Evan A. Enquist, University of Wisconsin-LaCrosse, U.S.
Mike R. Bumgarner, University of Wisconsin-Madison, U.S.
Rachel M. Barkley, Drake University, U.S.
Heath J. Weeks, Drake University, U.S.
Eric V. Swafford, Drake University, U.S.
Angela R. Dahl Miller, Drake University, U.S.
Christopher L. Kliethermes, Drake University, U.S.
David S. Senchina, Drake University, U.S.
The benefits of undergraduate research experiences are many and include skill development (such as interpersonal communication, critical thinking, or technical skills), knowledge enrichment, and other benefits reviewed extensively elsewhere (Goenka, 2005; Lopatto, 2007; Russell, Hancock, & McCullough, 2007; Sleister, 2007). Genuine research experiences bridge the gap between simply reading about science and being active practitioners (Chopin, 2002) and play key roles in helping students explore or decide on careers in science (Lopatto, 2007).
Many different models for conducting undergraduate research exist, running a spectrum from the traditional apprenticeship style mode (single student and single faculty working one-on-one) to collaborative efforts involving students of different ages and mentors from academia, community, and industry. The traditional model involves one or a few students interacting with faculty and/or staff and graduate students in internship- or apprenticeship-like roles in a faculty member’s research lab (Dolan & Johnson, 2010). An alternate of this model is the “one-room schoolhouse” approach where dozens of students interact in a research lab and older students help mentor younger students (Henderson, Buising, & Wall, 2008). Undergraduates who perform roles of both researcher and peer mentor synergistically may experience heightened benefits (Sabatini, 1997).
Increasingly, original research is replacing “cookbook” labs in the teaching laboratory. Recent examples include a sixteen-student upper-level genetics course that used a model of yeast mutagenesis (Sleister, 2007) and a junior-level nursing education course where students identified health risks to campus residents and developed an action plan to characterize their extent and develop an intervention (Rodriguez, 2012). In both instances, a single research project formed the focus for the entire semester. The advantages of such approaches over traditional instruction are that they expose students to the genuine scientific process, complete with possibilities of failure and “messy data” (Hutchinson & Atwood, 2002), and they emphasize depth over breadth. Peer mentoring can also be used in conjunction with these models, and the synergistic benefits mentioned previously (Sabatini, 1997) occur in these systems as well.
Most reports of undergraduate research models are written solely by faculty members from the perspective of themselves or the academic programs they’re associated with, and most focus on reporting of objectifiable outcomes such as survey results, skills acquisition, or research productivity (Zydney, Barnett, Shahid, & Bauer, 2002). Few relay comments directly from the students, and even fewer involve students in the presentation of the pedagogy, though such reports are beginning to emerge (Wood, 2003). Additionally, we could not locate any reports that included comments from non-faculty university personnel, such as professional & technical (P&T) staff, despite current research underscoring similarities in role between faculty and staff in teaching environments (Cook-Sather & Shore, 2007). Thus, staff members constitute an unrepresented population in the general dialogue regarding undergraduate research.
The purpose of this manuscript is to present a dialogue about undergraduate research experiences in an exercise science laboratory at Drake University. Compared to previous reports of undergraduate research models, this paper is novel because it includes the viewpoints of not only students and faculty but also project-associated staff members, a population often neglected or excluded from such conversations. Undergraduate research experiences may be perceived differently by students, staff, and faculty. To explore these differences, three students, three staff members, and two faculty members all involved in undergraduate research during the first six years of an exercise science laboratory participated.
Our manuscript is organized into five sections. First, we describe the research context and personnel in our author team. Second, we present a novel model for developing and reflecting upon undergraduate research experiences, which we call the 8D model. Third, we individually reflect and cooperatively dialogue upon undergraduate experiences in our laboratory from our respective roles and highlight similarities and differences in our experiences. Fourth, we summarize what we learned and how it relates to work done by others and share some different solutions we have developed or are considering implementing in response to our reflections or previously encountered roadblocks. Fifth and finally, we discuss advantages, disadvantages, and limitations of the 8D model.
Research Context and Personnel
In this section we will describe the research setting and associations of the eight co-authors with the setting. Drake University is a private liberal arts institution located within the central Midwest in Des Moines, Iowa. Our Exercise Science & Sports Medicine Research Laboratory was established within the Biology Department informally in 2006 and given a permanent physical space in 2008 (Figure 1). Research projects within the laboratory vary in scope pursuant to student research interests and curriculum needs; however, our main student research focus is the foot and ankle. All projects involve work with human subjects, and all utilize a peer-mentoring approach where a designated student “research captain” assumes primary responsibility for the study and mentors other students during the research process, either in a teaching laboratory setting or an independent (thesis) research setting. Staff and faculty serve as facilitators in a team-based approach with students as described elsewhere (Karsai, Knisley, Knisley, Yampolsky, & Godbole, 2011); thus, our model is not the traditional apprenticeship-type, but more team-based and integrated into a broader biology curriculum, consistent with recommendations recently made by the American Association for the Advancement of Science (Wei & Woodin, 2011).
