“Managing people, and every PI I’ve ever talked to, this is where we have no idea what we’re doing.”
Note. N = 32. The only additional response provided was writing skills, which 12 (38%) PIs mentioned.
The most common responses included management skills (56%). Investigators described needing to manage people in particular, but also projects. Next, investigators highlighted the importance of collaboration skills (44%), including being able to bring together multiple people and work well with diverse individuals. Relatedly, investigators reported needing interpersonal skills (41%)—skills that foster their ability to interact well with people and communicate with them.
A small sub-group of investigators (16%) specifically mentioned leadership skills, or activities related to leadership, such as motivating or inspiring people and creating a caring environment. Overall, investigators utilized “management” more commonly in their terminology to describe their work-related tasks. Notably, just 9% of investigators mentioned “mentoring,” or mentoring activities, such as developing the skills of others, teaching, supporting, or guiding. This is interesting considering that, of the terms used in scientific research, mentoring is more common than management or leadership.
We asked researchers how they learned the skills that they need that are not scientific in nature. As shown in Table 3 , the most common response, provided by 73% of the investigators, was that they learned to navigate management and leadership responsibilities “on-the-job” through “trial-and-error.” Investigators described a process of making mistakes and then trying something new, and they portrayed the learning process as occurring “on the fly,” through “osmosis,” through “trial by fire,” or by “playing it totally by ear.”
Methods for Learning Necessary Skills
Illustrative Quotes | # of times addressed | % of researchers | |
---|---|---|---|
On-the-job, trial- and-error | “When you start your own lab it’s sort of the ultimate on the job training because before that you’re taught how to be a scientist, you’re not taught how to be a lab manager.” “I set up my own lab, and so there were a lot of mistakes made right away, but I think I always look back on myself and reflect on myself and the situations and learn through those mistakes.” “Navigating that is totally by trial and error. I’m not even sure, I’m getting better, I’m probably better now over time, but you know, it needs constant refinement.” | 22 | 73% |
Mentors or other models | “I think I learned by observing my former advisor. I was very lucky to be a student and a post doc with two fantastic mentors.” “Seeing what’s worked in other labs and doing those things, and what hasn’t worked in other labs, and trying not to do those things.” | 12 | 40% |
Graduate or post-doctoral experience | “I trained a grad student before, especially when I was a post-doc, so it’s not a total shock to me.” “I was very fortunate to be in a really large, well-funded lab in my post doc where I was allowed to do a fair amount of mentoring there.” | 10 | 33% |
Natural ability | “I’m a people person; I like to interact with people.” “Some of it, I think, comes from temperament.” | 4 | 13% |
Medical residency | “Being a resident and running resident teams or being a fellow and running a clinical team, kind of helped translate into how do you get everybody to work together towards a common goal.” “For the people aspect of it, the residency actually was really a great training ... it involved a lot of interaction with people.” | 3 | 30% |
Note. N = 30 (2 un-codeable responses).
Several PIs specifically noted the lack of formal training on these issues, and many emphasized the need to learn these skills earlier. Additionally, several described their lack of skills and the slow learning process as “haphazard and hazardous” and “high-stakes.” One described worrying about having detrimental effects on the careers of individuals in the lab stating, “You hope that you don’t ruin someone’s life in the process. It’s pretty high stakes to be learning on-the-job.”
Many of the investigators specifically noted that their graduate or post-doctoral experience did not adequately prepare them; however, 33% reported that their graduate training or post-doctoral experience provided some development in this regard. Another 40% mentioned learning some of these skills from mentors or other models. However, a sub-set of these individuals reported learning practices to avoid by working with poor models. Finally, 30% of the researchers who were also physicians (those with MD/PhD degrees) mentioned that their medical residency assisted in learning skills necessary for interacting well with others.
We asked PIs how well prepared they felt when they started their careers to navigate issues in research that are not scientific in nature or to mentor trainees and manage staff. Most were forthcoming about lacking preparation. Overall, 50% felt that they were inadequately prepared, and 40% described being modestly prepared. Notably, just 10% stated that they were prepared (N = 30, two responses were un-codeable due to unclear answers). Several mentioned that they had been overly confident, and others noted that training for science is different than the skills needed for running a lab. A couple speculated that they might be further ahead in their careers if they had been better prepared. As illustrated in the following quotes, the PIs described the early stages of their careers, in particular, as challenging. One researcher noted, “I would say that’s [management] something that I wasn’t prepared for, it was sort of like jumping into the deep end as far as that goes.” Another described the transition to running a lab as follows, “[It’s] shocking the dramatic transition that occurs, the type of responsibilities and time management from going from post-doc to running a lab ... you go from doing the work to managing the work and redefine what works means.”
