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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).

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] .

Action Research

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Action research is an approach to research which aims at both taking action and creating knowledge or theory about that action as the action unfolds. It starts with everyday experience and is concerned with the development of living knowledge. Its characteristics are that it generates practical knowledge in the pursuit of worthwhile purposes; it is participative and democratic as its participants work together in the present tense in defining the questions they wish to explore, the methodology for that exploration, and its application through cycles of action and reflection. In this vein they are agents of change and coresearchers in knowledge generation and not merely passive subjects as in traditional research. In this vein, action research can be understood as a social science of the possible as the collective action is focused on creating a desired future in whatever context the action research is located.

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Action Research As an Ethics Praxis Method

Banks, S., & Brydon-Miller, M. (2018). Ethics in participatory research for health and social well-being . Abingdon: Routledge.

Book Google Scholar

Bradbury, H. (2015). The Sage handbook of action research (3rd ed.). Sage: London.

Bradbury, H., Mirvis, P., Neilsen, E., & Pasmore, W. (2008). Action research at work: Creating the future following the path from Lewin. In P. Reason & H. Bradbury (Eds.), The Sage handbook of action research (2nd ed., pp. 77–92). London: Sage.

Chapter Google Scholar

Bradbury, H., Roth, J., & Gearty, M. (2015). The practice of learning history: Local and open approaches. In H. Bradbury (Ed.), The Sage handbook of action research (3rd ed., pp. 17–30). London: Sage.

Brydon-Miller, M., Greenwood, D., & Maguire, P. (2003). Why action research? Action Research, 1 (1), 9–28.034201[1476–7503(200307)1:1].

Article Google Scholar

Chevalier, J. M., & Buckles, D. J. (2019). Participatory action research. Theory and methods for engaged inquiry (2nd ed.). Abingdon: Routledge.

Coghlan, D. (2010). Seeking common ground in the diversity and diffusion of action research and collaborative management research action modalities: Toward a general empirical method. In W.A. Pasmore, A.B.. (Rami) Shani and R.W. Woodman (Eds.), Research in organizational change and development (vol 18, pp. 149–181). Bingley: Emerald.

Google Scholar

Coghlan, D. (2016). Retrieving the philosophy of practical knowing for action research. International Journal of Action Research, 12 , 84–107. https://doi.org/10.1688/IJAR-2016-01 .

Coghlan, D. (2019). Doing action research in your own organization (5th ed.). London: Sage.

Coghlan, D., & Brydon-Miller, M. (2014). The Sage encyclopedia of action research . London: Sage.

Coghlan, D., & Shani, A.B.. (Rami). (2017). Inquiring in the present tense: The dynamic mechanism of action research. Journal of Change Management , 17, 121–137. https://doi.org/10.1080/14697017.2017.1301045 .

Coghlan, D., Shani, A.B.. (Rami), & Hay, G.W. (2019). Toward a social science philosophy of organization development and change. In D.A. Noumair & A.B.. (Rami) Shani (eds.). Research in organizational change and development (Vol. 27, pp. 1–29). Bingley: Emerald.

Gearty, M., & Coghlan, D. (2018). The first-, second- and third-person dynamics of learning history. Systemic Practice & Action Research., 31 , 463–478. https://doi.org/10.1007/s11213-017-9436-5 .

Greenwood, D., & Levin, M. (2007). Introduction to action research (2nd ed.). Thousand Oaks: Sage.

Heron, J., & Reason, P. (1997). A participatory inquiry paradigm. Qualitative Inquiry, 3 , 274–294.

Heron, J., & Reason, P. (2008). Extending epistemology within a cooperative inquiry. In P. Reason & H. Bradbury (Eds.), The Sage handbook of action research (2nd ed., pp. 366–380). London: Sage.

Huxham, C. (2003). Actionresearch as a methodology for theory development. Policy and Politics, 31 (2), 239–248. https://doi.org/10.1332/030557303765371726 .

Koshy, E., Koshy, V., & Waterman, H. (2011). Action research in healthcare . London: Sage.

Lonergan, B. J. (2005). Dimensions of meaning. In B. J. Lonergan (Ed.), The collected work of Bernard Lonergan (Vol. 4, pp. 232–244). Toronto: Toronto University Press.

Marshall, J. (2016). First person action research: Living life as inquiry . London: Sage.

Owen, R., Bessant, J., & Heintz, M. (2013). Responsible innovation: Managing the responsible emergence of science and innovation in society . London: Wiley.

Pasmore, W. A. (2001). Action research in the workplace: The socio-technical perspective. In P. Reason & H. Bradbury (Eds.), The handbook of action research (pp. 38–47). London: Sage.

Revans, R. W. (1971). Developing effective managers . London: Longmans.

Revans, R. (1998). ABC of action learning . London: Lemos& Crane.

Schein, E. H. (2013). Humble inquiry: The gentle art of asking instead of telling . Oakland: Berrett-Kohler.

Shani, A.B.. (Rami), & Coghlan, D. (2019). Action research in business and management: A reflective review. Action Research . https://doi.org/10.1177/1476750319852147 .

Susman, G. I., & Evered, R. D. (1978). An assessment of the scientific merits of action research. Administrative Science Quarterly, 23 , 582–601. https://doi.org/10.2307/2392581 .

Torbert, W. R., & Associates. (2004). Action inquiry . San Francisco: Jossey-Bass.

Whitney, D., & Trosten-Bloom, A. (2010). The power of appreciative inquiry: A practical guide to positive change . Oakland: Berrett-Kohler.

Williamson, G., & Bellman, L. (2012). Action research in nursing and healthcare . London: Sage.

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Coghlan, D. (2022). Action Research. In: Glăveanu, V.P. (eds) The Palgrave Encyclopedia of the Possible. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-90913-0_180

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Action research.

Eileen S. Johnson Eileen S. Johnson Oakland University
https://doi.org/10.1093/acrefore/9780190264093.013.696
Published online: 29 May 2020

Action research has become a common practice among educational administrators. The term “action research” was first coined by Kurt Lewin in the 1930s, although teachers and school administrators have long engaged in the process described by and formally named by Lewin. Alternatively known as practitioner research, self-study, action science, site-based inquiry, emancipatory praxis, etc., action research is essentially a collaborative, democratic, and participatory approach to systematic inquiry into a problem of practice within a local context. Action research has become prevalent in many fields and disciplines, including education, health sciences, nursing, social work, and anthropology. This prevalence can be understood in the way action research lends itself to action-based inquiry, participation, collaboration, and the development of solutions to problems of everyday practice in local contexts. In particular, action research has become commonplace in educational administration preparation programs due to its alignment and natural fit with the nature of education and the decision making and action planning necessary within local school contexts. Although there is not one prescribed way to engage in action research, and there are multiple approaches to action research, it generally follows a systematic and cyclical pattern of reflection, planning, action, observation, and data collection, evaluation that then repeats in an iterative and ongoing manner. The goal of action research is not to add to a general body of knowledge but, rather, to inform local practice, engage in professional learning, build a community practice, solve a problem or understand a process or phenomenon within a particular context, or empower participants to generate self-knowledge.

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Action research

A type of applied research designed to find the most effective way to bring about a desired social change or to solve a practical problem, usually in collaboration with those being researched.