The three student co-authors in this article represent the diversity of projects conducted in the laboratory. Evan tested a computerized, motorized shoe that adjusts midsole stiffness based on ground characteristics by examining lower limb muscle activity patterns (via a technique called electromyography or EMG) during four gym exercises. The study performed by Evan is used in the model presented in this paper. Mike performed a validation study for a popular video game that promotes physical activity by directly comparing physiological and performance variables during the video game to actual running, gym, or basketball exercises. Rachel explored the effects of different shoe and sock materials on perceived and actual foot temperature during brief bouts of treadmill running.
All three students conducted their experiment in concert with an exercise science laboratory course section, where students enrolled in the course assisted in the experiment and Evan, Mike, and Rachel were research captains for their respective groups. Research has shown that a synergy between peer mentoring and researching develops in such system, augmenting both skills and content acquisition for the research captains (Sabatini, 1997).
The three staff members (Heath, Eric, and Angie) have worked with numerous students and classes in differing contexts over the years. Heath and Eric have been associated mainly with classroom projects; whereas, Angie has been associated mainly with thesis projects. Eric has been associated with the greatest number of projects, but primarily those involving strength training. Angie has mentored numerous thesis research projects pertaining to ankle taping and spatting in the context of football, reflecting her primary role at Drake University as the lead athletic trainer for the football team. Heath was associated with a project pertaining to the effects of different ankle bracing appliances on back squat performance.
Regarding the faculty, Chris has been associated mainly with thesis projects and David is the principal investigator for the lab. Additionally, we come from diverse academic backgrounds, with Chris coming from more of a genetics and psychology background and David coming from more of an exercise science, immunology, and botany background. Chris has participated in both classroom and thesis projects when those projects have involved a perceptual element, such as when subjects are asked to gauge the relative masses of different shoes.
Importantly, although all eight of us have worked in the same physical research setting in the same spirit of experiments, we have not worked together in terms of specific projects or even academic years, with the exception of David. Some of us were involved in only one project; whereas, others have been involved in many. While this diversity enriches the breadth of experiences possible in a group dialogue, it also imposes limitations in terms of shared experiences. Recent examples of student work from our team may be found elsewhere (Barkley, Bumgarner, Poss, & Senchina, 2011; Bumgarner & Senchina, 2013; Faganel, Drake, Dahl-Miller, & Senchina, 2013; Reuter, Dahl, & Senchina, 2011).
Mainly through trial-and-error over the years, our laboratory has organically grown a model that embodies our approach to undergraduate research, which we named the 8D model (because it contains eight components each represented by a word starting with the letter “D,” after Drake University). Apart from this manuscript, the model serves as a “checklist” for us to develop undergraduate research experiences that include all the key elements of the scientific process for our field. Within the context of this manuscript, the model served as a framework for reflection (and may possibly be useful as a catalyst for other research teams).
The 8D model is presented in Figure 2. Figure captions present the model generally; whereas, the figure illustrations and text within this section demonstrate the model’s application to a specific student’s (Evan’s) research project. Undergraduate research experiences start when an interested student and university personnel (1) discuss a potential project. Depending on the nature of the project, different students, staff, and faculty become involved. In the case of Evan’s project, student interest in a recently marketed computerized, motorized cross-training shoe was the impetus for dialogue, which in turn, led to brainstorming about how the manufacturer’s claims might be tested and a literature review on similar technology. Step 1 often becomes inseparable from (2) design; in our model, Step 2 is multidimensional and includes selecting and piloting appropriate experimental techniques and obtaining Institutional Review Board (IRB, or ethics committee) approval. For Evan’s experiment, we were able to piggyback off a previous, similar study conducted in our lab by Robert J. Fechner in the preceding year; consequently, the main focus was on optimizing techniques and obtaining IRB approval.
The next action is to (3) do the experiment in small-scale with all relevant personnel (students, staff, and faculty). After a representative sample of data is collected, personnel (4) decide if the experiment is appropriately addressing the research questions and if any unidentified problems or areas of improvement exist; this conversation naturally leads the group to (5) develop solutions that improve the experiment. Considering steps #3-5 within the context of Evan’s experience, initial data collection sessions with eight total subjects revealed two problems related to the EMG electrodes—inconsistent placement by various student investigators and electrodes falling off and having to be replaced mid-experiment due to sweating. To address the first problem, Evan opted that only he and one other student-investigator would place electrodes on subjects using an agreed-upon method. To address the second problem, Evan tested various tapes to hold the electrodes in place and chose to wrap the electrodes onto the subjects’ legs using electrical tape because of its flexibility, adhesiveness, and ease of removal. During step #5 of Evan’s project, an additional problem occurred when the control buttons for the motor of the right shoe quit working. Evan was able to find a newer model of the same shoe on eBay and then modified his experiment slightly so he could do a comparison of the older and newer shoe models.
With midstream adjustments implemented, the student-investigators (6) do (again) the full experiment and collect all necessary data. Afterwards personnel (7) debrief by analyzing and considering the findings’ implications, applications to the initial research question, and applications to society. So that others can benefit from the work, a team representative (preferably the student captain) does something to (8) disseminate the findings, such as through a conference poster, presentation, or publication. Evan went on to collect data for a total pool of 20 subjects; preliminary data analyses suggested that subjects’ leg muscles sometimes exhibited greater muscle activity (suggesting those muscles were working harder) when the shoes had softer midsoles. Evan presented his findings in poster format at a local undergraduate research conference.