We asked the PIs to describe their mentoring practices or management style at this point in their careers. With the exception of a couple “very junior” investigators, most PIs were able to articulate their approach to managing their labs. Overall, the themes included a constructive set of practices (shown in Table 4 ). Although most of the mid-career and senior PIs reported feeling fairly confident in their approach at this stage, some noted the need for continual refinement, feedback, and adjustment. Additionally, a couple noted that they recognized that they may need to change practices such as being rigid about deadlines, too “hands off,” or “micro-managing.”
Mentoring and Management Practices
Illustrative Quotes | # of times addressed | % of researchers | |
---|---|---|---|
Foster open communication | “If something isn’t working out, there’s a communication that occurs; how do we try to fix that?” “I really encourage the people in the lab to speak their mind, I listen to them, I consult with them on many, many things before I make a decision.” | 13 | 41% |
Meet regularly | “Meet with everybody on a regular basis, at least once a week, to have them update me with what’s going on.” “Review everybody’s work at least once a week pretty thoroughly to go through all of the technical details ... usually I talk with them briefly [on a daily basis]” | 12 | 38% |
Personalize approach to each individual | “I take time to get to know people, trying to understand their level of expertise, their strengths ... maybe gaps exist in their training ... I establish a relationship... then try to be attentive to different styles and different individual needs.” “I tend to adapt my management style to individual needs.” | 10 | 31% |
Guide while encouraging independence | “They’re supposed to be learning how to be independent, so I try to encourage that I give advice and they comment, but I try to give them opportunity to really shape their own research.” “I think on one hand, to be really close to my trainees and trying to understand what they are doing, advising them, and at the same time giving them significant freedom in what they are doing from day to day.” | 9 | 28% |
Create positive environment | “I want everyone in this lab to be happy I want to make sure this is an environment I provide. I try very hard to make everybody comfortable and happy.” “Research is never going to be a very smooth process ... people in my lab deal with that very well For my part, you have to have patience ... we always stick together and try to find the solution for the problems.” | 9 | 28% |
Set clear deadlines | “I set pretty firm guidelines in terms of what I expectI don’t tell them how to get them done, I just kind of set the bar.” “We usually discuss what the projects for the week are, and what our goals are for when those projects are complete ... and how to adjust plans if things aren’t going according to the plan.” | 8 | 25% |
Expect self-motivation | “My expectation is you drive yourself You need to be self-driven.” “I expect people to be self-motivated, and to generate their own thoughts I work well with people who are kind of self-driven.” | 5 | 16% |
Note. N = 32.
Of the themes reported, the top responses included fostering open communication (41%) and meeting regularly (38%). The underlying theme of these responses was problem-solving. Open communication and regular meetings allowed the lab to address problems immediately and move projects forward. Several PIs also noted being available daily for ad-hoc meetings. Some (28%) emphasized the critical importance of finding a balance between guiding people while also encouraging them to be independent. Additionally, one-third (31%) noted the importance of personalizing one’s management or mentoring style to individual needs. Other themes included creating a positive environment (28%) and setting clear deadlines (25%).
We wanted to ascertain whether investigators would welcome programs intended to assist them with lab leadership and management. Rather than asking them about their general interest, we contextualized this question by asking the PIs about their reactions to a specific hypothetical intervention—one that would be intensive in terms of the commitment required of a PI. We described a feedback and coaching intervention that would utilize a lab climate survey to obtain feedback about lab practices and culture from members of the lab and the PIs own self-assessment. Subsequently, PIs would receive aggregated results and coaching in areas of desired change in lab practices. After developing an initial plan for change, coaching would take place quarterly via telephone to assist PIs with following through on their plans.
A majority of PIs (74%) strongly supported the program and described it as valuable (N = 31, one response was missing due to running out of time). A small group (19%) was unsure about the proposed intervention or thought it could be potentially useful. Only 2 individuals (6%) stated that it was not a good idea, citing that it may be time-consuming or difficult to get anonymous feedback from members of the lab. Several of the PIs’ statements illustrated their openness to improving their management practices and reiterated their recognition of the importance of lab management. One researcher indicated, “I would welcome it. I would always like to improve my lab, improve the culture in the lab, and any advice or help that I can get from the outside I would welcome.” Our question prompted another researcher to note, “As I said, you’re not taught management.... Am I managing most efficiently? I don’t know.... I would be open to hearing about ideas ... I’d be flexible to change; it would be good to have feedback.” Finally, another investigator stated:
If I look back ... and I look at the single thing that I’ve screwed up the most it would be management ... management and management practices, and execution. Anything that helps that game would be better, and especially if people are like, you know, particularly focused on science.
