-Being
• The Effectiveness of Using Debate Activities in Language Arts
• Exploring the Influence of Positive Affirmations on Classroom Climate
• Investigating the Benefits of Using Concept Mapping in History Essays
• Strategies for Incorporating Media Literacy in Social Studies
• Analyzing the Impact of Mindful Reflection Practices on Homework Completion
• The Role of Peer Collaboration in Enhancing Artistic Skills
• Investigating the Benefits of Using Educational Apps for Vocabulary Acquisition
• The Effectiveness of Mindful Breathing Exercises in Test Preparation
• Assessing the Impact of Flipped Learning in Science Laboratories
• Strategies for Promoting Civic Engagement in Social Studies Classes
• Exploring the Influence of Outdoor Learning on Scientific Inquiry
• Investigating the Benefits of Using Learning Stations for Literature Analysis
• The Role of Mindful Movement in Improving Physical Education Experiences
• Analyzing the Effectiveness of Virtual Reality in Language Learning
• Strategies for Incorporating Global Perspectives in Geography Education
• Assessing the Impact of Mindful Coloring Activities on Stress Reduction
• The Effectiveness of Using Educational Games for History Review
• Investigating the Benefits of Mindful Breathing Exercises in Mathematics
• Exploring the Influence of Classroom Rituals on Study Habits
• The Role of Mindful Listening Practices in Enhancing Oral Communication
• Analyzing the Impact of Student-Led Workshops on Study Skills
• Strategies for Promoting Critical Media Literacy in Language Arts
• Assessing the Benefits of Mindfulness Practices in Physical Fitness
• The Effectiveness of Using Educational Apps for Music Appreciation
• Investigating the Influence of Classroom Decor on Artistic Expression
• Exploring the Impact of Mindful Eating Practices on Nutrition Awareness
• The Role of Peer Assessment in Improving Science Fair Projects
• Analyzing the Benefits of Mindful Breathing Exercises in History Classes
• Strategies for Promoting Teamwork in Physical Education
• Assessing the Impact of Classroom Celebrations on Cultural Understanding
• The Effectiveness of Using Conceptual Maps in Geography Education
• Investigating the Benefits of Mindful Movement Breaks in Mathematics
• The Role of Mindful Listening Practices in Improving Musical Skills
• Analyzing the Impact of Student-Led Discussions in Philosophy Classes
• Strategies for Incorporating Environmental Stewardship in Science Education
• Assessing the Benefits of Using Educational Games for Physical Fitness
• Exploring the Influence of Classroom Decor on Mathematical Interest
• Investigating the Effectiveness of Virtual Reality in Art Appreciation
• The Role of Mindful Movement in Enhancing Physical Education Experiences
• Strategies for Promoting Cultural Competency in Language Arts
• Analyzing the Impact of Mindful Breathing Exercises on Test Anxiety
• The Effectiveness of Using Educational Apps for Science Exploration
• Investigating the Benefits of Peer Teaching in Mathematics Classes
• Exploring the Influence of Classroom Rituals on Language Arts Skills
• Assessing the Impact of Mindful Coloring Activities on Creative Expression
• The Role of Mindful Listening Practices in Improving Public Speaking
• Investigating the Benefits of Using Learning Stations for History Learning
• The Effectiveness of Peer Assessment in Improving Writing Skills
• Strategies for Promoting Digital Literacy in Geography Education
• Analyzing the Impact of Mindful Eating Practices on Healthy Habits
• Assessing the Benefits of Using Educational Games for Social Studies
• The Effectiveness of Mindful Movement Breaks in Science Education
• Exploring the Influence of Classroom Decor on Writing Motivation
• Investigating the Role of Mindfulness Practices in Mathematics Anxiety
• Strategies for Incorporating Financial Literacy in Social Studies
• Analyzing the Benefits of Using Concept Mapping in Science Labs
• The Role of Mindful Breathing Exercises in Improving Music Education
• Exploring the Impact of Virtual Reality on Foreign Language Acquisition
• Assessing the Benefits of Mindful Movement Breaks in History Classes

Tips for Conducting Action Research in the Classroom

• Setting Clear Research Goals and Objectives: Clearly define the goals and objectives of the research to ensure a focused and purposeful investigation.
• Involving Stakeholders in the Research Process: Engage students, parents, and colleagues in the research process to gather diverse perspectives and insights.
• Collecting and Analyzing Relevant Data: Use a variety of data collection methods, such as surveys, observations, and assessments, to gather comprehensive and meaningful data.
• Reflecting on Findings and Adjusting Teaching Practices: Regularly reflect on the research findings and be open to adjusting teaching practices based on the insights gained from the research.

Case Studies or Examples

Highlighting successful action research projects provides inspiration and practical insights for teachers. 

Sharing case studies or examples of impactful research can demonstrate the positive outcomes and improvements that can result from well-conducted action research.

In conclusion, action research is a valuable tool for educators seeking to enhance their teaching practices and improve student outcomes. 

Selecting the right topics from a list of topics for action research in the classroom is crucial for the success of action research projects, and teachers should consider alignment with goals, relevance to students, feasibility, and potential impact. 

By exploring a diverse range of topics, teachers can embark on meaningful action research journeys, contributing to the continuous improvement of education.

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Open Access

Peer-reviewed

Research Article

Emotional signatures of climate policy support

Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Center for Climate Change Communication, George Mason University, Fairfax, Virginia, United States of America

Roles Data curation, Writing – review & editing

Roles Funding acquisition, Writing – review & editing

Affiliation Yale Program on Climate Change Communication, Yale University, New Haven, Connecticut, United States of America

• Teresa A. Myers, 
• Connie Roser-Renouf, 
• Anthony Leiserowitz, 
• Edward Maibach

• Published: March 27, 2024
• https://doi.org/10.1371/journal.pclm.0000381
• Reader Comments

The optimal emotional tone for climate communication has been debated by scholars and the press, but little is known about the effects of emotions on different types of policy support. In this paper we examine multiple discrete emotions people experience in reaction to climate change, and assess the strength of these emotions as predictors of support for different types of mitigation and adaptation policies. Using multi-wave, cross-sectional, nationally representative samples of American adults, we test whether guilt, anger, hope, fear, and sadness are uniquely associated with support for different types of climate policies. Guilt is most strongly related to support for personally costly policies, hope to support for proactive policies, and fear to support for regulatory policies. This research suggests that communicators should consider how their climate campaign’s emotional tone aligns with their policy goals.

Citation: Myers TA, Roser-Renouf C, Leiserowitz A, Maibach E (2024) Emotional signatures of climate policy support. PLOS Clim 3(3): e0000381. https://doi.org/10.1371/journal.pclm.0000381

Editor: Ferdous Ahmed, IUBAT: International University of Business Agriculture and Technology, MALAYSIA

Received: December 7, 2022; Accepted: February 13, 2024; Published: March 27, 2024

Copyright: © 2024 Myers et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Data are available in the supporting information files.

Funding: Funding sources are: The 11th Hour Project (AL), the Energy Foundation (AL, TM, & EM), the Grantham Foundation for Protection of the Environment (AL), and the MacArthur Foundation (AL). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

" You are right to be frustrated . Folks in my generation have not done enough to deal with a potentially cataclysmic problem that you now stand to inherit…I want you to stay angry . I want you to stay frustrated . Channel that anger , harness that frustration , keep pushing harder and harder for more because that’s what’s required to meet this challenge . " - Former U . S . President Barack Obama , November 8 , 2021 , at COP26 in Glasgow , addressing youth climate activists [ 1 ]

As we enter a seminal era in responding to the climate crisis, leaders (such as former President Obama, quoted above) are using emotionally evocative language in an attempt to harness the myriad of emotional responses to the climate crisis and drive greater demand for action. Researchers, too, have identified emotions as critical to climate responses. Brosch concludes: “Recent empirical and meta-analytic research has consistently found affect and emotions experienced toward climate change to be among the most important predictors of climate change-related judgments” [ 2 , p. 25, emphasis added, see also 3 , 4 ].

Although for many years emotions were discredited as elements of rational consideration [see 5 , 6 , for reviews of the theoretical development], contemporary work, such as the Affective Intelligence Model, has demonstrated that affective emotional reactions serve as cues that draw attention to an issue and signal that an issue deserves prioritization; in effect incorporating emotional cues into a rational decision framework [ 7 , 8 ]. Similarly, according to Nabi [ 8 ], discrete emotions can be frames that privilege certain information and influence future judgments. Core to this perspective is the idea that different emotions result from distinct situational appraisals [ 9 – 12 ] and lead to divergent action paths, or tendencies [13–16; also called “action readiness,” 5 ]; with some arguing that what distinguishes emotions from transient experiences of feeling (un)pleasantness are these proclivities to act in different ways in response to an event, defining emotions as “felt action tendencies” [ 9 ]. Emotions, in sum, arise as a response to appraising a situation as relevant to a person’s interests or welfare; distinct (or discrete) emotions emerge depending on the multiple ways that individuals assess the situation [ 2 , 14 , 17 ]. In turn, these emotional responses prime individuals to act.

Therefore, as emotional reactions lead to different action tendencies, and emotions are strong predictors of climate policy support, understanding the role of emotional reactions in responding to the climate crisis should include examining how these emotions are associated with specific preferences for policy action. In this paper we consider how different emotions (guilt, anger, hope, sadness, and fear) relate to distinct policy preferences, asking the question: are different discrete emotional reactions to climate change associated with support for different types of climate policies?

The connections between emotional responses to climate change, their corresponding action tendencies, and policy preferences

Many emotions have been linked to climate change and a long tradition of research in the psychological sciences has shown that these emotional states give rise to distinct action tendencies (examples described in detail below) [ 13 – 15 ]. Researchers have argued that it is essential to differentiate and clarify the ways that emotions are linked to various outcomes [ 17 ], but to this point, the link between emotions and policy support has not systematically differentiated the types of policy content, although broader work on climate policy support has sought to clarify various dimensions of climate policy that can influence support [ 18 , 19 ]. Therefore, taking several of the emotions most frequently found concerning climate change–guilt, anger, hope, sadness, and fear–we examine how the action tendencies associated with these emotions may lead to specific policy preferences.

