Issue B
Issue C
An alternative to the above would be to combine the literature review, but have separate chapters/sections for the data.
If you have been sponsored by a specific organisation, or your college has arranged for a placement on which your dissertation will be based, they may want a different kind of report or presentation. The structure of the report will depend on the scope you have been given, in particular to recommend or implement changes.
If you are limited to analysing a situation and making a proposal for change, or you are reflecting on a project from the past, Maylor and Blackmon (2005, p. 407) recommend that you should concentrate on:
The academic parts such as the literature review and the research methodology should be either condensed or put in an appendix, although you should include (in the body of the report) enough to show the validity of your recommendations.
If you are tasked with solving a business problem and expected to lead (to some extent) the resulting change, you are into the realm of action research. This is different to applied research and the structure of your report may be able to reflect this – speak to your supervisor to confirm. If so, Dick (1993) recommends:
Introduction | Describe the situation and the reason for the project or study. Explain the structure of the thesis and the reasons for it. |
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Research methodology | Outline and justify your approach. Explain the topic then consider possible research approaches, emphasising the need for responsiveness. |
Iteration A Iteration B Iteration C etc. | Action research generally consist of a number of ‘plan-implement-review’ cycles. For each stage/major finding, clearly summarise then discuss the conclusions you have reached, your reasoning, the relevant confirming and disconfirming literature, and the implications. |
Conclusions | What are the overall conclusions of the research or project? What ultimately happened? What does the study contribute – what is now understood that was less well understood before? |
The inclusion of prelims and end matter is another way in which the dissertation differs from the more run of the mill piece of written work. The former require Roman as opposed to Arabic numerals for page numbers.
Here is a rough guideline as to what should be included:
Title page | Title; author surname and initials; ‘A thesis submitted to…in partial fulfillment of the requirements for the degree of…in month/year’ (wording as directed by institution) |
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Abstract | A short summary covering the topic, the rationale for choosing it, the methodology and the conclusion |
Executive summary | A short summary giving a background to the issue discussed, the main recommendations, evidence for them, and the methods used to arrive at them |
Contents page | List main chapters/sections |
List of main figures and diagrams | |
Acknowledgements | Thank the people who were especially helpful to you in compiling the report |
Main body | See above |
References | All the works referred to in the body of the report, with full citations |
Bibliography | Other sources which you used but did not quote, also listed in full |
Appendices | Material that is relevant but not essential to the main report: could include your research instrument, background information, etc. |
Exactly what to include will depend on your audience and the length of the report: the contents page, list of figures and acknowledgements can be omitted for a short report, while a business-orientated report should have an executive summary rather than an abstract (you may find it useful to leave in the former in an academic report for the benefit of any sponsors).
Writing style, presentation and layout are all important in gaining you a good mark.
We have already talked about how the dissertation will be divided into chapters or sections: within those divisions, there will be others, marked by headings and subheadings. This is another difference from the essay, but one that will work in your favour as these headings can serve as ways of organising your thoughts as you plan.
Use a font that is easy to read (and one you like as you will get very used to seeing it on the screen!), and make sure you have wide margins.
This should be formal, concise and academic. Here are a few guidelines:
It’s helpful to consider writing as a reverse pyramid, in which you start off working on the more conceptual aspects and finish off with the detail of grammar, punctuation and spelling. Here are some stages you might go through:
Writing is also a process of pruning – of bits that are not essential to your main thesis, and above all of excess words so you can meet your word length (remember how you never thought you could write that many words?). You will probably find that you can get rid of ‘nice to have but not essential’ material at stage 3, and that at stage 4 you prune your style so that you get rid of unnecessary verbiage. Writing to word limit is very important and is considered a key management attribute.
Putting in references is something best not left to the end – if you have kept good notes on your sources you should be able to put these in as you go along. But you will obviously need to check that all your references are correct before finally submitting your report.
Group projects can provide particular interpersonal challenges, as teams cope with difference of views, non-performing team members etc., and particular problems can arise at the writing stage. If you split up the chapters amongst different people, then you will get different writing styles and even ideas about what the report is about. Ways of ensuring consistency included swapping around writing and editing, so that the text gets seen by a different pair of eyes, or having an overall ‘master editor’.
We’ve already mentioned the importance of planning; we can’t over emphasise the importance of allowing yourself enough time at the end for printing and binding – remembering that everyone else will be mobbing the repro department and monopolising the printers. The other thing to avoid is endlessly tinkering with an otherwise complete report – if you have met your objectives, hand it in.v
June 15th, 2019, how to use your dissertation skills to market your employability.
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Estimated reading time: 10 minutes
Many of you will be doing your dissertation right now (or have done one already) and might be wondering how to make it work for your applications. Thankfully, your dissertation will give you a whole set of skills and assets that will be attractive to employers. Listed here are just a small selection of the qualities you can develop by doing a dissertation, and how they relate to working in the real world.
One thing that everyone has to do for their dissertation is research. This is a very important skill to have in the working world. Good research skills mean that you know what is and isn’t relevant to a project, and that you know how to apply information effectively to meet your needs.
You should also apply your research skills when looking for a job. Employers look for people that are knowledgeable about the company and the industry, as this means you may have more innovative and informed ideas about how to move forward. This also shows a dedication to the company and industry, which is also very attractive to employers.
Problem solving can be a bit of a buzz term, but it’s so much more than that: it shows that you have initiative, you’re adaptable, and that you have critical thinking skills.
If you can show an employer an obstacle you came across during your dissertation and then demonstrate how you overcame that (and possibly what you’d do differently), then they will be able to see how you will react to issues that arise during your employment.
For instance, if you found your argument didn’t quite work and you had to reassess your methods, then that shows you know when to change your tactics and that you have the self-awareness to understand when you’re pursuing the wrong outcome.
Employers want to know that you can concisely communicate ideas and information, whether this is on paper or in person.
Writing a dissertation demonstrates that you can take a set of complex arguments and write them up in a way that is both understandable and convincing. This is something that will relate to all parts of your career, from report writing to persuading colleagues, employees, or managers of what the best course of action for the company is too.
Likewise, if you’ve done a dissertation you’ve probably discussed your ideas with your academic advisor, tutor, course mates, and others. If you can show you’ve taken advice from these people about your dissertation, then employers will know that you can be a team player and respect the opinions of others.
This may not be the case for everyone, but sometimes your dissertation topic will be on something that can be a starting point for your career and/or further study.
You can use your dissertation as a case study for your knowledge of the industry or work that you’re interested in pursuing after your course, and to show that you have a good sense of the kinds of issues that might arise when you’re in the job.
A lot of companies request that you have numerical skills, so if you’ve dealt with large sets of data for your dissertation then you can unequivocally prove this.
Not only that, but if you’ve been using a software package like SPSS for your data analysis you can show that you also have strong computer skills and have data analysis experience. Don’t forget about programmes like Microsoft Excel too: if you know your way around a pivot table, make sure this is clear!
If you’ve managed to complete a large piece of work like a dissertation, then you can probably manage a company project. Completing your dissertation means that you can work under pressure and stay calm while managing multiple deadlines.
Whether or not you were in the library at 4am sobbing into your notes the day before it due is irrelevant: you completed a large project once, and so that shows you can absolutely do it again!
As mentioned briefly above, if you’ve managed completing a large piece of work like a dissertation, then you can manage a project at work. However this is more than just meeting deadlines and staying focused under pressure.
Project management is shorthand for a huge range of skills, including time management, working alone, team work, communication, and perseverance. If you can break down your project management skills into these individual abilities, and show how you have used them, then you will stand out to employers who will then know you know what they’re looking for.
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The dissertation is a task that is considered to be the most sophisticated. The standards of writing used in the dissertation are different from other writings. It is misunderstood as an essay or assignment writing, however, it is not. It demands at least 15k for a complete dissertation and you cannot write a single word out of the context.
Every student in the final semester has to face this activity as without writing a dissertation they cannot pass the program. It includes different challenges related to various requirements that are essential for writing a dissertation. Professional dissertation help has always helped students to make a quality masterpiece of the dissertation and acts as the right way to the destination.
Writing a dissertation is not an easy task it requires some specific and basic set of skills. Other than skills, time and commitment also play an important role in the completion of the dissertation. It is not one day or a week’s work. You have to commit a certain time every day to accomplish the requirements of writing a dissertation. Let’s discuss in detail some of the most basic skills that are essential to write a dissertation.
List of Skills
Reading plays an important role in the development of the mind. Once you start understanding the written words it will grow the ability of your mind accordingly. It also helps to grasp an understanding of the specific subject. It further assists you to increase the amount of your knowledge tank by developing reading skills. Reading the relevant information helps you guide the way towards experiencing the writing of the professionals.
Reading is an essential step for the completion of the dissertation. The dissertation requires thorough searches of the relevant information and demands to read the same. These informational articles are lengthy and require reading habits to effectively read the entire document. If you read it consciously then only you will be able to grasp the required information to be used in your dissertation.
There are many activities provided in the schools, colleges and universities that include writing. Such as assignment and essay writing. These small activities help students to practice writing and slowly develop their writing skills throughout the program. This writing skill is very essential to write a dissertation. Think of yourself, would you will be able to write 15k words without developing writing skills? For the dissertation, it’s not.
Writing skills help you to get a good command on the basics, such as grammar, spelling, punctuations, usage of right words and standards of writing. These basics will definitely help you during the dissertation writing.
Analytical skills are vital for completing a dissertation. Writing is not the only thing that matters in the dissertation. It is a chapter and portion in the dissertation where certain samples have to be collected for the performance of specific statistical tests. These tests have to be analysed according to the results and findings. Therefore, analytical skills are considered as a key source in preparing a dissertation.
Critical thinking refers to removing the entire limitations for the specific topic or the subject. This helps to think beyond the limits and to develop and introduce new ideas. This is the reason that it has become a necessity for writing a dissertation. You have to search for the relevant articles, grasp the information and think about the circumstances. This will assist you to use your entire knowledge in a significant manner and to be used the same in your dissertation.
It is also an important and basic part of writing the dissertation. If you have seen the structure of a dissertation, you must know that there is a requirement of writing a “problem statement” at the very beginning of the dissertation. This is what exactly you are doing throughout the process of dissertation, that is, finding the solution for the problem. This is the reason that it is one of the essential skills to be on my list.
Active listening is considered as important in the dissertation process as reading skills. This helps you to grasp the required information through various channels of information. It is also one of the most effective ways of gathering the required information that is essential for your dissertation writing. It also helps you to develop your writing skills dramatically. It is a saying that “Most people do not listen with the intent to understand; they listen with the intent to reply. However, in the case of the dissertation it should be opposite to that, which is, listening to acquire the information.
Dissertation writing has always been a stress creator for the students. I understand that it is not an easy task to be accomplished. Plus, it is also a necessity for your academics and degree, so for students who cannot understand the requirements of writing the dissertation or for those who cannot spare time out of a busy schedule, I would recommend approaching professional dissertation writing services . This can help you get the experience of professional writing and to get a deep understanding of the topic that can be helpful in your final exams. I hope that acquiring the discussed skills will help you complete your entire dissertation on your own.