Although what we proposed was intensive, several of the PIs stressed that they liked the tailored nature of the program, and that there is a need generally for leadership and management resources tailored to scientists. About half of those who supported the proposed program emphasized that PIs at early career stages in particular might benefit. However, one PI’s comment highlighted the importance of the timing of interventions, noting that something like this might be most appropriate once one’s research team started to get particularly complicated.
I would say I wouldn’t have felt much value for it maybe five years ago. It’s kind of at a point where there’s enough going on in a lab where it starts to get complicated personnel wise; then that would start to be really useful. In a small lab with junior faculty, I wouldn’t necessarily find value in it, but at this point I would.... You don’t even know what your issues are going to be until you’re kind of in the middle of it.
Our interviews with NIH-funded genetic researchers revealed that researchers consider leadership and management essential for performing research effectively. However, PIs reported that they were inadequately prepared to navigate the social and organizational elements of their scientific careers based solely on their scientific training. They emphasized that they learned the necessary leadership and management skills on-the-job through trial-and-error. Notably, the traditional means employed to impart scientists with requisite knowledge and skills—namely mentoring and graduate training—did not appear to be significant sources for learning to perform leadership and management activities central to research. Certainly, scientific training affords trainees with problem-solving skills that may facilitate acquiring such expertise through experience ( K. Barker, 2010 ), but this study reinforces the proposal that the scientific community must better prepare scientists to navigate these aspects of their careers ( Evans, 2012 ; Hede, 2007 ; Kvaskoff & McKay, 2014 ; Laursen, 2014 ; Leiserson & McVinney, 2015 ; Seeliger, 2012 ). The present effort provides some recommendations for how to approach such an effort. However, we need additional research on approaches for developing scientists’ leadership and management skills and basic research on leadership and management in research.
Our findings suggest several best practices for researchers. Overall, it is important to be intentional about leadership and management practices that one employs and to refine these practices continually across one’s career. Elemental to this effort is openness to feedback from lab members and advice from peers and colleagues. Additionally, one must be mindful of the outcomes of different approaches to coordinating and monitoring the work of research team members. Important practices include fostering open communication and meeting regularly, particularly to serve the interest of troubleshooting problems. It is also important to be attentive to the individual needs of those whom one manages or mentors, and to balance providing appropriate guidance while also allowing independence. Finally, it is prudent to gauge and monitor the workgroup climate or culture within a lab, working towards fostering one conducive to creativity, integrity, and productivity. Our findings also suggest that scientists, particularly those early in their careers, should seek out available resources and training opportunities. Finally, it is important for researchers to be mindful that their behaviors and practices as lab directors and research mentors have a lasting impact on those within their labs.
These points imply broader practical recommendations for leaders of research institutions. In the academic setting studied in the present effort, investigators desired access to leadership and management resources and training opportunities tailored to scientists. Institutional leaders should assess whether such a need exists in their organizations. Additionally, if extant resources and programs are available, leaders should ensure that they are sufficiently advertised, particularly when onboarding new investigators. Not only could such efforts improve practices in performing scientific work and enhance the quality of training and mentoring of junior scientists, but support from administrative officials may also influence the broader institutional culture. Finally, institutions should assess the outcomes of such programs and share their findings with others in the scientific community.
Of course, a major issue moving forward is what should be the nature of training and development efforts for scientists. A set of established approaches for leadership and management development and education exist in the organizational psychology and business disciplines ( Day, Fleenor, Atwater, Sturm, & McKee, 2014 ; DeRue & Myers, 2014 ; Doh, 2003 ; Snook, Nohria, & Khurana, 2011 ), which may provide best practices to guide future work. However, it is unclear which techniques and topics translate to the scientific context, reinforcing the importance of defining learning objectives and assessing the outcomes of training and developmental interventions ( Antes & Schuelke, 2011 ; Arthur, Bennett, Edens, & Bell, 2003 ; Riggio, 2008 ).