Figure 2: Steps in the 8D Model
Reflections on Personal Experiences
All eight co-authors were asked to reflect upon their experiences in light of the 8D model. Chris and David generated a panel of four questions, each with three subparts, and asked all others in the group to use them as a platform for discussion. Each co-author pondered these questions privately before submitting a written response to each item. The questions encompassed general impressions, the role of peer mentoring, interactions with human subjects, and sense of personal accomplishment. Here, we share three of those questions and our responses to them. Because there were eight of us and representing the entire dialogue would be intractable, we elected to use representative quotes or summaries when we were of like opinion, but gave individual quotes when there were differing viewpoints.
Question 1: Considering the project overall, did it (a) match up with the 8D model or not? (b) Which aspects of the 8D model did we succeed the most in, and (c) which aspects do we need the most improvements in? For question 1a, most of us felt our experiences aligned fairly well with the 8D model.
Mike said: I feel as though we followed it very closely when conducting the study. Dr. Senchina and I met to determine what questions we were looking to answer. We discussed how to set up the study to best answer these in an objective way. The study was performed with help from the class and we met periodically to talk about potential problems that arose such as the learning curve associated with the activities.
Discrepancies from the model were also identified.
Heath said: The project did not involve much initial student dialogue or planning.
This was because his study was conducted in a classroom setting and other groups had already performed initial steps of the model (out of logistical necessity). Rachel and Evan felt they were not as involved in steps 1 and/or 2 as with other steps in the model, and Mike felt step 6 could have been enhanced.
For question 1b, as a group we believed we did best at accomplishing the middle steps of the 8D model; however, the students had very different opinions from one another, and the staff and faculty members had similar opinions.
Rachel said: We were the most successful at dissemination of the study results. Not only were the results of the study presented at DUCURS for other Drake students and faculty to see but the results were also published.
Evan said: I believe that the most successful aspects of the 8D model were steps 3 through 6. We were successful with our initial subjects but hit several minor glitches in protocol efficiency and equipment malfunction. We were quickly able to develop solutions and overcome all experimental issues. We recruited more and more participants making a respectable sample size with ever increasing efficiency with each subject in the lab.
Mike said: I felt very good about steps 1-5. We had a thorough discussion on how to set up and execute the study and I felt comfortable working with the students. We spent time at each point in the 8D model discussing how to improve.
By contrast, staff and faculty members mostly identified the middle steps of the model as being most successful, as two examples attest.
Eric said: When the end product results in meaningful data and information that can be presented to an interested community while increasing the understanding of certain concepts, then that should be considered successful. Specifically, for our project I would consider the application or step 3 of “Doing” excellent because the students, once informed of the process, followed through with minimal difficulty in running trials, collecting data and processing it as well which involves steps 4, 6, 7, and 8.
Chris said: [My] project was a good example of how the mentor/student relationship should go. The experiment was well designed, such that interpretable results would have been obtained regardless of the outcome (if there was or was not a pattern to the weight rankings, the data still meant something). What I also like about the project is that the experimental measures are relatively easy to obtain, meaning that the student has the “freedom to fail” in the project, with no disastrous loss of precious samples, ethical concerns, etc, if something didn’t work as planned.
For question 1c, as a group, we harbored widely divergent viewpoints regarding areas for improvement, even within student, staff, or faculty subgroups. The wide-ranging responses elicited by Question 1c prompted deeper exploration. “Time” was identified as the primary reason why the model was neglected in some aspects.
Mike said: I felt the second half was not as involved. Much of this was due to a lack of time since the study began in mid to late fall, near the end of the semester. I would have enjoyed going deeper into the data as a whole and coming up with new questions or ways to improve upon what we had already done.
Evan said [at the Debrief step]: While the student captain, other main student contributors, and mentor directly discussed the results of the study, many of the other students who were involved in data collection may not have found out the results of the study. Part of the problem with debriefing in this study was that students in the class did most of the data collection in the fall semester; however, all of the data was not collected until mid-second semester. The second semester data was mainly collected by the student captain and other major student contributors. While we knew the study results, many of the class students involved may have not been informed.
In both of these examples, the main issue seemed to be the format of the semester. Staff and faculty members within our group had similar feelings
Angie said: If we had more time and resources I believe the students could do a more thorough study and further develop their experiments.
Heath said: Steps 1 & 2 were not a part of this project, due to time and student constraints, but, if possible, their inclusion would give students a greater sense of ownership of their project and a much more complete picture of the research process (from start to end).
Chris said: Especially in the context of the laboratory classroom, both semester and class formats often don’t allow for as deep of involvement in the initial steps of the model as I’d wish. When you’re charged to introduce students to many techniques during the course, troubleshooting for any single technique must often be done before students arrive.
We will share some possible solutions to the issue of time and timing in the “What We Learned” section.
Question 2: In all of our projects there is a student “captain” who is in charge of the project and coordinates other students. (a) Which parts of the 8D model were the students best involved in (if any)? (b) Which parts of the 8D model should students be more involved in (if any)? (c) Could you provide some specific ways to accomplish this?