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With the higher education reform putting forward the professionalization of doctoral students, doctoral education has been strongly focused on generic transferable skills to ensure employability. However, doctoral training should not forget core skills of research and especially the ability to formulate research questions, which are the key to original research and difficult to develop at the same time. Learning how to develop a research question is traditionally seen as a one-to-one learning process and an informal daily transmission between a novice and a senior researcher. The objective of this paper is to offer a framework to design doctoral programs aimed at supporting the process of development of research questions for doctoral candidates guided by their supervisors. We base our proposal on two doctoral training programs designed with a pedagogical strategy based on dialogs with peers, whether they be students, supervisors, or trainers from a diversity of scientific backgrounds. The resulting framework combines three learning challenges faced by doctoral students and their supervisors when developing their research question, as well as training objectives corresponding to what they should learn and that are illustrated by the scaffolds we have used in our training programs. Finally, we discuss the conditions and originality of our pedagogical strategy based on the acquisition of argumentation skills, taking both the subjective dimensions of PhD work and the added value of interactions with a diversity and heterogeneity of peers into account.
Avoid common mistakes on your manuscript.
With the higher education reform ongoing in the Western world, doctoral education has undergone “a shift from the master–apprentice model to the professional model” (Poyatos Matas, 2012 ), focusing doctoral education on doctoral graduate employability (Cardoso et al., 2022 ) and thus on generic transferable skills (Christensen, 2005 ). However, Poyatos Matas ( 2012 ) warns doctoral educators of the danger of reducing doctoral education to a business or team skills approach, arguing the “importan[ce of maintaining] an adequate balance between skill-based and knowledge-based approaches to doctoral education.” Along the same line, Christensen ( 2005 ) argues that training in transferable skills “should not be overemphasised with respect to original research.” Nevertheless, Poyatos Matas ( 2012 ) does not explicitly explain what the core skills of research, grouped into a broad category referred to as “research skills,” are among seven other skills listed by the European Universities Association’s Salzburg principles.
Among research skills, the way the research question is formulated is critical. As Einstein and Infeld expressed it in 1971 , “the formulation of a problem is often more essential than its solution […]. To raise new questions, new possibilities, to regard old questions from a new angle, requires creative imagination and marks real advance in science.” In this article, we consider the development of a research question as a process that consists of determining and reducing the identified problems, whether scientific or socio-economic, and translating them into a relevant and treatable question (Callon, 1984 ). We assume that it is a key process for research activities and a skill that PhD students have to acquire during their PhD experience. However, learning how to develop a research question is far from being easy, as revealed by the multiplication of methodological guides and tutorials on this topic. As researchers and human resource advisors working in a multidisciplinary research institute (INRAE) Footnote 1 , we have also observed many PhD students struggling to formulate their research question, which may seriously inhibit the writing of the final manuscript, whether it be a thesis by publication or not. Some authors have pointed out that the current graduate school education system has largely focused on producing better learners and problem solvers, thus neglecting problem-finding or creativity development in doctoral education (Whitelock et al., 2008 ). Preparing a “research proposal” and developing a researchable question is even recognized as a critical step for doctoral students (Zuber-Skerrit & Knight, 1986 ), becoming a “threshold to cross” during the PhD journey (Chatterjee-Padmanabhan & Nielsen, 2018 ). It thus appears essential to explore the challenges of research question development and how doctoral training programs can contribute to its learning.
The objective of our article is to offer a framework to think about and design doctoral training programs that support the development of research questions for doctoral candidates guided by their supervisors. Our proposal is grounded in two doctoral training programs designed with a pedagogical strategy based on dialogs with peers, whether they be other students, supervisors, or trainers from a diversity of scientific backgrounds. This article is structured into four sections. We present our theoretical background in order to explore the diversity of approaches to develop a research question, laying out our vision of doctoral experience and education, and the way in which the concept of scaffolding has been used in the learning processes that underlie the development of research questions (“ Theoretical background ” section). We then present our methodology, combining an analysis of the literature, our experience in conducting research, supervising and training doctoral students and their supervisors, and our case studies (“ Materials and methods ” section). Our results consist of a framework that combines three learning challenges and the corresponding training objectives, illustrated by scaffoldings we have used in our training programs (“ Results: scaffolding learning challenges for the development of the research question within a thesis ” section). Finally, we discuss the conditions and originality of our proposal based on the acquisition of argumentation skills, with the consideration of the subjective dimensions of PhD work and the added value of interactions with a diversity and heterogeneity of peers (“ Discussion: Enriching peer-learning scaffolding to support the development of a research question as a dialogical process ” section).
Opening up the process of research question development: a diversity of approaches.
According to the literature about the development of research questions, it is a task that is difficult to formalize and for which several approaches coexist. It may differ according to the disciplines (Xypas & Robin, 2010 ) as well as according to the practical context of the doctoral thesis (i.e., participative research, methodological or fundamental research, financial support). We identified four approaches to research question development:
Gap-spotting (e.g., Locke & Golden-Biddle, 1997 ), the more classical approach, which consists in identifying gaps in existing literature that need to be filled.
Challenging the assumptions underlying existing theory in order to develop and evaluate alternative assumptions. Such an approach aims at coming up “with novel research questions through a dialectical interrogation of one’s own familiar position, other stances, and the domain of literature targeted for assumption challenging” (Alvesson & Sandberg, 2013 ). These authors explicitly adopt a critical perspective of gap-spotting, which they consider as a form of “underproblematization.”
Expressing a contrastive stance to create dialogical space, presented as critical in order to develop a convincing research question (Mei, 2006 ). This approach has addressed the research question formulation by focusing on the writing process.
Problem-solving study based on a negotiation about the “problem framing” involving scientists and stakeholders, and which focuses on practical problem-solving (Archbald, 2008 ).
The literature and our experience show that these different approaches coexist, but do not fall within the same temporality. For example, gap-spotting can be an operation that takes place at the beginning of the research process and which is limited in time, whereas the negotiation of problems between scientists and stakeholders can be much longer and can arise at different stages of the research process. In the same way, challenging existing theories can be a long and incremental process that evolves as the doctoral student acquires new knowledge from scientific literature along the doctoral path or due to an unexpected observation in the field. Trafford and Leshem ( 2009 ) also explain how research begins with a gap in knowledge or professional practices and how research questions evolve with new inputs from the literature, fieldwork, and the progressive establishment of a conceptual framework and theoretical perspectives, to finally end up by proposing a “justifiable contribution to knowledge”. In this perspective, the formulation of a research question can be considered as an incremental path that continues during the doctoral journey.
The knowledge and know-how involved in research question development are thus of a very specific nature (metacognition, implicit, diversity of thinking, etc.), rendering it impossible to design doctoral training programs focused on this complex task as a simple “knowledge transfer”. Moreover, beyond the cognitive learning required, it also refers to more developmental challenges, both for doctoral students and their supervisors, since it is embedded in their specific epistemological and social working situation.
We consider research and, thus, doctoral experience as an activity involving affects, interests, and social networks (Shapin, 2010 ). In line with other scholars (Lonka et al., 2019 ; Sun & Cheng, 2022 ; Xypas & Robin, 2010 ), we argue that doctoral education should rely on a person-centered approach. This means paying attention to doctoral students’ profiles, their perceptions of the academic environment and their professional aims, i.e., the individual contexts of each PhD thesis and the diversity of PhD researchers’ needs and goals (Inouye, 2023 ), as well as their conceptions of research or epistemological backgrounds (Charmillot, 2023 ). We thus consider the PhD process as a professional experience with its multidimensional nature and the distinct quests of PhD students (quest for the self; intellectual quest; professional quest) when navigating their doctoral paths (Skakni, 2018 ).
This type of view leads to a developmental approach of the PhD journey, with doubts, uncertainties, and paradoxes in becoming doctoral researchers, and a “transformation of understanding and of self” (Rennie & Kinsella, 2020 ). Influenced by their personal trajectories and post-PhD goals, doctoral students may thus adopt various approaches in the yearly phase of the PhD process when developing their research projects, whether writing a research proposal constitutes or not a formal step to becoming a full doctoral candidate Footnote 2 . We also consider the PhD experience as a transformative process of a bidirectional nature, for both doctoral students and their supervisors (Halse & Malfroy, 2010 ; Kobayashi, 2014 ).
When it comes to doctoral education, this point of view implies the necessity to combine both generic support and individual guidance, to tailor training and to take each of the doctoral student’s stage of development into account. It also requires that trainers take on the role of facilitators more than those “who know”, in a socio-constructivist approach to learning. Nevertheless, designing doctoral training dedicated to research question development throughout the doctoral journey opens up questions on how to promote such learning in the workplace.
In line with Vygotsky’s approach to learning, we consider that the concept of scaffolding can be beneficial to understanding how PhD supervisors can assist their doctoral students in learning how to develop their research question. Firstly defined by Wood et al. ( 1976 ) as a process similar to parents helping infants to solve a problem, this concept has proven to be an efficient pedagogical strategy to support learning in science (Lin et al., 2012 ). It can then be connected to Vygotski’s Zone of Proximal Development (ZPD) ( 1978 ), consisting of tasks that students cannot yet carry out on their own, but which they can accomplish with assistance. Scaffolding has been specified by Belland ( 2014 ) in instructional settings as a “just-in-time support provided by a teacher/parent (tutor) that allows students (tutees) to meaningfully participate in and gain skill at problem solving”. Beyond this use within formal instruction, it has been put forward as “a central educational arrangement in workplace learning”, considered as a “socially-shared situation between master and apprentice” (Nielsen, 2008 ). Scholars argued that scaffolding could also be used to improve higher-order thinking abilities through social interaction, such as argumentation when solving ill-structured problems or when building dialectical arguments.
Three critical features are central to successful scaffolding:
Firstly, the notion of a shared understanding of the goal of the activity is crucial (Puntambekar & Hübscher, 2005 ), requiring an “intersubjectivity” between the tutor and the tutee (Belland, 2014 ), which is reached when they collaboratively redefine the task. The stake here is to make sure that learners are invested in the task, as well as to help sustain this motivation, encouraging them to be informed participants who understand the point of the activity, the value and use of the strategies and “making it worthwhile for the learner to risk the next step” (Wood et al., 1976 ).
Secondly, the tutor should provide the tutee with a graduated assistance based on an ongoing diagnosis of the tutee’s current level of skill, which Belland ( 2014 ) sums up by “providing just the right amount of support at just the right time, and backing off as students gained skill”. Therefore, scaffolding is highly contingent on both the task and the learner’s characteristics, thus being “dynamically adjusted according to tutee ability” (Belland, 2014 ) and requiring the tutor to manage a careful calibration of support (Puntambekar & Hübscher, 2005 ).
Thirdly, scaffolding is successful when the learner controls and takes responsibility for the task, thus moving towards autonomous activity. Scaffolding should then promote this transfer of responsibility, as well as including its own fadeout as internalization progresses.
First focused on the interactions between individuals, the scaffolding concept is now being more broadly applied to artifacts, resources, and environments designed as scaffolds (Puntambekar & Hübscher, 2005 ), with three main “scaffolding modalities”:
One-to-one scaffolding, which “consists of a teacher’s contingent support of students within their respective ZPDs”, considered as the ideal modality with a tailored scaffolding;
Peer scaffolding, which goes beyond the original idea of assistance by a more capable individual (Wood et al., 1976 ) and which hypothesizes that peers can also provide such support;
Computer/paper/artifact-based scaffolding, which emerged as a solution to the dilemma that teachers cannot provide adequate one-to-one scaffolding to all students in a classroom.