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How do you define action research.

Professor David Coghlan explains action research as an approach that crosses many academic disciplines yet has a shared focus on taking action to address a problem. He describes the difference between this approach and empirical scientific approaches, particularly highlighting the challenge of getting action research to be taken seriously by academic journals

Dr. Nataliya Ivankova defines action research as using systematic research principles to address an issue in everyday life. She delineates the six steps of action research, and illustrates the concept using an anti-diabetes project in an urban area.

This is just one segment in a whole series about action research. You can find the rest of the series in our SAGE database, Research Methods:

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What is Action Research?

Considerations, creating a plan of action.

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Action research is a qualitative method that focuses on solving problems in social systems, such as schools and other organizations. The emphasis is on solving the presenting problem by generating knowledge and taking action within the social system in which the problem is located. The goal is to generate shared knowledge of how to address the problem by bridging the theory-practice gap (Bourner & Brook, 2019). A general definition of action research is the following: “Action research brings together action and reflection, as well as theory and practice, in participation with others, in the pursuit of practical solutions to issues of pressing concern” (Bradbury, 2015, p. 1). Johnson (2019) defines action research in the field of education as “the process of studying a school, classroom, or teacher-learning situation with the purpose of understanding and improving the quality of actions or instruction” (p.255).

Origins of Action Research

Kurt Lewin is typically credited with being the primary developer of Action Research in the 1940s. Lewin stated that action research can “transform…unrelated individuals, frequently opposed in their outlook and their interests, into cooperative teams, not on the basis of sweetness but on the basis of readiness to face difficulties realistically, to apply honest fact-finding, and to work together to overcome them” (1946, p.211).

Sample Action Research Topics

Some sample action research topics might be the following:

Examining how classroom teachers perceive and implement new strategies in the classroom--How is the strategy being used? How do students respond to the strategy? How does the strategy inform and change classroom practices? Does the new skill improve test scores? Do classroom teachers perceive the strategy as effective for student learning?
Examining how students are learning a particular content or objectives--What seems to be effective in enhancing student learning? What skills need to be reinforced? How do students respond to the new content? What is the ability of students to understand the new content?
Examining how education stakeholders (administrator, parents, teachers, students, etc.) make decisions as members of the school’s improvement team--How are different stakeholders encouraged to participate? How is power distributed? How is equity demonstrated? How is each voice valued? How are priorities and initiatives determined? How does the team evaluate its processes to determine effectiveness?
Examining the actions that school staff take to create an inclusive and welcoming school climate--Who makes and implements the actions taken to create the school climate? Do members of the school community (teachers, staff, students) view the school climate as inclusive? Do members of the school community feel welcome in the school? How are members of the school community encouraged to become involved in school activities? What actions can school staff take to help others feel a part of the school community?
Examining the perceptions of teachers with regard to the learning strategies that are more effective with special populations, such as special education students, English Language Learners, etc.—What strategies are perceived to be more effective? How do teachers plan instructionally for unique learners such as special education students or English Language Learners? How do teachers deal with the challenges presented by unique learners such as special education students or English Language Learners? What supports do teachers need (e.g., professional development, training, coaching) to more effectively deliver instruction to unique learners such as special education students or English Language Learners?

Remember—The goal of action research is to find out how individuals perceive and act in a situation so the researcher can develop a plan of action to improve the educational organization. While these topics listed here can be explored using other research designs, action research is the design to use if the outcome is to develop a plan of action for addressing and improving upon a situation in the educational organization.

Considerations for Determining Whether to Use Action Research in an Applied Dissertation

When considering action research, first determine the problem and the change that needs to occur as a result of addressing the problem (i.e., research problem and research purpose). Remember, the goal of action research is to change how individuals address a particular problem or situation in a way that results in improved practices.
If the study will be conducted at a school site or educational organization, you may need site permission. Determine whether site permission will be given to conduct the study.
Consider the individuals who will be part of the data collection (e.g., teachers, administrators, parents, other school staff, etc.). Will there be a representative sample willing to participate in the research?
If students will be part of the study, does parent consent and student assent need to be obtained?
As you develop your data collection plan, also consider the timeline for data collection. Is it feasible? For example, if you will be collecting data in a school, consider winter and summer breaks, school events, testing schedules, etc.
As you develop your data collection plan, consult with your dissertation chair, Subject Matter Expert, NU Academic Success Center, and the NU IRB for resources and guidance.
Action research is not an experimental design, so you are not trying to accept or reject a hypothesis. There are no independent or dependent variables. It is not generalizable to a larger setting. The goal is to understand what is occurring in the educational setting so that a plan of action can be developed for improved practices.

Considerations for Action Research

Below are some things to consider when developing your applied dissertation proposal using Action Research (adapted from Johnson, 2019):

Research Topic and Research Problem -- Decide the topic to be studied and then identify the problem by defining the issue in the learning environment. Use references from current peer-reviewed literature for support.
Purpose of the Study —What need to be different or improved as a result of the study?
Research Questions —The questions developed should focus on “how” or “what” and explore individuals’ experiences, beliefs, and perceptions.
Theoretical Framework -- What are the existing theories (theoretical framework) or concepts (conceptual framework) that can be used to support the research. How does existing theory link to what is happening in the educational environment with regard to the topic? What theories have been used to support similar topics in previous research?
Literature Review -- Examine the literature, focusing on peer-reviewed studies published in journal within the last five years, with the exception of seminal works. What about the topic has already been explored and examined? What were the findings, implications, and limitations of previous research? What is missing from the literature on the topic? How will your proposed research address the gap in the literature?
Data Collection —Who will be part of the sample for data collection? What data will be collected from the individuals in the study (e.g., semi-structured interviews, surveys, etc.)? What are the educational artifacts and documents that need to be collected (e.g., teacher less plans, student portfolios, student grades, etc.)? How will they be collected and during what timeframe? (Note--A list of sample data collection methods appears under the heading of “Sample Instrumentation.”)
Data Analysis —Determine how the data will be analyzed. Some types of analyses that are frequently used for action research include thematic analysis and content analysis.
Implications —What conclusions can be drawn based upon the findings? How do the findings relate to the existing literature and inform theory in the field of education?
Recommendations for Practice--Create a Plan of Action— This is a critical step in action research. A plan of action is created based upon the data analysis, findings, and implications. In the Applied Dissertation, this Plan of Action is included with the Recommendations for Practice. The includes specific steps that individuals should take to change practices; recommendations for how those changes will occur (e.g., professional development, training, school improvement planning, committees to develop guidelines and policies, curriculum review committee, etc.); and methods to evaluate the plan’s effectiveness.
Recommendations for Research —What should future research focus on? What type of studies need to be conducted to build upon or further explore your findings.
Professional Presentation or Defense —This is where the findings will be presented in a professional presentation or defense as the culmination of your research.

Adapted from Johnson (2019).

Considerations for Sampling and Data Collection

Below are some tips for sampling, sample size, data collection, and instrumentation for Action Research:

Sampling and Sample Size

Action research uses non-probability sampling. This is most commonly means a purposive sampling method that includes specific inclusion and exclusion criteria. However, convenience sampling can also be used (e.g., a teacher’s classroom).