Guilt → Internal blame → Atonement → Support for personally costly policies.

The emotional experience of guilt arises from an appraisal of internal blame, that is connecting a negative situation with one’s own (in)actions [ 14 ]. This experience of distress associated with believing oneself (or one’s ingroup) to have contributed negatively to an outcome, has been shown to lead to behavior that seeks to repair the harm caused [ 20 , 21 ]. In the general environmental context, guilt has been positively associated with both intention and behavior [ 22 – 24 ], including willingness to engage in personally costly practices such as conserving energy and paying green taxes [ 25 ]. In the context of climate change, research has shown that individuals experience guilt when responsibility is focused on individuals, and that such guilt feelings are associated with a desire for atonement, that is to make right the wrong the person believes they have committed [ 26 ]. Atonement action tendencies may therefore be more associated with support for personally costly policy options, in comparison to other types of public policies. Personally costly policies are policy mechanisms where the costs are clear to the public, rather than hidden as is often the case [ 27 , 28 ], and include examples like paying a fee to promote renewable energy or having a gasoline tax.

• H1: Guilt will be more strongly related to support for personally costly policies than other policies.

Anger → External blame → Retribution → Support for regulatory policies.

Conversely, anger arises when an individual assesses that the blame for a negative situation is external. This external blame then leads to the tendency to seek retribution to neutralize the obstacle [ 29 ]. Anger arising from perceiving injustice that resulted in unfair outcomes has been associated with participation in collective action [ 30 ] and desire for retribution [ 13 ]. Anger is often centered on a concrete and identifiable culprit as the cause of the situation [ 12 , 14 ]. This tendency toward retribution may manifest in increased support for regulatory policies . According to Lemaire, “regulation is commonly referred to as the government’s ‘stick.’ Regulatory instruments are used to define norms and acceptable behavior, or to limit activities in a given society. The law, backed up with the threat of sanction, represents the “stick” used to prescribe or prevent certain types of behavior. Any infringement of the rules brings the specter of sanction” (p. 59) [ 31 ]. In the context of climate policy options, we anticipate that anger will be more associated with a preference to regulate emissions from carbon producers, in an attempt to address the perceived wrongs that they have perpetuated [ regulatory policy support ; 32 , 33 ] than to support for other types of climate policy options.

• H2: Anger will be more strongly related to support for regulatory policies than other policies.

Hope → Positive future expectation → Goal pursuit → Support for proactive policies.

Hope is a future-oriented positive assessment of an uncertain situation [ 14 ] and can be an emotion that arises from a longing to prevent a dreaded outcome, assessing that doing so might be possible, and has been highlighted as a missing component in the climate-action chain [ 16 , 34 – 36 ]. Hope has been theorized to be a motivator for action [ 37 , 38 ], and has been linked to movement toward the goal that one desires [ 14 ]. Therefore, hope may be more linked to support for proactive policies, in comparison to other policy options. Proactive policies are future-oriented policies that address climate change by investing in new technologies, infrastructure, or financial incentives for behavioral change (similar to positive remuneration [ 39 ], aka “carrots” [ 27 ]). These might include providing tax incentives or rebates for energy efficiency improvements or the physical installation of railway networks or electric vehicle charging stations.

• H3: Hope will be more strongly related to support for proactive policies than other policies.

Sadness → Irrevocable loss → Restitution → Support for climate justice policies.

Sadness arises when an irreparable loss is thought to have occurred and can lead to an effort to reestablish what has been lost [ 15 ]. In the context of climate change, research in the U.S. has found that people perceive more losses for people who are distant in time and space, and to other species, rather than to themselves [ 40 – 42 ]. This psychological distance may lead individuals to support policies that provide restitution for those most affected (although importantly, people may also experience sadness for their own losses and desire restitution for their own suffering). Thus, we propose that sadness may be associated with support for policies that produce climate justice and protect people who are disproportionately harmed by the impacts of and responses to climate change [ 43 , 44 ].

• H4: Sadness will be more related to support for climate justice policies than other policies.

Fear → Uncertainty → Protection → Support for self-protective policies: regulatory and/or proactive?

Fear and anxiety often stem from perceiving a threat to oneself or emotionally significant others and can lead to a desire for protection [ 6 , 8 , 12 , 45 , 46 ]. However, the relationship between fear and action is unclear [ 47 ], with some studies finding a link between fear and action outcomes [ 48 – 51 ], while others do not, perhaps due to differences in self-or response efficacy, the level of fear experienced [ 52 ], or the novelty of the threat [ 45 ]. Fear has been specifically linked to support for more severe regulation in some arenas [ 53 ] and to a desire for implementation of new laws (vs. enforcement of existing laws) in others [ 54 ], including support for new fuel efficiency standards in the context of climate change [ 46 ]. Given these tendencies, it may be that fear is more associated with support for regulatory and/or proactive policy options, in comparison to other types of policies (both defined above).

• RQ1: Will fear be more related to support for regulatory and proactive policies than other policies?

Data for this project comes from a multi-wave nationally representative cross-sectional survey of US adults administered approximately every six months since 2010 by Ipsos (formerly Knowledge Networks). Ipsos recruits panel members using both random digit dialing and address-based sampling techniques to generate maximum coverage of US adults. Individuals who chose to participate but did not have Internet access were loaned computers and given Internet access. The surveys were designed to measure attitudes and beliefs about climate change. Only waves that included relevant emotion and policy support items were included in this analysis, resulting in an inclusion of fifteen waves from 2010 to 2022 (N = 16,605, see S1 Table for the month and year of each survey wave that was included and for access to the data and S1 Data for the data used in the analysis). 51% of participants were female and the average age of participants was in the 45–54 age range. 73% of participants reported their race and ethnicity as “White, Non-Hispanic.” Education was measured on a 14-point scale from no formal education (1) to a professional or doctorate degree (14), with the average level of education as “some college, no degree” (10.5). Political ideology was measured with the stem: “In general, do you think of yourself as…”, with the response options: “very liberal” (1), “somewhat liberal” (2), “moderate, middle of the road” (3), “somewhat conservative” (4), and “very conservative” (5). The average was 3.10, closest to “middle of the road”, SD = 1.075.

Ethics statement

This research was reviewed and approved by the George Mason University and Yale University Institutional Research Boards (GMU IRB protocol number 531283–19; Yale IRB protocol number 2000031972). Written formal consent was obtained from all participants, online.

Measurement

For both policy support and emotion measurement, not all items were asked on all waves; therefore, means were calculated with the available items from a given wave (see S1 Table for item wording and availability of items by wave).

Policy support.

To develop the policy support measures an iterative approach was used. First, all policy support items across the dataset were coded as matching one or more of the four categories defined (see S1 Table for item wording). As there was substantial variation in the number of times each item was asked, as well as variation in the number of co-occurrences that any two measures were asked in a given wave, traditional means of assessing reliability could not be used (i.e. Cronbach’s alpha or a structural equation measurement model). Therefore, we ran correlations between all measures coded in a given category (i.e. regulatory) and took the average of the correlations. If any measure had an average intercorrelation of less than r = .5, the item with the lowest intercorrelation was removed and the averages for the remaining measures recalculated in an iterative fashion until all measures had an average intercorrelation of .5 or above with the other items in a given category.

As the response options varied across items, all items were standardized before being averaged to calculate the policy support measures. This process resulted in the following measures: personally costly policy support was measured with 16 items (M = 0.015, SD = 0.924, average intercorrelation = 0.595; example item: “How much would you support or oppose a cap and trade system if it significantly reduced global warming pollution, but raised your household energy costs by 15 dollars a month?”); regulatory policy support was measured with 32 items (M = -0.002, SD = 0.846, average intercorrelation = 0.613; example: “How much do you support or oppose the following policies? ‘Regulate carbon dioxide (the primary greenhouse gas as a pollutant.’”); proactive policy support was measured with 17 items (M = 0.009, SD = 0.856, average intercorrelation = 0.588; example: “How much do you support or oppose the following policies? ‘Generate renewable energy (solar and wind) on public land in the U.S.’”); and climate justice policy support was measured with 10 items (M = -0.012, SD = 0.919, average intercorrelation = 0.689; example item: “How much do you support or oppose the following policies? ‘Increase federal funding to low-income communities and communities of color who are disproportionately harmed by air and water pollution.’”). For all measures higher scores indicate higher support for that type of policy.

Emotions were measured with the stem: “How strongly do you feel each of the following emotions when you think about the issue of global warming?” Response options ranged from “not at all” (1) to “very strongly” (4). All items were standardized for inclusion in the analysis to maintain consistency with the policy support items, but unstandardized means and standard deviations are provided here for context. Guilt was measured with the average of two items–guilty and ashamed ( r = 0.743, p < .001, M = 1.871, SD = 0.877), anger with the average of four items–angry, disgusted, outraged, and betrayed (α = 0.908, M = 2.297, SD = 0.965), hope with the average of four items–hopeful, courageous, brave, and resilient (α = 0.766, M = 2.312, SD = 0.885), sadness with the average of three items–sad, depressed, and hopeless (not all items were asked every wave, so reliability was not able to be assessed with Cronbach’s alpha; however, the average intercorrelation was 0.687, all p’s < .001, M = 2.256, SD = 0.969), and fear with the average of three items–afraid, anxious, and panicked (α = 0.895, M = 2.105, SD = 1.062).