In addition to traditional training models, we should also explore other potentially viable developmental techniques, such as providing investigators feedback from lab climate surveys and coaching ( Ely et al., 2010 ; Feldman & Lankau, 2005 ; M. Mumford, Peterson, & Robledo, 2013 ). Notably, new measures of leader effectiveness tailored to the scientific enterprise may be necessary to assess training and developmental interventions (and such measures would facilitate research efforts as well). Furthermore, future discussion about leadership and management training and development for investigators should also consider educational practices in undergraduate and graduate education in the sciences ( National Research Council, 2015a ).
Although more basic research on scientific leadership and management must guide appropriate content, existing evidence suggests that social judgment and interpersonal skills, in addition to problem-solving skills and technical expertise, underlie leadership in professional settings. Such competencies include the ability to build and maintain relationships, present oneself well, communicate effectively, build teams, and support others ( R. A. Barker, 1997 ; Hogan & Kaiser, 2005 ; M. Mumford et al., 2003 ; M. Mumford, Zaccaro, Harding, & Jacobs, 2000 ). Indeed, the PIs in our interviews emphasized the importance of these skills, and they appear to be emphasized in existing, albeit limited, leadership training programs offered for scientists ( Laursen, 2014 ). Coupled with scientists’ existing problem-solving skills and technical expertise, enhanced social and interpersonal skills would likely better equip investigators for responsibilities such as fostering an open, innovative, high-integrity work environment, engaging others in participatory decision-making, and effectively distributing leadership among lab members or research team members ( Salazar, Lant, Fiore, & Salas, 2012 ). However, to be effective and credible, leadership development programs, particularly those focusing on emotional and interpersonal competencies, must be grounded in research ( Riggio & Lee, 2007 ).
Additionally, business skills, such as planning, budgeting, staffing, monitoring progress, and setting priorities, are imperative ( Hogan & Kaiser, 2005 ; T. Mumford, Campion, & Morgeson, 2007 ). Indeed, the investigators we interviewed raised this point. Such skills assist researchers with tasks such as hiring and training staff, planning project timelines and milestones, and overseeing work. In designing training and development interventions, it may also be necessary to consider the relative priority of different competencies at different stages in a scientist’s career ( M. Mumford, Marks, Connelly, Zaccaro, & Reiter-Palmon, 2000 ). Additionally, developmental efforts should consider the dynamic needs of investigators across the stages of scientific projects ( Antes & Schuelke, 2011 ; National Research Council, 2015b ), including how investigators simultaneously manage multiple projects in multiple stages. Moreover, the skills investigators need may also vary depending on the level of support provided by institutions such as support in budget development and management.
Another model for training and development efforts would prepare researchers to be reflective and adaptive in their approach to leading and managing in their labs and across their careers ( Ashford & DeRue, 2012 ; Nesbit, 2012 ). Such an approach would encourage investigators to recognize leadership and management responsibilities and roles in scientific work and foster a leader self-identity ( Day & Harrison, 2007 ; Pearce, 2007 ). A reflective, adaptive approach allows individuals to change and tailor their leadership style and practices appropriately for a given context, project, or career stage, and it facilitates self-directed learning and growth by encouraging individuals to extract lessons from their experience ( Ashford & DeRue, 2012 ; Cohen, 2012 ; Puccio, Mance, & Zacko-Smith, 2013 ). The comments of the participants in our study suggest that they engage in this reflective approach to some extent intuitively, and formal training could provide support and knowledge to accelerate this natural approach to developing leadership skills.
Several practical considerations emerge from these points. First, investigators already juggle many duties and responsibilities ( James, 2011 ; National Science Board, 2014 ). Thus, it may seem unreasonable to suggest that they participate in leadership training. Theoretically, well-executed training would save investigators time by helping them to address issues before they emerge and being more mindful about practices that foster successful research. Indeed, some of the PIs in this study reported learning things the “hard way” and speculated that this had slowed them down; others have reinforced the hazards of learning to lead “on-the-fly” ( Kreeger, 1997 ). Overall, this potential critique reinforces the need to utilize best practices and assess leadership development and training efforts to demonstrate their value. Additionally, offering support and services on-demand, for instance through consultation services or access to online resources, might allow investigators to obtain the right kind of information and assistance at the right times.
Second, engaging issues related to “soft skills” and asking for assistance to improve one’s practices may be unfamiliar to researchers who tend to be analytic, self-reliant, and self-confident ( Feist, 1998 ). Moreover, those trained in the life and physical sciences may be skeptical of the insights about leadership and management practices offered by the social sciences ( Sapienza, 2004 ). However, researchers are naturally open-minded, which many mitigate these concerns ( Robledo et al., 2012 ). It is important, however, to consider how to best frame such efforts. It is unclear to what extent investigators find different terminology appealing—for example, career development, professional development, leadership development, or management training.
