citations
Overview of the action research approaches referred to in the included articles, indicating those papers that are mentioned as “the origin” of action research. Studies that either name an approach as being the origin of action research, or are being named as such, are highlighted in blue for better readability.
Overview of action research approaches referred to in the included articles. Arrows indicate citations between the action research approach papers. The number of times that the articles included in this review cited each approach is indicated in the box. We have used different arrow thicknesses for better readability. Blue boxes indicate those papers that were available and checked for citations.
As previously described, an activity was identified as a “best practice” if researchers already planned their project with this in mind (eg, mentioning it in the description of methods). Lessons learned were those points that researchers came to know during their project. These were mostly reported in the discussion section. In total, 85 best practices and 66 lessons learned were identified, which were clustered into 22 categories of best practices and 16 categories of lessons learned. Among the 44 papers, 3 papers did not indicate any best practices that they followed, whereas 12 papers did not include any identifiable lessons learned. There were 8 overlapping categories, identified as best practices in some articles and as lessons learned in others. These will be discussed in more detail below.
The identified best practices in the 44 studies were most often related to the use of a specific method (n=9), namely personas (n=2), world café, journey mapping, role play, scenarios, case studies, design cards, and mixing different types of data collection methods (all n=1). Other best practices were a continuous evaluation of the project and a reflection on the process by the research team (n=8). The importance of establishing active contact between researchers and stakeholders and raising the confidence and skills of stakeholders was emphasized by 7 studies. The improvement of stakeholder skills mainly referred to research and analytical skills, allowing stakeholders to set up their own studies or continue the work after the project was finished. There were several specific suggestions to improve the regular project team meetings, for example, to always use the same agenda or to share a common area (office space) to make contact easier. Some other best practices concern the reporting and presentation of outcomes (n=6). The complete list of best practice categories can be found in Table 3 .
Overview of all best practice categories and number of mentions per category (N=44).
Best practices category | Number of mentions, n | |||
| | |||
| | Personas | 2 | |
| World Café | 1 | ||
| | Journey mapping | 1 | |
| Role play | 1 | ||
| | Scenarios | 1 | |
| | Case study | 1 | |
| | Design cards | 1 | |
| | Abstract vs personal methods of data collection | 1 | |
| Continuous evaluation and reflection | 8 | ||
| ||||
| | Share resources and findings (on the internet) allowing others to benefit from it | 4 | |
| | Present findings to the community or target group in a suitable manner | 2 | |
| Start with close examination of context (observation and literature) | 5 | ||
| Agile development and Scrum | 3 | ||
| 2 | |||
| | Combining these 2 approaches | 1 | |
| | Keeping the line between stakeholders and researchers blurred and not performing RCTs | 1 | |
| Gradual scaling up | 2 | ||
| Immediately resolve problems and apply lessons learned | 2 | ||
| Frequent or regular (face-to-face) meetings, active contact (eg, shared space), and same transparent agenda | 7 | ||
| Raising stakeholder confidence and skills (eg, analytical skills so that they can set up their own studies) | 7 | ||
| Clearly defining the role of each partner (equal involvement is not always good) | 5 | ||
| Finding committed stakeholders with intrinsic motivation (to carry on with the project after the researchers have left) | 5 | ||
| Reference group (with technical, juridical, and clinical expertise) | 4 | ||
| Stepping into each other's shoes (experiencing the other’s tasks and familiarizing oneself with what the other does) | 3 | ||
| Investing in relationship between partners (also nonwork activities) | 3 | ||
| Adapting methods or schedules to the needs of stakeholders | 3 | ||
| Neutral position of the researcher (no steering or predetermined outcomes, serving as a communication link instead) | 3 | ||
| Patient- and stakeholder-generated content (eg, personas) | 2 | ||
| Different disciplines | 2 | ||
| Living labs as context for action research | 2 | ||
| Actively encouraging pilot participation | 2 | ||
| Paying attention to economic or business values | 3 |
Apart from the best practices, the lessons learned from each study were identified. The most common lessons learned were increasing stakeholder knowledge and skills (n=8) and continuous evaluation of the project and reflection on the process (n=6). Both of these had been identified as best practices in other articles (more on this overlap below). Recommendations for the use of specific methods were also common (n=5). Lessons learned regarding reporting, adapting the project to fit the needs of stakeholders, fostering a welcoming environment, and the questionable replicability of the research were each mentioned 4 times. All lessons learned are shown in Table 4 .
Overview of all lessons learned categories and number of mentions per category (N=44).