Critical Concepts in Data Collection

Triangulation- - Dosemagen and Schwalbach (2019) discussed the importance of triangulation in Action Research which enhances the trustworthiness by providing multiple sources of data to analyze and confirm evidence for findings.

Trustworthiness —Trustworthiness assures that research findings are fulfill four critical elements—credibility, dependability, transferability, and confirmability. Reflect on the following: Are there multiple sources of data? How have you ensured credibility, dependability, transferability, and confirmability? Have the assumptions, limitations, and delimitations of the study been identified and explained? Was the sample a representative sample for the study? Did any individuals leave the study before it ended? How have you controlled researcher biases and beliefs? Are you drawing conclusions that are not supported by data? Have all possible themes been considered? Have you identified other studies with similar results?

Sample Instrumentation

Below are some of the possible methods for collecting action research data:

Pre- and Post-Surveys for students and/or staff
Staff Perception Surveys and Questionnaires
Semi-Structured Interviews
Focus Groups
Observations
Document analysis
Student work samples
Classroom artifacts, such as teacher lesson plans, rubrics, checklists, etc.
Attendance records
Discipline data
Journals from students and/or staff
Portfolios from students and/or staff

A benefit of Action Research is its potential to influence educational practice. Many educators are, by nature of the profession, reflective, inquisitive, and action-oriented. The ultimate outcome of Action Research is to create a plan of action using the research findings to inform future educational practice. A Plan of Action is not meant to be a one-size fits all plan. Instead, it is mean to include specific data-driven and research-based recommendations that result from a detailed analysis of the data, the study findings, and implications of the Action Research study. An effective Plan of Action includes an evaluation component and opportunities for professional educator reflection that allows for authentic discussion aimed at continuous improvement.

When developing a Plan of Action, the following should be considered:

How can this situation be approached differently in the future?
What should change in terms of practice?
What are the specific steps that individuals should take to change practices?
What is needed to implement the changes being recommended (professional development, training, materials, resources, planning committees, school improvement planning, etc.)?
How will the effectiveness of the implemented changes be evaluated?
How will opportunities for professional educator reflection be built into the Action Plan?

Sample Action Research Studies

Anderson, A. J. (2020). A qualitative systematic review of youth participatory action research implementation in U.S. high schools. A merican Journal of Community Psychology, 65 (1/2), 242–257. https://onlinelibrary-wiley-com.proxy1.ncu.edu/doi/epdf/10.1002/ajcp.12389

Ayvaz, Ü., & Durmuş, S.(2021). Fostering mathematical creativity with problem posing activities: An action research with gifted students. Thinking Skills and Creativity, 40. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1871187121000614&site=eds-live

Bellino, M. J. (2018). Closing information gaps in Kakuma Refugee Camp: A youth participatory action research study. American Journal of Community Psychology, 62 (3/4), 492–507. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ofs&AN=133626988&site=eds-live

Beneyto, M., Castillo, J., Collet-Sabé, J., & Tort, A. (2019). Can schools become an inclusive space shared by all families? Learnings and debates from an action research project in Catalonia. Educational Action Research, 27 (2), 210–226. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=135671904&site=eds-live

Bilican, K., Senler, B., & Karısan, D. (2021). Fostering teacher educators’ professional development through collaborative action research. International Journal of Progressive Education, 17 (2), 459–472. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=149828364&site=eds-live

Black, G. L. (2021). Implementing action research in a teacher preparation program: Opportunities and limitations. Canadian Journal of Action Research, 21 (2), 47–71. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=149682611&site=eds-live

Bozkuş, K., & Bayrak, C. (2019). The Application of the dynamic teacher professional development through experimental action research. International Electronic Journal of Elementary Education, 11 (4), 335–352. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=135580911&site=eds-live

Christ, T. W. (2018). Mixed methods action research in special education: An overview of a grant-funded model demonstration project. Research in the Schools, 25( 2), 77–88. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=135047248&site=eds-live

Jakhelln, R., & Pörn, M. (2019). Challenges in supporting and assessing bachelor’s theses based on action research in initial teacher education. Educational Action Research, 27 (5), 726–741. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=140234116&site=eds-live

Klima Ronen, I. (2020). Action research as a methodology for professional development in leading an educational process. Studies in Educational Evaluation, 64 . https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S0191491X19302159&site=eds-live

Messiou, K. (2019). Collaborative action research: facilitating inclusion in schools. Educational Action Research, 27 (2), 197–209. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ehh&AN=135671898&site=eds-live

Mitchell, D. E. (2018). Say it loud: An action research project examining the afrivisual and africology, Looking for alternative African American community college teaching strategies. Journal of Pan African Studies, 12 (4), 364–487. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ofs&AN=133155045&site=eds-live

Pentón Herrera, L. J. (2018). Action research as a tool for professional development in the K-12 ELT classroom. TESL Canada Journal, 35 (2), 128–139. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ofs&AN=135033158&site=eds-live

Rodriguez, R., Macias, R. L., Perez-Garcia, R., Landeros, G., & Martinez, A. (2018). Action research at the intersection of structural and family violence in an immigrant Latino community: a youth-led study. Journal of Family Violence, 33 (8), 587–596. https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132323375&site=eds-live

Vaughan, M., Boerum, C., & Whitehead, L. (2019). Action research in doctoral coursework: Perceptions of independent research experiences. International Journal for the Scholarship of Teaching and Learning, 13 . https://proxy1.ncu.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edsdoj&AN=edsdoj.17aa0c2976c44a0991e69b2a7b4f321&site=eds-live

Sample Journals for Action Research

Educational Action Research

Canadian Journal of Action Research

Sample Resource Videos

Call-Cummings, M. (2017). Researching racism in schools using participatory action research [Video]. Sage Research Methods http://proxy1.ncu.edu/login?URL=https://methods.sagepub.com/video/researching-racism-in-schools-using-participatory-action-research

Fine, M. (2016). Michelle Fine discusses community based participatory action research [Video]. Sage Knowledge. http://proxy1.ncu.edu/login?URL=https://sk-sagepub-com.proxy1.ncu.edu/video/michelle-fine-discusses-community-based-participatory-action-research

Getz, C., Yamamura, E., & Tillapaugh. (2017). Action Research in Education. [Video]. You Tube. https://www.youtube.com/watch?v=X2tso4klYu8

Bradbury, H. (Ed.). (2015). The handbook of action research (3rd edition). Sage.

Bradbury, H., Lewis, R. & Embury, D.C. (2019). Education action research: With and for the next generation. In C.A. Mertler (Ed.), The Wiley handbook of action research in education (1st edition). John Wiley and Sons. https://ebookcentral.proquest.com/lib/nu/reader.action?docID=5683581&ppg=205

Bourner, T., & Brook, C. (2019). Comparing and contrasting action research and action learning. In C.A. Mertler (Ed.), The Wiley handbook of action research in education (1st edition). John Wiley and Sons. https://ebookcentral.proquest.com/lib/nu/reader.action?docID=5683581&ppg=205

Bradbury, H. (2015). The Sage handbook of action research . Sage. https://www-doi-org.proxy1.ncu.edu/10.4135/9781473921290

Dosemagen, D.M. & Schwalback, E.M. (2019). Legitimacy of and value in action research. In C.A. Mertler (Ed.), The Wiley handbook of action research in education (1st edition). John Wiley and Sons. https://ebookcentral.proquest.com/lib/nu/reader.action?docID=5683581&ppg=205

Johnson, A. (2019). Action research for teacher professional development. In C.A. Mertler (Ed.), The Wiley handbook of action research in education (1st edition). John Wiley and Sons. https://ebookcentral.proquest.com/lib/nu/reader.action?docID=5683581&ppg=205

Lewin, K. (1946). Action research and minority problems. In G.W. Lewin (Ed.), Resolving social conflicts: Selected papers on group dynamics (compiled in 1948). Harper and Row.