Although worded slightly different, Question 2 is very similar to Question 1 with one crucial exception— Question 1 prompted each of us to think about the general project from our personal vantages, and Question 2 specifically required us to consider undergraduate research from the students’ eyes. How we approached this question differed based on our role. The students within our group were themselves the research captains, so for them the word “student” meant those students who assisted them. By contrast, for staff and faculty the word “student” could encompass either the student research captain or any of the assisting students.
Our responses to Question 2a mirrored our responses to Question 1b, and our responses to Question 2b reflected our responses to Question 1c, so those topics will not be revisited here. Everyone found this redundancy reassuring, as it suggests those members of our team may be fulfilling the primary mission of keeping the research process student-focused.
One novel and critical theme that emerged during Question 2a was how much the student captains valued the other students involved in the project, not just for their assistance in data collection but for their intellectual involvement. It also became apparent how much the staff and faculty valued the research captains.
Mike said: I really valued their suggestions during steps 3-4 as problems arose and we were able to come up with better ways of doing things.
Angie said: The students were very heavily involved in the projects and do a very good job of taking the lead with them.
Question 2c solicited areas for improvement, and our responses quickly returned to those issues we raised during Question 1c. The main theme we derived was once again that the undergraduate research experience could best be enhanced by deeper involvement of all students in the initial stages, and possibly at the latter stages also.
Mike said: More student input in setting up the study could only help. They might have been better able to see potential issues.
Rachel said: For students that are involved with a study at a greater level than just data collection, it would be helpful to involve them in experimental design and initial literature searches on both the potential experimental techniques and the possible research questions that could be addressed. By doing some background reading on a research topic, students may gain a broader understanding of the project and discover other experimental methods to study a given research question. Forcing students to become actively involved in the initial stages of a project may help them to understand the project aims more completely.
Staff members felt similarly to the students.
Heath said: I think a good way of incorporating more dialogue into the research process would be to broadly introduce the area of study and then assign a homework assignment asking the students to brainstorm about the topic and, possibly, start designing an experiment. Then, the next time you meet, the topic can be discussed, similar research themes can be identified, and (hopefully) the research design is a close match with the project. This discussion would need a moderator to help direct the conversation.
Eric said: Students struggle with beginning a study in the sense that they are unsure of how to develop a research question and then design a study to investigate that question specifically without confounding variables. Additionally, on first completion of the study design many students believe that the process is set in stone and cannot be changed especially if they have completed several trials.
Faculty members also felt similarly, but noted additional considerations.
Chris said: This is a tricky issue for undergraduates, especially for some who may have very little instruction in experimental design. On the practical side, the biggest question the student should answer is, “what is the experimental question being asked?” A well-stated question usually lends itself to one or at most a few different experimental designs. The student could then be guided through formulating various ways to address the question experimentally, with an eye towards how the data obtained will ultimately be analyzed.
David said: Ideally every student would have the opportunity to be involved from start to finish, but my expectations differ whether the student is a research captain or assisting in data collection. Students may be taking the class simply to explore the topic or to fulfill a general education or major graduation requirement. For most, deep involvement in the entire experiment is not only logistically difficult but may be inappropriate. The schedule and curriculum of the class pose logistical constraints too. I oftentimes need to select certain aspects to emphasize, or some to exclude for the sake of the bigger picture.
We will revisit some possible solutions to this topic in subsequent sections.
Question 3: Considering your role, (a) what did you do well and why do you feel that way, and (b) in what areas would you like to grow personally (if any) and why you do you feel that way? (c) What was the biggest reward for you personally from participating in a student research project?
Question 3 is the most introspective and personal. Students within our team had very different responses to Question 3a, whereas both staff and faculty members had very similar responses, which revolved around their being a facilitator (versus a direct participant) as their biggest contribution to the team.
Rachel said: I think I did best at trying to keep student data collectors focused and on task during data collection sessions. I tried to ensure that the data was collected at the appropriate time. I also tried to keep the participants involved in conversation and try to make them feel comfortable with the experiment. If they or students collectors had questions about the experimental procedures or study overall, I tried to answer the questions as completely as possible.
Evan said: I feel that I was dedicated to the research and successfully lead a team of students in the completion of many hours of data collection. I took the time outside of class and lab work to practice the study protocol.
Mike said: I think I handled the logistics well such as recruiting subjects and keeping the study on pace. I also felt as though I did a good job summarizing and presenting the data at the conference.
For Question 3b regarding personal growth, Evan and Mike felt similarly.
Evan said: I would like to enhance my teamwork and leadership skills. I believe that in the research atmosphere teamwork is pivotal for success. I also wish to enhance my leadership skills to direct a team of researchers in conducting quality, accurate research.
Mike said: I thought I could have done better communicating with the class. There were times where I was unsure about how well the students knew what was going on.
Rachel said: As the student captain for the experiment, I feel that I should have devoted more time and effort to the initial and final stages of the study rather than the majority to the data collection sessions.
Staff members each responded uniquely.
Eric said: I would want to become a facilitator that students know they can count on for their development in becoming successful researchers in whatever field they choose.
Angie said: I would personally like to have more of an idea of the whole process.