Finally, although leadership training and development are certainly not a panacea, future work might consider whether a leadership and management framework provides an umbrella for integrating the currently disparate conversations about topics such as mentoring, responsible conduct in research, professionalism, mentoring, research rigor and transparency, and team science. These topics all highlight social and organizational dimensions in designing, performing, and communicating scientific work. Such an approach might answer calls to make responsible conduct of research training more relevant to the daily work of scientists and to explore ways to foster engagement of ethical issues in research through connecting them directly to the practice of science ( Devereaux, 2014 ; Kalichman, 2014a ; Smith, 2001 ).
Notably, the basis for effective leadership development interventions is an understanding of the practice of leadership and management in science. Thus, there is an urgent need for empirical research examining the social and organizational elements of scientific research. This research should examine the mechanisms and processes proposed in the existing, although scarce, literature on scientific leadership ( Hemlin et al., 2013 ; M. Mumford et al., 2003 ; National Research Council, 2015b ; Robledo et al., 2012 ). For instance, this work might examine processes in team alignment and knowledge integration ( Drath et al., 2008 ; Salazar et al., 2012 ). Other issues such as conflict resolution, project management, building a lab culture, cross-cultural communication, and interacting with difficult colleagues may also be fruitful directions ( K. Barker, 2010 ; Cohen, 2012 ). There is an existing, expansive base of related research in the workplace psychology and organizational behavior disciplines, but future research must take into account the unique qualities of scientific work and the distinct qualities of staff and collaborators engaged in it.
Future work must also examine explicit connections between leadership and management practices and the ethics, integrity, and transparency of research. With a few notable exceptions—for instance, an investigator recounted realizing that inadequate oversight of a graduate student had comprised the integrity of data generated during the student’s tenure in the lab—investigators in our study generally did not raise such connections. Two opposing explanations may account for this. Investigators may implicitly acknowledge the connection between practices they employ to manage their research and the effectiveness and integrity of the research. Alternatively, PIs may lack awareness of the significance of ethical issues in their work ( McCormick et al., 2012 ). It is also important to understand connections between management practices and the productivity of scientific labs and teams—what practices yield scientific productivity while also supporting the quality and integrity of the work?
The present study focused primarily on management issues in the lab setting, but future work should also consider the multiple levels at which investigators may lead in their careers and the multiple types of scientific organizations ( M. Mumford et al., 2003 ). For example, leadership takes place in collaborative, even multi-site and international, teams, in scientific disciplines (e.g., leadership roles in a professional society), in communities and among the public, and in administrative roles (e.g., a division chief or department chair). Additionally, leadership across multiple levels must be considered; for instance, how administrative leadership at the organizational or departmental level influences leadership within labs ( Bland & Ruffin, 1992 ; Robledo et al., 2012 ). Future research on leadership and management in science will also need to consider differences and commonalities across academic, industry, and entrepreneurial organizational contexts ( M. Mumford et al., 2003 ).
To address these research questions about scientific leadership, we must consider several significant practical issues that emerge. Notably, who should study, fund, and publish “metascience” ( Hu, 2016 ) on leadership and management in research? Interdisciplinary teams comprised of social scientists and those from specific social, life, or physical science disciplines may be best equipped to employ social science methods to test research questions while also appreciating unique features of specific scientific disciplines. But, funding agencies and journals typically focus on specific diseases or disciplines. Research issues that span all scientific research do not have clear funding or publication outlets ( Ioannidis, Fanelli, Dunne, & Goodman, 2015 ). Often this work is published in a wide range of disciplines, making it difficult for scholars studying similar issues to locate each other’s work ( Ioannidis et al., 2015 ). Additionally, these efforts are likely to be unfunded secondary projects of interest to individual researchers, and as such, potentially funded inadequately to address the necessary large and complex questions.
These findings provide some useful future directions for research, training, and development regarding leadership and management in science, but they are not without limitations. The first limitation relates to the generalizability of the findings because the PIs were at one academic institution. However, this allowed us to hold constant the potential influence of institutional culture, which was not of interest in this particular study. Additionally, we ensured that our sample was diverse and representative of biomedical researchers conducting NIH-funded genetic research. They were diverse in terms of nation of origin (i.e., international or U.S.), and they conducted varied types of research (e.g., human, animal, computational) funded by a variety of NIH institutes. They were also diverse in career stage, and our sample was representative of the NIH-funded population in terms of gender.