Beyond the advantages and limitations of each scaffolding modality, various scholars have discussed the challenges of designing scaffolding in complex environments. It can be a question of taking the heterogeneity of learners into consideration when designing tools (Puntambekar & Hübscher, 2005 ), of building dynamic assessments and fading into the whole environment (Puntambekar & Hübscher, 2005 ; Belland, 2014 ), or of considering the learning environment by combining tools and agents (Puntambekar & Hübscher, 2005 ) in a system of “distributed scaffolding” (Tabak, 2004 ). Lastly, beyond the dyadic relationship between the master and the apprentice, many authors have shown the distributed and collective nature of scaffolding at the workplace (Filliettaz, 2011 ), pointing out the role of “the entire work community” in workplace learning. This enlargement of the concept of scaffolding appears to be especially relevant for the learning of research question development, which is a long process that results from a diversity of interactions, as shown in the previous sub-section.
In her report of the Bologna seminar on Doctoral Programs for the European Knowledge Society, Christensen ( 2005 ) argues that only training by doing research can provide doctoral candidates with core skills such as “problem solving, innovative, creative and critical thinking”. Until now, the traditional model of doctoral education was based on a supervisor-centered model and a transmission model “where the apprenticeship learns from the master by observation” (Poyatos Matas, 2012 ). Such informal learning thus takes place in private spaces, pointing out the lack of explicit knowledge on “what the academic career involves, the norms, values, and ethics embedded in their disciplines, and the expectations of work habits that they would be expected to meet” (Austin, 2009 ).
Even if this master-apprenticeship model was previously adequate, it turns out to be outdated because of the evolution of doctoral conditions. The increasing control and limitation of PhD duration and the obligation of regular reporting about the progress of the PhD leave less room and time for mimetic and trial-and-error learning. This is especially true in the case of specific doctoral education models such as the PhD by publication, the professional doctorate, the practice-based doctorate (Poyatos Matas, 2012 ), and the case of traditional PhDs. However, most of the time, doctoral students remain “without fully learning how to frame their own questions and design and conduct their own studies” (Austin, 2009 ). It is thus not surprising that the offer of learning supports for PhD students has greatly increased, with a wide diversity of options (handbooks, YouTube channels, writing courses or groups, etc.). Among the diverse training programs offered to doctoral students and sometimes supervisors, some doctoral schools and universities have also created specific training programs to support research question development, while some authors like Inouye ( 2020 ) put forward that training and supervision should include explicit training on the Research Proposal as a “threshold to cross” (see footnote n°2). On the basis of this diversity of offers, we identified three main scaffoldings corresponding to the three main modalities identified in the previous section: artifacts, peer-learning groups (e.g., Chatterjee-Padmanabhan & Nielsen, 2018 ; Poyatos Matas, 2012 ; Zuber-Skerritt & Knight, 1986 ), and supervisors (e.g., Manathunga et al., 2006 ; Whitelock et al., 2008 ).
Following a developmental approach to the PhD process, the present study aims at offering a generic framework to think about and design doctoral programs that scaffold the learning of the development of research questions.
Building a framework by combining our experiences with the literature.
This research was based on two distinct doctoral training programs that we designed and independently ran over a period of 10 years. Having reflected together on our department’s doctoral training policy, we then progressively formalized the issues at stake in doctoral training and analyzed how our programs responded to them. The importance and difficulties of learning how to develop research questions during doctoral studies then became crucial, leading us to formalize what we had learned from our two programs. In this article, these programs are our case studies, i.e., the situation where we conducted an empirical inquiry to investigate the scaffolding of research question development and from which we can expand and generalize theories on doctoral training (Yin, 2018 ).
For each case study, we combined several methods to collect data:
We used ethnographic techniques (Parker-Jenkins, 2018 ) with a participant observer stance. As researchers conducting research and supervising doctoral students, as HR advisors supporting doctoral students and researchers at INRAE, and as trainers and coordinators in two doctoral training programs, we are involved in prolonged and repeated periods of observation. We thus documented detailed field notes that were revisited as research data.
We built a corpus of pre-existing documents presenting the two doctoral programs (brochures, Website contents, scientific articles, time schedules and targeted objectives at each sequence). For each document, we carried out an open-coding operation to identify the narratives about research question development.
We gathered feedback spontaneously expressed by the trainees during the training courses, the hot debriefs occurring at the end of each course, and training assessments one month after the course, as well as in the course of our activity (in individual HR interventions or in reading the acknowledgements of a PhD thesis).
In parallel with data collection, we carried out a review of the literature on the evolution of doctoral education and the emerging learning challenges for doctoral students and their supervisors, some epistemological articles on research question development and the process of doctoral experience, empirical articles describing training for research question development and seminal articles, and reviews on scaffolding in education sciences. We undertook a cross-reading of this literature to build a conceptual framework identifying the key concepts to study training for research question development: scaffolds, scaffolding objectives, learning challenges, and scaffolding practices. We then analyzed our data to identify the scaffolds mobilized in each case study, the objectives of this scaffolding, and the learning challenges of research question development considered as a scaffolding system. Finally, we characterized our scaffolding practices, i.e., the way in which we, as trainers, concretely support the learning required to achieve the challenges of research question development. Both training programs result from a continuous improvement process based on the feedback of the trainees: with such feedback and our own observations, we were thus able to identify and select the most effective teaching methods in line with our objectives to support the learning of research question development. Behind the classical scaffolding modalities identified in the literature, we chose to identify the diversity of very contextual scaffolding practices and devices used, which we then linked to our training objectives. For each program, we also detailed how these objectives relate to the larger learning challenges of research question development. This led us to formalize a generic grid, which was tested and improved by using it to describe each of our programs.
As a public research institute, the main goals of INRAE are to produce and disseminate scientific knowledge, with a specific focus on the contribution to education and training. Given the broad field of competences within INRAE devoted to the development of agriculture, food and the environment, and its inherent multidisciplinary nature, the thesis defended may draw from extremely various disciplines, ranging from molecular biology to sociology, with a dominance of life and environmental sciences. Moreover, INRAE is a targeted research institute that works with and for various partners in higher education and research, industry, and the agricultural sector and regional governments. This means that many research projects, including doctoral research, are designed and carried out within partnerships with these various stakeholders. INRAE doctoral students are supervised by INRAE researchers, mainly within complex multidisciplinary supervision teams together with French or international academic partners.
In this context, we have developed our vision of research activity and doctoral experience (see the “ Our vision of the PhD experience and doctoral education ” section) and have been designing, improving, and leading two doctoral training programs for more than 10 years (Table 1 ), which share common postulates such as the following:
Considering the PhD process as a part of the professional trajectory.
Aiming at supporting autonomy of doctoral students through the enhancement of their capacity to defend the choices they have made to build research questions, thus also aiming at helping supervisors to adopt a companionship stance.
Considering research question development as an activity, which implies the choice of pedagogical principles based on action learning rather than knowledge transfer.
Considering diversity as an asset, we base our training programs on multidisciplinary workshops.
Nevertheless, they differ in terms of the training audience and times of training in the PhD process:
Course A is only open to doctoral students of the ACT Footnote 3 division of INRAE, whereas course B trains both doctoral students and their supervisors belonging to the different divisions of INRAE.
Doctoral students may attend course A three times during their thesis, whereas course B is designed to train doctoral students once during their thesis, at the end of the first year.
In this section, we present a generic framework to think about and design doctoral training programs with the aim of scaffolding the learning of research question development. It combines learning challenges (LC) faced by doctoral students and their supervisors when formulating their research question and training objectives (TO) corresponding to what the participants should learn. We also illustrate how each of these TO can be scaffolded, drawing on some examples from our training programs.
As a professionalization period, the PhD process is considered as a peer-learning process (Boud & Lee, 2005 ) that relies on a mentoring relationship that aims at developing the autonomy of the young researcher (Willison and O’Regan, 2007 ). Developing doctoral agency (Inouye, 2023 ) and, more specifically, promoting a subject-centered approach (Sun & Cheng, 2022 ) to research question development is the first learning challenge that we identified. We then consider that the doctoral student is the one who makes the subject evolve, who reflects and chooses the components of the research question. We divide this first learning challenge into three training objectives and various sub-objectives (see Fig. 1 ), one focused on the doctoral student, one on the supervisor, and one on their relative roles.
Training objectives set out for the challenge: “to empower doctoral students in their research question development”
First, the doctoral student needs to understand the expectations, nature, and difficulties of PhD research and, specifically, of research question development (TO1). This encompasses the sub-objective of understanding the iterative and unplanned nature of the research process as well as making it clear with their supervisor(s) how their creativity can be expressed regarding institutional or financial constraints. For many authors, problem finding or identifying and describing a research question is part of doctoral subjective creativity and a key for an original contribution to knowledge. At the same time, we observe, as other scholars (Brodin, 2018 ; Frick, 2011 ; Whitelock et al., 2008 ) have, that there is a lack of explicit expectations on creativity in doctoral education, which is then limited by scholarly traditions and institutional requirements. During research question development, “standing at the border between the known and the unknown” Footnote 4 can put doctoral students in a situation of uncertainty about their identity and purpose (Trafford & Leshem, 2009 ). For Frick ( 2011 ), doctoral becoming requires an alignment between “how students view themselves in relation to the research process of becoming a scholar (ontology), how they relate to different forms of knowledge (epistemology), how they know to obtain and create such knowledge (methodology), and how they frame their interests in terms of their values and ethics within the discipline (axiology)”. At the crossroads between these four dimensions, research question development is thus a key process that stimulates doctoral student becoming and that requires the support of supervisors so that their students can understand what is expected of them. Knowing that this can be a source of stress for doctoral students, we put the subject of “what is a research process” up for discussion between supervisors and students in course B. After discussing with other students on their perception of creativity in their thesis, students are invited to watch, together with their supervisors, a video calling for scientists to stop thinking of research as a linear process from question to answer but, instead, as a creative and eventually sinuous path (see footnote n°4). Students often express a sense of relief later on when they work with their supervisors on the second reformulation of the thesis subject. In this way, doctoral students become aware that a formulation is likely to evolve during the thesis and feel more comfortable about formulating one that is in no way definitive at the end of the course. In the same way, in course A, we invite the second-year PhD students to work on the transformation of their research subject in order to illustrate its evolution. We ask them to write the formulation of their subject as worded in the PhD offer or initial PhD contract and the formulation that they would use today to describe it. We then collectively work with the other PhD students at various stages in their thesis to identify the differences between the two formulations, so that the concerned second-year PhD students may explain their choices, eventualities, or constraints that led to the transformation of the subject. During debriefs, trainees express that this exercise helped them to understand that this transformation is an integral part of the research process.