Analyses were conducted in Mplus version 7, utilizing maximum likelihood estimation with robust standard errors (MLR; this approach also allows the inclusion of incomplete data, that is cases with missing items, by estimating the coefficients with the data that is available). A fully saturated structural equation model was fit, predicting each of the types of policy support from all of the emotions, controlling for political ideology, age, race, education, gender, and wave. Wave was treated categorically, using a fixed effect regression approach; in this approach, a dummy variable is entered for each wave included, and therefore the estimates of the predictors (in this case the discrete emotions) represent the common relationship across waves, controlling for any wave-level heterogeneity [ 55 , p. 289–290]; see Table A and Table B in S1 Text for coefficients of controls predicting emotions and types of policy support). All covariances between types of policy support and between the emotions were freely estimated. Model constraints tested whether the paths between each emotion on a specific type of policy support were equal (H1-H4, and RQ1; see the bottom of S1 Text for model code).

The analyses tested whether the strength of the relationship of each emotion to policy support depended on the type of policy: personally costly policies, regulatory policies, proactive policies, or climate justice policies. Results showed that guilt was most strongly associated with personally costly support (supporting H1; see Table 1 for all coefficients and Table C in S1 Text for the statistical comparison of the strength of each of the coefficients, also see Fig 1 for visualization of the relationships). Anger was most strongly associated with personally costly policy support (not supporting H2); hope was most strongly associated with proactive policy support (supporting H3); and sadness was also most associated with proactive policy support (not supporting H4). Fear was most associated with regulatory policy support (in line with research question four).

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Note: All of the measures of emotions and policy support were standardized. Additionally, the figure scales are restricted to the minimum and maximum observed values on both the x and y-axes to allow readers to more clearly see the pattern of results. See Table 1 for all coefficients.

https://doi.org/10.1371/journal.pclm.0000381.g001

https://doi.org/10.1371/journal.pclm.0000381.t001

Results show promising support for our core argument–that each discrete emotion is more strongly associated with support for a specific type of climate policy than for other types. Specifically, as predicted, guilt was most strongly related to personally costly policy support, and hope to proactive policy support. Also, as predicted, fear was most strongly related to regulatory policy support, suggesting that regulatory policies may be viewed as more self-protective than other forms of policies, including those that are proactive. Contrary to our predictions, anger was more strongly related to support for personally costly policies (rather than regulatory policies; which may be because we did not measure the target of anger, see limitations section), and sadness was most strongly related to support for proactive policies (rather than climate justice policies).

As a whole, these results are in line with previous research that found that the discrete emotional reactions were linked with discrepant political outcomes in other contexts, such as immigration policy (where anxiety and fear were associated with support for cooperative immigration policy and anger associated with support for domestic-focused policy [ 56 ]) and voter support following a terrorist event (anger was associated with support for far-right politics, while fear reduced support for those policy options [ 45 ]). Thus, this current research furthers our understanding that emotionality, in general, is important for understanding climate policy support, and begins to make the case that understanding the link between specific emotions and support for particular policy outcomes adds to our ability to predict such support.

These findings are relevant to people and organizations seeking to promote greater public support for climate policies. Research on political advertising has demonstrated that emotional political campaigns are more successful at engaging voter turnout than less emotional campaigns [ 6 ], and the same may prove true for generating support for climate policy engagement–sustained presentation of information that engages audiences emotionally may encourage publics to support—and voice their support—for particular climate policies. As previously shown, emotions are important predictors of policy support [ 2 – 4 ] and this work indicates that advocates should consider tailoring their emotional appeals based in part on the types of policy options they are promoting–especially if they are seeking to advance one particular type of policy proposal. Thus, for those supporting regulatory options, communicating fear about climate change might be a useful strategy. Similarly, when advocating for personally costly solutions, arousing guilt might resonate with some audiences, especially audiences not predisposed to support climate policies. And when advocating for proactive solutions, messengers could emphasize hope for the future. Finally, for those advocating for general climate policy solutions, fear was the emotion most strongly associated with all types of policy support (compared to the other emotions).

Limitations

This analysis has several important limitations. Foremost is that this research is correlational and cross-sectional in nature and therefore cannot make causal claims; however, we believe that the theoretical direction of causality from emotion to policy support is more plausible than the reverse directionality (a claim we cannot test in this analysis). Further research should test these relationships experimentally.

Secondly, there was intercorrelation between the emotions (see Table D in S1 Text and between some types of policy support (see Table E in S1 Text ), indicating that people who feel strongly about climate change experience a range of emotions and people who support one type of policy often support other types as well. This high intercorrelation might show that “a rising tide lifts all boats”–or that, strong emotionality about climate change is likely associated with strong support for any type of policy; however, the analysis does also indicate unique relationships between specific emotions and specific types of policy support in addition to this general trend. As margins for political engagement on any contemporary issue are often razor thin, any additional edge can be useful, and we think this perspective offers one potential way to incrementally increase the effectiveness of policy appeals.

Additionally, we note that the measurement of anger fails to assess the target of the anger that the respondent is feeling, and as such, it is likely that people across the ideological spectrum are angry about different aspects of climate change (e.g., inaction or action on the issue, respectively) and thus, the nature of the relationship between anger and support for policies likely differs by political ideology, so that it is more positive for liberals than conservatives. Future research should measure the target of anger to correct for this limitation.

Furthermore, due to practical constraints, we do not explore the potential moderating role of political identity and ideology. However, we know that political affiliation is associated with both climate emotions and support for climate policy [ 17 , 57 – 59 ]. Additionally, some emotions, such as anger and fear have been found to increase biased processing [ 60 ], while guilt may be associated with a willingness to reconsider support for a political position, even if it is in opposition to one’s political identity [ 61 ]. Therefore, future work should consider the moderating influence of political identity.

Finally, we note that our measurement of key items varies by wave of the instrument. While combining data from multiple data collections into one analysis provides the advantage of expanding the breadth of measurement across contributing data collections, allowing for fuller measurement of concepts than any single collection [ 62 ], it also introduces exogenous heterogeneity and potential measurement invariance concerns into the modeling. We addressed this limitation by reviewing the codebooks from all individual data collections and flagging potential policy support items from each domain (step 1); narrowing the item set on theoretical grounds (step 2); and, finally, performing correlational tests to identify problematic items (removing an item if it’s average intercorrelation was less than .5; step 3). These three steps correspond to the recommendations of Integrative Data Analysis [IDA] experts. IDA methodologists further recommend conducting a factor analysis across data collections, which necessitates a set of items that is the same across all datasets that would allow disparate items to be linked into the measurement structure. When such a set of items is not available, IDA proponents recommend conducting a bridging calibration study (a new data collection) that includes some items from each contributing study to allow for formal linking [ 62 ]. While that step was not feasible for this analysis, future research would benefit from improving measurement by conducting a bridging study.

Further policy action is vital to address the mounting challenges arising from our changing climate, and engaging the public’s emotions is an integral component of generating and sustaining support for policy action. This research finds that specific emotions are uniquely associated with support for specific types of climate policy preferences. These findings indicate that the types of emotions aroused may influence the type of solutions that will be preferred. As climate policies vary along many dimensions—including, and perhaps most importantly, their ability to effect real-world improvements, understanding how these specific emotions are evoked—and what results when they arise—is important to consider. Future work should examine experimentally whether messages that target these emotions are more effective at increasing support for the specific policy types, but in the meantime, communicators may wish to consider how their campaign’s emotional tones match their targeted policy goals.

Supporting information

S1 table. this file contains the item wording for each emotion and policy support measure, as well as the survey wave in which each item appeared..

https://doi.org/10.1371/journal.pclm.0000381.s001

S1 Text. This file contains tables with supplemental statistical information, along with the MPlus code for the model presented in the paper.

https://doi.org/10.1371/journal.pclm.0000381.s002

S1 Data. This file contains the data analyzed in this manuscript.

https://doi.org/10.1371/journal.pclm.0000381.s003

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Scientific Consensus

It’s important to remember that scientists always focus on the evidence, not on opinions. Scientific evidence continues to show that human activities ( primarily the human burning of fossil fuels ) have warmed Earth’s surface and its ocean basins, which in turn have continued to impact Earth’s climate . This is based on over a century of scientific evidence forming the structural backbone of today's civilization.

NASA Global Climate Change presents the state of scientific knowledge about climate change while highlighting the role NASA plays in better understanding our home planet. This effort includes citing multiple peer-reviewed studies from research groups across the world, 1 illustrating the accuracy and consensus of research results (in this case, the scientific consensus on climate change) consistent with NASA’s scientific research portfolio.

With that said, multiple studies published in peer-reviewed scientific journals 1 show that climate-warming trends over the past century are extremely likely due to human activities. In addition, most of the leading scientific organizations worldwide have issued public statements endorsing this position. The following is a partial list of these organizations, along with links to their published statements and a selection of related resources.

American Scientific Societies

Statement on climate change from 18 scientific associations.

"Observations throughout the world make it clear that climate change is occurring, and rigorous scientific research demonstrates that the greenhouse gases emitted by human activities are the primary driver." (2009) 2

American Association for the Advancement of Science

"Based on well-established evidence, about 97% of climate scientists have concluded that human-caused climate change is happening." (2014) 3

American Chemical Society

"The Earth’s climate is changing in response to increasing concentrations of greenhouse gases (GHGs) and particulate matter in the atmosphere, largely as the result of human activities." (2016-2019) 4

American Geophysical Union

"Based on extensive scientific evidence, it is extremely likely that human activities, especially emissions of greenhouse gases, are the dominant cause of the observed warming since the mid-20th century. There is no alterative explanation supported by convincing evidence." (2019) 5

American Medical Association

"Our AMA ... supports the findings of the Intergovernmental Panel on Climate Change’s fourth assessment report and concurs with the scientific consensus that the Earth is undergoing adverse global climate change and that anthropogenic contributions are significant." (2019) 6

American Meteorological Society

"Research has found a human influence on the climate of the past several decades ... The IPCC (2013), USGCRP (2017), and USGCRP (2018) indicate that it is extremely likely that human influence has been the dominant cause of the observed warming since the mid-twentieth century." (2019) 7

American Physical Society

"Earth's changing climate is a critical issue and poses the risk of significant environmental, social and economic disruptions around the globe. While natural sources of climate variability are significant, multiple lines of evidence indicate that human influences have had an increasingly dominant effect on global climate warming observed since the mid-twentieth century." (2015) 8

The Geological Society of America

"The Geological Society of America (GSA) concurs with assessments by the National Academies of Science (2005), the National Research Council (2011), the Intergovernmental Panel on Climate Change (IPCC, 2013) and the U.S. Global Change Research Program (Melillo et al., 2014) that global climate has warmed in response to increasing concentrations of carbon dioxide (CO2) and other greenhouse gases ... Human activities (mainly greenhouse-gas emissions) are the dominant cause of the rapid warming since the middle 1900s (IPCC, 2013)." (2015) 9

Science Academies

International academies: joint statement.