Mertler, C. A. (Ed.). (2019). The Wiley handbook of action research in education. John Wiley and Sons. https://ebookcentral.proquest.com/lib/nu/detail.action?docID=5683581

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Action Research: What it is, Stages & Examples

Action research is a method often used to make the situation better. It combines activity and investigation to make change happen.

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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2 Action Research as a Process for Professional Learning and Leadership

ESSENTIAL QUESTIONS

What is the role of action research in professional learning and leadership?
What are the educational contexts that action research takes place?
What are the critiques of action research as a methodology?
What are the basic stages of an action research project?

In the previous chapter, we were able to explore the idea of action research, the purpose of action research, and the theoretical underpinnings of action research. Hopefully, you now have a good understanding of the landscape of action research and the contours in which it can take shape in educational contexts. It is important to emphasize that the primary aim of conducting action research in an educational context is to study and improve upon an educator’s, or group of educators’, practice. This chapter will explore some of the practical aspects of action research, in particular, the forethought and planning required to engage in a successful action research experience.

As we begin to transition from the theoretical to the more practical aspects of action research, we want to provide a few questions to consider:

How does the epistemological, ontological, and theoretical basis of action research fit with your pedagogical philosophy in the classroom? Will using action research require any paradigmatic shifts in how you approach your pedagogy?
What are the pedagogical benefits of using action research in your educational context?
What are the most significant affordances and challenges of using action research in your educational context?

After considering the questions above, we think it is important from a practical standpoint to consider and situate action research as part of an educator’s responsibility to professional learning and leadership.

Action Research as Professional Learning and Leadership

Thus far, we have made the case that action research is a useful methodology for educators because it formalizes a process you already use to improve your pedagogy; but how does it benefit you as a professional and your professional identity? In Becoming Critical Carr and Kemmis (2003) list characteristics of action research that make it integral to critical professional learning for educators. We have summarized their five characteristics of action research as a methodology for educators:

Five Characteristics of Action Research as a Methodology for Educators

action research rejects positivist notions of rationality, objectivity, and truth and instead has an openness to competing possibilities for effective pedagogical practice in educational contexts;
action research employs educators’ reflective and interpretive categories, and uses the language of educators as a basis for educators to explore and develop their own pedagogical theorizing;
action research allows educators’ unrealized self-understandings to be discerned by analyzing their own practices and understandings;
action research connects reflection to action, enabling educators to overcome barriers to pedagogical change through awareness of social and systemic factors influencing their educational context;
action research involves deep consideration of theory and practice and to demonstrate this critically self-reflective action, researchers develop and organize knowledge in which truth is evidenced through its relation to practice.

To synthesize these five characteristics in terms of practical knowledge, we think it is important to now consider a “so what?” type of question. After learning these characteristics, why would an educator engage in action research for the purpose of professional learning or leadership? The following five principles correspond to the five characteristics above:

Why an Educator would Engage in Action Research

the development of an educator’s pedagogy is not about developing a set of “surefire” technical competencies; it is concerned with finding the most effective practices for the students in their educational context;
one way for educators to be consistently informed on pedagogy and increase their skills is through actively being involved in a culture of inquiry that dually relies on the latest educational research and their own classroom to spark new inquiry;
by doing action research, educators are engaged in the process of hypothesizing, theorizing, and developing self-knowledge related specifically to their practice;
when educators engage in action research, they develop agency and gain control of knowledge, and address questions for themselves, instead of being subservient to the knowledge enacted on their educational context;
when educators are engaged in research, educators are naturally engaged in educational theorizing because they are reflecting on practice systematically and critically, to close the distance between educational theory practice, which many educators feel (Hopkins, 2003).

Professional learning in education takes many forms. Action research is unique in the realm of professional learning because it is tailored to the educator’s real time pedagogical foci, issues, or needs. Professional learning opportunities often fail to meet the expectations of educators because they are meant for large groups of teachers, either based on a school, topic, subject, or course. Even at the course level of professional learning, while the content may be the same for each teacher, the students and educational context are different for each teacher – which creates unique challenges that educators want to address through their professional learning. One advantage of traditional professional learning sessions is the group aspect, or collaborative thinking that takes place. Action research is flexible enough that collaborative inquiry could be part of the process, and educators could include colleagues as part of their research. In many ways, action research not only contributes to professional learning, but also provides professional leadership to colleagues.

Professional leadership in education, or teacher leadership, also takes many forms. Danielson (2007) lists teacher leadership in her framework for teaching, as one of several professional responsibilities for educators. Educators who engage in action research and share their findings, are working to impact professional learning, and subsequently student learning, beyond their classrooms. Engaged educators who attain and continue to receive recognition in the teaching profession invest a lot of time and energy to stay informed and further develop their skills. Danielson (2007) notes that these educators are in a prime position to exercise leadership among their colleagues. Often times educators view conferences and professional learning sessions as the only opportunities to further develop their skills and become leaders among their colleagues. However, Danielson (2007) goes on to describe a distinguished educator as someone who engages in a combination of seeking “out opportunities for professional development and makes a systematic effort to conduct action research” (105). In this way, professional learning is a part of the action research process that engages educators in reflection and conversations outside of their educational context, while also potentially providing an alternative lens to analyze their data.

Data-driven decision making by administrators, teachers, and teams of educators, often facilitated by teacher leaders, is a prevalent practice in schools that impacts educator performance and student learning. This sort of professional learning through collaborative inquiry provides vital contextual data to improve pedagogy in classrooms and throughout the school. Sagor (2010) defines collaborative action research as ”the team inquiry process, when a group of individuals who are a part of a specific PLC, grade-level, or teacher learning team engage in inquiry and research.” These teams can become a means for collaboratively engaging in action research and developing data that is relative to the school. Data is most valuable to an educational context when it is deeply relatable and relevant to the specific educational context. Data specifically related to the educational context can increase a school’s capacity to focus on curricular and instructional strategies with the greatest potential to support student learning. In an effort to spark professional leadership, and as we discuss the process of action research in future chapters, please discuss with colleagues the potential action research projects in your own classroom and think about how to leverage those toward your school’s PLC, professional learning, or school-wide improvement plans. Thinking about your action research in this way adds another layer of purpose and makes action research a truly valuable process for improvement throughout your educational context.

What Will Action Look Like in My Classroom?