Heath said: I would like to increase my familiarity of similar studies so that students could get better feedback from me.
Faculty also had unique responses.
David said: I want to interfere less in activities that students could be self-sufficient in.
Chris said: I am very new to mentoring students…[but watching veteran faculty provides] a great example of how a good student/mentor dynamic can be used constructively.
Finally, we reflected on what we had accomplished through our personal involvement.
Mike said: It was very rewarding to take on a leadership role in a study like this. I felt very invested in it and genuinely interested in the outcome. I believe that I gained several important skills such as collaborating with others, verbal and written communication and taking on responsibility for logistics. It wasn’t what I would have thought of as a “normal” undergraduate research project but it was certainly a worthwhile experience. It was an important part of my college experience.
Evan said: I believe that the biggest reward I received from participating in student research is experience and confidence. Experiencing first hand all of the hours of prepping subjects, problem solving and analyzing data allowed me to gain valuable research experience not attainable by all undergraduate students. I also received confidence in my ability to make subjects feel comfortable and give accurate and easy to follow instructions so that subjects enjoy participating in research.
Rachel said: The rewards for being involved in a student research project are two-fold. First, being involved in the project made me realize how much time and devotion to a project are necessary in order to gain enough results to make a study worth pursuing. Secondly, although it may be obvious, human subjects research is different than scientific lab research in that with human subjects you not only have to work around participants’ schedules and ensure their safety and comfort throughout the experimental period but also communication skills are more of a necessity for success.
The responses of all five staff and faculty members together shared one obvious common denominator—the reward for them was in the students.
Angie said: I think it is great to see the students really own a project and grow during the process. It prepares them well for the real world.
Heath said: The largest reward for me was seeing the class come together and work together to make the study operational.
Eric said: To watch the students become excited about the scientific process and getting involved with the development and implementation of a research project is very rewarding. In the end, the student’s expressions of appreciation are extremely rewarding because it is then that they understand the time and effort that is required for research projects.
Chris said: I enjoy helping people think through complicated data sets, and help them reach conclusions they might not otherwise have arrived at.
David said: The biggest reward is seeing the students grow as scientists and contribute to scientific knowledge, preferably by having fun most of the time even if hard work is involved.
Separately from the three questions given above, we asked a fourth question which centered on our interactions with human subjects (the most important aspect of our research from a compliance standpoint, and a common denominator across all our projects) within the framework of the 8D model. This fourth question also demonstrates an additional, distinct manner in which the 8D model can be applied. Since the topic of ethics is tangential to the theme of the other three questions, our dialogue on research ethics is presented in the Appendix.
What We Learned
From the above dialogue, it appears that the 8D model provided a sufficient framework for individual reflection and that the questions functioned as acceptable tools for comparing our experiences. Although the reflective process revealed specific information about past individual projects, there are several broader “big ideas” that emerge as well.
Importantly, yet perhaps predictably, we confirmed our initial suspicions that student experiences were very different from the experiences of staff and faculty. This was most apparent in the responses to questions 1b, 1c, and 3a. Similar dissimilarities have been reported by other teams using a dialogue-like process. In one example, graduate students thought about mentoring in terms of selecting good mentors; whereas, mentors framed it in terms of characteristics and development of mentors (Noor & Heil, 2012); yet, in another example, students in a summer research program perceived their biggest gains as being related to development whereas faculty mentors say their gains as primarily professional socialization (Hunter, Laursen, & Seymour, 2006). Thus several reasons including age, life experience, and career goals likely explain these differences.
Student members of our team were coming to the conversation with only one major experiment under their belt; whereas, staff and faculty members have worked with multiple students over multiple years, many of us having done so before coming to Drake University. Students who were exposed to multiple projects may have different perspectives, and some researchers have differentiated stages of personal development at the undergraduate level (Gonzalez, 2001); thus, students who had experienced multiple projects would likely had different responses. The staff and faculty in our team would like to point out that almost two dozen student research captains have passed through the lab in six years; we invited these three particular students to the conversation because they are exceptional and would provide thoughtful feedback.
What we learned about student experiences is that going through the process of individual introspection and then group-share facilitated by the 8D model better enabled all to see the laboratory through the students’ perspective. For the faculty and staff, this insight has prompted us to initiate more frequent and deliberate conversations with students about their experiences throughout the research process. We believe that other teams will gain similar benefits from employing the 8D model.
Staff & Faculty Experiences
Staff reflections were different from faculty reflections, as evidenced by comparing the responses in questions 1c, 2c, and 3b. Even though both faculty and staff are “university personnel,” research teams need to be aware of possible differences in experiences, expectations, and work stresses between these two groups (Horton, 2006). Because this manuscript is novel in its inclusion of staff members, there are no other studies to directly compare. Previously, we noted how blurred the line is between staff and faculty in the context of the post-secondary teaching environment (Cook-Sather & Shore, 2007). Though we found differences in some dialogue items, responses to questions 1a, 1b, 2a, 2b, 3a, and 3c were similar between staff and faculty.
What we learned about staff and faculty experiences is that the 8D model provided similar benefits in this respect as it did with student perspectives, though staff and faculty experiences were more similar to each other than either was to student experiences. Differences between staff and faculty responses were most apparent in those questions regarding how to improve personally or how to improve the laboratory experience whereas similarities were most apparent in regards to benefits gained from the experience.