"Climate change is real. There will always be uncertainty in understanding a system as complex as the world’s climate. However there is now strong evidence that significant global warming is occurring. The evidence comes from direct measurements of rising surface air temperatures and subsurface ocean temperatures and from phenomena such as increases in average global sea levels, retreating glaciers, and changes to many physical and biological systems. It is likely that most of the warming in recent decades can be attributed to human activities (IPCC 2001)." (2005, 11 international science academies) 1 0

U.S. National Academy of Sciences

"Scientists have known for some time, from multiple lines of evidence, that humans are changing Earth’s climate, primarily through greenhouse gas emissions." 1 1

U.S. Government Agencies

U.s. global change research program.

"Earth’s climate is now changing faster than at any point in the history of modern civilization, primarily as a result of human activities." (2018, 13 U.S. government departments and agencies) 12

Intergovernmental Bodies

Intergovernmental panel on climate change.

“It is unequivocal that the increase of CO 2 , methane, and nitrous oxide in the atmosphere over the industrial era is the result of human activities and that human influence is the principal driver of many changes observed across the atmosphere, ocean, cryosphere, and biosphere. “Since systematic scientific assessments began in the 1970s, the influence of human activity on the warming of the climate system has evolved from theory to established fact.” 1 3-17

Other Resources

List of worldwide scientific organizations.

The following page lists the nearly 200 worldwide scientific organizations that hold the position that climate change has been caused by human action. http://www.opr.ca.gov/facts/list-of-scientific-organizations.html

U.S. Agencies

The following page contains information on what federal agencies are doing to adapt to climate change. https://www.c2es.org/site/assets/uploads/2012/02/climate-change-adaptation-what-federal-agencies-are-doing.pdf

Technically, a “consensus” is a general agreement of opinion, but the scientific method steers us away from this to an objective framework. In science, facts or observations are explained by a hypothesis (a statement of a possible explanation for some natural phenomenon), which can then be tested and retested until it is refuted (or disproved).

As scientists gather more observations, they will build off one explanation and add details to complete the picture. Eventually, a group of hypotheses might be integrated and generalized into a scientific theory, a scientifically acceptable general principle or body of principles offered to explain phenomena.

1. K. Myers, et al, "Consensus revisited: quantifying scientific agreement on climate change and climate expertise among Earth scientists 10 years later", Environmental Research Letters Vol.16 No. 10, 104030 (20 October 2021); DOI:10.1088/1748-9326/ac2774 M. Lynas, et al, "Greater than 99% consensus on human caused climate change in the peer-reviewed scientific literature", Environmental Research Letters Vol.16 No. 11, 114005 (19 October 2021); DOI:10.1088/1748-9326/ac2966 J. Cook et al., "Consensus on consensus: a synthesis of consensus estimates on human-caused global warming", Environmental Research Letters Vol. 11 No. 4, (13 April 2016); DOI:10.1088/1748-9326/11/4/048002 J. Cook et al., "Quantifying the consensus on anthropogenic global warming in the scientific literature", Environmental Research Letters Vol. 8 No. 2, (15 May 2013); DOI:10.1088/1748-9326/8/2/024024 W. R. L. Anderegg, “Expert Credibility in Climate Change”, Proceedings of the National Academy of Sciences Vol. 107 No. 27, 12107-12109 (21 June 2010); DOI: 10.1073/pnas.1003187107 P. T. Doran & M. K. Zimmerman, "Examining the Scientific Consensus on Climate Change", Eos Transactions American Geophysical Union Vol. 90 Issue 3 (2009), 22; DOI: 10.1029/2009EO030002 N. Oreskes, “Beyond the Ivory Tower: The Scientific Consensus on Climate Change”, Science Vol. 306 no. 5702, p. 1686 (3 December 2004); DOI: 10.1126/science.1103618

2. Statement on climate change from 18 scientific associations (2009)

3. AAAS Board Statement on Climate Change (2014)

4. ACS Public Policy Statement: Climate Change (2016-2019)

5. Society Must Address the Growing Climate Crisis Now (2019)

6. Global Climate Change and Human Health (2019)

7. Climate Change: An Information Statement of the American Meteorological Society (2019)

8. American Physical Society (2021)

9. GSA Position Statement on Climate Change (2015)

10. Joint science academies' statement: Global response to climate change (2005)

11. Climate at the National Academies

12. Fourth National Climate Assessment: Volume II (2018)

13. IPCC Fifth Assessment Report, Summary for Policymakers, SPM 1.1 (2014)

14. IPCC Fifth Assessment Report, Summary for Policymakers, SPM 1 (2014)

15. IPCC Sixth Assessment Report, Working Group 1 (2021)

16. IPCC Sixth Assessment Report, Working Group 2 (2022)

17. IPCC Sixth Assessment Report, Working Group 3 (2022)

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COA-GPT: Generative Pre-trained Transformers for Accelerated Course of Action Development in Military Operations † † thanks: This research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-23-2-0072. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein. This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by the Information Systems Technology (IST) Panel, IST-205-RSY - the ICMCIS, held in Koblenz, Germany, 23-24 April 2024.

The development of Courses of Action (COAs) in military operations is traditionally a time-consuming and intricate process. Addressing this challenge, this study introduces COA-GPT, a novel algorithm employing Large Language Models (LLMs) for rapid and efficient generation of valid COAs. COA-GPT incorporates military doctrine excerpts and domain expertise to LLMs through in-context learning, allowing commanders to input mission information – in both text and image formats – and receive strategically aligned COAs for review and approval. Uniquely, COA-GPT not only accelerates COA development, producing initial COAs within seconds, but also facilitates real-time refinement based on commander feedback. This work evaluates COA-GPT in a military-relevant scenario within a militarized version of the StarCraft II game, comparing its performance against an expert human and state-of-the-art reinforcement learning algorithms. Our results demonstrate COA-GPT’s superiority in generating strategically sound COAs more swiftly, with the added benefits of enhanced adaptability and alignment with commander intentions. COA-GPT’s capability to rapidly adapt and update COAs during missions presents a transformative potential for military planning, particularly in addressing planning discrepancies and capitalizing on emergent windows of opportunity. Performance videos of our method can be seen at https://sites.google.com/view/coa-gpt .

Index Terms:

I introduction.

The future battlefield presents an array of complex and dynamic challenges for Command and Control (C2) personnel, requiring rapid and informed decision-making across multifaceted domains. As warfare continues to evolve, integrating and synchronizing diverse assets and effects across air, land, maritime, information, cyber, and space domains becomes increasingly critical. The C2 operations process, encompassing planning, preparation, execution, and continuous assessment, must adapt to these complexities while dealing with real-time data integration and operating under conditions of Denied, Degraded, Intermittent, and Limited (DDIL) communication [ 1 , 2 ] .

In this high-stakes environment, maintaining decision advantage – the ability to make timely and effective decisions faster than adversaries – is paramount. The Military Decision Making Process (MDMP)  [ 3 ] , a cornerstone of C2 planning  [ 4 ] , faces the pressing need to evolve with the accelerating pace and complexity of modern warfare [ 5 ] . This necessitates executing the MDMP within increasingly shorter timescales to exploit fleeting opportunities and respond adaptively to the dynamic conditions of the battlefield.

The development of Courses of Action (COAs), a core element of decision-making, highlights these challenges. Traditionally, COA development is meticulous and time-intensive, relying heavily on military expertise. The demands of modern warfare require more efficient COA development and analysis methods.

Enter Large Language Models (LLMs), a transformative technology in the field of natural language processing [ 6 , 7 , 8 ] . LLMs have shown immense potential in various applications, including disaster response [ 9 , 10 , 11 ] and robotics [ 12 , 13 , 14 ] , by processing extensive data to generate human-like text from given prompts. This research paper proposes COA-GPT, a framework that explores the application of LLMs to expedite COA development in military operations via in-context learning.

COA-GPT leverages LLMs to swiftly develop valid COAs, integrating military doctrine excerpts and domain expertise directly into the system’s initial prompts. Commanders can input mission specifics and force descriptions – in both text and image formats - receiving multiple, strategically aligned COAs in a matter of seconds.

Our main contributions are:

COA-GPT, a novel framework leveraging LLMs for accelerated development and analysis of COAs, integrating military doctrine excerpts and domain expertise effectively.

Empirical evidence showing that COA-GPT outperforms existing baselines in generating COAs, both in terms of speed and alignment with military strategic goals.

Demonstration of COA-GPT’s ability to improve COA development through human interaction, ensuring that generated COAs align closely with commanders’ intentions and adapt dynamically to battlefield scenarios.

II Military Relevance

The current C2 processes in military operations are predominantly linear and involve numerous sequential steps, which can be cumbersome and slow in the fast-paced environment of modern warfare [ 3 , 2 ] . The advent of AI in military planning, particularly the COA-GPT system, presents an opportunity to radically streamline these processes.

COA-GPT significantly enhances the MDMP by enabling the concurrent development and analysis of COAs. This facilitates quicker decision-making and enhances operation control, leading to the swift generation of actionable intelligence for informed command decisions. Integrating AI tools like COA-GPT in C2 processes can reduce military operations’ physical footprint, lessening the need for extensive personnel and logistics, and aligning with the vision of distributed command structures.