Lesson learned category | Number of mentions, n | |||
| Continuous reframing or renegotiation (flexibility), baby steps | 6 | ||
| ||||
| | Field work | 1 | |
| | Randomized controlled trial | 1 | |
| | Case study | 1 | |
| | Action circles | 1 | |
| | Fun methods (quiz, game, puzzle) as learning opportunities | 1 | |
| ||||
| | Open source | 2 | |
| Higher level of sophistication necessary | 1 | ||
| Also include nonproject target group | 1 | ||
| | Integration of literature | 3 | |
| | Regular meetings to check on progress and motivate the stakeholders (reality check) | 2 | |
| | Triangulation of data to decrease biases | 2 | |
| ||||
| | Accompanying stakeholders until they find that the process is done | 1 | |
| | Action research leading to other collaborative activities | 1 | |
| Commitment to action research necessary (eg, through specific funding) | 1 | ||
| Ethical restrictions | 1 | ||
| Immediate reflection impossible | 1 | ||
| Raising stakeholder confidence and skills, knowledge sharing | 8 | ||
| ||||
| | Including action research in work schedule | 1 | |
| | Researchers taking over some of the stakeholders’ usual tasks to make schedule less busy | 1 | |
| | Adequate feedback methods | 1 | |
| | Identifying unique strengths | 1 | |
| Investing in relationship between partners | 3 | ||
| Accepting that participation is different for everyone and can change over time | 3 | ||
| ||||
| | Language barrier | 1 | |
| | Finding a common language | 1 | |
| Enthusiastic local ”champion” to start the project and help keep people motivated | 2 | ||
| Involving authorities or local government (address issues at multiple levels) | 2 | ||
| Actively breaking down power structure | 1 | ||
| Fostering a positive, welcoming environment for change | 4 | ||
| Questionable replicability | 4 | ||
| Active researcher involvement and presence in environment | 2 | ||
| Drawing attention to external influences | 1 | ||
| Ethical issues | 1 | ||
| Diffusion of innovation | 1 | ||
| Organizational expectations | 1 |
As stated earlier, some aspects were identified as best practices in some articles and as lessons learned in others. In total, we identified 7 such overlapping aspects. Overall, the most mentioned aspect was the importance of raising stakeholder skills and confidence (n=15, where best practices= 7 and lessons learned=8). Many articles reported the need for stakeholders to learn new skills, for example related to academic research, or the need to be convinced about their ability to perform these tasks. Almost all the studies that reported this as a best practice or lesson learned involved health care professionals as stakeholders. Other commonly mentioned points were recommendations for specific methods, even though the suggested methods differed (n=14, where best practices=9 and lessons learned=5) and there was continuous reframing and evaluation of the project (n=14, where best practices=8 and lessons learned=6). Continuous reframing often referred to the iterations of planning, action, and evaluation in AR projects. Studies that described this mostly did not include this cyclical nature of AR in their definition of it. In total, there were 10 recommendations regarding the reporting and presentation of results (best practices=6 and lessons learned=4), for example calling for open and accessible publishing of outcomes. The best practices and lessons learned included recommendations about meeting regularly (n=9, where best practices=7 and lessons learned=2), adapting to the needs of stakeholders (n=8, where best practices=3 and lessons learned=5), and investing in the relationship between partners (n=6, where best practices=3 and lessons learned=3).
When observing the publication timeline, most of the overlapping aspects appeared as a lesson learned in earlier publications, and then as a best practice in papers published at a later point in time. This was the case regarding stakeholder skills, appearing as a lesson learned in 1999 [ 33 ] and as a best practice in 2016 [ 25 ]; continuous reframing of the project was a lesson learned in 2003 [ 19 ] and best practice in 2009 [ 42 ]; further, having regular meetings was a lesson learned in 2006 [ 72 ] and a best practice in 2018 [ 27 ], and adapting the research to stakeholder needs was a lesson learned in 2007 [ 32 ] and a best practice in 2016 [ 77 ]. Such a clear timeline could not be seen for accessible reporting, appearing as a lesson learned in 2017 [ 78 ] and a best practice in 2007 [ 45 ], and the relationship between partners appearing as a lesson learned in 2017 [ 36 ] and as a best practice in 2008 [ 38 ].
To identify recommendations on how to conduct AR in eHealth studies, this literature review analyzed the setting, AR description, and best practices and lessons learned in 44 studies. The most important recommendations from this review, which will be discussed in more detail below, are as follows: actively raising stakeholder skills and confidence; fulfilling multiple roles and tasks as a researcher; fostering constant reflection and evaluation; ensuring open and accessible dissemination; reporting in a more structured and comprehensive way.
These recommendations are not exclusively related to eHealth, despite them being derived from a review of eHealth AR studies. Hence, it is possible that the recommendations are also relevant for AR in various other fields. Therefore, where possible, examples from different disciplines are discussed below to explain or supplement a recommendation.
Being involved in a project as coresearcher can potentially increase stakeholders’ confidence, besides teaching them new skills [ 79 ]. However, this does not happen automatically. Similar to our findings, the narrative review conducted by Harrison and colleagues [ 80 ] also identified educating the research team as the most important task when stakeholders are involved in health care research. Nevertheless, there is limited research on how skill training for stakeholders could look like, and this can vary greatly between studies. Stakeholders in some eHealth studies might need to learn content-related information [ 81 ], whereas other studies require methodological or statistical skills [ 54 ]. Researchers should provide adequate training and material for their project and encourage stakeholders to make use of it. The studies included in this review that recommended stakeholder skill training almost exclusively worked with health care professionals. The relationship between recommending skill training and working mainly with health care professionals remains unclear. A possible explanation could be that other stakeholder groups in other studies already had the necessary skills and thus did not require any additional training. Another possibility is that other stakeholders were not given the same roles that health care professionals held, and therefore, they did not need skill training. Finally, as we will discuss later, reporting of AR activities was not always very extensive. Thus, stakeholders outside the health care sector were possibly trained, and these studies did not report on this aspect. Generally, not all participants prefer the same level of engagement in a project, and researchers should respect these preferences [ 82 ].