Now that we have discussed the relevance of action research for professional learning and leadership, it may be a little easier to conceptualize an action research project, or perhaps you already have an idea ready to start. O’Leary (2004) provides a useful list of processes related to action research that could help you think about your initial plans. Here are some questions to think about related to the processes of an action research project:

Does it address a practical problems(s)? Educators typically identify a practical problem in their educational context that has multiple possible ways to be addressed. The impetus to improve professional practice prioritizes change.
Does it generate knowledge? Generating knowledge promotes change. By addressing this practical problem, you will generate knowledge.
Does it enact changes in your pedagogy/classroom/school? The changes generated by the knowledge will be useful to enact change relatively close to the conclusion of the research project.
Is it participatory? Action research is participatory, and the primary researcher is involved in the action, potentially along with other researchers and stakeholders.
Could it be a cyclical process? Action research is a cyclical process that results from emerging knowledge. Once better situational understanding is gained through research, a change can be implemented and researched again, resulting in an evaluative practice that reciprocates between informed action and critical reflection.

I want to emphasize that this is one of interpretations of the processes involved in the action research process, and you should adapt these basic processes to fit your needs as an educator and researcher. These processes will also become clearer in purpose as we discuss the contexts for action research.

The Contexts for Considering Action Research

Action research can take place in many professional settings and contexts. As we think about some of those contexts we will focus on the most common in educational settings. I have also provided some examples for research in each context.

Improving Classroom Practice

These projects are conducted by educators in their classroom context and focus on pedagogical, curricular, or instructional aspects of their practice. Examples could include:

How can Socratic questioning improve engagement in class discussions?
Who participates more in my class?
How can integrated social studies and ELA lessons improve students’ reading scores?
Will learning diaries in mathematics lessons enhance students’ conceptual understanding?
How can Flipgrid help connect student interests to content standards?

Examining an Educational Theme

These projects allow educators to examine new ideas or themes that they have encountered in professional learning opportunities. Examples could include:

How can I implement personalized learning in my classroom?
Can I integrate all subjects into a problem-based inquiry project?
In what ways do Breakout Box activities prepare students for content-based learning?
Do exercise balls help students focus longer while sitting at their seats?

Educational Context Focus

These projects focus on interaction between humans and the ecological space of the context. Examples could include:

How can using non-letter grades improve communication with parents?
How can we increase engagement at parent meetings?
Does going outside and doing yoga improve student focus in the afternoon?
What is the effect of eliminating homework?
Does presenting to community members, outside the school community, improve engagement or motivation for group projects?
What anti-bullying strategies reduce verbal teasing?

Implementing a New Initiative Based on Policy or Research

These projects are sparked by new policy or research data or are related to district or state-wide initiatives. These are often group or collaborative projects. Examples could include:

What are the best methods to prepare teachers for a school-wide one-to-one device launch?
Do weekly meetings help support first-year teachers?
Adopting the new formative assessment framework for inquiry-based learning.

Critiques of Action Research

Action research is a fairly new form of acceptable educational research; therefore, educators should be aware of some of the common critiques you may hear when presenting or sharing your research. These critiques can also be easily dealt with in the planning and development of your action research project. The following are three of the most common critiques of action research.

Critique #1: Action research lacks rigor and trustworthiness in comparison to other methodologies…

The rigor of a research project is shaped by the manner in which data collection and analysis are conducted in the research process. For example, rigor can develop in data collection by using a variety of research methods to collect data (discussed further in Chapter 6). Sharing data with critical friends and colleagues, or triangulating the data, would demonstrate rigor in the data analysis process. Issues of trustworthiness are raised around the question: Can you be/maintain objectivity when you are conducting research on your own practice? Trustworthiness can be viewed as the strength of the inference made possible by the given research study. Trustworthiness can be achieved primarily through triangulation of data (multiple sources of data) and a clear description of context, participants, processes, and analysis which allows for transferability as a reader. Maintaining a rigorous data collection and analysis process will help with trustworthiness, but also being clear in your epistemological stance and positionality from the beginning of the project also contributes to trustworthiness. Rigor and trustworthiness can easily be addressed through developing a research plan and sticking to it. Adherence to ethical research (IRB) will also add to trustworthiness, we will discuss this in a later chapter.

Critique #2: Action research findings are not generalizable to other educational contexts…

Generalizability is often a concern for quantitative researchers who are trying to solve problems across large portions of the population. Simply put, the action researcher is not concerned with generalizable data that can provide answers to other educators in different contexts (However, it is great if this happens!). The action researcher is primarily concerned with generating knowledge based on the actions within their own situated context. Action research findings are generalizable only within specific situations and within that specific educational context, which is described and considered as part of the research process. Sharing findings could be applicable to educators who are interested or who are in similar circumstances, either locally, nationally, or globally.

Critique #3: Action research is based on a deficit model…

The problem-solving nature of action research may give an appearance that it is based on a deficit model. This is not necessarily the case; however, if researchers are not conscious of deficit thinking or deficit models of thinking, it is possible to engage in action research based on perceived student deficits. From my perspective, developing strategies for solving a problem within a situation with the sole purpose of improving practice is not rooted in deficit thinking, especially if they really generate knowledge. Regardless, researchers need to be aware of deficit thinking and make sure their research questions do not rely on assumptions about students’ weaknesses based on demographic groupings.

What’s Ahead? Thinking about the Stages of Action Research

The models of action research presented in Chapter 1 all described action research as a cyclical process. It is exciting to think about a cyclical process of professional learning to improve your practice; however, it can also be overwhelming to think about the process. We think it is helpful to have some awareness of what may happen during the project, represented in distinct stages, to provide an overview of the whole process. This will help you plan more efficiently, but we think it is also important to be flexible and understand that your project does not always need to follow that order. Here is what to expect:

Identifying a topic in the educational context
Reviewing related literature
Revising the topic
Developing a research question
Plan research activities
Collect data
Analyze data
Action implementation
Reflection on action
Report, share, or document.

Each of these steps has some brief considerations, yet I would like to discuss these steps in three broad areas of focus due to the overlap of these considerations.

Topic Development

Researching in Action

Action Implications

Identifying and developing a topic that is important and relevant to your practice is vitally essential. Your topic not only shapes the area of educational knowledge you will contribute to, but it will also shape your research question. It is usually helpful to identify and write down three to five potential topics. In addition to writing the topic down, describe why each topic is important or relevant to you, your practice, your students, and/or your educational context. Then, if you are still having a hard time deciding on a topic, write down the intended benefits for you, your practice, your students, and/or your educational context. It may also be helpful to discuss your ideas with others, to help focus your thoughts and provide another perspective on the feasibility of completing a study on a particular topic, its relevance and implications for practice.

Once you have identified a topic, it is important to conduct a literature review (discussed fully in Chapter 3) to find out what the field of education has researched in regards to your topic. This will help you understand what we know and don’t know about your topic. Once you have conducted a thorough literature review you will feel capable of potentially revising your topic to reflect the knowledge base, and possibly narrow the scope of your project for your own purposes.

Lastly, you will be able to develop a research question (discussed fully in Chapter 4) based on your topic, the reviewed literature, and your intended outcomes.

Researching Action

After you have thoroughly vetted a topic and developed a research question, you will be ready to begin the process of researching your topic in your educational context. In consideration of your research question, you can begin to plan your research activities—when and how you will conduct the research in your educational context (Chapter 4). This will include a timeline of activities. You will then begin planning your data collection (Chapter 5) methods and fit those into your timeline. You will also need to think about a proposed process, or order for analyzing your data. This may seem strange; however, it helps contribute to the rigor and validity of your study to have a plan that fits within your epistemological stance.