This learning challenge also implies that doctoral students and their supervisors clarify their respective roles regarding research question development (TO2). The degree to which supervisors encourage doctoral students to think and act autonomously has been shown to be associated with students’ supervision satisfaction and greater research self-efficacy (Overall et al., 2011 ). This can be done firstly by clarifying the distinction between the supervisor(s)’s research project, professional career issues and those of the PhD. In course B, asking the doctoral students and their supervisors to describe and discuss the thesis supervision ecosystem has been observed as one of the crucial steps in this clarification of their respective roles in research question development. For doctoral students, research question development also implies that they take ownership of the subject, whereas it was often initially written by the supervisors. In course B, the rule “letting the student speak first” has been expressed by doctoral students as very useful for taking on the role, especially during the three workshops focused on the formulation of the thesis subject. In course A, we ask the doctoral students to present the professional context of their PhD (research project, subsidy, disciplines of the supervisors, proximity of the supervisors to the subject, etc.). This presentation helps the trainees to clarify the contextual framing of the PhD students’ theses, as well as the margin of freedom. For their part, supervisors need to let the PhD students develop their research question by themselves and find the right stance, with a careful balance between “hands-off” and “hands-on” (Gruzdev et al., 2020 ). In course B, supervisors first exchange between themselves about what it means to supervise a thesis and their role in the PhD process. The three reformulation workshops are then practical opportunities to take on this role: experiencing this role of being a support and not the leader of the PhD project is sometimes seen as difficult by supervisors who are used to being research project leaders, but they also admit that it is a necessary step to experience the supervision stance.
Supervisors also need to understand the challenges faced by PhD candidates in the development of research questions (TO3) by first abandoning the assumption of the already autonomous student (Manathunga & Goozée, 2007 ). According to Halse and Malfroy ( 2010 ), the supervisor is “responsible for recognizing and responding to the needs of different students”, within a “learning alliance” with the student. When it comes to formulating their research question, it becomes important to be able to situate their own role with their values and desires in the research process, in general, and, in particular, in the development of the research question, which is not just made up of rational intellectual choices. For this objective, supervisors have to be able to clearly identify the doctoral student’s state of progress in the development of the research question within the thesis and, more broadly, the doctoral student’s values and desires in doing research (Skakni, 2018 ). In course B, we ask them to step back and remain silent (even stolid!) when their doctoral students present their subject. While listening and writing down their observations, they foster their understanding of the states of progress and the orientations chosen by the students. With this rule, we then observe that most of them are able to adopt the correct stance for later workshops when they are asked to work with students on their research question.
The second learning challenge focuses on making the PhD students (and their supervisors) aware of the diversity of ways of doing research and especially various forms and processes of research question development (see the “ Opening up the process of research question development: a diversity of approaches ” section) and situating oneself in this diversity. Many authors argue that doctoral education should highlight scientific pluralism (Pallas, 2001 ), opening the epistemological doctoral experience in order to question the implicit norm of neutrality of the positivist ideal (Charmillot, 2023 ). This is particularly true when it comes to the development of research questions for “wicked problems” (Rittel & Webber, 1973 ), i.e., economic, political, and environmental issues involving many stakeholders with different values and priorities. In this context, developing research questions often requires analysis at the crossroads between several disciplines (Bosque-Perez et al., 2016 ) and between different social stakes (Manathunga et al., 2006 ). It requires reinforcing a scientific culture favorable to this practice of multi-/inter-/transdisciplinarity (Kemp & Nurius, 2015 ), then making interdisciplinary research skills a part of graduate education (Pallas, 2001 ; Bosque-Perez et al., 2016 ). Doctoral students then have to develop their awareness about the diversity of forms and processes of research question development, requiring that they are able to understand this diversity, to know how they themselves relate to different forms of knowledge (Frick, 2011 ), and to acknowledge their performativity in the world.
Within this second learning challenge, we distinguish four training objectives (Fig. 2 ), all concerning doctoral students and their supervisors.
Training objectives for the challenge: “to be aware of the diversity of ways of doing research, to be able to situate oneself in this diversity”
Both of them need to understand and respect the diversity of research stances (TO4). In both of our case studies, we ensure that a diversity of disciplines is represented in each working group, and we guarantee the mutual respect among them. We facilitate the expression of all doctoral students about how they are developing their research question, thus illustrating the diversity of research stances. During the hot debrief of course A, trainees regularly point out the discovery of this diversity as a positive outcome, which helps them to situate their own work. Moreover, discussing research question development within small and heterogeneous groups in terms of disciplines is experienced by participants as a strength “to take a step back and clarify key points” (student, course B, 2017), acknowledging that “working with other disciplines, it helped us to refocus and clarify the subject” (supervisor, course B, 2023).
Doctoral students and their supervisors also need to be able to formulate questions and clearly explain the doctoral research project, especially the way they develop their research question, whatever their discipline may be (TO5). This is why active participation is required in the workshops in both case studies, putting doctoral students and supervisors in the position of an active learner, not a passive trainee. Since such workshops may be very demanding for the PhD student and might be emotionally intense, it is of utmost importance that the trainers carefully manage the collective discussion, guaranteeing trust, mutual respect, and achieving balance in speaking. In particular, doctoral students and their supervisors are the ones who know the scientific community(ies) to which they will contribute and are the only ones who can assess the relevance of the subject. Participants are then asked to question the PhD students without calling the relevance of their theses into question. When aiming at promoting the expression of PhD students as human subjects , trainers have to pay particular attention to the fact that participants do not reformulate the subject for the students but, on the contrary, help them to open up the possibilities, to sort out, and to clarify the status of the elements presented. Trainers also use expression modes such as the questioning forms (open/closed questions), the subject pronouns used (I/we), and the origin of the arguments or events expressed by the PhD student as points of vigilance for managing the group discussion and as levers to go deeper into the questioning and analysis of the PhD students’ thinking about their research questions.
They both have to examine (in their own research and that of others) the place of stakeholders in the development of the research question (TO6). In course A, we use the conceptual framework of translation from Callon ( 1984 ) to analyze how a social problem can be translated into a research question. In course B, the framework given to trainees to develop their research question specifically points out the distinction to be made between the academic research stakes and the stakes for society. They also have to understand how the diversity of ways of scientific knowledge production perform or do not perform in problematic situations (TO7).
The third learning challenge concerns the staggered process of formulation of the research question throughout the PhD process. For many authors, the formulation of a “researchable question” or “research conceptualization” (Badenhorst, 2021 ) by the doctoral student is the first step in the doctoral research process with the writing, and sometimes formal presentation, of a “research proposal”. It is often seen as a threshold in the doctoral journey (Chatterjee-Padmanabhan & Nielsen, 2018 ) and a key feature of “doctorateness”, combining gaps in knowledge, contributions to knowledge, research questions, conceptual frameworks, and research design (Trafford & Leshem, 2009 ). For Frick ( 2011 ), the preparation of a proposal requires background reading and “demarcation of the research question”. It consists in knowing to which scientific issues the thesis will contribute and in identifying the relevant disciplinary concepts. Mastering the various modes of communication in the development of a research question is of utmost importance for PhD students, enabling them to accurately formulate their research question (Lim, 2014 ), as well as to take most of their supervisors’ or other researchers’ (colleagues, reviewers) feedback into consideration (Carter & Kumar, 2017 ). More widely, knowing how to formulate their research question is not sufficient without being able to step back from their own formulation. Boch ( 2023 ) expresses it as a necessary reflexivity in research writing, which means becoming aware of oneself in research and integrating this experience into the writing in an argumentative and convincing way. Stepping back from their research question also puts forward the need for doctoral students to be clear about the translations and reductions made (Callon, 1984 ), their research strategies (Inouye, 2023 ), or research stances (Hazard et al., 2020 ).
This learning challenge includes three training objectives (Fig. 3 ), two of them concerning the doctoral student and the third one concerning the students and their supervisors.
Training objectives for the challenge: “to know how to express their research question throughout the research process”
Doctoral students must clearly lay out the research stakes (both academic and for society) throughout their thesis process (TO8). In course B, we give learners a framework to think about and discuss research question development as a combination of three main ingredients (operational and scientific stakes, research question, strategy), requiring that students make the difference between the scientific stakes and the thesis objective clear, while defining the scope of the thesis within broader issues (European project, lab project). In course A, the conceptual framework of the translation from Callon is useful to recognize the driving forces of the reductions and translations in order to identify them and their consequences on the formulation of the research question. It helps clarify their research practices and understand how they contribute to the development of the research strategy, beyond what has been done so far. In course A, we use a trajectory to identify the consistency and the sense of the various research practices of the 3 rd year PhD students. In course B, the “research strategy,” viewed both as a “realized” and “planned” one (Mintzberg, 1987 ), is useful as both a hindsight (what have been my choices so far?) and planning tool (how to reach my research objective as I can express it today?), allowing students to put the weight of their thesis schedule into perspective.
In order to progress in their reflection, the doctoral students need to understand the importance of different oral and written (scientific or not) communications for making the formulation of their research question evolve (TO9). In course A, when designing the trajectory of the 3 rd year PhD students, we question them about their scientific communications or articles and about the consequences they had on the evolution of the formulation of their research question. We also ask them about the impact of the different feedback they had at the time of these communications and articles (from peers, from supervisors and other researchers, and from stakeholders) on the development of their research question. In course B, there are three exercises focused on the research question. While being considered as difficult, these exercises are also seen by trainees as effective for training themselves in expressing (orally and then on a written basis) their own subject and receiving feedback and questions from other students and their supervisors. We can observe that research questions and soundness of argumentation deeply evolve throughout the week, to the great satisfaction of students and their supervisors.
Doctoral students, as well as their supervisors for the research carried out under their responsibility, have to understand and explain the consequences of research question choices on the ways knowledge produced in the thesis could be used in the real world (TO10). In course A, we use a heuristic tool to help PhD students to understand the relevance for action of the knowledge they generate (Hazard et al., 2020 ).
Learning how to build a research question is traditionally seen as a one-to-one learning process based on informal and daily transmission between a novice and a senior researcher. In order to open up this informal process, we have grounded our pedagogical strategy in multiple opportunities for dialog with peers, whether it be other students, supervisors, or trainers. Taken as a whole, it thus combines interdisciplinarity, peer-learning, and dialogical principles that result in the construction of an “overall distributed scaffolding strategy” (Belland, 2014 ) and that create synergy between peer scaffolding, one-to-one and media scaffolding (Belland, 2014 ).
Firstly, our case studies emphasize speaking and argumentation skills rather than writing competencies. Many research works like Zuber-Skerritt and Knight ( 1986 ), Maher et al. ( 2013 ), Kumar and Aitchison ( 2018 ), and Badenhorst ( 2021 ) have explored the needs and modalities of doctoral education in terms of writing, even from the supervisor’s perspective (González-Ocampo & Castelló, 2018 ). Our pedagogical choice contrasts with this focus on doctoral writing since we give trainees many dialogical opportunities to train themselves to orally express and defend their intellectual autonomy. Doing so, we join Cahusac de Caux et al. ( 2017 ) who argue, “peer feedback and discussion benefits students by helping them verbalise their internal reflective thinking, fostering reflective practice skills development”. Even if we use some media-based scaffoldings, tools are not at the core of our case studies: our objective is instead to help trainees to put their thoughts into words, in line with the cognitive apprenticeship of Austin ( 2009 ), referring to a specific kind of apprenticeship for the less easily observed processes of thinking.