Different aspects of the role and tasks of the researcher in an AR project are discussed. Brydon-Miller and Aragón describe the many different tasks that action researchers need to fulfil as their “500 hats” [ 83 ]. These are not specific to eHealth studies, but they can occur in any AR study. As researchers and stakeholders have many varied duties, their roles are not fixed and might change over the course of the project [ 19 ]. One main task of the researchers that continues throughout the project is the need to foster a welcoming environment for all stakeholders [ 42 ]. Researchers should also be present and actively involve themselves at a higher level than that needed in non-AR projects [ 38 ]. Additional AR-specific tasks for the researchers include investing in partner relationships [ 35 ] or breaking down power structures [ 28 ]. Generally, AR studies demand more self-reflection and awareness from the researchers than other projects and researchers should keep this in mind when entering an AR project.
The importance of continuous reframing and evaluation of the project was emphasized in several studies. Although evaluation is 1 of the AR cycles, studies providing recommendations on this topic rarely included this in their definition of AR. Owing to the lack of reports on AR cycles, which will be discussed below, it is unclear if these studies still followed the AR cycles without reporting on them. However, sometimes, it seems that periodic planned evaluation is not enough. Instead, the participants need to regularly reflect on the current status of the project and their role in it. Therefore, new AR projects should create suitable spaces for evaluation and reflection in ways that fit the projects and stakeholders. This is especially important because reflection can become difficult once a person is in the middle of the project [ 49 ]. Holeman and Kane [ 53 ] emphasize that reflection should not only take place within the project, but it should also be explicitly reported to help other researchers. If action researchers take reflection seriously and include honest evaluations in their publishing, the AR community members can learn from each other. Additionally, researchers and other stakeholders within the project learn and benefit from constant reflection [ 9 ].
Another important aspect concerns paying attention to open and understandable dissemination of results within the community and among researchers. Action researchers need to communicate findings to the academic world while also finding ways to inform the target group about the project in ways that suit the target users’ needs. An example of open and accessible dissemination can be found in Canto-Farachala and Larrea [ 83 ]. They present the results of their AR project regarding territorial development on an interactive website, allowing others to learn from their work. However, it seems that accessible reporting is still not the norm in AR, as Avison and colleagues [ 62 ] describe that many AR studies are generally “published in books rather than as articles. Action researchers have large and complicated stories to tell.” Future AR projects should attempt to narrate their stories in such a way that others can learn from them.
The different way of describing AR studies also leads to another issue, incomplete and elusive reporting. Although most studies did provide at least a short description of what they saw as AR, 7 studies provided no definition at all. Additionally, there were only 4 studies that included 3 or all of the 4 aspects of the AR definition in their description. Even the most mentioned aspects appeared in less than half of the included papers. Even though most papers did cite an AR approach of definition, some did not. In combination with the often-limited descriptions of AR, this makes it difficult to obtain a clear picture of how AR is perceived and performed in a particular study. This resonates with what Bradbury and colleagues [ 9 ] describe as 1 of the quality points of AR, namely “action research process and related methods (should be) clearly articulated and illustrated.” The best practices and lessons learned that were extracted from the included studies were seldom mentioned explicitly. Best practices were often hidden in the description of the project, without much reasoning. Similarly, lessons learned were often described as adaptations made during the project or as plans for the future. Although we observed that some lessons learned turned into best practices over time, we think that researchers could benefit more from each other’s work by providing concrete recommendations. This review is a step in that direction. Both aspects show that the reporting of AR studies in eHealth can be improved to show more clearly what eHealth AR projects can look like and help others in setting up such projects with specific recommendations.
Approximately a third of the included papers (14 out of 44) were published more than 10 years ago. This also means that some of the technologies that are described in the older papers are now relatively old. However, this literature review focuses mainly on the AR methodology and lessons learned about doing action research. Therefore, there was no exclusion criterium regarding the publication date of the papers.
The search yielded several PD-related papers. These papers could have been included, given that some definitions of PD are very similar to AR. However, as our aim was to provide an overview of how AR is done, these were excluded as the researchers of these studies themselves did not identify their studies as being related to AR (ie, not referring to, mentioning, or describing AR). Although this offers a clearer picture of how researchers conduct AR, it also creates a potential limitation in that best practices and lessons learned could be enriched from PD literature.
This overview of AR approaches focuses mostly on the interconnectedness among the approaches, without a comprehensive comparison of the content. Comparing the approaches with regard to the specific aspects of AR that they describe would be a review in and of itself, going beyond the scope of this current review. Therefore, we decided to focus on the definitions that the authors themselves provided even when they also cited AR approaches, as these are most likely to reflect their own vision of AR.