Although our reflections did not explicitly touch on the following points, it is clear that this approach has provided several advantages beyond undergraduate research sensu stricto. For the staff and faculty, it provided teaching-research balance appropriate for teaching-focused schools such as Drake University, allowing personnel to meet both teaching and research missions (Parra, Osgood, & Pappas, 2010). This was reflected most clearly in the dialogue with regards to question 3, specifically 3c. The aforementioned balance also reinforced the synergy between faculty research and teaching quality that is well-documented elsewhere (Prince, Felder, & Brent, 2007); however, for such a relationship to work, the quality of both elements must be ensured (Chmielewski & Stapleton, 2009). Obstacles to this synergy and some possible solutions will be elaborated in the next subsection.
We believe these projects also solve the problem of providing genuine research experiences to both thesis and classroom students, as opposed to the spate of scullery tasks some report as their undergraduate research experience (P. Hunter, 2007). Combining the roles of peer mentor and researcher also augments undergraduates’ acquisition of content and skills, as noted previously (Sabatini, 1997), resulting in synergy at the student level. Some researchers have opined that the benefits to the research captain are much larger than for the individuals being mentored (Micari, Streitwiesser, & Light, 2006). Student responses to question 3c once more corroborate this inference.
More recently, we’ve refined our model well enough that student co- or first-authored publications are becoming more frequent and students are assuming larger responsibilities for them. Student-authored publications are rewarding for all parties involved—for the students they provide a sense of pride and evidence of work done, but for staff or faculty they supply evidence of effective mentoring and successful science (Burks & Chumchal, 2009).
What we learned about synergy is that the 8D model fostered both development and recognition of synergy for students, staff, and faculty alike, but in different ways. We believe that similar benefits would be experienced by other teams following the model so long as the pace of research is established by the students.
Research in Teaching Laboratory Contexts
In terms of how reflection facilitated by the 8D model prodded us to consider areas for improvement, members of our team believed that students should be more involved in both preliminary and concluding aspects of the experimental process (steps 1-2 and 7-8 in the 8D model, respectively). Responses to items 2b especially (because the question prompted direct reflection), 1b, and 3b evidenced this conclusion. Of all the outcomes from reflecting with the 8D model, this one perhaps generated the most follow-up discussion (and sometimes disagreement) among the staff and faculty.
The main contention was what is feasible in a typical laboratory classroom setting. The typical exercise science teaching laboratory (such as Bio 133L Kinesiology Lab or Bio 134L Exercise Physiology Lab at Drake University) enrolls 16 students to comply with University expectations; however, our physical space and equipment limitations, and the need to work closely with subjects, often necessitate dividing the students into two groups of eight that come during separate times. Each class meets 1.5 hours once a week, yielding 24 contact hours during a semester.
From an instructional planning standpoint, it is difficult to include all elements of the 8D model within those time constraints, especially considering that a typical sample size of 12-16 subjects is needed for robust findings and we can typically only accommodate two subjects within a given class period. Other research teams have articulated similar frustrations (Butler, Dong, Snyder, Jones, & Sheets, 2008; Desai et al., 2008). Another issue is timing associated with the IRB review process—if a class develops an experiment at the start of the semester, time is needed for the committee to review and for the students to revise proposals before experimentation can occur. With only 24 contact hours, this is a tall and, in most instances, intractable order. Indeed, even students noted timing constraints in their responses to question 1c.
Necessity has stimulated us to develop two creative solutions to this problem. The first solution we tried was to have all students within a lab section perform all elements of the 8D model but out of sequence. For instance, a class section may conduct a pre-formulated and IRB-approved experiment (starting at step 3 in the 8D model and moving through step 6) for the first two-thirds of the semester, analyze and present their findings for the culminating project of the lab (steps 7 and 8), but then spend one or two periods at the end of the semester brainstorming on follow-up or extensions which next year’s class could complete (touching on steps 1 and 2) and finally vote on what next semester’s class should research. Instructors then spend the break between semesters preparing and filing IRB paperwork for the next lab section so it is ready at the commencement of the following semester (if a student research captain is associated with the project, that student may or may not be involved in the paperwork process depending on individual circumstances). This approach has both strengths and weaknesses. It allows students to experience all aspects of the model, but it does so out of the natural sequence and in a way that students never feel the main project is “theirs.”
A second solution we developed more recently is to change how we wrote lab-associated IRB proposals such that they were broad and contained several mini-protocols that students could select from and customize; thus, students would elect to do just a portion of the protocol. Our first attempt at this second solution was this most recent semester. Under the framework of “shoe and sock testing,” we proposed and successfully obtained approval for an IRB that allows for 4-5 different tests in eight different exercise or sport contexts: basketball, baseball, gait analysis, gym exercises, running, soccer, track, and volleyball. Thus, even if two class sections chose the same sport context, they might still have different projects depending on what footwear they chose to test (baseball cleats of different stud configurations, or cleats of different heights, or cleats with different types of ankle straps, etc) and which elements of the protocol they deemed most appropriate to answering their question. Our one initial experience with this second solution was that such an approach was feasible in a half-semester time span and resulted in (perceived) higher levels of student ownership in the research.