Once your plan is set, you can begin the data collection process. After data collection, you can begin the analysis of the data (Chapter 6).

After you have analyzed your data, you should have some indication as to implications for your research question. You will have the opportunity to reflect on the research, take action, and eventually share or report your findings. Many of you will have reason to change an action in your educational context, whether it is the following week, the next semester, or next school year. This is where the cyclical process of action research can take shape.

Action Research in Action: A Vignette

As a classroom teacher, I was often engaged in action research without realizing it, and typically this process began from reflection. As a graduate student, weekly reflections on the required readings in my Teachers as Researchers course prompted me to identify issues in my classroom to address, either through pedagogical changes or adjustments to my curriculum. In a less formal way, action research naturally emerged as part of my yearly evaluations with administration. In one particular year, after reflecting on my own practice, I realized (rather, admitted) that my junior-level English students did not enjoy our classroom novel studies, resulting in a lack of engagement and poor performance for many of them. The ‘start and stop’ method—where students read a chapter, then stop to either discuss the chapter or take a quiz—did not replicate how people read books, and it is no wonder that it destroyed my students’ desire to engage with the novels they were assigned. This is where action research emerged—I established a driving question for my own classroom problem: How can I adapt whole novel studies to reflect the natural reading process, take into account each students’ reading level, and improve overall reading performance and engagement?

The next step in this process was to find research that already existed on whole novel studies in the classroom and use that information as a catalyst for my own research. I read several examples of alternative methods to whole novel studies, but most of what I could find was based on a middle school classroom. This was good news! It meant, on a large scale, my action research would have a place in the broad educational context by filling an existing void in the information available to classroom teachers. On a small scale, this meant other teachers in my own department could benefit from what I design since a lack of resources exists in this area.

After reading several examples of alternative methods, I adapted the practices that seemed to fit best with my own students and created my own version of how to work with whole novels in the high school English classroom. I implemented this method in two different courses, one of which was considered an ‘advanced’ course, with students at all different reading levels. I tracked their progress in multiple ways and recorded the information on spreadsheets for future use. After a successful first attempt at changing my practice, I presented the findings to my colleagues at a department meeting, and many adapted my method to use in their own classrooms.

Though this example of action research does not reflect a formalized project, it speaks to how teachers naturally engage in the process of questioning and problem-solving to create change for their students. It also demonstrates the value in what teachers discover in their own classrooms. Researchers are often criticized for being too far removed from classroom practice to really understand what teachers need; but teacher researchers have the opportunity to be their own guide and to potentially influence teacher praxis in positive and practical ways.

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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Action research.

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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/

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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.


Purpose	To draw conclusions. Focus is on advancing knowledge in the field. Insights may be generalized to other settings.	To make decisions. Focus is on the improvement of practice. Limited generalizability.
Context	Theory: Hypotheses/research questions derive from more general theoretical propositions.	Practice: Research questions derive from practice. Theory plays secondary role.
Data Analysis	Rigorous statistical analysis.	Focus on practical, not statistical significance
Sampling	Random or representative sample.	Clientele or students with whom they work.

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

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Last Updated: Mar 12, 2024 3:14 PM
URL: https://guides.library.ucmo.edu/actionresearch

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Methodology
What Is Action Research? | Definition & Examples

What Is Action Research? | Definition & Examples

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

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.

	Action research	Traditional research
		and findings
		and seeking between variables

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 24 June 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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The purpose of action research

The purpose of action research is to gather information in an attempt to solve a problem or make an improvement, which may have been highlighted as a result of self-evaluation or student feedback. While this is the core purpose, the motivations may be different, the motivation may be sincere and the goal to be improvement of student education, behaviour or morale, alternatively the motivation could be disingenuous, including aspects such as increasing chances of promotion, making teaching easier or promoting one’s own agenda.

The aim of action research is to be able to answer a question/hypothesis, such as will allowing mobile phone use within lessons increase the levels of referencing within assignments? Experienced teachers will be able to provide large quantities of anecdotal evidence, including aspects such as levels of engagement decreases and behaviour worsens, however, without performing an action research project, the question remains unanswered in any reliable form.

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Frequently asked questions

What is the main purpose of action research.

Frequently asked questions: Methodology

Attrition refers to participants leaving a study. It always happens to some extent—for example, in randomized controlled trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

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.”

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

Content validity shows you how accurately a test or other measurement method taps into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalizations —often the goal of quantitative research . As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research .

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones.

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is best used in the following cases:

If there is no sampling frame available (e.g., people with a rare disease)
If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
If the research focuses on a sensitive topic (e.g., extramarital affairs)

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Reproducibility and replicability are related terms.

Reproducing research entails reanalyzing the existing data in the same manner.
Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data .
A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
A successful replication shows that the reliability of the results is high.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Purposive and convenience sampling are both sampling methods that are typically used in qualitative data collection.

A convenience sample is drawn from a source that is conveniently accessible to the researcher. Convenience sampling does not distinguish characteristics among the participants. On the other hand, purposive sampling focuses on selecting participants possessing characteristics associated with the research study.

The findings of studies based on either convenience or purposive sampling can only be generalized to the (sub)population from which the sample is drawn, and not to the entire population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection, using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity , because it covers all of the other types. You need to have face validity , content validity , and criterion validity to achieve construct validity.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

Convergent validity : The extent to which your measure corresponds to measures of related constructs
Discriminant validity : The extent to which your measure is unrelated or negatively related to measures of distinct constructs

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as “people watching” with a purpose.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

Response variables (they respond to a change in another variable)
Outcome variables (they represent the outcome you want to measure)
Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

Explanatory variables (they explain an event or outcome)
Predictor variables (they can be used to predict the value of a dependent variable)
Right-hand-side variables (they appear on the right-hand side of a regression equation).

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

Open-ended and flexible
Impossible to answer with “yes” or “no” (questions that start with “why” or “how” are often best)
Unambiguous, getting straight to the point while still stimulating discussion
Unbiased and neutral

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when:

You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
You are constrained in terms of time or resources and need to analyze your data quickly and efficiently.
Your research question depends on strong parity between participants, with environmental conditions held constant.

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions.
Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses.
Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts.

The four most common types of interviews are:

Structured interviews : The questions are predetermined in both topic and order.
Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
Unstructured interviews : None of the questions are predetermined.
Focus group interviews : The questions are presented to a group instead of one individual.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

Inductive generalization : You use observations about a sample to come to a conclusion about the population it came from.
Statistical generalization: You use specific numbers about samples to make statements about populations.
Causal reasoning: You make cause-and-effect links between different things.
Sign reasoning: You make a conclusion about a correlational relationship between different things.
Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Triangulation can help:

Reduce research bias that comes from using a single method, theory, or investigator
Enhance validity by approaching the same topic with different tools
Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

It’s time-consuming and labor-intensive, often involving an interdisciplinary team.
Your results may be inconsistent or even contradictory.