This review illustrates how AR is conducted in eHealth studies. Studies that fulfilled the inclusion criteria mainly took place in western countries and lasted for 2 to 3 years. Different stakeholders were involved, but the most commonly involved groups were health care professionals and patients. As for the methods used, most studies opted for focus groups and interviews. Even though many studies cited the AR approach proposed by Reason and Bradbury [ 8 ], their own definitions of AR were often not explicit in terms of how they implemented AR. Future projects should report their AR definition as well as the best practices and lessons learned more clearly. Other recommendations include paying attention toward developing the skill and confidence of the stakeholders, being aware of the changing role of the researcher, frequently evaluating the project, and disseminating results in an understandable manner.
ADR | action design research |
AR | action research |
HCI | human computer interaction |
PAR | participatory action research |
PD | participatory design |
Multimedia appendix 2.
Authors' Contributions: KO performed the literature search and analysis and was a major contributor in designing the study and writing the manuscript. CG contributed to the design of the study, assisted with the search and analysis, and made major contributions to the manuscript. FN and LvV contributed to the design of the study and substantially revised the manuscript. All authors read and approved the final manuscript. This project has received funding from the European Union’s Horizon 2020 research and innovation program (grant 857188).
Conflicts of Interest: None declared.
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Published on October 26, 2022 by Shona McCombes . Revised on November 21, 2023.
A research question pinpoints exactly what you want to find out in your work. A good research question is essential to guide your research paper , dissertation , or thesis .
All research questions should be:
How to write a research question, what makes a strong research question, using sub-questions to strengthen your main research question, research questions quiz, other interesting articles, frequently asked questions about research questions.
You can follow these steps to develop a strong research question:
The way you frame your question depends on what your research aims to achieve. The table below shows some examples of how you might formulate questions for different purposes.
Research question formulations | |
---|---|
Describing and exploring | |
Explaining and testing | |
Evaluating and acting | is X |
Example research problem | Example research question(s) |
---|---|
Teachers at the school do not have the skills to recognize or properly guide gifted children in the classroom. | What practical techniques can teachers use to better identify and guide gifted children? |
Young people increasingly engage in the “gig economy,” rather than traditional full-time employment. However, it is unclear why they choose to do so. | What are the main factors influencing young people’s decisions to engage in the gig economy? |
Note that while most research questions can be answered with various types of research , the way you frame your question should help determine your choices.
Research questions anchor your whole project, so it’s important to spend some time refining them. The criteria below can help you evaluate the strength of your research question.
Criteria | Explanation |
---|---|
Focused on a single topic | Your central research question should work together with your research problem to keep your work focused. If you have multiple questions, they should all clearly tie back to your central aim. |
Answerable using | Your question must be answerable using and/or , or by reading scholarly sources on the to develop your argument. If such data is impossible to access, you likely need to rethink your question. |
Not based on value judgements | Avoid subjective words like , , and . These do not give clear criteria for answering the question. |
Criteria | Explanation |
---|---|
Answerable within practical constraints | Make sure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. |
Uses specific, well-defined concepts | All the terms you use in the research question should have clear meanings. Avoid vague language, jargon, and too-broad ideas. |
Does not demand a conclusive solution, policy, or course of action | Research is about informing, not instructing. Even if your project is focused on a practical problem, it should aim to improve understanding rather than demand a ready-made solution. If ready-made solutions are necessary, consider conducting instead. Action research is a research method that aims to simultaneously investigate an issue as it is solved. In other words, as its name suggests, action research conducts research and takes action at the same time. |
Criteria | Explanation |
---|---|
Cannot be answered with or | Closed-ended, / questions are too simple to work as good research questions—they don’t provide enough for robust investigation and discussion. |
Cannot be answered with easily-found facts | If you can answer the question through a single Google search, book, or article, it is probably not complex enough. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation prior to providing an answer. |
Criteria | Explanation |
---|---|
Addresses a relevant problem | Your research question should be developed based on initial reading around your . It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. |
Contributes to a timely social or academic debate | The question should aim to contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. |
Has not already been answered | You don’t have to ask something that nobody has ever thought of before, but your question should have some aspect of originality. For example, you can focus on a specific location, or explore a new angle. |
Chances are that your main research question likely can’t be answered all at once. That’s why sub-questions are important: they allow you to answer your main question in a step-by-step manner.
Good sub-questions should be:
Here are a few examples of descriptive and framing questions:
Keep in mind that sub-questions are by no means mandatory. They should only be asked if you need the findings to answer your main question. If your main question is simple enough to stand on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your subject, the more sub-questions you’ll need.
Try to limit yourself to 4 or 5 sub-questions, maximum. If you feel you need more than this, it may be indication that your main research question is not sufficiently specific. In this case, it’s is better to revisit your problem statement and try to tighten your main question up.
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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.
Methodology
Statistics
Research bias
The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .
A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.
As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.
This involves:
A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“ x affects y because …”).
A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses . In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.
Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .
However, it should also fulfill criteria in three main areas:
If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.
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Sharing my journey through landscapes of practice.
The minute I wrote that title, I realised that in a strict sense it is a little back to front. We all know that our choice of research methodology should follow the definition of our aims, objectives and research question – form should follow function! At least that is what the text books say.
But I’ll readily confess that I became a research student because I wanted the opportunity to learn more about and experience action research – others do that too for example some embark on a PhD because they want to home their quantitative data analysis skills. So the ‘search’ for a research question and defining aims and objectives is also informed by the sort of knowledge, skills and experience I want to develop through my PhD and ultimately the sort of researcher I want to be.
Although I produced a draft research proposal last July, I felt uncomfortable about the research question I’d included, it didn’t seem to home in on what was interesting to me. So I’ve been trying to focus on what an action research question looks like – unlike other forms of research there aren’t lots of published research proposals/protocols that you can easily locate so it is hard to get a feel for what you are trying to emulate. And, action research books just simply say ‘form your research question’ as if it isn’t a problematic thing to do.
The main problem comes with the ‘dual’ function of action research – it is simultaneously a process to generate knowledge AND a process to improve a situation. This distinction is described in different ways in the literature. I have two favourites…
In literature discussing doing action research for academic accreditation (e.g. Zuber-Skerritt and Perry (2002); Zuber-Skerritt and Fletcher (2007); Coghlan and Brannick (2014)), a distinction is made between the Thesis Action Research which is carried out independently by the research candidate and the Core Action Research which is carried out collaboratively. The ‘core action research’ is understood as being the fieldwork phase of the ‘thesis action research’. The Thesis action research kind of operates at a meta-level – i.e. research on the core action research. This means that the ‘thesis action research’ can have a different research question to the ‘core action research’.
The second way of making the distinction is even more powerful and quite exciting because it builds on the work of Checkland who developed soft systems methodology so it feels quite systemsy. It appears in information system research discussions of action research (e.g. McKay and Marshall 2001, 2007). The authors argue that action research has dual imperatives – what they refer to as a research imperative AND a problem solving imperative*. Drawing on the idea of action research as a cyclical process, they argue that the dual imperatives mean that two interlinked cycles are operating – a research cycle and a problem solving cycle each driven by their own interests, aims and objectives and therefore different understandings of progress and success. Importantly, they argue that it is important not to conflate the Methodology for the research (i.e. action research) with the Problem solving methodology (which could be any one of a range of organisational development or change management methodologies including systemsy ones like SSM or systemic inquiry). The balance of the two imperatives is really important – focus on the problem solving imperative, then it becomes more like consultancy than research with potential risks to the ‘rigour’ of your findings. Whereas focussing on the research imperative can lead to stakeholders in the research setting and participants feeling ‘done to’.
Taking the two distinctions together offers another helpful insight. In my case, the research imperative is fulfilled independently as the ‘thesis action research’ – I am its owner and its customer is the academic community. The ‘knowledge’ it generates is judged through the academic lens of validity, reliability and so on with all the caveats that those words have when drawing on qualitative data. The problem solving imperative is fulfilled by the participants together as a collaborative problem solving process. The participants are the co-owners and they and their stakeholders are the main customers. It can be referred to generally as the core action research – but in itself it needs to be understood through the lens of creating improvement/change with learning and knowing-in-action being more important than formal propositional knowledge. The change could be understood as ‘new’ learning generated through a process of social learning and/or it could be understood as new procedures, new practices, new ‘systems’ etc.
Back to the Checkland connection. According to Checkland, research consists of a framework of ideas (F), which are employed via a methodology (M) to investigate an area of interest (A). As a result of the research, learning will take place about F, and/or M and/or A. McKay and Marshall (2001, 2007) argue that the dual imperatives of action research result in an adaptation to this general model. The setting in which the research takes place has a ‘real world’ problem situation (P) which enables the researcher to find out about the area of interest (A). As already mention there are two methodologies in use – the research methodology (MR) and the problem solving methodology (MPS). This means the research can tell us about any combination of:
P – the real world problem situation A – the area of research interest F – the framework of ideas MR – i.e. action research (a methodological contribution) MPS – i.e. the chosen methodology to improve the situation
And so, opens up different options for framing your research aim(s) and question(s)…
It could focus on the area of research interest (A). The setting for the research is one example – a case study if you like – of the research phenomenon of interest. The research is about understanding and exploring this situation. You could do this by other research methods but the value of using action research is you take a dynamic perspective of the forces and factors that shape the phenonenon of interest and you go back to test your ideas as the research proceeds. As Lewin is cited as saying – you can’t understand a system unless you try to change it. In my case then a research question is something like “What shapes policy work practice and its development in English local government?”
It could focus on the real world problem situation (P). In my case the question would be something like “What is policy work practice like in local authority X?” In my view this could by a risky route to take – whilst providing a thick description of the real world problem situation could be valuable to help with the generalisable lessons, there is a risk that the findings in themselves aren’t useful to third parties i.e. those not directly involved. From the point of view of the research imperative, the Thesis has to make some attempt to go beyond the specific case and generalise. However, this question could well be a natural part of the process in the research setting whereby the participants inquire – it belongs to the problem solving imperative, not the research one.