Another potential limitation includes that the investigators self-selected as volunteers for the interview study. Therefore, they may be those most interested in issues related to operating a lab or leading a research team. Indeed, their responses suggested that they were reflective about their lab management practices. Overall, it is unclear whether our findings would generalize to other groups of scientists in other settings.
Finally, all of our participants could be considered highly successful: they are PIs at a leading medical research center with NIH funding. While this is a limitation in terms of the generalizability of findings, it is also a strength in terms of learning about the management practices of successful researchers.
In conclusion, the NIH-funded principal investigators that we interviewed at a top-tier US academic medical center decidedly indicated that leadership and management are essential to performing effective research. Moreover, they observed that scientific training does not prepare researchers for these activities, and they encouraged the development of programs to better train investigators. Ultimately, equipping investigators to navigate the social and organizational dimensions of scientific work serves to foster the quality, integrity, and societal impact of scientific research. But, efforts must follow best practices in leadership development and assessment, and empirical research on leadership and management in science should serve as their basis. Several practical concerns emerge in light of the foregoing observations, such as who should study, fund, and publish such work. We hope that the present study inspires the scientific community to take on this challenge.
Source of Support
This study was supported in part by a National Center for Advancing Clinical and Translational Science Award, 2UL1 TR000448-06, and by the National Human Genome Research Institute, K01HG008990. The content is solely the responsibility of the authors and does not necessarily represent official views of the National Institutes of Health.
Disclaimers
The authors have no conflicts of interests or disclaimers to report.
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Published on October 26, 2022 by Shona McCombes . Revised on November 21, 2023.
A research question pinpoints exactly what you want to find out in your work. A good research question is essential to guide your research paper , dissertation , or thesis .
All research questions should be:
How to write a research question, what makes a strong research question, using sub-questions to strengthen your main research question, research questions quiz, other interesting articles, frequently asked questions about research questions.
You can follow these steps to develop a strong research question:
The way you frame your question depends on what your research aims to achieve. The table below shows some examples of how you might formulate questions for different purposes.
Research question formulations | |
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Describing and exploring | |
Explaining and testing | |
Evaluating and acting | is X |
Example research problem | Example research question(s) |
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Teachers at the school do not have the skills to recognize or properly guide gifted children in the classroom. | What practical techniques can teachers use to better identify and guide gifted children? |
Young people increasingly engage in the “gig economy,” rather than traditional full-time employment. However, it is unclear why they choose to do so. | What are the main factors influencing young people’s decisions to engage in the gig economy? |
Note that while most research questions can be answered with various types of research , the way you frame your question should help determine your choices.
Professional editors proofread and edit your paper by focusing on:
See an example
Research questions anchor your whole project, so it’s important to spend some time refining them. The criteria below can help you evaluate the strength of your research question.
Criteria | Explanation |
---|---|
Focused on a single topic | Your central research question should work together with your research problem to keep your work focused. If you have multiple questions, they should all clearly tie back to your central aim. |
Answerable using | Your question must be answerable using and/or , or by reading scholarly sources on the to develop your argument. If such data is impossible to access, you likely need to rethink your question. |
Not based on value judgements | Avoid subjective words like , , and . These do not give clear criteria for answering the question. |
Criteria | Explanation |
---|---|
Answerable within practical constraints | Make sure you have enough time and resources to do all research required to answer your question. If it seems you will not be able to gain access to the data you need, consider narrowing down your question to be more specific. |
Uses specific, well-defined concepts | All the terms you use in the research question should have clear meanings. Avoid vague language, jargon, and too-broad ideas. |
Does not demand a conclusive solution, policy, or course of action | Research is about informing, not instructing. Even if your project is focused on a practical problem, it should aim to improve understanding rather than demand a ready-made solution. If ready-made solutions are necessary, consider conducting instead. Action research is a research method that aims to simultaneously investigate an issue as it is solved. In other words, as its name suggests, action research conducts research and takes action at the same time. |
Criteria | Explanation |
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Cannot be answered with or | Closed-ended, / questions are too simple to work as good research questions—they don’t provide enough for robust investigation and discussion. |
Cannot be answered with easily-found facts | If you can answer the question through a single Google search, book, or article, it is probably not complex enough. A good research question requires original data, synthesis of multiple sources, and original interpretation and argumentation prior to providing an answer. |
Criteria | Explanation |
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Addresses a relevant problem | Your research question should be developed based on initial reading around your . It should focus on addressing a problem or gap in the existing knowledge in your field or discipline. |
Contributes to a timely social or academic debate | The question should aim to contribute to an existing and current debate in your field or in society at large. It should produce knowledge that future researchers or practitioners can later build on. |
Has not already been answered | You don’t have to ask something that nobody has ever thought of before, but your question should have some aspect of originality. For example, you can focus on a specific location, or explore a new angle. |
Chances are that your main research question likely can’t be answered all at once. That’s why sub-questions are important: they allow you to answer your main question in a step-by-step manner.