Secondly, our training programs make the most of the diversity and heterogeneity of peers, whether they be more or less experienced in supervision, from various disciplines, or at different stages of their thesis, thus enriching peer-learning scaffolding. All the participants, in their capacity as scientists, are considered as peers who are able to understand the work of other researchers, regardless of the discipline and the thesis subject. It is also by striving to understand and question subjects that are sometimes far from their field of research that researchers acquire the capacity for analysis, synthesis, and hindsight that is necessary in research work. By setting up dialogical spaces to help inexperienced researchers hone their argumentation skills, our training programs implement our view of research in practical terms as a collective process and of doctoral education as a professional socialization process, thus requiring that research organizations facilitate collective practices in the workplace (Malfroy, 2005 ). Moreover, with the inherent heterogeneity of participants, these workshops also constitute places where the multidisciplinarity and plurality of the sciences are experienced firsthand, convergent with Manathunga et al. ( 2006 ) or Bosque-Perez et al. ( 2016 ). Doing so, we are taking part in the debate of whether scaffolds need to contain domain-specific knowledge (Belland, 2014 ) by saying that there is no need for discipline or domain-specific scaffolds. Moreover, being active on one’s own case as well as on others’ situations is an efficient training strategy to move away from the objects and routines of a discipline or community when expressing ideas between specialists. Such collective reflexivity, sometimes turning into an analysis of professional practices, is a classic vocational training principle known to enhance the development of professionalization in the long term. What we add in our training sessions is the heterogeneity of participants, which is a resource for reflexivity, but that has to be carefully managed.
Thirdly, trainees are considered as human subjects engaged in their PhD with their various motivations and professional projects, which can strongly impact the way they see their thesis and envision their research work (Skakni, 2018 ), as well as their affinities and values, their doubts, and fears. Thanks to our focus on oral exchanges, we are then able to reveal and deal with these subjective dimensions of PhD work, which are often hidden when training PhD students in scientific writing. More precisely, expressing one’s doctoral experience and professional situations experienced is known as an efficient scaffolding practice within the collaborative reflective writing of “learning journals” with peer feedback (Boldrini & Cattaneo, 2014 ). We have shown how to implement such scaffolding in small groups of doctoral students with the facilitation of experienced researchers.
However, our proposal requires that some binding conditions be met:
Learning to formulate a research question through dialog with peers requires spending time, in our case, 4 full days, within small groups to ensure that everyone can take part in it and take advantage of the feedback of others.
This dialog is made possible and emphasized by the diversity of participants (either in terms of discipline, stage of the thesis, experience, etc.).
Managing both the human and scientific conditions of this dialog requires reflexive and open-minded trainers that adopt a facilitating stance.
As a result, our perspective on scaffolding is not merely an issue of training technique but, on the contrary, a situated perspective that echoes the view of Nielsen ( 2008 ) on training “both as part of a social practice and as part of the learner’s trajectory of participation”, within an expansive process inspired by Engeström’s work. With this developmental view on doctoral experience, we acknowledge that research question development is a process that goes beyond the limited time of a 4-day training program. Trainee feedback collected after their participation in course A or B revealed that they continue the work begun during the training programs, on the basis of the given scaffolding (e.g., “I feel that we familiarized ourselves with these tools [referring to the concepts of translation and reduction] because we work on them and I started to think. […] I know these tools will remain in my head until I write my thesis and that I really learned a lot” Hot debrief, course A, 2016). It is also not rare that trainees mention their participation in course A or B to their PhD steering committees as having helped to frame/define their research question. Course A or B is also frequently mentioned as an essential support in acknowledgement of their PhD thesis. Although limited in time, the training programs studied in this article act as an accelerator in research question development (e.g. course B “we saved several months”, supervisor, 2017, “In just 2 days, everything became much clearer and more focused”, student, 2021). We thus assume that they contribute to awareness and reflexivity on research activity and to the professional development of trainees, which is particularly crucial in France with the pressure put on thesis duration and the absence of formal recognition of the research proposal stage.
Our experience puts forward two avenues for future research. Firstly, bringing together doctoral students at different stages of their thesis and then offering them the opportunity to participate each year of their PhD process opens a window on to their intellectual trajectory and a situated adjustment of our scaffolding practices. Secondly, training doctoral supervisors—and trainers involved in these doctoral programs—remains of utmost importance to make scaffolding last and be adapted throughout the next months and years.
This study examined the learning challenges and objectives required for the task of research question development throughout the PhD process, both for doctoral students and their supervisors. We have drawn some lessons for the scaffolding of these challenges and objectives from two different doctoral training programs that we have been designing and leading for more than 10 years.
Considering the development of a research question as a dialogical process, we suggest three conditions to scaffold these learnings: firstly, offering many dialogical opportunities is an effective way for students to train themselves to express their intellectual autonomy and to defend their research project; secondly, making the most of the diversity and heterogeneity of peers, whether they be more or less experienced in supervision, from various disciplines, or at different stages of their thesis, thus enriching peer-learning scaffolding, proved to be beneficial when the multidisciplinarity and plurality of the sciences are experienced firsthand; and finally, giving priority to oral communication allows trainers and trainees to reveal and deal with the subjective dimensions of PhD work and their various motivations and professional projects that always underlie the development of a research question. Taken as a whole, our work seriously rises to the challenge of training reflexive researchers with an acute awareness of the collective nature of research and an intellectual openness to the plurality of sciences.
INRAE, the French public research institute devoted to the development of agriculture, food and the environment ( https://www.inrae.fr/en ), continuously hosts some 2000 PhD students.
For example, in the UK, writing and defending a research proposal allows a Transfer of Status from an initial probationary status to that of a full doctoral candidate (Inouye, 2020 ), whereas in France, there is no such formal assessment.
The ACT research division of INRAE aims at understanding and supporting transformative changes in socio-ecosystems and agrifood systems, which take actors’ practices and strategies into account in order to promote sustainable innovations and transitions, particularly at the territorial level.
As Uri Alon puts it in his TED video: “Why science demands a leap into the unknown” https://www.ted.com/talks/uri_alon_why_science_demands_a_leap_into_the_unknown .
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Girard, N., Cardona, A. & Fiorelli, C. Learning how to develop a research question throughout the PhD process: training challenges, objectives, and scaffolds drawn from doctoral programs for students and their supervisors. High Educ (2024). https://doi.org/10.1007/s10734-024-01258-2
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Toddlers engage more regions of their brains around 16-months to help them develop important cognitive skills, enabling them to follow simple instructions and control impulses. Findings from the study, led by the Universities of Bristol and Oxford, and published in Imaging Neuroscience , suggests 16 months is a critical period for brain development.
A child's first two years of life are crucial for developing cognitive skills , particularly executive functions that help adjust thoughts, actions, and behaviors for everyday life.
Inhibitory control is one important executive function. This particular skill allows individuals to stop themselves from doing something out of impulse, habit or temptation. It's already known that inhibitory control begins to develop in infancy and grows into early childhood . However, until now, the brain mechanisms involved in its development were unclear.
Researchers at the Oxford University Baby Lab and Bristol University Baby Lab sought to examine the brain activity of 16-month-old toddlers by using a child-friendly brain imaging technique called functional near-infrared spectroscopy (fNIRS). They gave 103 toddlers a simple touchscreen task to complete that would require them to use inhibitory control skills.
This experiment allowed researchers to see which brain areas were activated when inhibitory control skills were used. The study replicated a previous experiment with the same group of children when they were 10 months old.
The earlier study found that 10-month-olds used the right side of their prefrontal and parietal cortex for inhibitory control. In this latest study, the team show that by 16 months, toddlers use the left parietal cortex and both sides of the prefrontal cortex more extensively.
Interestingly, these brain changes occur despite how well children performed in the task staying the same between 10 and 16 months. Testing the same group of children at 10- and 16-months of age, the team found, as babies grow into toddlers, they continue to struggle to stop themselves from doing a habitual action, but the brain activation associated with this skill changes dramatically. This indicates that 16-month-old toddlers are using more areas of the brain than at 10 months even if their observable skills remained the same.
The results reveal that 16 months is a critical period for brain development , enabling toddlers to follow simple instructions and control impulses.
The study was led by Abigail Fiske, postdoctoral researcher at the University of Oxford, and Karla Holmboe, Associate Professor in Developmental Science at the University of Bristol's School of Psychological Science.
They said, "These results are exciting because they shed new light on substantial changes in the brain across the transition from infancy to toddlerhood, despite there being no improvement in inhibitory control skills over this period.
"Our findings contribute new knowledge about the role of brain areas in early development and could help future research piece together a picture of how an important cognitive skill ( inhibitory control ), and the brain areas involved, develop from infancy to adulthood."
Fiske and Holmboe added, "What are the implications for parents and caregivers? It's often noticed that toddlers frequently struggle to stop themselves from doing something. In our study we have shown that lots of changes are happening in toddlers' brains, and we think that these changes support them in learning this important new skill."
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Published on November 11, 2022 by Shona McCombes and Tegan George. Revised on November 20, 2023.
Choosing your dissertation topic is the first step in making sure your research goes as smoothly as possible. When choosing a topic, it’s important to consider:
You can follow these steps to begin narrowing down your ideas.
Step 1: check the requirements, step 2: choose a broad field of research, step 3: look for books and articles, step 4: find a niche, step 5: consider the type of research, step 6: determine the relevance, step 7: make sure it’s plausible, step 8: get your topic approved, other interesting articles, frequently asked questions about dissertation topics.
The very first step is to check your program’s requirements. This determines the scope of what it is possible for you to research.
Some programs have stricter requirements than others. You might be given nothing more than a word count and a deadline, or you might have a restricted list of topics and approaches to choose from. If in doubt about what is expected of you, always ask your supervisor or department coordinator.
Start by thinking about your areas of interest within the subject you’re studying. Examples of broad ideas include:
To get a more specific sense of the current state of research on your potential topic, skim through a few recent issues of the top journals in your field. Be sure to check out their most-cited articles in particular. For inspiration, you can also search Google Scholar , subject-specific databases , and your university library’s resources.
As you read, note down any specific ideas that interest you and make a shortlist of possible topics. If you’ve written other papers, such as a 3rd-year paper or a conference paper, consider how those topics can be broadened into a dissertation.
After doing some initial reading, it’s time to start narrowing down options for your potential topic. This can be a gradual process, and should get more and more specific as you go. For example, from the ideas above, you might narrow it down like this:
All of these topics are still broad enough that you’ll find a huge amount of books and articles about them. Try to find a specific niche where you can make your mark, such as: something not many people have researched yet, a question that’s still being debated, or a very current practical issue.
At this stage, make sure you have a few backup ideas — there’s still time to change your focus. If your topic doesn’t make it through the next few steps, you can try a different one. Later, you will narrow your focus down even more in your problem statement and research questions .
There are many different types of research , so at this stage, it’s a good idea to start thinking about what kind of approach you’ll take to your topic. Will you mainly focus on:
Many dissertations will combine more than one of these. Sometimes the type of research is obvious: if your topic is post-war Irish poetry, you will probably mainly be interpreting poems. But in other cases, there are several possible approaches. If your topic is reproductive rights in South America, you could analyze public policy documents and media coverage, or you could gather original data through interviews and surveys .
You don’t have to finalize your research design and methods yet, but the type of research will influence which aspects of the topic it’s possible to address, so it’s wise to consider this as you narrow down your ideas.
It’s important that your topic is interesting to you, but you’ll also have to make sure it’s academically, socially or practically relevant to your field.