It could focus on the research methodology (MR). This is more focused on making a methodological contribution and would be something like “What are the value and limitations of action research in understanding policy work practice and its development?”. Most research will include an element of this – potentially in an implicit way – as the strengths and limitations of the research are generally included as part of the Thesis or the research articles. The ‘answer’ comes as much from rigorous reflection on the experience of the process as it does from empirical data. This feels like a ‘sideline’ – something to be aware of but not the main purpose of the research.
It could focus on the ‘problem solving’ methodology (MPS). This is more like an evaluation – an assessment of whether the ‘problem solving’ methodology is useful and creates a ‘better’ situation. It has parallels with an experiment – you hypothesise that using problem solving methodology X will create an improvement in the situation – and your research therefore focusses on evaluating what changes if any arise and if so why. From the reading I have done so far I think this is a key way that action research is framed – “a what happens if I” orientation. In my case then a research question would be something like “Is [methodology] an effective way of making improvements to policy work practice in English local government?” This of course throws up other issues in terms of what constitutes an improvement, what constitutes effective and who gets to define that.
It could be on the framework of ideas (F). I’m struggling to articulate this a little more and maybe that is because I have yet to really identify, home in on, and justify my framework of ideas. In general I know that they all seem to fall into the area of things that feel systemsy – particularly the soft and critical traditions and social learning. McKay and Marshall (2001, 2007) don’t seem to suggest that there are different Fs for the research imperative and the problem solving imperative, but in theory they may not be congruent (probably leading to some cognitive discomfort!). So I know I have some work to do here articulating my F for myself and others. But a tentative research question about my tentative F would be something like “To what extent and in what ways are systems thinking and social learning helpful ideas in researching and developing policy work practice?”
Of course, there is no reason why these questions can’t be combined in a research project – making knowledge contributions and methodological ones. But you’d need to design your data generation and analysis differently to answer each question so in my view I need to major on one – make it my primary question – and then treat anything else as a useful ‘by product’ of the process.
The distinction of research imperative and problem solving imperative has also helped me develop clarity on how to write my research proposal. Again books can be a little light on action research proposals and what may be different in them from research proposals from other disciplines. But a general observation I have made is that some seem to imply there is no real difference whereas others imply a great deal of difference…but what I have realised is that this is all about whether you frame your proposal through the lens of the research imperative or the problem solving imperative.
Framing a proposal through the lens of the research imperative is more consistent with ‘traditional’ research proposals. You set the scene by talking about what is already known about your phenomenon of interest, what the debates are and where the gaps are. You then talk about what your research aims to do, what its question is. The problem solving imperative surfaces more when you talk about the setting in which the research will take place – what is the problematic situation that participants will be addressing there and how that offers an opportunity to generate data that will help you with your research aim and question.
Framing a proposal through the lens of the problem solving imperative is more like a business case for change. You start by describing the real world instance of the situation perceived as problematic in its wider context – why it needs to be improved and how you are going to set about doing that and later explain how the activities of research will complement and enhance that improvement/change journey. The more I think about this the more I realise it isn’t a RESEARCH proposal at all – it is a change or improvement proposal. In my case, this isn’t what my university wants but it could be what the stakeholders in the setting where I am going to do the research want. I think it gets confused a little in books because in some cases universities are asking for this type of proposal. One of the issues I have worried about with my research proposal is that I define too much up front, by myself, rather than involve the participants themselves in the ‘proposal’ – what I may find as I embark on the core action research is that this type of proposal is generated as part of the ‘action’ that the participants choose to take together. As I said above this is their process, they are the owners not me – I am their facilitator or helper.
*I’m a little uncomfortable with the framing of ‘problem solving’ here – I’d prefer to say something like ‘improving a situation perceived as problematic’ – but that is quite clumsy and wordy. So I am using ‘problem solving’ as the authors do but with some caveats about taking the words too literally.
Coghlan, D. and Brannick, T. (2014), Doing action research in your own organisation Fourth Edition., London: Sage Publications.
McKay, J. and Marshall, P. (2001), The dual imperatives of action research. Information Technology & People , 14(1), pp.46–59.
McKay, J. and Marshall, P. (2007), Driven by two masters, serving both: the interplay of problem solving and research in information systems action research projects. In Kock, N. (Editor), Information Systems Action Research: An applied view of emerging concepts and methods. New York: Springer US, pp. 131–158.
Zuber‐Skerritt, O. and Fletcher, M. (2007), The quality of an action research thesis in the social sciences. Quality Assurance in Education , 15(4), pp.413–436.
Zuber-Skerritt, O. and Perry, C. (2002), Action research within organisations and university thesis writing. The Learning Organization , 9(3/4), p.171.
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If you want to become a better writer, ignore the lore and follow the science..
Posted June 24, 2024 | Reviewed by Devon Frye
Most writers assume they write well. Yet most writers grapple with the reality of writing as a black box.