What we learned about employing the 8D model in academic/teaching lab contexts is that typical class period and semester formats do not readily facilitate implementation of the model, at least with the caliber of experiment we employ. Such reflections prompted us to develop two solutions to the problem: either performing the steps of the 8D model out of sequence, or writing more general IRB proposals that allowed for project flexibility. Our experiences are prompting us to transition from the former to the latter because the latter better mirrors the actual scientific process. We hope that our experiences will save other lab teams, especially those of junior faculty members, from having to embark on similar troubleshooting ventures by providing them with alternatives that are conducive to the 8D model.
Research in Thesis Project Contexts
Another concern shared by some staff and faculty is the timing of thesis projects in relation to graduation, and again responses to questions 1b, 2b, and 3b echo these sentiments. Freshmen are often eager to jump right into a research project, but with a lack of the sophistication of understanding, maturity, or content knowledge necessary (Denofrio, Russell, Lopatto, & Lu, 2007); they also haven’t allowed themselves the opportunity to find the work-play balance required for college (Segal, Hanover, & Phillips, 1967). It is often not until the senior year that students are ready to fully undertake a research project, and the concerns discussed in the three preceding paragraphs once again come into play within a thesis research context. In comparison to the classroom laboratory context where the early steps of the 8D model are most difficult to implement, step 8 has consistently been the most problematic with thesis projects, especially when students are genuinely involved in the publishing process (Burks & Chumchal, 2009). The middle (data collection) steps may also be tricky if the experiment requires large chunks of contiguous time, difficult because of course scheduling.
Necessity has again encouraged us to develop possible solutions to this problem; in contrast to our troubleshooting with teaching labs, we’ve had larger variation in success with our solutions for thesis projects. One solution we tried is to divide a single student thesis project across three semesters (steps 1-2, 3-6, and 7-8). While this approach is perhaps the most pedagogically solid of our attempts, it requires that thesis students start during their junior year (which is not always practical and which also excluded students who are not ready until their senior year). Such approaches violate the typical two-semester senior year thesis model common at many schools and oftentimes pre-programmed into the curriculum (Ford, Bracken, & Wilson, 2009). Nevertheless, it has been the most feasible for our setting.
A second solution we tried is to have thesis students perform all steps of the 8D model but out of sequence. As discussed above within the classroom setting, in this option it is the thesis student that starts with step 3 of the 8D model and then makes recommendations for the next thesis student, and all the same advantages and disadvantages apply. Rarely, we’ve had instances where a student starts the model at step 7 or 8 (this is possible only when the student helped assist in another project and is familiar enough to analyze or present it before embarking on their own, and only occurs when the project’s research captain either graduates before completion of the project or produces too much data to process before graduation). Our experiences with this approach have been less favorable than other alternatives, and we’ve largely abandoned it except in rare instances.
A third possible solution we tried with even less success is to have younger students “shadow” older students prior to initiating their own thesis project; such an approach provides the student with more exposure than the traditional approach, but requires additional dedication and foresight from students early in their undergraduate career.
We will likely continue to utilize all three approaches based on individual student needs and preferences, but favor the first. An alternative not yet explored by our lab but advanced by others is to have a multi-year project where any individual student is responsible for just a portion (Henderson et al., 2008); this obviates problems such as obtaining sufficient human subject sample sizes in a small time frame because multiple students each test a fraction of the subject pool during their tenure (FitzPatrick & Campisi, 2009).
What we learned about employing the 8D model in the context of thesis projects is that thesis projects presented unique challenges from the teaching lab context, including how best to balance the logistical requirements of the experiment with the logistical realities of students’ lives. Of the three solutions we’ve explored, we’ve had best success with a temporal structure that divides the experience across three semesters starting sometime in the junior year. As with our teaching lab experiences, we hope our reflections will save other labs some troubleshooting time by providing them with thoughts on how to best weave the 8D model with current academic structures.
In this manuscript we presented a system (the 8D model) for fostering introspection by students, staff, and faculty jointly involved in an undergraduate exercise science research lab that allowed us to better understand each other’s perspectives. Not unexpectedly, students, staff, and faculty had different perspectives of the undergraduate research experience. “Time” was consistently identified as the major limiting factor to the experience. Direct communication by the students to the staff and faculty helped the latter groups better identify directions for future growth of the lab.
Advantages of the 8D model over previous models are many. First and most obviously, the 8D model is the first to value and include both instructional and technical staff members in the dialogue. To the best of our knowledge, no previous model has included staff voices. Second, the model serves as both a roadmap during the research process and a reflecting mirror afterwards; in the latter capacity, it provides a structured, formalized mechanism for dialogue. Third, the model does not necessarily depict the research process as linear but allows for doubling back such as encountered during experimental troubleshooting (steps 4-6). Fourth, the model is general enough that it can be applied to diverse settings, providing stability should the model be used by the same individuals over time.