There are four main types of triangulation :

Data triangulation : Using data from different times, spaces, and people
Investigator triangulation : Involving multiple researchers in collecting or analyzing data
Theory triangulation : Using varying theoretical perspectives in your research
Methodological triangulation : Using different methodologies to approach the same topic

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps:

First, the author submits the manuscript to the editor.
Reject the manuscript and send it back to author, or
Send it onward to the selected peer reviewer(s)
Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardization and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Every dataset requires different techniques to clean dirty data , but you need to address these issues in a systematic way. You focus on finding and resolving data points that don’t agree or fit with the rest of your dataset.

These data might be missing values, outliers, duplicate values, incorrectly formatted, or irrelevant. You’ll start with screening and diagnosing your data. Then, you’ll often standardize and accept or remove data to make your dataset consistent and valid.

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimize or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyze, detect, modify, or remove “dirty” data to make your dataset “clean.” Data cleaning is also called data cleansing or data scrubbing.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

In multistage sampling , you can use probability or non-probability sampling methods .

For a probability sample, you have to conduct probability sampling at every stage.

You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

These are four of the most common mixed methods designs :

Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions.
Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

No, the steepness or slope of the line isn’t related to the correlation coefficient value. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes.

To find the slope of the line, you’ll need to perform a regression analysis .

Correlation coefficients always range between -1 and 1.

The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.

The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation.

These are the assumptions your data must meet if you want to use Pearson’s r :

Both variables are on an interval or ratio level of measurement
Data from both variables follow normal distributions
Your data have no outliers
Your data is from a random or representative sample
You expect a linear relationship between the two variables

Quantitative research designs can be divided into two main categories:

Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

The priorities of a research design can vary depending on the field, but you usually have to specify:

Your research questions and/or hypotheses
Your overall approach (e.g., qualitative or quantitative )
The type of design you’re using (e.g., a survey , experiment , or case study )
Your sampling methods or criteria for selecting subjects
Your data collection methods (e.g., questionnaires , observations)
Your data collection procedures (e.g., operationalization , timing and data management)
Your data analysis methods (e.g., statistical tests or thematic analysis )

A research design is a strategy for answering your research question . It defines your overall approach and determines how you will collect and analyze data.

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Correlation describes an association between variables : when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.

Causation means that changes in one variable brings about changes in the other (i.e., there is a cause-and-effect relationship between variables). The two variables are correlated with each other, and there’s also a causal link between them.

While causation and correlation can exist simultaneously, correlation does not imply causation. In other words, correlation is simply a relationship where A relates to B—but A doesn’t necessarily cause B to happen (or vice versa). Mistaking correlation for causation is a common error and can lead to false cause fallacy .

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

A positive correlation means that both variables change in the same direction.
A negative correlation means that the variables change in opposite directions.
A zero correlation means there’s no relationship between the variables.

Random error is almost always present in scientific studies, even in highly controlled settings. While you can’t eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables .

You can avoid systematic error through careful design of your sampling , data collection , and analysis procedures. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment ; and apply masking (blinding) where possible.

Systematic error is generally a bigger problem in research.

With random error, multiple measurements will tend to cluster around the true value. When you’re collecting data from a large sample , the errors in different directions will cancel each other out.

Systematic errors are much more problematic because they can skew your data away from the true value. This can lead you to false conclusions ( Type I and II errors ) about the relationship between the variables you’re studying.

Random and systematic error are two types of measurement error.

Random error is a chance difference between the observed and true values of something (e.g., a researcher misreading a weighing scale records an incorrect measurement).

Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are).

On graphs, the explanatory variable is conventionally placed on the x-axis, while the response variable is placed on the y-axis.

If you have quantitative variables , use a scatterplot or a line graph.
If your response variable is categorical, use a scatterplot or a line graph.
If your explanatory variable is categorical, use a bar graph.

The term “ explanatory variable ” is sometimes preferred over “ independent variable ” because, in real world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so “explanatory variables” is a more appropriate term.

The difference between explanatory and response variables is simple:

An explanatory variable is the expected cause, and it explains the results.
A response variable is the expected effect, and it responds to other variables.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

A control group that receives a standard treatment, a fake treatment, or no treatment.
Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

There are 4 main types of extraneous variables :

Demand characteristics : environmental cues that encourage participants to conform to researchers’ expectations.
Experimenter effects : unintentional actions by researchers that influence study outcomes.
Situational variables : environmental variables that alter participants’ behaviors.
Participant variables : any characteristic or aspect of a participant’s background that could affect study results.

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

Only requires small samples
Statistically powerful
Removes the effects of individual differences on the outcomes

Disadvantages:

Internal validity threats reduce the likelihood of establishing a direct relationship between variables
Time-related effects, such as growth, can influence the outcomes
Carryover effects mean that the specific order of different treatments affect the outcomes

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

Prevents carryover effects of learning and fatigue.
Shorter study duration.
Needs larger samples for high power.
Uses more resources to recruit participants, administer sessions, cover costs, etc.
Individual differences may be an alternative explanation for results.

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a dice to randomly assign participants to groups.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomization. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

It’s caused by the independent variable .
It influences the dependent variable
When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered.

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

There are three key steps in systematic sampling :

Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups.

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

In single-stage sampling , you collect data from every unit within the selected clusters.
In double-stage sampling , you select a random sample of units from within the clusters.
In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

The American Community Survey is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity as they can use real-world interventions instead of artificial laboratory settings.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference with a true experiment is that the groups are not randomly assigned.

Blinding is important to reduce research bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

In a single-blind study , only the participants are blinded.
In a double-blind study , both participants and experimenters are blinded.
In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalization .

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organization to understand its culture.
Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Phenomenological research involves investigating phenomena through people’s lived experiences.
Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

When conducting research, collecting original data has significant advantages:

You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

The type of soda – diet or regular – is the independent variable .
The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

Using careful research design and sampling procedures can help you avoid sampling bias . Oversampling can be used to correct undercoverage bias .

Some common types of sampling bias include self-selection bias , nonresponse bias , undercoverage bias , survivorship bias , pre-screening or advertising bias, and healthy user bias.

Sampling bias is a threat to external validity – it limits the generalizability of your findings to a broader group of people.

A sampling error is the difference between a population parameter and a sample statistic .

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment and situation effect.

The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).

The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

Longitudinal study	Cross-sectional study
observations	Observations at a in time
Observes the multiple times	Observes (a “cross-section”) in the population
Follows in participants over time	Provides of society at a given point

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Discrete and continuous variables are two types of quantitative variables :

Discrete variables represent counts (e.g. the number of objects in a collection).
Continuous variables represent measurable amounts (e.g. water volume or weight).

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

The independent variable is the amount of nutrients added to the crop field.
The dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

A testable hypothesis
At least one independent variable that can be precisely manipulated
At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

How you will manipulate the variable(s)
How you will control for any potential confounding variables
How many subjects or samples will be included in the study
How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables .

External validity is the extent to which your results can be generalized to other contexts.

The validity of your experiment depends on your experimental design .

Reliability and validity are both about how well a method measures something:

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Campaign to Ban Landmines Nepal

By Helen M.