That is, we know that writing works, but we’re a bit fuzzy on what makes readers grasp the meaning of some sentences instantly and without noticeable effort, while we find others difficult to understand after repeat re-readings. And contrary to popular belief, clear writing has virtually nothing to do with content, sentence length, or writing style.
Instead, we perceive sentences as clear when they map onto the methods our reading brains use to make sense of writing. Knowing the most important ones, including the below, could help make you a better writer.
1. Active voice makes sentences easier to read.
In dozens of studies, researchers have found that readers comprehend sentences more rapidly when sentences reflect the causal order of events. Two factors determine these outcomes.
First, human brains naturally perceive cause and effect, a likely survival mechanism. In fact, infants as young as six months can identify cause and effect, registered as spikes in heart rate and blood pressure.
Second, English sentence structure reflects causes and effects in its ordering of words: subject-verb-object order. In key studies, participants read sentences with active voice at speeds one-third faster than they read sentences in passive voice. More significantly, these same participants misunderstood even simple sentences in passive voice about 25 percent of the time.
As readers, we also perceive active sentences as both shorter and easier to read because active voice typically makes sentences more efficient. Consider the difference between the first sentence below, which relies on passive voice, and the second, which uses active voice.
2. Actors or concrete objects turn sentences into micro-stories.
We read sentences with less effort—or cognitive load—when we can clearly see cause and effect, or, “who did what to whom,” as Ina Bornkessel-Schlesewsky puts it.
Bornkessel-Schlesewsky, a professor of cognitive neuroscience at the University of South Australia, used functional Magnetic Resonance Imaging (fMRI), to spot brains reacting to meaning and word order in sentences. Unsurprisingly, when the subjects of sentences are nouns clearly capable of performing actions, readers process sentences with greater speed and less effort. For actors, writers can choose people, organizations, publications—any individual, group, or item, intentionally created, that generates impact.
In addition to our unconsciously perceiving these sentences as easy to read and recall, we can also more readily identify actors in sentences. Furthermore, these nouns enhance the efficiency of any sentence by paring down its words. Take the examples below:
3. Pronouns send readers backward, but readers make sense of sentences by anticipating what comes next.
Writers typically love to use pronouns as the subjects of sentences, especially the demonstrative pronouns this, that, these, those, and it , believing that these pronouns help link their sentences. Instead, pronouns save writers time and effort—but significantly cost readers for two likely reasons.
First, readers assume that pronouns refer to a singular noun, rather than a cluster of nouns, a phrase, or even an entire sentence. Second and more importantly, when writers use these pronouns without anchoring nouns, readers slow down and frequently misidentify the pronoun referents. In fact, readers rated writing samples with high numbers of sentences using demonstrative pronouns as being less well-written than sentences that used actors as subjects or pronouns anchored by nouns.
Pronoun as subjects: [Katie Ledecky] estimated that she swims more than 65,000 yards—or about 37 miles—a week. That adds up to 1,900 miles a year, and it means eons of staring at the black line that runs along the bottom of a pool. Actor as subject: [Katie] Ledecky swims up to 1,900 miles a year, mileage that entails seeming aeons of staring at the black line that runs along the bottom of a pool.
4. Action verbs make sentences more concrete, memorable, and efficient.
For years, old-school newspaper and magazine editors urged writers to use action verbs to enliven sentences.
However, action verbs also offer readers and writers significant benefits in terms of their memorability, as revealed in one study of readers’ recall of verbs. Of the 200 verbs in the study, readers recalled concrete verbs and nouns more accurately than non-action verbs.
In fact, when we read concrete verbs, our brains recruit the sensory-motor system, generating faster reaction times than abstract or non-action verbs, processed outside that system . Even in patients with dementia , action verbs remain among the words patients can identify with advanced disease, due to the richness of semantic associations that action verbs recruit in the brain.
5. Place subjects and verbs close together.
Over the past 20 years, researchers have focused on models of reading that rely on our understanding of sentence structure, a focus validated by recent studies.
As we read, we predict how sentence structure or syntax unfolds, based on our encounters with thousands of sentences. We also use the specific words we encounter in sentences to verify our predictions, beginning with grammatical subjects, followed by verbs.
As a result, readers struggle to identify subjects and verbs when writers separate them—the more distance between subjects and verbs, the slower the process of identifying them correctly. Moreover, readers make more errors in identifying correct subjects and verbs—crucial to understanding sentences—with increases in the number of words between subjects and verbs, even with relatively simple sentence structure.
Ironically, as writers tackle increasingly complex topics, they typically modify their subjects with phrases and adjective clauses that can place subjects at one end of the sentence and verbs at the opposite end. This separation strains working memory , as readers rely on subject-verb-object order in English to understand the sentence’s meaning. Consider, for example, this sentence from an online news organization:
In Florida, for instance, a bill to eliminate a requirement that students pass an Algebra I end-of-course and 10th-grade English/language arts exams in order to graduate recently cleared the Senate’s education committee.