The easiest way to make sure your research is relevant is to choose a topic that is clearly connected to current issues or debates, either in society at large or in your academic discipline. The relevance must be clearly stated when you define your research problem .
Before you make a final decision on your topic, consider again the length of your dissertation, the timeframe in which you have to complete it, and the practicalities of conducting the research.
Will you have enough time to read all the most important academic literature on this topic? If there’s too much information to tackle, consider narrowing your focus even more.
Will you be able to find enough sources or gather enough data to fulfil the requirements of the dissertation? If you think you might struggle to find information, consider broadening or shifting your focus.
Do you have to go to a specific location to gather data on the topic? Make sure that you have enough funding and practical access.
Last but not least, will the topic hold your interest for the length of the research process? To stay motivated, it’s important to choose something you’re enthusiastic about!
Most programmes will require you to submit a brief description of your topic, called a research prospectus or proposal .
Remember, if you discover that your topic is not as strong as you thought it was, it’s usually acceptable to change your mind and switch focus early in the dissertation process. Just make sure you have enough time to start on a new topic, and always check with your supervisor or department.
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
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:
All research questions should be:
You can assess information and arguments critically by asking certain questions about the source. You can use the CRAAP test , focusing on the currency , relevance , authority , accuracy , and purpose of a source of information.
Ask questions such as:
A dissertation prospectus or proposal describes what or who you plan to research for your dissertation. It delves into why, when, where, and how you will do your research, as well as helps you choose a type of research to pursue. You should also determine whether you plan to pursue qualitative or quantitative methods and what your research design will look like.
It should outline all of the decisions you have taken about your project, from your dissertation topic to your hypotheses and research objectives , ready to be approved by your supervisor or committee.
Note that some departments require a defense component, where you present your prospectus to your committee orally.
The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.
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Post graduate master’s degree qualifications are increasingly required to advance allied health profession careers in education, clinical practice, leadership, and research. Successful awards are dependent on completion of a research dissertation project. Despite the high volume of experience gained and research undertaken at this level, the benefits and impact are not well understood. Our study aimed to evaluate the perceived impact and legacy of master’s degree training and research on allied health profession practice and research activity.
A cross-sectional online survey design was used to collect data from allied health professionals working in the United Kingdom who had completed a postgraduate master’s degree. Participants were recruited voluntarily using social media and clinical interest group advertisement. Data was collected between October and December 2022 and was analysed using descriptive statistics and narrative content analysis. Informed consent was gained, and the study was approved by the university research ethics committee.
Eighty-four responses were received from nine allied health professions with paramedics and physiotherapists forming the majority (57%) of respondents. Primary motivation for completion of the master’s degree was for clinical career progression ( n = 44, 52.4%) and formation of the research dissertation question was predominantly sourced from individual ideas ( n = 58, 69%). Formal research output was low with 27.4% ( n = 23) of projects published in peer reviewed journal and a third of projects reporting no output or dissemination at all. Perceived impact was rated highest in individual learning outcomes, such as improving confidence and capability in clinical practice and research skills. Ongoing research engagement and activity was high with over two thirds ( n = 57, 67.9%) involved in formal research projects.
The focus of master's degree level research was largely self-generated with the highest perceived impact on individual outcomes rather than broader clinical service and organisation influence. Formal output from master’s research was low, but ongoing research engagement and activity was high suggesting master’s degree training is an under-recognised source for AHP research capacity building. Future research should investigate the potential benefits of better coordinated and prioritised research at master’s degree level on professional and organisational impact.
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Higher levels of research engagement by healthcare organisations and clinicians are associated with improved organisational performance and clinical outcomes [ 1 , 2 , 3 ]. The Allied Health Professions (AHPs) comprise one third of the health and social care workforce in the United Kingdom and when engaged in research, offer substantial benefit to population health and organisational performance [ 4 ]. The strategic focus on AHP research has grown substantially in recent years. This includes the first ever national research and innovation strategy for AHPs in England, as well as clear strategic intention through AHP clinical research networks hosted by the National Institute for Health Research [ 5 , 6 ]. These strategies reinforce the need for capacity building, engagement, and cultural improvements for advancing AHP research. Realising these ambitions has, to date, been limited by insufficient funding, career infrastructure, and organisational support [ 7 ].
Alongside the strategic ambitions for AHP research, is the increasing requirement for post-graduate master’s degree qualifications for career progression in academic, leadership and clinically advanced AHP roles. For example, 69% of Advanced Clinical Practitioners (ACP’s) state the requirement for master’s degree qualification for their current ACP role [ 8 ].
With few exceptions, a master’s degree award is dependent on the successful completion of a supervised research dissertation project. This is usually accompanied by taught research methodology to support the development of research knowledge and skills. Master’s degree research ideas are conceived in a variety of ways, either as stand-alone projects, supplied by a university academic as one part of a larger programme of work, or developed in collaboration with a health service [ 9 ]. AHP research projects developed collaboratively between health and academic centres are more likely to be widely disseminated, impactful on clinical practice, and lead to further research compared to projects undertaken exclusively within a university setting [ 10 ].
Despite the high cumulation of training and research at this level over the years, the broader impact on clinical services, employing organisations, and the wider research community is currently unknown [ 11 ]. Beyond the fulfilment of individual learning objectives, it is difficult to determine what real-world impact AHP master’s research offers in terms of original knowledge contribution. Similarly, the rate of conversion of AHP master’s degree research to peer reviewed publications or conference proceedings remains unexplored [ 12 ]. This situation risks a low return on investment in terms of the generation and translation of knowledge to address the challenges faced by AHPs in healthcare practice [ 13 ]. Responsible practice in AHP post graduate training and research should, in part, be concerned with reducing waste that arises from decisions about what research to prioritise, as well as educational benefit to the individuals [ 14 ]. Aligning and coordinating more AHP master's degree research activity through collaboration may prevent AHP dissertations entering the “relevance waste quadrant” [ 15 ]. Models of portfolio research, which are coordinated efforts to address the highest priority knowledge gaps through research collaborations, represent an alternative approach to the current system [ 16 ].
The primary aim of our study is to evaluate the perceived impact and sustained effect of master’s degree research dissertation projects on AHP research capacity, capability, and clinical practice. In doing this, we have set out five supporting objectives:
To understand how master’s degree research dissertation questions were determined.
To establish the rate of conversion of master’s degree research to traditional measures of research output and dissemination.
To establish whether successful completion of master’s degree research promotes the maturation of ongoing research active clinicians.
To determine the perceived impact of research skills developed through master’s degree completion on AHP research capacity building within individuals and organisations.
To determine the perceived impact of master’s degree research on clinical practice and services.
An online cross-sectional survey design was chosen as the method to conduct this study, and it is being reported according to the consensus-based checklist for reporting of survey studies [ 17 ]. A bespoke survey was constructed using Microsoft Forms software and was hosted online via Microsoft Office 365. The survey comprised 27 questions arranged into sections to collect data on participant demographics, and the experience, outcomes, and perceived impact of master’s degree training and completion of a research dissertation project (see additional file 2 in supplementary information). To develop the survey, a pilot survey was undertaken using four qualified AHP volunteers to appraise the structure, content, and readability of the questions. Feedback from the pilot was used to revise and finalise the survey.
The target population were AHPs, which is an umbrella term for fourteen different professions usually employed in a variety of roles across health, care, academic, and voluntary sectors ( https://www.england.nhs.uk/ahp/role/ ). Participants were eligible to take part if they were 1) qualified AHPs currently working in the United Kingdom (UK), 2) held a post graduate master’s degree award, and 3) were able to provide informed consent. Participants were ineligible if their master’s degree was obtained as a pre-registration qualification, and they did not meet the other inclusion criteria. A target sample size of 139 was calculated by estimating the proportion of all registered AHPs in the UK holding a master’s degree qualification. This estimation was determined by profiling the qualifications of AHP staff in two large National Health Service (NHS) teaching hospitals. To account for a sampling calculation error, a confidence interval (95%) and margin of error (5%) threshold were applied accordingly (see additional file 3 in supplementary information).
Participant recruitment was achieved through advertising on social media platforms, and via newsletters and bulletins circulated by AHP professional and clinical interest groups. Participant information was provided outlining the study details, anonymity of survey responses, and the requirement to provide informed consent and eligibility at the start of the online survey. Those taking part were asked to reflect on their experiences of completing a post graduate master’s degree and research dissertation project in relation to its impact and legacy. The ‘one response per participant’ feature was enabled to prevented multiple completion of the survey by the same participant. The survey was live for data collection for three months running from October to the end of December 2022. During data collection, several efforts were made to promote the survey through social media to increase participation.
The survey data was analysed in two ways. First, descriptive statistics were used to analyse numerical, multiple choice, and ordinal scale data. Second, free text responses providing reflective accounts and experiences underwent coding and content analysis using NVivo software (version 12).
This study was approved by the university research ethics committee (registration number: 221613) and was conducted in accordance with the principles of good clinical practice.
The survey received 84 responses from nine of the fourteen allied health professions, which represents 60% of the target sample of 139. The majority of responses were from physiotherapists ( n = 40, 47.6%) and respondents had been qualified for a median (IQR) of 18 years (12–23). Respondents worked in a variety of clinical specialties, with emergency/pre-hospital medicine ( n = 18, 21.4%), neurology ( n = 12, 14.3%) and critical care ( n = 11, 13.1%) the most common. Most respondents had completed their master’s degree after 2010 ( n = 68, 81%) and were employed at band 6 grade when starting ( n = 39, 46.4%). Most respondents worked in the NHS ( n = 78, 92.3%) and had undertaken a Master of Science (MSc) award ( n = 70, 83.3%). Most participants were employed in a higher paid position after completing their master's degree ( n = 62, 73.8%). The full characteristics of the respondents are detailed in Table 1 .
Respondents predominantly formed their dissertation research questions from their own area of interest (Table 2 ). Less than 10% of the dissertation questions were based on published research priorities or set by the Higher Education Institute (HEI), regional or local healthcare organisation/collaborative ( n = 7, 8.3%). A variety of methodologies were used to conduct the master’s research dissertation with evidence synthesis being the most common ( n = 30, 35.7%).
Formal research output from the dissertations was low (Table 2 ). Half the dissertations were presented at a local research symposium ( n = 44, 52.4%), 27.4% ( n = 23) were published in a peer reviewed journal, and over a third of dissertations had no output at all ( n = 30, 35.7%). Master’s degree programmes contributing to the peer reviewed publications as a proportion of students were Master by Research (MRes) ( n = 5, 45.5%), and MSc ( n = 18, 25.7%).
Of the dissertations formed through the individual's own ideas, 27.6% ( n = 16) were published in a peer reviewed journal, compared to 57.1% ( n = 4) of those set through research priorities, or the HEI/healthcare organisation. The most common methodologies published in a peer review journal were evidence synthesis ( n = 7, 30.4%), qualitative interviews/focus groups ( n = 6, 26.1%) and quantitative experimental studies ( n = 6, 26.1%). The methodology of dissertation projects with the highest proportion of peer reviewed journal publication was qualitative interviews/focus groups ( n = 7, 36.8%).
The respondents reported their master's degree dissertation as having a positive impact on their professional development (Fig. 1 ). Qualitative content analysis of the free text responses demonstrated that respondents felt the dissertation increased their research capability and confidence at multiple stages of the research process while providing opportunities for networking and collaborations.