Good sub-questions should be:
Here are a few examples of descriptive and framing questions:
Keep in mind that sub-questions are by no means mandatory. They should only be asked if you need the findings to answer your main question. If your main question is simple enough to stand on its own, it’s okay to skip the sub-question part. As a rule of thumb, the more complex your subject, the more sub-questions you’ll need.
Try to limit yourself to 4 or 5 sub-questions, maximum. If you feel you need more than this, it may be indication that your main research question is not sufficiently specific. In this case, it’s is better to revisit your problem statement and try to tighten your main question up.
If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.
Methodology
Statistics
Research bias
The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .
A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.
As you cannot possibly read every source related to your topic, it’s important to evaluate sources to assess their relevance. Use preliminary evaluation to determine whether a source is worth examining in more depth.
This involves:
A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (“ x affects y because …”).
A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses . In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.
Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .
However, it should also fulfill criteria in three main areas:
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Example research questions.
Topic | Subtopic | Issue or Problem | Research Question |
---|---|---|---|
High School Education | Drop-outs | Socio-cultural impacts on high school completion | What are the socio-cultural influences on high school completion and how might these be addressed? |
Higher Education | Access | Barriers to college entry | How well are college access interventions working in North Carolina? |
K-12 | Special Education | School administrators views of the disabled | How do K-12 principals' beliefs about disabilities affect their leadership of students with disabilities? |
Middle School | Mathematics | Serving the learning needs of gifted and challenged middle school students in mathematics | What impact would a tiered system in middle school mathematics have on learning by students with varying aptitudes for mathematics? |
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Driving a positive work culture means making space for challenge—here are the questions business leaders should be asking their teams
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The study from Imperial’s Center for Responsible Leadership analyzed over 30 hours of recorded meetings, focusing on real-time interactions between leaders and their teams.
Based on this research, the report outlined key strategies and question styles that leaders can use to draw out diverse perspectives and open up the decision-making process.
According to the report, the key to encouraging meaningful feedback from employees lies in the type of questions leaders ask and their precise wording.
Broad or open-ended questions—such as “You wanted to say something?”—are likely to result in superficial agreement rather than constructive challenge. Instead, leaders should ask questions that directly invite alternative viewpoints and make team members accountable for their input.
Examples of questions that build challenge into the discussion:
These questions signal that alternative viewpoints are welcome, actively encouraging team members to critically engage with the issues at hand and share their honest opinions.
When employees feel unable to voice concerns or challenge decisions, this can result in a culture of fear or silence and can even threaten an organization’s growth and future.
“The consequences of a corporate culture where teams are hesitant to challenge leaders can be dire. This can include financial damage and service failure,” wrote Celia Moore, professor and academic director of the Center for Responsible Leadership and lead author of the report.
A well-known example is the 2021 collapse of asset manager Archegos Capital, which led to a $5.5 billion loss for global investment bank Credit Suisse. The bank largely attributed this failure to a ‘cultural unwillingness to engage in challenging discussions,’ according to a report published in July of that year.
But targeted questions are just one part of a broader strategy to foster a positive, open, and constructive work environment. Leaders must take deliberate steps to create an atmosphere where challenge is valued as an integral part of the decision-making process.
The way leaders respond to challenges is crucial. Merely expressing gratitude towards a team member without specifically addressing the challenge raised can stifle further input.
Instead, challenge should be legitimized and directly addressed. For instance, the response “That’s a fair challenge, we could definitely go with that option,” goes beyond superficial acknowledgement and demonstrates genuine engagement with the issue.
The report outlines several practical strategies that leaders can implement to cultivate an environment where constructive challenge is prioritized.
In light of these findings, the Center for Responsible Leadership is offering masterclasses for leadership teams on how to bring about constructive challenge within their organizations.
Orginally posted @ Entrepenuer.com
The prominent psychiatrist Carl Jung once stated, “To ask the right question is already half the solution of a problem.” As a CEO coach, I see that as leaders ascend the ranks of an organization, their questions become much more important than their answers .