On the other hand, when we place the subject and verb close together and use modifiers after the verb, we ease readers’ predictions and demands on working memory:
In Florida, the Senate’s education committee recently cleared a bill to eliminate two graduation requirements: an Algebra I end-of-course and 10th-grade English language arts.
Jane Yellowlees Douglas, Ph.D. , is a consultant on writing and organizations. She is also the author, with Maria B. Grant, MD, of The Biomedical Writer: What You Need to Succeed in Academic Medicine .
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Action research (AR) is a methodical process of self-inquiry accomplished by practitioners to unravel work-related problems. This paper analyzed the action research reports (ARRs) in terms of ...
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 ...
Thus, action research is often a cyclical process. The action research report that you write is based on this process. Typically, an action research report is written in the same way as you would write an original research article. However, you need to ensure that your report has the following components: The context or background.
Action research is a way for you to continue to grow and learn by making use of your own experiences. The only theories involved are the ideas that you already use to make sense of your experience. Action research literally starts where you are and will take you as far as you want to go. DESIGNING A STUDY.
Th ere are two reasons for this: It transforms you, the researcher, as you grow in understanding of the issue(s) you study (Cunlif e, 2004, 2005; James, 2005, 2006a, 2009; Schön, 1983, 1987). Data-driven decisions have increased power to infl uence stakeholders, and AR Research protocols insist that you gather data.
This brings us back to the essential steps of action research: identifying the problem, devising an action plan, implementing the plan, and finally, observing and reflecting upon the process. Your action research report should comprise all of these essential steps. Feldman and Weiss (n.d.) summarized them as five structural elements, which do ...
Step 7: Developing an Action Plan. Once the data have been analyzed and the results of the analysis interpreted, the next step in the action research process is the development of an action plan. This is really the ultimate goal of any action research study—it is the "action" part of action research.
Action Research (AR) is an ideal methodology to enable practical and emancipatory outcomes, as well as to generate relevant and authentic theory. Consequently, it has gained popularity worldwide. However, this emerging paradigm of AR in the Social Sciences has been widely misunderstood and misused by researchers, educators and practitioners. ...
Writing an action research paper follows the principles and structure detailed in Chap. 4. However, some important aspects regarding action research project reports are (partly) different from other reports. We address these idiosyncrasies based on the standard structure of a scientific paper. Structure of the paper
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 ...
Specifically, action. research is defined as one form of meaningful research that can be conducted by teachers with. students, colleagues, parents, and/or families in a natural setting of the classroom or school. Action research allows teachers to become the "researcher" and provides opportunities for them.
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 ...
Action Research is an international, interdisciplinary, peer reviewed, quarterly published refereed journal which is a forum for the development of the theory and practice of action research. The journal publishes quality articles on accounts of action research projects, explorations in the philosophy and methodology of action research, and considerations of the nature of quality in action ...
The 'observing' stage of action research involves collecting data, for example via surveys, focus groups, interviews, observations, reflective journal writing, and/or assessments. For language ...
The Do's and Don'ts. Make yourself familiar with the complexities and requirements of action research before conducting the study. This will help you in preparing the introduction to the dissertation. The first step is to write a winning proposal to establish your research problem and decide on the research's approach and direction. Action research problems play a critical role in ...
Overview of the action research approaches referred to in the included articles, indicating those papers that are mentioned as "the origin" of action research. Studies that either name an approach as being the origin of action research, or are being named as such, are highlighted in blue for better readability.
Action Research can build capacity to change the structural forces that are killing our planet and therefore ourselves. Action researchers can transformatively grapple with the issues of power that keep the current unsustainable system in place. This will mean practicing con-sciously with mutually transforming power.
A good research question is essential to guide your research paper, dissertation, or thesis. All research questions should be: Focused on a single problem or issue. Researchable using primary and/or secondary sources. Feasible to answer within the timeframe and practical constraints. Specific enough to answer thoroughly.
The Institutionalization of Action Research Allan Feldman was the action research facilitator for the Scope, Sequence and Coordination (SS&C) 3100 Schools2 project funded by the National Science foundation. The goal of the project was to reform the teaching of science on the secondary level in California.
Purpose of Study. This action research study sought to locate and evaluate instructional strategies for use in teaching pre-algebra to a specific group of seventh grade students. The purpose for doing so was to improve the effectiveness of instruction as determined by measurable student growth observed during a series of instructional units.
This paper examines the experiences and insights of 34 graduate students in an elementary education master's degree program as they engaged in an action research project during two required action ...
The 'core action research' is understood as being the fieldwork phase of the 'thesis action research'. The Thesis action research kind of operates at a meta-level - i.e. research on the core action research. This means that the 'thesis action research' can have a different research question to the 'core action research'.
Action verbs make sentences more concrete, memorable, and efficient. For years, old-school newspaper and magazine editors urged writers to use action verbs to enliven sentences.
Take our quiz to find out which one of our nine political typology groups is your best match, compared with a nationally representative survey of more than 10,000 U.S. adults by Pew Research Center. You may find some of these questions are difficult to answer. That's OK.
The aims and objectives of this action research are to: To improve students' active participation in classroom teaching and learning. To explore the reasons why students hardly take part in ...