Perceived impact of master’s degree research on professional and clinical service development
Most participants continued to engage in research activities after their dissertation ( n = 65, 77.4%) through supporting others ( n = 63, 75%), taking part in formal research projects ( n = 57, 67.9%) and publishing research papers ( n = 41, 48.8%) (Table 3 ). Less than ten percent (9.5%, n = 8) reported being deterred from undertaking further research (Fig. 1 ).
The wider perceived impact of the dissertation on services in which the respondents worked was more varied (Fig. 1 ). Improved service user outcome/experience and team practice was reported by 60.7% ( n = 51) and 53.6% ( n = 45) respectively. Analysis of free text responses demonstrated wide ranging perceived impact on services from no local impact to improved team education, service delivery and application of evidence-based practice.
Our study evaluated the perceived impact of master's degree level research on AHP professional development, research capacity, and clinical practice. Our findings indicate a relatively low level of dissemination and formal output arising from master’s degree research, but a high perception of impact on individual AHPs and the clinical services in which they work. The level of ongoing engagement in research activity following master’s degree completion was high indicating a positive legacy in this respect. The degree to which this meaningfully contributes to AHP research capacity building requires further investigation.
The majority (69%) of master’s degree research questions were developed from the respondent’s own ideas rather than drawing on published research priorities or collaborations between health and academic organisations. The limited use of research priorities may be explained by a potential lack of awareness. A qualitative study of 95 AHPs working in Australia found that in the absence of a recognised framework to guide research prioritisation, individual clinicians conducted research in areas important to them [ 18 ]. Pursuing individual preferences in this way stemmed from evaluations of their personal work, departmental policies or procedures, models of care innovation, and a clear preference for research which “tested solutions”. Similarly, Amalkumaran et al. (2016) explored critical care research priorities and found that research topics suggested by professional sub-groups tended to be related to their daily practice rather than broader research priorities [ 19 ].
It is also possible that the choice of research question is influenced by the career motivation of the individual AHP. A UK wide cross-sectional survey of AHPs working in health and social care reported primary motivators for research participation were to develop skills (80%) and increase job satisfaction (63%), rather than contribute to the prioritised evidential knowledge base [ 20 ]. Davis et al. (2019) also recognise this self-actualising motivation for research participation in their AHP cohort [ 18 ]. It is possible that the debut, non-commissioned research activity introduced by master’s level academic programmes emphasises process over content , decreasing the alignment of research activity with known research priorities.
We found a low conversion rate from master’s dissertation completion to formal research output. This is well illustrated in that just one in four (27.4%) master’s theses resulted in a peer-reviewed publication. Similar publication rates have been reported in master’s students of other healthcare disciplines; these are also considered low by way of expected research output [ 21 ]. Understanding this further is challenging due to the limited research in this subject area, which suggests a lack of interest and/or perceived importance. However, there are two key issues that arguably counter this view. First, master’s degree research projects are typically approved by a university research ethics committee, and thus are guided by the principle that the value in their conduct and knowledge contribution should outweigh the burden or risks to participants [ 22 ]. Fidelity to this principle can only be meaningfully appraised if the results are published for wider critical evaluation. Second, AHP skill and success level in research activities, such as writing for peer-reviewed publication is widely and consistently reported as low [ 23 , 24 , 25 ]. This clearly represents an area for improvement for AHPs and failing to challenge the development of this skill in those undertaking post graduate level research seems counter intuitive. Higher rates of master’s degree research publication could offer a meaningful contribution to AHP research capacity building, since our findings suggest there is continued engagement in research activity from this group beyond completion of their studies.
Respondents to our survey indicated a good level of research engagement after master’s degree training. Over three quarters reported continued involvement in research beyond the completion of their programme. This finding supports the idea that research education is a key lever and greatly needed to successfully build AHP research capacity [ 26 , 27 ]. However, the degree to which master’s degree training translates to growth in the research capacity of individuals has not been subject to causal investigation. Proxy indicators of individual research capacity from our cohort can be found in the self-reported high levels of research confidence and capability derived from master’s degree training (Fig. 1 ) and ongoing research activity. This activity included 60% taking part in formal research projects, around half had published research papers, and over a third had embarked on a higher research degree. The lack of previous research in this area makes it challenging to fully contextualise our findings, but in conducting our study, we have set out a benchmark for the perceived impact of masters degree training on individual AHP research capacity for future investigation.
We explored higher level outcomes of master’s degree training on research capacity building, such as those that might influence policy, career pathways, and organisational practice. Using the Kirkpatrick-Barr model of educational outcomes, we found the activity and outcomes from our cohort aligned best to an individual learner level [ 28 ]. This finding is typical of outcomes from education at this level, which centre largely on the individuals through self-reported satisfaction and perceptions of learning [ 29 ]. Understanding the impact of research education and training in relation to higher Kirkpatrick-Barr outcomes requires objective and longitudinal evaluation of research metrics and impact at organisational and system level [ 30 ]. This is likely to include contributions to larger programmes of work requiring large grant awards, significant publications, and translation of those research findings to health organisation and system level innovation [ 31 , 32 ]. Research capacity building at this level is known to be challenging due to the inherent complexities involving political, financial, structural, and cultural factors [ 33 ]. To overcome this, the use of theoretical frameworks has been suggested to help conceptualise and integrate a culture and proliferation of AHP research at various health system structural levels [ 34 ]. The positioning of AHP master’s degree training and research activity as part of this may foster greater academic-health system collaboration for professional, service user, and population benefit [ 35 ].
The perceived impact of master’s degree research included improvements to service user outcomes, clinical pathways, and organisational policies and/or guidelines. Research impact, defined as the demonstrable benefit of research to individuals and society, is complex and requires wide stakeholder engagement to determine whether research has addressed known priorities through effective translation of knowledge from its findings [ 36 ]. The self-generated research questions and low level of dissemination and output reported by our cohort suggests a degree of dissonance between the level of perceived impact versus what is measurably impactful to clinical services and end users. This difference may be explained by the challenges in defining and quantifying research impact for novice researchers, which is described as an ambiguous and subjective concept [ 37 ]. It is therefore not surprising to see the highest levels of reported impact from our cohort was on their own professional development in terms of improved confidence, leadership and research capability, and clinical practice development. Without a more objective assessment of the wider impact from the research undertaken at this level, it is difficult to reconcile its actual impact. The emergence of assessment frameworks, such as the visible impact of research tool, make it accessible for relatively inexperienced researchers to understand how their research has led to visible changes and impact on services and other research consumers [ 38 ].
A key strength of our study lies in its novelty; we believe it to be the first to evaluate the perceived impact of research undertaken by AHPs at master’s degree level. This represents an important first step in highlighting the conduct and contribution of research undertaken at this level, as well providing opportunities to improve future practice and impact. There are several limitations to our study. We only managed to recruit 60% of our target sample via a non-probability sampling technique, which included a lack of representation from five of the 14 professions. This means our findings are vulnerable to sampling bias by potentially excluding AHPs who do not use social media or subscribe to clinical interest groups, which were the two main platforms for our recruitment. Our recruitment practice and the method of a self-reporting survey means our findings are not generalisable to the wider AHP population and they should be interpreted with these limitations in mind. A further limitation is the disproportionate representation of two of the fourteen allied health professions. Responses from paramedics and physiotherapists constituted 57% of our data with very few responses from seven other professions and no responses from five of the professions.
The perceived impact of AHP master’s degree training and research was highest on individual development rather than service and organisation outcomes. This is likely to derive from the individual motivation in undertaking post-graduate study and self-determined research dissertation focus. Whilst the formal research output arising from the master’s research was relatively low, the legacy in terms of ongoing research engagement and activity was positive indicating that master’s degree completion maybe an under-recognised source of AHP research capacity building. Our study provides novel insights into the perceived impact of AHP master’s degree level research. Future research should explore the feasibility and benefits of coordinating AHP master’s degree research with local or national priorities to understand the impact beyond that realised at an individual level.
All data generated or analysed during this study are included in this published article [and its supplementary information files].
Allied Health Professions
Advanced Clinical Practitioner
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Qualitative data analysis software
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Higher Education Institute
Masters by Research
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The authors would like to thank all the allied health professionals who gave their time to participate in this survey.
Dr Owen Gustafson, Clinical Doctoral Research Fellow (NIHR301569), is funded by Health Education England (HEE)/National Institute for Health Research (NIHR). The views expressed in this publication are those of the authors and not necessarily those of the NIHR, NHS or the UK Department of Health and Social Care.
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All authors conceived and designed the study. All authors designed the survey content and structure. TC prepared the online survey. All authors promoted recruitment to the survey. EK and OG undertook data analysis and interpretation. TC prepared Fig. 1 . OG prepared Tables 1 , 2 and 3 . AT wrote the background and part of the discussion. TC wrote the abstract, methods, part of the discussion, and conclusion. EK and OG wrote the results. All authors reviewed the manuscript and consented to publication.
Correspondence to Terry Cordrey .
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The study was approved by Oxford Brookes University research ethics committee and assigned registration number: 221613. This study was conducted according to the relevant guidelines and regulations of the Declaration of Helsinki. Survey respondents were required to read the participant information sheet and provide informed consent prior to taking part.
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When it comes to artificial intelligence, appearances can be deceiving. The mystery surrounding the inner workings of large language models (LLMs) stems from their vast size, complex training methods, hard-to-predict behaviors, and elusive interpretability.
MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers recently peered into the proverbial magnifying glass to examine how LLMs fare with variations of different tasks, revealing intriguing insights into the interplay between memorization and reasoning skills. It turns out that their reasoning abilities are often overestimated.
The study compared “default tasks,” the common tasks a model is trained and tested on, with “counterfactual scenarios,” hypothetical situations deviating from default conditions — which models like GPT-4 and Claude can usually be expected to cope with. The researchers developed some tests outside the models’ comfort zones by tweaking existing tasks instead of creating entirely new ones. They used a variety of datasets and benchmarks specifically tailored to different aspects of the models' capabilities for things like arithmetic, chess, evaluating code, answering logical questions, etc.