Solutions such as COA-GPT can integrate with war gaming simulators and battlefield sensor data in real-time, enabling quick adaptation to battlefield dynamics. This approach emphasizes early COA analysis integration for swift optimization and comparison  [ 5 ] . Additionally, by integrating human feedback, COA-GPT allows personnel to adapt AI-generated COAs with their expertise and situational awareness for informed final selections. C2 personnel dynamically interact with COA-GPT to specify objectives, input data, set planning constraints, and adjust proposed COAs, ensuring decisions align with strategic intent and situational requirements.

III Related Work

Iii-a planning with large language models.

The integration of Large Language Models (LLMs) in the plan of action development has been applied to various sectors, including disaster response operations. Similar to military operations, disaster response demands rapid, informed decision-making under severe time constraints and high-pressure conditions [ 15 , 16 , 17 ] . Traditionally, action plan development in such contexts has been a laborious process, heavily reliant on the experience and expertise of the personnel involved. Given the stakes involved, where delays can result in loss of life, there is a critical need for more efficient and reliable plan development methodologies [ 18 , 19 , 15 , 20 ] . In the realm of disaster response, the DisasterResponseGPT  [ 21 ] algorithm leverages the capabilities of LLMs to quickly generate viable action plans, integrating essential disaster response guidelines within the initial prompt.

The recent studies by Ahn et al. (2022)  [ 12 ] and Mees et al. (2023)  [ 14 ] expand the scope of LLM applications to include robotic and visual affordances, illustrating how LLMs can be grounded in real-world contexts. Continuing to show the potential of LLMs for planning, the introduction of Voyager by Wang et al. (2023)  [ 22 ] , an LLM-powered embodied lifelong learning agent in Minecraft, represents an important step in autonomous, continual learning and skill acquisition in complex, ever-changing environments. Similarly, the STEVE-1  [ 23 ] model showcases the potential of LLMs in guiding agents to follow complex instructions in virtual settings, leveraging advancements in text-conditioned image generation and decision-making algorithms.

The integration of LLMs into planning has significantly advanced rapid decision-making capabilities in a diverse range of scenarios. COA-GPT builds upon these foundations and demonstrates the versatility of LLMs in translating strategic concepts into actionable plans for military operations.

III-B AI for Military Planning and Operations

The application of AI and LLMs in military planning and operations is a field of growing interest and significant potential. The First-Year Report of ARL Director’s Strategic Initiative, focusing on Artificial Intelligence for Command and Control (C2) of Multi-Domain Operations  [ 24 ] , exemplifies this trend. The report discusses ongoing research into whether AI could support agile and adaptive C2 in multi-domain forces.

Exploring the synergy between gaming platforms and military training, Goecks et al. (2023) provide insight into how AI algorithms, when combined with gaming and simulation technologies, can be adapted to replicate aspects of military missions  [ 25 ] . In a similar vein, Waytowich et al. (2022)  [ 26 ] demonstrate the application of deep reinforcement learning (DRL) in commanding multiple heterogeneous actors in a simulated command and control task, modeled on a military scenario within StarCraft II. Their findings indicate that agents trained via an automatically generated curriculum can match or even surpass the performance of human experts and state-of-the-art DRL baselines.

In addition to these developments, Schwartz (2020)  [ 27 ] delves into the application of AI in the Army’s MDMP, specifically in the COA Analysis phase. They demonstrate how AI can assist commanders and their staff in quickly developing and optimizing multiple courses of action in response to the complexities of modern, hyper-contested battlefields. The study also highlights the increasing importance of Multi-Domain Operations (MDO) and the challenges presented by near-peer adversaries equipped with advanced Anti-Access Area Denial (A2AD) capabilities.

In contrast to these AI-driven approaches, traditional military planning processes, as outlined in U.S. Army’s ATP 5-0.2  [ 28 ] , involve comprehensive guidelines for staff members in large-scale combat operations. While providing a consolidated source of key planning tools and techniques, these traditional methodologies often lack the agility and adaptability offered by modern AI systems in rapidly changing combat environments.

In the evolving landscape of military planning and operations, the integration of AI and LLMs signifies a shift towards more agile and adaptive command and control strategies. COA-GPT exemplifies this shift, leveraging LLMs for accelerated COA development, thus addressing the limitations of manual planning processes and previous automated approaches.

IV Methods and Experiments

In this research, we leveraged the in-context learning capabilities of LLMs to create COA-GPT, a virtual assistant designed to efficiently generate COAs for military operations.

COA-GPT is prompted to understand that it serves as a military commander’s assistant to aid C2 personnel in developing COAs. It is aware that its inputs will include mission objectives, terrain information, and details on friendly and threat forces as provided by the commander in text and/or image format. It is also instructed to use specific commands to assign tasks for each asset in the friendly forces. Furthermore, COA-GPT has access to military doctrine excerpts, covering forms of maneuver (envelopment, flank attack, frontal attack, infiltration, penetration, and turning movement), offensive tasks (movement to contact, attack, exploitation, and pursuit), and defensive tasks (area defense, mobile defense, and retrograde). The complete system prompt and doctrinal excerpts given to COA-GPT are reproduced in Appendix  -A .

As depicted in Figure 1 , the COA-GPT assistant communicates with C2 personnel via natural language. It receives mission-related information such as objectives, terrain details, friendly and threat force description and arrangement, and any planning assumptions the C2 staff might have. For the LLM in the back end, we use OpenAI’s GPT-4-Turbo (named “ gpt-4-1106-preview ” in their API) for text-only experiments and GPT-4-Vision (named “ gpt-4-vision-preview ”) for tasks where mission information is given in both text and image format.

Upon receiving this information, COA-GPT generates several COA options, each with a designated name, purpose, and visual representation of the proposed actions. Users can select their preferred COA and refine it through textual suggestions. COA-GPT processes this feedback to fine-tune the selected COA. Once the commander approves the final COA, COA-GPT conducts an analysis and provides performance metrics.

The generation of COAs by COA-GPT is remarkably swift, completing in seconds. Including the time for commander interaction, a final COA can be produced in just a few minutes. This efficiency underscores COA-GPT’s potential to transform COA development in military operations, facilitating rapid adjustments in response to planning phase discrepancies or emerging opportunities.

IV-A Scenario and Experimental Setup

Our evaluation of the proposed method is conducted within the Operation TigerClaw scenario  [ 24 ] , which is implemented as a custom map in the StarCraft II Learning Environment ( PySC2 )  [ 29 ] . This platform enables artificial intelligence (AI) agents to engage in the StarCraft II game. Operation TigerClaw   [ 24 ] presents a combat scenario where Task Force 1–12 CAV is tasked with seizing OBJ Lion by attacking across the Thar Thar Wadi, eliminating the threat force. This objective is depicted in Figure  2 .

In PySC2 , the scenario is realized by mapping StarCraft II units to their military equivalents, adjusting attributes like weapon range, damage, unit speed, and health. For instance, M1A2 Abrams combat armor units are represented by modified Siege Tanks in tank mode, mechanized infantry by Hellions, among others  [ 24 ] (see Appendix -C for more details). The Friendly Force consists of 9 Armor, 3 Mechanized infantry, 1 Mortar, 2 Aviation, and 1 Reconnaissance unit. The Threat Force includes 12 Mechanized infantry, 1 Aviation, 2 Artillery, 1 Anti-Armor, and 1 Infantry unit.

In terms of terrain, a custom StarCraft II map  [ 24 ] was made to depict the TigerClaw area of operations, as shown in Figure  3 . In this scenario, the Threat Force is controlled by the default in-game StarCraft II AI. They are programmed to automatically move to fixed defensive positions to defend the three main Thar Thar Wadi crossings. Upon detecting the Friendly Force within range, they open fire. Additionally, the Threat Aviation unit performs a fixed patrol route covering the three crossing points, while also engaging any Friendly Force assets that come into range.

IV-B COA Generation

COA-GPT processes mission objectives and terrain information in text format for all experimental scenarios, which are described as follows:

Mission Objective. “Move friendly forces from the west side of the river to the east via multiple bridges, destroy all hostile forces, and ultimately seize objective OBJ Lion East at the top right corner of the map (coordinates x: 200, y: 89).”

Terrain Information. “The map is split in two major portions (west and east sides) by a river that runs from north to south. There are four bridges that can be used to cross this river. Bridge names and exit coordinates are as follows: 1) Bridge Bobcat (x: 75, y: 26), 2) Bridge Wolf (x: 76, y: 128), 3) Bridge Bear (x:81, y: 179), and 4) Bridge Lion (x: 82, y: 211).”

For the experiments using LLM with image processing capabilities, COA-GPT takes as input a frame of a Common Operational Picture (COP) that overlays force arrangements in a satellite image of the terrain, as depicted in Figure  4 .

Information regarding Friendly and Threat forces, detailing all assets present in the scenario, is fed to COA-GPT in JSON format:

Example Friendly Force Asset: “{‘unit_id’: 4298113025, ‘unit_type’: ‘Armor’, ‘alliance’: ‘Friendly’, ‘position’: ‘x’: 12.0, ‘y’: 203.0}”

Example Threat Force Asset: “{‘unit_id’: 4294967297, ‘unit_type’: ‘Mechanized infantry’, ‘alliance’: ‘Hostile’, ‘position’: ‘x’: 99.0, ‘y’: 143.0}”

Mission objective, terrain, and force information are integrated into a single COA generation prompt, as shown in Appendix  -B , that is then used to query the LLM in the back end.