Program Support Officer, Mines Action Canada

Brown suitcase with multiple country flags drawn on it. Also a brown globe in front of the suitcase

Helen Martin, International Development and Globalization Internship Country: Nepal Canadian NGO: Mines Action Canada (MAC) Local NGO: Ban Landmines Campaign Nepal

The experience and lessons I have learned while in another country, I would argue, cannot be taught inside a classroom. The chance to make mistakes and learn not just the material but the environment within which one must navigate to achieve one's goal is invaluable. The opportunity to travel, learn, and work in an engaging and fulfilling setting is only possible due to the enormous amounts of support from the university, and every respective organization and the confidence that can be found in oneself to challenge and explore the multitude of faucets that encompass the global world we live in today.

In Nepal, the Campaign to Ban Landmines is an excellent experience to see solutions, obstacles, collaborations, and legal and cultural frameworks of an ever-changing society. The opportunity to see the tenacity of people strive and thrive to create something new as a community is amazing, especially after years of conflict and uncertainty due to natural disasters, the long-lasting implications and obstacles that they face, yet with tenacity and sheer will, people come together to create something, not brand new, but certainly unique is its composition. The opportunity to not only observe but to some degree participate, has been indescribable. The ability to learn purpose beyond the act of creating reports, and reading hundreds of documents because of a due date, these acts now have significance which provides a learning experience I highly recommend.

Many thanks to all involved for facilitating and ensuring the safety and accessibility of this opportunity that we have the privilege of attempting.

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COMMENTS

What Is Action Research?
Action research is a research method that aims to simultaneously investigate and solve an issue. In other words, as its name suggests, action research conducts research and takes action at the same time. It was first coined as a term in 1944 by MIT professor Kurt Lewin.A highly interactive method, action research is often used in the social ...
1 What is Action Research for Classroom Teachers?
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 and Systematic, Intentional Change in Teaching Practice
By tracing action research literature across four subject areas—English language arts (ELA), mathematics, science, and the social studies—it reflects contemporary emphasis on these subjects in the public school "core" curriculum and professional development literature (Brady, 2010) and provides a basis for comparative analysis.The results contribute to the scholarship of teaching ...
PDF What is Action Research?
Action research - which is also known as Participatory Action Research (PAR), community-based study, co-operative enquiry, action science and action learning - is an approach commonly used for improving conditions and practices in a range healthcare environments (Lingard et al., 2008; Whitehead et al., 2003).
Action research
v. t. e. Action research is a philosophy and methodology of research generally applied in the social sciences. It seeks transformative change through the simultaneous process of taking action and doing research, which are linked together by critical reflection. Kurt Lewin, then a professor at MIT, first coined the term "action research" in 1944.
What is action research and how do we do it?
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. ... London: Falmer. 192 + ix pages. Examines three action research studies undertaken by a teacher and how they related ...
Action Research
Abstract. Action research is an approach to research which aims at both taking action and creating knowledge or theory about that action as the action unfolds. It starts with everyday experience and is concerned with the development of living knowledge. Its characteristics are that it generates practical knowledge in the pursuit of worthwhile ...
Action Research
Summary. Action research has become a common practice among educational administrators. The term "action research" was first coined by Kurt Lewin in the 1930s, although teachers and school administrators have long engaged in the process described by and formally named by Lewin. Alternatively known as practitioner research, self-study ...
Action Research
Comprehensive overview of the theoretical, conceptual, and applied/practical presentations of action research as it is found and conducted solely in educational settings The Wiley Handbook of Action Research in Education is the first book to offer theoretical, conceptual, and applied/practical presentations of action research as it is found and conducted solely in educational settings.
Action Research Resource
Action research is a qualitative method that focuses on solving problems in social systems, such as schools and other organizations. The emphasis is on solving the presenting problem by generating knowledge and taking action within the social system in which the problem is located. The goal is to generate shared knowledge of how to address the ...
Action Research: What it is, Stages & Examples
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.
Action Research as a Process for Professional Learning and Leadership
Sagor (2010) defines collaborative action research as "the team inquiry process, when a group of individuals who are a part of a specific PLC, grade-level, or teacher learning team engage in inquiry and research.". These teams can become a means for collaboratively engaging in action research and developing data that is relative to the school.
Getting Started
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.
PDF What Is Action Research?
This chapter is organized into four sections that deal with these issues. 1 What action research is and is not. 2 Different approaches to action research. 3 Purposes of action research. 4 When and when not to use action research. 1 What action research is and is not. Action research is a form of enquiry that enables practitioners in every job ...
What Is Action Research?
Action research is a research method that aims to simultaneously investigate and solve an issue. In other words, as its name suggests, action research conducts research and takes action at the same time. It was first coined as a term in 1944 by MIT professor Kurt Lewin. A highly interactive method, action research is often used in the social ...
Learn the Importance of Action Research in Education at SIUE
The primary purpose of action research in education is to identify specific challenges within the classroom and develop practical solutions based on evidence-based practices. By incorporating action research, educators can continuously improve their teaching methodology. It helps in enhancing student engagement, retention and overall achievement.
Action Research
the purpose of the research and whether 'action research' is the appropriate method; ... However, like case studies, action research is usually concerned with single situations, for example, a single group or company. Therefore, although the approach can generate theoretical propositions that go beyond single situations, action research is ...
The Meaning and Role of Action Research in Education
Purpose: This study generally aimed to (1) identify the most difficult part of the action research process as evaluated by the teachers; (2) find out implications of conducting action research in ...
The purpose of action research
The purpose of action research. The purpose of action research is to gather information in an attempt to solve a problem or make an improvement, which may have been highlighted as a result of self-evaluation or student feedback. While this is the core purpose, the motivations may be different, the motivation may be sincere and the goal to be ...
Action Research in Education
The purpose of action research is to provide teacher-researchers with a method for solving problems in schools so that they may improve both student learning and teacher effectiveness. Action ...
(PDF) Action research
Abstract and Figures. Action research (AR) is a research approach that is grounded in practical action (the action component) while at the same time focused on generating, informing and building ...
(PDF) Action Research: A Guide to Process and Procedure
In this paper, the authors discuss some of the concerns and challenges underlying the conduct of action. research studies, and consider reasons for these concerns. They identify three elements ...
What is the main purpose of action research?
Attrition refers to participants leaving a study. It always happens to some extent—for example, in randomized controlled trials for medical research. Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group.As a result, the characteristics of the participants who drop out differ from the characteristics of those who ...
Campaign to Ban Landmines Nepal
Helen Martin, International Development and GlobalizationInternship Country: NepalCanadian NGO: Mines Action Canada (MAC)Local NGO: Ban Landmines Campaign NepalThe experience and lessons I have learned while in another country, I would argue, cannot be taught inside a classroom. The chance to make mistakes and learn not just the material but the environment within which one must navigate to ...

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Research Methods and Design

Action research

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What is Action Research?

Origins of Action Research

Sample Action Research Topics

Considerations for Determining Whether to Use Action Research in an Applied Dissertation

Considerations for Action Research

Considerations for Sampling and Data Collection

Sampling and Sample Size

Critical Concepts in Data Collection

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Action Research: What it is, Stages & Examples

What is action research?

Stage 1: Plan

Stage 2: Act

Stage 3: Observe

Stage 4: Reflect

Identify the action research question or problem

Review existing knowledge

Plan the research

Collect data

Analyze the data

Reflect on the findings

Develop an action plan

Implement the action plan

Evaluate and monitor progress

Reflect and iterate

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