When users interact with language models, any arithmetic is usually in base-10, the familiar number base to the models. But observing that they do well on base-10 could give us a false impression of them having strong competency in addition. Logically, if they truly possess good addition skills, you’d expect reliably high performance across all number bases, similar to calculators or computers. Indeed, the research showed that these models are not as robust as many initially think. Their high performance is limited to common task variants and suffer from consistent and severe performance drop in the unfamiliar counterfactual scenarios, indicating a lack of generalizable addition ability. The pattern held true for many other tasks like musical chord fingering, spatial reasoning, and even chess problems where the starting positions of pieces were slightly altered. While human players are expected to still be able to determine the legality of moves in altered scenarios (given enough time), the models struggled and couldn’t perform better than random guessing, meaning they have limited ability to generalize to unfamiliar situations. And much of their performance on the standard tasks is likely not due to general task abilities, but overfitting to, or directly memorizing from, what they have seen in their training data. “We’ve uncovered a fascinating aspect of large language models: they excel in familiar scenarios, almost like a well-worn path, but struggle when the terrain gets unfamiliar. This insight is crucial as we strive to enhance these models’ adaptability and broaden their application horizons,” says Zhaofeng Wu, an MIT PhD student in electrical engineering and computer science, CSAIL affiliate, and the lead author on a new paper about the research. “As AI is becoming increasingly ubiquitous in our society, it must reliably handle diverse scenarios, whether familiar or not. We hope these insights will one day inform the design of future LLMs with improved robustness.” Despite the insights gained, there are, of course, limitations. The study’s focus on specific tasks and settings didn’t capture the full range of challenges the models could potentially encounter in real-world applications, signaling the need for more diverse testing environments. Future work could involve expanding the range of tasks and counterfactual conditions to uncover more potential weaknesses. This could mean looking at more complex and less common scenarios. The team also wants to improve interpretability by creating methods to better comprehend the rationale behind the models’ decision-making processes. “As language models scale up, understanding their training data becomes increasingly challenging even for open models, let alone proprietary ones,” says Hao Peng, assistant professor at the University of Illinois at Urbana-Champaign. “The community remains puzzled about whether these models genuinely generalize to unseen tasks, or seemingly succeed by memorizing the training data. This paper makes important strides in addressing this question. It constructs a suite of carefully designed counterfactual evaluations, providing fresh insights into the capabilities of state-of-the-art LLMs. It reveals that their ability to solve unseen tasks is perhaps far more limited than anticipated by many. It has the potential to inspire future research towards identifying the failure modes of today’s models and developing better ones.” Additional authors include Najoung Kim, who is a Boston University assistant professor and Google visiting researcher, and seven CSAIL affiliates: MIT electrical engineering and computer science (EECS) PhD students Linlu Qiu, Alexis Ross, Ekin Akyürek SM ’21, and Boyuan Chen; former postdoc and Apple AI/ML researcher Bailin Wang; and EECS assistant professors Jacob Andreas and Yoon Kim.
The team’s study was supported, in part, by the MIT–IBM Watson AI Lab, the MIT Quest for Intelligence, and the National Science Foundation. The team presented the work at the North American Chapter of the Association for Computational Linguistics (NAACL) last month.
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Cats scratching furniture may not be inevitable. Getty Images hide caption
Even the biggest cat lover has to admit feeling a little helpless when their pet just won't stop scratching the furniture.
Fortunately, there may be a science-backed way to prevent our feline friends from shredding our couches and rugs. Yasemin Salgirli Demirbas, a professor of veterinary physiology at the University of Prince Edward Island co-wrote a research paper on why cats scratch. It’s not because they’re out to get you.
Scratching “is not a behavior that’s displayed to punish the owners,” Demirbas said in a Morning Edition interview with hosts Sacha Pfeiffer and A Martinez.
She says the research team found a relationship between scratching and environmental factors like loud noises or kids. This highlights the importance of shielding your cat from these stressors when crafting a plan to solve your cat’s furniture-scratching habit.
Still, cats are divas, says Mikel Delgado, a certified animal behaviorist and cat behavior consultant from Sacramento, California, so giving them an outlet for damage-free scratching like several scratching posts can be helpful.
“You need to have more than one scratching post, and you want to put them in locations that your cat is likely to use them,” said Delgado. “That might mean right next to your couch if the couch is a place that your cat really enjoys scratching.”
Demirbas and Delgado detailed these additional steps cat owners can take to keep their favorite feline from scratching up the furniture.
You could build these spaces in your home by making a pillow cave, or getting a cat bed or crate. These escapes could help your cat calm down, and reduce its desire to scratch. Demirbas said the research team saw a decrease in scratching when her team “designed an environment for our cats.”
The murderous creature you live with is a murderous creature, a study confirms, use positive reinforcement.
It’s easy to get frustrated if your cat is resistant to this training. Delgado notes it is easy to do more harm than good if you take that frustration out on the cat. She still recommends nudging them towards alternative outlets, which she says is “much more effective than yelling at your cat, or trying to chase them away from the couch, or squirting them with water - all methods I do not recommend.”
Monitor the way you play.
Your behavior could also contribute to the cat’s stress. If your cat doesn’t get to catch its prey when playing, that pent-up energy can get released later on through scratching. Demirbas discussed one example: “if you let them play with laser toys, you will see that they keep chasing this dot, but at the end they get nothing.” The cats don’t like this, she says, it made one cat frustrated: “he felt like he’s an unsuccessful hunter.”
The audio version of this story was produced by Christopher Thomas. The digital was edited by Treye Green.
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Craft a convincing dissertation or thesis research proposal. Write a clear, compelling introduction chapter. Undertake a thorough review of the existing research and write up a literature review. Undertake your own research. Present and interpret your findings. Draw a conclusion and discuss the implications.
Most dissertations run a minimum of 100-200 pages, with some hitting 300 pages or more. When editing your dissertation, break it down chapter by chapter. Go beyond grammar and spelling to make sure you communicate clearly and efficiently. Identify repetitive areas and shore up weaknesses in your argument.
Design a productivity alliance with your colleagues. Dissertation writing can be lonely, but writing with friends, meeting for updates over your beverage of choice, and scheduling non-working social times can help you maintain healthy energy. See our tips on accountability strategies for ideas to support each other.
A dissertation is a long-form piece of academic writing based on original research conducted by you. It is usually submitted as the final step in order to finish a PhD program. Your dissertation is probably the longest piece of writing you've ever completed. It requires solid research, writing, and analysis skills, and it can be intimidating ...
There are many other resources at Oxford that can help support your essay writing skills and if you are short on time, the Oxford Study Skills Centre has produced a number of short (2-minute) videos covering different aspects of essay writing, including: Extended essays and dissertations.
Definition of Dissertation and Thesis. The dissertation or thesis is a scholarly treatise that substantiates a specific point of view as a result of original research that is conducted by students during their graduate study. At Cornell, the thesis is a requirement for the receipt of the M.A. and M.S. degrees and some professional master's ...
Time to recap…. And there you have it - the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows: Title page. Acknowledgments page. Abstract (or executive summary) Table of contents, list of figures and tables.
Checklist: Dissertation 0 / 20. My title page includes all information required by my university.. I have included acknowledgements thanking those who helped me.. My abstract provides a concise summary of the dissertation, giving the reader a clear idea of my key results or arguments.. I have created a table of contents to help the reader navigate my dissertation.
A dissertation or thesis is likely to be the longest and most difficult piece of work a student has ever completed. It can, however, also be a very rewarding piece of work since, unlike essays and other assignments, the student is able to pick a topic of special interest and work on their own initiative. Writing a dissertation requires a range ...
When starting your thesis or dissertation process, one of the first requirements is a research proposal or a prospectus. It describes what or who you want to examine, delving into why, when, where, and how you will do so, stemming from your research question and a relevant topic. The proposal or prospectus stage is crucial for the development ...
The dissertation represents the final piece of academic work in your degree course, designed to synthesize and showcase the knowledge and skills you've developed. It provides a structured opportunity to delve deeply into an academic area of interest, allowing you to conduct original research and contribute new insights to your field.
A thesis is a long-term, large project that involves both research and writing; it is easy to lose focus, motivation, and momentum. Here are suggestions for achieving the result you want in the time you have. The dissertation is probably the largest project you have undertaken, and a lot of the work is self-directed.
301 Recommends: Our Dissertation Planning Essentials workshop will look at the initial stages and challenges of preparing for a large-scale dissertation project.. Our Dissertation Writing workshop will break down the process of writing a dissertation and explore approaches to voice and style to help develop a way of writing academically.. Our Creativity and Research interactive workshop looks ...
5. Keep the Reader in Mind. Always keep the reader in mind when writing your introduction. Consider what they need to know to understand your research and why it is important. Aim to engage and inform your reader, making them interested in your study and eager to read the rest of your dissertation.
Digital Study Skills; Dissertations and Major Projects. Dissertations and Major Projects; Starting Research for your Dissertation; Your Research Question; ... This guide will help you apply your research skills to finding a question, planning, conducting, and communicating your research, and completing your project successfully. ...
A key part of your dissertation or thesis is the methodology. This is not quite the same as 'methods'. The methodology describes the broad philosophical underpinning to your chosen research methods, including whether you are using qualitative or quantitative methods, or a mixture of both, and why. You should be clear about the academic ...
Study skills are the skills you need to enable you to study and learn efficiently - they are an important set of transferable life skills. ... Working on a dissertation, thesis or other research project can be the most challenging part of study. Our guide offers practical advice and explains how to work on each part of a research document ...
Note making for dissertations: First steps into writing Welcome to this guide about how to make notes strategically and effectively for long-form writing projects such as dissertations and theses. Note making (as opposed to note taking) is an active practice of recording relevant parts of reading for your research as well as your reflections ...
Anglia Business School (Cambridge, UK) requires its students to produce a dissertation of maximum 8,000 words, which should demonstrate: Evidence of scholarly research, which can be empirical (i.e. consciously obtained through surveys etc.) or library-based. Evidence of independent thought. Interpretation of evidence - mere description is not ...
Thankfully, your dissertation will give you a whole set of skills and assets that will be attractive to employers. Listed here are just a small selection of the qualities you can develop by doing a dissertation, and how they relate to working in the real world. Research skills. One thing that everyone has to do for their dissertation is research.
For the dissertation, it's not. Writing skills help you to get a good command on the basics, such as grammar, spelling, punctuations, usage of right words and standards of writing. These basics will definitely help you during the dissertation writing. Analytical skills. Analytical skills are vital for completing a dissertation.
With the higher education reform putting forward the professionalization of doctoral students, doctoral education has been strongly focused on generic transferable skills to ensure employability. However, doctoral training should not forget core skills of research and especially the ability to formulate research questions, which are the key to original research and difficult to develop at the ...
Toddlers engage more regions of their brains around 16-months to help them develop important cognitive skills, enabling them to follow simple instructions and control impulses. Findings from the ...
Step 1: Check the requirements. Step 2: Choose a broad field of research. Step 3: Look for books and articles. Step 4: Find a niche. Step 5: Consider the type of research. Step 6: Determine the relevance. Step 7: Make sure it's plausible. Step 8: Get your topic approved. Other interesting articles.
Post graduate master's degree qualifications are increasingly required to advance allied health profession careers in education, clinical practice, leadership, and research. Successful awards are dependent on completion of a research dissertation project. Despite the high volume of experience gained and research undertaken at this level, the benefits and impact are not well understood.
The study compared "default tasks," the common tasks a model is trained and tested on, with "counterfactual scenarios," hypothetical situations deviating from default conditions — which models like GPT-4 and Claude can usually be expected to cope with. ... Logically, if they truly possess good addition skills, you'd expect reliably ...
Learning how to properly study and take notes can overall help improve a student's or parent's experience during the school year. Here are some tips provided by Louisiana State University's Center ...
Exploring Perceptions of Business Owners on Competency-Based Hiring: A Dissertation Study - Kindle edition by Lamar, Gina. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Exploring Perceptions of Business Owners on Competency-Based Hiring: A Dissertation Study.
Lupus is a complex autoimmune disease in which the immune system turns on the body, producing antibodies that attack the skin, joints, kidneys, brain or other organs. In the study, the researchers ...
Even the biggest cat lover has to admit feeling a little helpless when their pet just won't stop scratching the furniture. Fortunately, there may be a science-backed way to prevent our feline ...