For integration with the PySC2 game engine, COA-GPT outputs COAs in JSON format, as detailed in the example COA statement found in Appendix  -A . These task allocations from COA-GPT are translated into specific function calls compatible with the PySC2 engine 1 1 1 PySC2 Action Definition:  https://github.com/google-deepmind/pysc2/blob/master/pysc2/lib/actions.py . , facilitating in-game actions based on the generated COAs. COA-GPT is programmed with knowledge of the specific game engine functions to command each asset:

attack_move_unit (unit_id, target_x, target_y): Directs a friendly unit to move to a specified coordinate, engaging hostile units encountered en route.

engage_target_unit (unit_id, target_unit_id, target_x, target_y): Orders a friendly unit to engage a specified hostile unit. If the target is out of range, the friendly unit will move to the target’s location before engaging.

A comprehensive COA encompasses a mission name, a brief strategic description, and designated commands for each asset involved, as defined by the presented game engine functions. During a simulation rollout, each asset strictly follows its initial command issued by COA-GPT at the start of the simulation. For instance, a command to e ⁢ n ⁢ g ⁢ a ⁢ g ⁢ e ⁢ _ ⁢ t ⁢ a ⁢ r ⁢ g ⁢ e ⁢ t ⁢ _ ⁢ u ⁢ n ⁢ i ⁢ t ⁢ ( X , Y , c ⁢ o ⁢ o ⁢ r ⁢ d x , c ⁢ o ⁢ o ⁢ r ⁢ d y ) 𝑒 𝑛 𝑔 𝑎 𝑔 𝑒 _ 𝑡 𝑎 𝑟 𝑔 𝑒 𝑡 _ 𝑢 𝑛 𝑖 𝑡 𝑋 𝑌 𝑐 𝑜 𝑜 𝑟 subscript 𝑑 𝑥 𝑐 𝑜 𝑜 𝑟 subscript 𝑑 𝑦 engage\_target\_unit(X,Y,coord_{x},coord_{y}) italic_e italic_n italic_g italic_a italic_g italic_e _ italic_t italic_a italic_r italic_g italic_e italic_t _ italic_u italic_n italic_i italic_t ( italic_X , italic_Y , italic_c italic_o italic_o italic_r italic_d start_POSTSUBSCRIPT italic_x end_POSTSUBSCRIPT , italic_c italic_o italic_o italic_r italic_d start_POSTSUBSCRIPT italic_y end_POSTSUBSCRIPT ) would specify unit X 𝑋 X italic_X to engage target unit Y 𝑌 Y italic_Y , maintaining this engagement until the battle concludes or a new COA is issued. Similarly, an a ⁢ t ⁢ t ⁢ a ⁢ c ⁢ k ⁢ _ ⁢ m ⁢ o ⁢ v ⁢ e ⁢ _ ⁢ u ⁢ n ⁢ i ⁢ t ⁢ ( Z , c ⁢ o ⁢ o ⁢ r ⁢ d x , c ⁢ o ⁢ o ⁢ r ⁢ d y ) 𝑎 𝑡 𝑡 𝑎 𝑐 𝑘 _ 𝑚 𝑜 𝑣 𝑒 _ 𝑢 𝑛 𝑖 𝑡 𝑍 𝑐 𝑜 𝑜 𝑟 subscript 𝑑 𝑥 𝑐 𝑜 𝑜 𝑟 subscript 𝑑 𝑦 attack\_move\_unit(Z,coord_{x},coord_{y}) italic_a italic_t italic_t italic_a italic_c italic_k _ italic_m italic_o italic_v italic_e _ italic_u italic_n italic_i italic_t ( italic_Z , italic_c italic_o italic_o italic_r italic_d start_POSTSUBSCRIPT italic_x end_POSTSUBSCRIPT , italic_c italic_o italic_o italic_r italic_d start_POSTSUBSCRIPT italic_y end_POSTSUBSCRIPT ) command directs unit Z 𝑍 Z italic_Z to move to a specified map coordinate, engaging any hostile units encountered en route. The PySC2 engine processes these commands at every simulation time step to ensure each asset is correctly controlled.

IV-C Human Feedback

As depicted in Figure  5 , the COA generated by our system is transformed into a graphical format accompanied by a concise mission summary for presentation to human evaluators. The evaluators can provide textual feedback, which COA-GPT then uses to refine and generate a new COA for subsequent feedback rounds.

To ensure a consistent and fair comparison and evaluation process across all generated COAs, we have standardized the human feedback process specifically for this work. The specific instructions provided in each feedback iteration for the COAs that incorporated human input are as follows:

First Iteration: “Make sure both our aviation units directly engage the enemy aviation unit.”

Second Iteration: “Make sure only our Scout unit is commanded to control Bridge Bobcat (x: 75 y: 26) and our other assets (not the aviation) are split in two groups and commanded to move towards both enemy artillery using the attack_move command.”

After receiving final approval from the human evaluators, COA-GPT proceeds to simulate the scenario multiple times, gathering and compiling various evaluation metrics for analysis.

IV-D Evaluation Metrics

The evaluation of the generated COAs is based on three key metrics recorded during the COA analysis: total reward, friendly force casualties, and threat force casualties:

Total Reward. This metric represents the total game score, which is tailored specifically for the TigerClaw mission scenario. It includes positive rewards for strategic advancements and neutralizing enemy units, and negative rewards for retreats and friendly unit losses. Specifically, agents gain +10 points for each unit advancing over bridges and for each enemy unit neutralized. Conversely, they lose -10 points for retreating over a previously crossed bridge and for each friendly unit lost.

Friendly Force Casualties. This metric counts the number of friendly force units lost during the simulated engagement. It reflects the operational cost in terms of friendly unit losses.

Threat Force Casualties. This metric tracks the number of enemy (threat force) units eliminated during the simulation, indicating the effectiveness of the COA in neutralizing the opposition.

IV-E Baselines

In this study, we benchmark our proposed method against an expert human and the two best-performing published approaches for this scenario: Autocurriculum Reinforcement Learning from a Single Human Demonstration  [ 26 ] and the Asynchronous Advantage Actor-Critic (A3C) algorithm in Reinforcement Learning  [ 30 , 26 ] :

Autocurriculum Reinforcement Learning   [ 26 ] . Utilizing a single human demonstration, this method develops a tailored curriculum for training a reinforcement learning agent via the A3C algorithm  [ 30 ] . The agent, which controls each friendly unit individually, accepts either image inputs from the environment or a vectorial representation detailing unit positions. We evaluate our method against both input modes, referred to as “Autocurr.-Vec” and “Autocurr.-Im”, respectively, in our results section.

Reinforcement Learning. As detailed in  [ 26 ] , this baseline employs the A3C algorithm, using either images or vector representations as inputs. Unlike the previous method, it does not incorporate a guiding curriculum for the learning agent. Both input modes are evaluated against our method, labeled as “RL-Vec” and “RL-Im”, respectively, in our results.

COA-GPT. This serves as an ablation study of our proposed approach but without human feedback. Labeled “COA-GPT” (text-only inputs) and “COA-GPT-V” (for experiments with vision models using both text and image inputs), this version generates COAs based solely on the initial mission data provided by the C2 personnel, without further human input.

COA-GPT with Human Feedback. This is our fully realized method. Beyond the initial mission information from the C2 personnel, this version also incorporates the impact of human feedback on the COA performance. We assess the changes after the first iteration of feedback, denoted as “COA-GPT+H1”, and after the second iteration, labeled “COA-GPT+H2” in the results. Similarly, for experiments using the LLM with vision capabilities the experiments are labeled “COA-GPT-V+H1” and “COA-GPT-V+H2”.

Expert Human. A human expert was tasked to complete the same scenario over 15 trials. Differently from COA-GPT, the human controlled the assets using a mouse a keyboard in real-time throughout the whole game. Similarly, the human user was only able to command attack-move or direct engage commands.

V Experimental Results

V-a qualitative results.

To illustrate the full realization of the proposed methodology, Figure  6 depicts the evolution of a generated COA in response to human feedback. Initially, the COA generated without human input (Figure  6 a) displays a certain configuration for the planned movement of friendly forces across bridges and their engagement with hostile units. After the first round of human feedback ( “Make sure both our aviation units directly engage the enemy aviation unit.” ), we see a strategic pivot (Figure  6 b); the friendly aviation units are now tasked to engage the enemy’s aviation assets directly. This adjustment reflects the human commander’s intent to prioritize air superiority. The second iteration of feedback — “Make sure only our Scout unit is commanded to control Bridge Bobcat (x: 75 y: 26) and our other assets (not the aviation) are split into two groups and commanded to move towards both enemy artillery using the attack_move command.” — as seen in Figure  6 c), results in a more nuanced approach: the friendly forces are divided, with specific units tasked to target enemy artillery positions. Additionally, the reconnaissance unit is ordered to secure the northern bridge and the friendly aviation is still tasked to engage the threat aviation, demonstrating that COA-GPT successfully followed the commander’s intent conveyed via textual feedback.

V-B Quantitative Results

For a comprehensive evaluation of COA-GPT, we generated five COAs for each method variant and conducted ten simulations for each, totaling 50 evaluation rollouts per baseline. All results discussed in this section represent the mean and standard deviation calculated across these 50 rollouts for each evaluation metric. It is important to note that the game of StarCraft II is mostly deterministic  [ 29 ] - with stochasticity mostly being injected via weapon speed in the case of our TigerClaw scenario - which implies that the variance present in the results originates from the diversity of the COAs generated by COA-GPT. The data for the Reinforcement Learning and Autocurriculum Reinforcement Learning baselines are sourced directly from their respective published work  [ 26 ] . Performance videos of COA-GPT can be seen at the project webpage  2 2 2 COA-GPT Project Webpage: https://sites.google.com/view/coa-gpt . .