Some disadvantages of the model can also be enumerated. The 8D model and four questions provided architecture for dialogue but to a certain extent excluded “free discussion,” which may have produced different information. We want to stress that there is nothing intrinsically special about the 8D model or these specific questions. We presented them here so that readers could understand the basis for our lab philosophy and how we approached this manuscript, and possibly so that other laboratory teams could use them in their own discussions or as a template for developing their own models and questions. It is possible to envision other offshoots for the model. For example, one reviewer for this paper suggested that the dialogue employed in this paper may represent a ninth “D”, a second debriefing stage in which all team members reflect on the lab.
The conversation presented in this manuscript has some limitations. Because we as an author team worked on different projects over multiple years, and are now spread out over three different states (all students having graduated), we were unable to converse as a single group of eight at any time during this project; instead, conversations occurred in pairs or small groups and were largely conducted by e-mail. If we had all co-worked in the lab simultaneously, our impressions may have been different or more consistent. On the other hand, the fact that we all experienced different projects perhaps yielded a more representative sample of the lab’s function.
This dialogue has demonstrated that the 8D model is a satisfactory vehicle for facilitating dialogues about undergraduate research experiences between faculty, staff, and students. It highlights the importance of such dialogue in improving laboratory experiences in terms of both better understanding each other and strengthening future endeavors. We hope that this manuscript serves as a catalyst for similar conversations within or between other undergraduate research labs both inside and outside of exercise science, whether those dialogues involve the specific models and questions employed here or similar vehicles.
Appendix: Application of the 8D Model to Human Subject Research
Question 4: Human experimental research subject ethics is an integral part of our work. (a) What aspects of human subject research ethics did students do well with (if any)? (b) What aspects of human subject research ethics should students improve in (if any)? (c) Could you provide some specific ways to accomplish this?
In contrast to previous questions, Question 4 was not only focused on just the student experience but also on the human research ethics component. Our laboratory’s success is directly contingent on the willingness of volunteers who participate in our studies, some of which involve intense or prolonged exercise bouts under artificial conditions. Human subject research ethics was important for us to investigate. All students who participate in our laboratory are expected to undergo a three-step training process which involves (1) an interactive lecture focusing on basic human research guidelines such as the Belmont principles, recruitment, confidentiality, safety, and administrative oversight; (2) an activity-based video where students examine a case study (Senchina, 2011); and (3) completion of one of two online training modules, one developed by the US Institutes of Health Office of Extramural Research (http://phrp.nihtraining.com/) and the other by the CITI program (http://www.citiprogram.org).
Regarding Question 4a, all three students in our group identified ensuring subject safety and promoting subject comfort (e.g., feeling comfortable in the laboratory setting with the procedures taking place) as the aspects they and their peers were most successful in accomplishing, but their responses were experiment-specific.
Rachel said: Students in general made sure that the participants in the study were comfortable throughout the running and resting periods. If the participants felt uncomfortable running with the temperature probes, students would re-tape the probes so that participants felt comfortable running.
Staff and faculty comments mirrored those of the students.
Angie said: The students did everything possible to make sure the subjects will not be injured including careful experimental techniques and monitoring weather conditions during testing times.
Heath said: I thought the students showed the proper respect for the subjects in their study and were able to make the subjects feel comfortable.
Regarding Question 4b, students had differing responses, with the biggest disagreement being how well the student-investigators attended to the subjects. These differences are understandable because each of the student research captains worked with different groups of students.
Evan said: The students who participated were trained to give the subjects their utmost attention and constantly examine the lab area to ensure the safety of those participating.
Rachel said: One thing to work on in the future with students collecting data would be to maintain their focus on the participant and the data being collected. There were probably too many students involved in data collection per participant. This tended to cause conversations to be among the student data collectors rather than involving the participant. It also may have resulted in inconsistencies for exact timing of data points since sometimes students did not pay attention to the timing, as they were too involved in conversation.
Staff and faculty members had quite different reactions to Question 4b. Chris expressed a general concern about undergraduate research experiences generally.
Chris said: With the advances in technology and social media, confidentiality may be more of a concern for participants especially at smaller institutions where many individuals interact throughout a large portion of the student population. Students may be inclined to post images or information regarding participants involved in a study without realizing the legal implication, although this ethical concern was not noticed during this particular study.
David said: I agree that students need to be more attentive to the subjects and less chummy amongst themselves. Another area we could improve on is being more diligent in offering towels and water/sports beverages to the subjects.
Our comments on Question 4c directly addressed items raised in Question 4b.
Rachel said: Reducing the number of students involved in collecting data for a single participant may help to keep the focus on the participant. This may also provide a safer environment for the participant.
Eric said: Obviously, it is vital to address these issues with the student researchers prior to collecting participant information and data collection. This discussion should involve why all participant personal information is confidential and the legal ramifications for divulging any information regarding a participant through any media or conversation.
All authors contributed to the writing of the manuscript. Trisha VanDusseldorp, Evan, Eric, and David served as experimenters or subjects in the photographs. Figure photographs were taken by Eric and his son Jack Swafford. We thank the faculty within the Drake University Biology Department for relinquishing the use of and remodeling a former teaching laboratory so we could have a permanent space for our research in 2008.
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Considering the project overall, did it (a) match up with the 8D model or not? (b) Which aspects of the 8D model did we succeed the most in, and (c) which aspects do we need the most improvements in?