As an individual contributor or junior manager, there’s a lot of stock put into solutions and trying to figure out that answer. Success is equivalent to how much you do and how efficiently you do it. The leverage here is in your tools, your systems and processes. For more senior managers or executives, though, the dynamic starts to shift. They’re less focused on their own output and start to define success as the output of their teams. The leverage here comes from the people who lead and deliver the outcomes.
As the definition of “success” changes, so too must the approach. How to get the most leverage out of people, people who are often leading others themselves? How to get the most relevant information in a noise of complexity? How to focus, motivate and empower others ? A lot of this comes down to developing the skill of asking really powerful questions .
Powerful questions are the cornerstone of effectiveness in my profession of coaching. They’re the currency that my clients and I trade in to develop deeper awareness and forward-meaning action. I know something about what makes good questions good and bad questions bad. And, although I do this full-time as my career, coaching is a core part of any effective leadership at scale. So, what’s the recipe to make a question truly powerful ? For that, I believe you need five key ingredients.
Often, I catch myself and others using questions as an argumentative tool to make a point. I call this weaponizing ; they are statements masquerading as questions. Imagine asking questions like, “This isn’t at all the right approach, what were you thinking?” or “Why in the world would you choose that option?” Even without the context or tone, you can imagine that these questions are intended to make a point , to convey an opinion. Powerful questions, on the other hand, come from a place of genuine curiosity and openness. There are no hidden statements behind them other than “I want to learn from you.”
A closed question is something that restricts the answers, usually a yes or no or a small subset of choices. “Are you making progress?” is a closed question. “Do you think we should go left or right?” is a closed question. This isn’t to imply that closed questions are bad ; in fact, they can be quite helpful to get clarity or encourage action. But really powerful questions are open, not closed. They begin with question words, especially the words “ what ,” “ why” and “ how .” These words invite a broader discussion, not a choice from a narrow set of possibilities.
As a shortcut, I find that oftentimes the best word to start a powerful question off with is “ what” instead of “why” or “how.” Asking, “Why did you do this?” can prompt someone to be defensive and try to answer in a way that justifies their choice. Asking, “How did you do this?” can have a similar effect or result in a more analytical or superficial answer. In contrast, try reframing the question in a less confrontational way, such as, “What was important to you about doing this?” or “What were the steps you took?” Regardless, another way to frame a question in a more encouraging way is to simply share the context for the question.
As leaders, we must continue to develop a sense of priority and focus on what truly matters , reflecting that in our questions. Instead of asking questions to collect answers on a dozen different topics, ask questions that get you a dozen perspectives on the one most important topic. Try to reflect on what the most important thing is and then zoom in, not out. Focus on what more instead of what else .
Finally, powerful questions are concise ; brief but potent. A short, sweet question is easier to understand, reflect on and respond to. There are two things to watch out for here: long questions and stacked questions. A powerful question should be short and fit comfortably into a simple sentence. If this isn’t easy, pause to reflect on how to make your question shorter. But avoid trying to restate the question after the fact, which can just create confusion. Stacking questions one after the other makes it difficult to understand what the true question is. It’s often better to ask a good question and stop short of adding the perfect question on top of it. Try to remember: Ask your question, then pause at the question mark.
Asking powerful questions is a skill — one that can be practiced and developed over time. Try noticing these five components of powerful questions as a structure for that practice. And, although this isn’t part of building powerful questions, don’t forget to truly listen to the reply. Think less of which question to ask next or what response to give, and try to stay present. Focus on understanding the answer. That is, after all, why we ask really powerful questions in the first place.
Jason R. Waller is a partner at Evolution and a lifelong student of leadership and personal growth; he believes that good leaders can change the world. After his own career in the military and consulting, he discovered his calling as a coach and set out to find and serve these leaders full-time.
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The study from Imperial's Center for Responsible Leadership analyzed over 30 hours of recorded meetings, focusing on real-time interactions between leaders and their teams. Based on this research, the report outlined key strategies and question styles that leaders can use to draw out diverse perspectives and open up the decision-making process.
Guest Post by Jason R. Waller Orginally posted @ Entrepenuer.com The prominent psychiatrist Carl Jung once stated, "To ask the right question is already half the solution of a problem." As a CEO coach, I see that as leaders ascend the ranks of an organization, their questions become much more important than their answers. As an individual contributor or junior manager, there's a lot of ...
prefered research method that informs the research question. This essay is about why this is a problem for the development ofleadership researchandwhatwecandoto addressthisissue. My argument is that because research method prefer-ences guide research questions, and leadership research is characterized by a strong preference for survey methods,