Figure  7 presents a comparison of all baseline methods in terms of the average and standard deviation of the total rewards received during evaluation rollouts. COA-GPT, even in the absence of human interaction and relying solely on textual scenario representations, produces Courses of Action (COAs) that surpass the performance of all AI baselines on average. This includes the previously established state-of-the-art method, Autocurriculum Reinforcement Learning, which utilizes image data. COA-GPT-V, which also uses a single image as additional input, has equivalent performance compared to the previous baselines. Additionally, Figure  7 illustrates that the effectiveness of the COAs generated by COA-GPT is enhanced further (as indicated by a higher mean total reward) and exhibits reduced variability (evidenced by a lower standard deviation) when subjected to successive stages of human feedback. When taking into consideration the performance after human feedback, COA-GPT with vision models (COA-GPT-V+H1 and COA-GPT-V+H2) achieve higher mean total rewards compared to all previous baselines. However, compared to the human expert, the best-proposed model achieves a 3.4% lower mean score, although it’s noteworthy that the human expert’s results demonstrate a larger variance.

Figures  8 and  9 provide a comparative analysis of the mean and standard deviation of friendly and threat force casualties, respectively, during the evaluation rollouts. In Figure  8 , we observe that the COA-GPT and COA-GPT-V, even when enhanced with human feedback (COA-GPT+H1, COA-GPT+H2, COA-GPT-V+H1 and COA-GPT-V+H2 models), exhibits higher friendly force casualties compared to other baselines. This outcome may be linked to COA-GPT’s lower control resolution: offering a single strategic command at the beginning of the episode rather than continuous command inputs throughout the episode, as seen in all the baseline methods. While this approach facilitates a more interpretable COA development process for human operators, it potentially increases casualty rates due to the limited tactical adjustments during COA execution. The human expert, who was also able to continuously command the assets throughout the episode, achieved the lowest number of friendly casualties and the highest number of hostile casualties, on average.

In contrast, Figure  9 will show that the lethality of COA-GPT towards threat forces remains consistent with other baselines, despite operating with lower control resolution. This indicates that COA-GPT and COA-GPT-V variations are capable of matching the effectiveness of other methods in neutralizing threats, even with the potential handicap of less granular command capabilities.

As an important aspect of operational efficiency, we evaluated the time required to generate COAs across all baselines. The Autocurriculum method required an extensive training period, involving 112 thousand simulated battles, equating to 70 million timesteps across 35 parallel workers, to achieve optimal performance with its final trained policy  [ 26 ] . In contrast, COA-GPT boasts the capability to generate actionable COAs within seconds, demonstrating a significant advantage in terms of rapid deployment. Moreover, COA-GPT exhibits remarkable flexibility, adapting to new friendly and threat force configurations and changes in terrain without the need for retraining. This adaptability extends to human commanders who can intuitively adjust COAs generated by COA-GPT. Such immediate adaptability is not present in the Autocurriculum and traditional Reinforcement Learning methods, which are inherently less flexible due to their reliance on extensive pre-training under fixed conditions before deployment.

VI Conclusions

This research presents an advancement in the field of military planning and decision-making through the development of COA-GPT. In the face of increasingly complex and dynamic future battlefields, COA-GPT addresses a critical need in C2 operations for rapid and informed decision-making. Leveraging the power of LLMs, both with text-only and text and images as input, COA-GPT substantially accelerates the development and analysis of COAs, integrating military doctrine excerpts and domain expertise via in-context learning.

The results from the evaluations presented further validate the effectiveness of COA-GPT. Notably, it demonstrates superior performance in developing COAs aligned to the commander’s intent, closely matching expert humans and outperforming other AI methods, including state-of-the-art Autocurriculum Reinforcement Learning algorithms. While COA-GPT exhibits significant advantages in terms of speed and adaptability, it is enhanced further by the integration of human feedback. This collaboration leads to COAs that are aligned to human intent, yet are generated much more rapidly, underscoring the tool’s potential to transform the pace and efficiency of military planning.

Moreover, the synergy between COA-GPT and human commanders enriches the decision-making process, enabling the exploration of a broader range of operational possibilities and adjustments in real-time. This collaborative approach combines the speed and adaptability of AI with the nuanced understanding and strategic insight of human expertise, facilitating faster, more agile decision-making in modern warfare.

In conclusion, COA-GPT represents a novel approach to enhance military C2 operations. Its ability to generate actionable COAs within seconds, coupled with its flexible adaptation to new scenarios and intuitive interaction with human commanders, highlights its practical utility and potential for rapid deployment in diverse military scenarios. The development and successful application of COA-GPT pave the way for further innovations in military AI, potentially reshaping how military operations are planned and executed in the future, especially as it demonstrates an improved capacity for dynamic adaptation to changing conditions and enhanced performance through human-AI collaboration.

VII Future Work

Future work will extend the application of our methodology beyond the initial scenario presented, exploring its effectiveness across a diverse range of terrain and force configurations. The proposed method can be adapted to present commanders with multiple COA options, who can further iterate and refine these plans, or be adjusted to fit any established operational workflow. Additionally, future simulation platforms aim to develop a more complex model of opposition forces. This involves transitioning from the current simplistic representation, with fixed patrols and defensive positions, to dynamic simulations that capture the enemy commanders’ intentions and strategies, thereby enhancing the realism and strategic depth of our simulations.

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-A COA-GPT System Prompt

Variable e ⁢ x ⁢ a ⁢ m ⁢ p ⁢ l ⁢ e ⁢ _ ⁢ c ⁢ o ⁢ a ⁢ _ ⁢ s ⁢ t ⁢ a ⁢ t ⁢ e ⁢ m ⁢ e ⁢ n ⁢ t 𝑒 𝑥 𝑎 𝑚 𝑝 𝑙 𝑒 _ 𝑐 𝑜 𝑎 _ 𝑠 𝑡 𝑎 𝑡 𝑒 𝑚 𝑒 𝑛 𝑡 example\_coa\_statement italic_e italic_x italic_a italic_m italic_p italic_l italic_e _ italic_c italic_o italic_a _ italic_s italic_t italic_a italic_t italic_e italic_m italic_e italic_n italic_t :

Variable a ⁢ d ⁢ d ⁢ i ⁢ t ⁢ i ⁢ o ⁢ n ⁢ a ⁢ l ⁢ _ ⁢ m ⁢ i ⁢ l ⁢ i ⁢ t ⁢ a ⁢ r ⁢ y ⁢ _ ⁢ i ⁢ n ⁢ f ⁢ o 𝑎 𝑑 𝑑 𝑖 𝑡 𝑖 𝑜 𝑛 𝑎 𝑙 _ 𝑚 𝑖 𝑙 𝑖 𝑡 𝑎 𝑟 𝑦 _ 𝑖 𝑛 𝑓 𝑜 additional\_military\_info italic_a italic_d italic_d italic_i italic_t italic_i italic_o italic_n italic_a italic_l _ italic_m italic_i italic_l italic_i italic_t italic_a italic_r italic_y _ italic_i italic_n italic_f italic_o :

-B COA Generation Prompt

Variable r ⁢ a ⁢ w ⁢ _ ⁢ u ⁢ n ⁢ i ⁢ t ⁢ s ⁢ _ ⁢ j ⁢ s ⁢ o ⁢ n 𝑟 𝑎 𝑤 _ 𝑢 𝑛 𝑖 𝑡 𝑠 _ 𝑗 𝑠 𝑜 𝑛 raw\_units\_json italic_r italic_a italic_w _ italic_u italic_n italic_i italic_t italic_s _ italic_j italic_s italic_o italic_n : Data returned from StarCraft II API: u ⁢ n ⁢ i ⁢ t ⁢ _ ⁢ i ⁢ d 𝑢 𝑛 𝑖 𝑡 _ 𝑖 𝑑 unit\_id italic_u italic_n italic_i italic_t _ italic_i italic_d , u ⁢ n ⁢ i ⁢ t ⁢ _ ⁢ t ⁢ y ⁢ p ⁢ e 𝑢 𝑛 𝑖 𝑡 _ 𝑡 𝑦 𝑝 𝑒 unit\_type italic_u italic_n italic_i italic_t _ italic_t italic_y italic_p italic_e , a ⁢ l ⁢ l ⁢ i ⁢ a ⁢ n ⁢ c ⁢ e 𝑎 𝑙 𝑙 𝑖 𝑎 𝑛 𝑐 𝑒 alliance italic_a italic_l italic_l italic_i italic_a italic_n italic_c italic_e , p ⁢ o ⁢ s ⁢ i ⁢ t ⁢ i ⁢ o ⁢ n 𝑝 𝑜 𝑠 𝑖 𝑡 𝑖 𝑜 𝑛 position italic_p italic_o italic_s italic_i italic_t italic_i italic_o italic_n . All details are in the PySC2 package documentation page 3 3 3 PySC2 Documentation: https://github.com/google-deepmind/pysc2/blob/master/docs/environment.md#observation . .

-C StarCraft II to TigerClaw Unit Mapping

Table I shows a list of StarCraft II units that were used as base to represent the military assets used in the TigerClaw scenario. Units had their speed, range, and damage modified to better approximate their military counterparts  [ 24 ] .

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Taking into account climate and nature in monetary policy and banking supervision around the world

Remarks by frank elderson, member of the executive board of the ecb and vice-chair of the supervisory board of the ecb, at an event on climate-related financial risks hosted by the banco central do brasil.

Rio de Janeiro, 27 March 2024

Many thanks to the Banco Central do Brasil for inviting me here today. I am honoured to be speaking in Rio de Janeiro’s botanical garden. It is home to more than 6,500 different species – just a fraction of the more than 130,000 species that are estimated to be found in Brazil, the most biodiverse country in the world. But even this little glimpse into Brazil’s biodiversity is more than sufficient to appreciate the concept of natural capital and the tremendous value it represents.

At the same time, global heating and nature degradation are putting this natural capital at risk. And central banks and supervisors around the world recognise that this poses a serious threat to the stability of our economies and the robustness of our financial system.

Let me be clear from the outset: central banks and supervisors are not, and do not intend to be, policymakers in the area of climate and nature. It is governments that are responsible for climate and nature policies. In my remarks today, I will explain why central banks and supervisors have no option but to take the ongoing climate and nature crises into account to deliver on their monetary policy and banking supervision mandates. And that is exactly what central banks and supervisors around the world are doing. We at the European Central Bank (ECB) are not alone in this work, as can be seen from the work being done by the Banco Central do Brasil and most other central banks and supervisors around the world.

The relevance of climate and nature for central banks and supervisors

Human-induced global heating and nature degradation are scientifically established facts. Their devastating consequences are becoming all the more apparent in the increasing number of hazards we are seeing around the world. We don’t yet know exactly how the climate and nature crises will continue to unfold, partly because governments are taking mitigation and adaptation measures. This uncertainty also means that we don’t know exactly how the economy and the financial system will be affected.

At the same time, analysis consistently shows the vital importance of climate and nature for central banks and supervisors.

First, whatever happens, the economic impact will be profound. If left unchecked, global heating and nature degradation will contribute to increased macroeconomic volatility as climate and nature events become more frequent and have a greater impact on the economy. A successful transition to a green and sustainable economy, meanwhile, will require vast investment flows that will alter the way our economies function.

Second, the economic benefits of a timely transition far outweigh the costs, especially when considered against the alternative scenarios of doing nothing or doing too little too late. [ 1 ]

Third, climate-related risks translate into financial risks. Early work by the Basel Committee on Banking Supervision (BCBS) shows that climate events are a driver of each traditional type of risk considered in the regulatory framework, from credit risk, liquidity risk and market risk to reputational and operational risk, including legal risk. [ 2 ] Floods, for example, could damage a company’s production facility, which could affect its ability to repay a loan, in turn leading to higher credit risk for the bank that provided the loan. Or consider what might happen if your house is built in an area vulnerable to wildfires. Your home could fall in value, leaving the bank that granted you the mortgage with higher risk on its balance sheet.

And these financial risks are not related solely to climate change. Last year, when looking at more than 4.2 million individual companies that account for over €4.2 trillion in corporate loans, we found that nearly 75% of all bank loans in the euro area are to companies that are highly dependent on at least one ecosystem service. [ 3 ] Examples of these services include the products we obtain from ecosystems, such as food, drinking water, timber and minerals; protection against natural hazards; or carbon uptake and storage by vegetation. If these ecosystem services continue to experience the level of degradation they are currently facing, the stability of individual financial institutions and the broader financial system will be at risk.

International standard-setting bodies driving global action

Recognising the relevance of climate and nature-related factors for the economy, including the financial system, international standard-setting bodies are increasingly turning their attention to this topic. This has resulted in substantial progress at the global level, although more work lies ahead of us.

For example, the BCBS has a dedicated Task Force on Climate-related Financial Risks, whose meeting this week is kindly hosted by the Banco Central do Brasil. Based on the work of this task force, the BCBS has taken concrete steps to incorporate climate-related financial risks into the Basel framework for the global prudential regulation of banks. And progress has been made across all three pillars of the prudential framework: regulation, supervision and disclosures. On the topic of disclosures, late last year the BCBS issued a consultation paper on a proposed climate-related disclosure requirements framework, building on the work done in various other fora. The deadline for comments was two weeks ago and we are now carefully assessing the feedback received.

Meanwhile, there is also progress on nature-related risks. In view of the Brazilian G20 Presidency’s priority to deepen work on sustainability-related risk, the Financial Stability Board (FSB) will this year complement its climate-related work with a stocktake of current and planned regulatory and supervisory initiatives regarding nature-related financial risks. This may build on the work already done by the Central Banks and Supervisors Network for Greening the Financial System (NGFS). Last year the NGFS – which has 138 members worldwide, including the Banco Central do Brasil – published a conceptual framework to guide action by central banks and supervisors in the area of nature-related risks.

The work currently being done by the BCBS, the FSB and the NGFS will ultimately find its way to other international standard-setting bodies and translate into concrete practices by individual central banks and supervisors.

ECB measures to take climate and nature into account

Let me give you some examples of actions we have taken at the ECB.

In 2021 we unveiled an ambitious climate action plan covering macroeconomic modelling, financial stability monitoring, data collection, risk assessment capabilities and our monetary policy operations. Many of the actions we planned have now been delivered. For instance, we have made significant progress in improving the models that we use in macroeconomic analysis supporting our monetary policy decisions. Moreover, we have in place a methodology to tilt the purchase of corporate bonds towards issuers with a better climate performance – if we ever need to buy corporate bonds again in the future. In the collateral framework for our lending operations, we only accept assets that comply with the relevant sustainability reporting requirements and we are looking at setting limits on the share of assets issued by entities with a large carbon footprint.

In the area of banking supervision, we have urged banks to ensure the sound management of climate and nature-related risks, using the supervisory expectations we published in 2020 as a starting point. These expectations give guidance on how banks should integrate climate and nature-related risks into their strategy, governance and risk management. It is very much consistent with the general supervisory principles that have been established by the BCBS.

Since the ECB first started discussing climate and nature-related risks with banks back in 2019, progress has undoubtedly been made. Banks have taken steps to integrate these risks into their strategy, governance and risk management. Although at present none of the banks under our supervision fully meets all our expectations, each of our expectations has already been fulfilled by at least one bank. It shows that progress is possible, and that it is not just taking place among a few banks, but across the board. This is good news, since we expect all banks under our supervision to be fully aligned with our supervisory expectations by the end of 2024. We will enforce this final deadline as well as several interim deadlines. In fact, a number of banks under our supervision have already received binding requirements to remedy shortcomings by a certain date. If they do not comply, they will have to pay a penalty for every day that the shortcomings remain unresolved.

Building on the results achieved and progress made, earlier this year the ECB announced a new climate and nature action plan. It sets out concrete steps to consider how, within our mandate, we can further support the green transition, assess the physical impacts of climate change and explore the materiality of nature-related risks. Moreover, when we completed a review of our operational framework for implementing monetary policy two weeks ago, we announced that climate change-related considerations will be incorporated into the design of future structural monetary policy operations.

Let me conclude.

The Amazon river is subject to the “Pororoca”, one of the largest tidal bores in the world. It is an enormous wave travelling from the mouth of the Amazon on the Atlantic coast up to 800 kilometres upstream.

The climate and nature crises are unfolding. Together they are overflowing the economy and the financial system, very much like the “Pororoca” overflows the Amazon basin. Even if mitigation and adaptation measures are taken, one thing is certain: the world, the global economy and the financial system will see profound change.

In the words of Brazilian author Paulo Coelho: “You drown not from plunging into the water, but from staying submerged in it.” Emerging from the climate and nature crises requires action from all authorities within their mandate. For central banks and supervisors, this means taking climate and nature into account in the pursuit of their monetary policy and supervisory objectives. If they failed to do so, they would be failing on their mandate. The work that we are doing individually and collectively proves that we will not allow this to happen.

Thank you for your attention.

Emambakhsh, T. et al. (2023), “ The Road to Paris: stress testing the transition towards a net-zero economy ”, Occasional Paper Series , No 328, ECB.

Basel Committee on Banking Supervision (2021), Climate-related risk drivers and their transmission channels , April.

Boldrini, S. et al. (2023), “ Living in a world of disappearing nature: physical risk and the implications for financial stability ”, Occasional Paper Series , No 333, ECB.

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Navigating the Supergoop! Class Action: Insights for Conscious Consumers

I n a society increasingly vigilant about skin health and the dangers of UV exposure, sunscreen has become a non-negotiable part of our daily routines. Amidst this backdrop, Supergoop!, a company that has positioned itself as a champion of sun protection, has come under legal scrutiny. A recent class action lawsuit alleges that Supergoop! LLC falsely advertised the SPF level of its Unseen Sunscreen SPF 40 products, claiming they do not actually provide the SPF 40 protection as labeled. This case has sparked a conversation about transparency, trust, and the rigorous standards consumers expect from skincare brands.

Unpacking the Allegations

The lawsuit filed by plaintiff MarceAnn Dunning contends that the actual SPF protection offered by Supergoop’s Unseen Sunscreen SPF 40 is “significantly lower” than advertised. This discrepancy raises concerns not only about potential consumer deception but also about the efficacy of the product in protecting skin from harmful UV rays, which are known to contribute to skin cancer and premature aging.

The Consumer’s Dilemma

For consumers, especially millennials who prioritize health, wellness, and ethical consumption, the allegations against Supergoop! strike at the heart of the trust placed in skincare brands. Sunscreen is more than a cosmetic—it’s a health product, and accurate SPF labeling is crucial for making informed decisions about sun exposure and protection.

Implications for the Skincare Industry

The Supergoop! class action highlights a broader issue within the skincare and beauty industry: the need for stringent testing, transparent marketing, and accountability. As consumers become more informed and discerning, companies may face increased scrutiny regarding their product claims, formulations, and the authenticity of their marketing narratives.

Tips for Informed Sunscreen Choices

1. Research and Reviews: Before purchasing sunscreen, research the brand and read reviews from multiple sources. Look for independent testing results if available.

2. Understand SPF: Familiarize yourself with what SPF ratings mean and how different levels of protection are determined. Remember, higher SPF provides better protection but must be applied generously and frequently.

3. Seek Broad-Spectrum Formulas: Choose sunscreens offering broad-spectrum protection to guard against both UVA (aging) and UVB (burning) rays.

4. Consider Your Skin Type and Lifestyle: Select a sunscreen formulation suited to your skin type and lifestyle needs, whether you’re looking for water resistance, non-comedogenic properties, or sensitivity-friendly ingredients.

5. Stay Updated: Follow news and updates from reputable sources about sunscreen efficacy and safety standards, staying informed about any changes or concerns in the market.

The Supergoop! class action lawsuit serves as a timely reminder of the critical role of vigilance and education in skincare choices. While the legal process unfolds, consumers are reminded of the importance of scrutinizing the products we use daily, advocating for transparency and integrity in the beauty industry. As we navigate these challenges, let’s commit to making informed, health-conscious decisions that prioritize our well-being and uphold the standards we deserve from the brands we support.