Exploring student preferences with a Q-sort: the development of an individualized renal physiology curriculum

Abstract

Medical education reform is underway, but the optimal course for change has yet to be seen. While planning for the redesign of a renal physiology course at the Duke School of Medicine, the authors used a Q-sort survey to assess students' attitudes and learning preferences to inform curricular change. The authors invited first-year medical students at the Duke School of Medicine to take a Q-sort survey on the first day of renal physiology. Students prioritized statements related to their understanding of renal physiology, learning preferences, preferred course characteristics, perceived clinical relevance of renal physiology, and interest in nephrology as a career. By-person factor analysis was performed using the centroid method. Three dominant factors were strongly defined by learning preferences: “readers” prefer using notes, a textbook, and avoid lectures; “social-auditory learners” prefer attending lectures, interactivity, and working with peers; and “visual learners” prefer studying images, diagrams, and viewing materials online. A smaller, fourth factor represented a small group of students with a strong predisposition against renal physiology and nephrology. In conclusion, the Q-sort survey identified and then described in detail the dominant viewpoints of our students. Learning style preferences better classified first-year students rather than any of the other domains. A more individualized curriculum would simultaneously cater to the different types of learners in the classroom.

medical education in the United States is evolving to account for changing attitudes towards learning and accountability. Education leaders have called for standardized outcomes, individualized learning, and classrooms that better integrate the clinical experience (16). Despite local curricular innovations at many medical schools, the optimal preclinical curriculum has yet to be defined.

Curriculum redesign has important professional implications for those in the practice of clinical medicine. In nephrology, for example, educators are concerned about student interest because National Residency Matching Program data from 2009 to 2014 show a 44% decline in the total number of applicants to nephrology programs and a fourfold increase in the number of unfilled nephrology training programs (27). Surveys of internal medicine subspecialty fellows showed that those who did not choose nephrology think that the care of patients with kidney disease is “too complicated” (18). Almost one-third of the respondents also thought renal physiology was the most difficult course in medical school, with acid-base disorders and electrolyte disorders cited as the most difficult topics to grasp (18). In this context, we sought to redesign our renal physiology course for first-year medical students to both meet the call for education reform and recapture interest in the role of the kidney in human health and disease. However, we knew that a robust assessment of our students was required before any curricular planning.

The first step in curriculum design is performing a targeted assessment of the learners (19). Electronic questionnaires with Likert scales are a popular method to survey learners for this purpose. However, Likert scale survey validity has been called into question (17). Research on attitudinal assessment with the Likert scale has shown that responses are influenced by survey structure, question characteristics, category characteristics, and response scale factors, all of which can potentially lead to systematic error and misguided interventions (2, 21, 23, 29).

Q-methodology, on the other hand, overcomes some of these barriers when measuring attitudes and opinions. Introduced in 1935, Q-methodology is a hybrid qualitative-quantitative research technique where participants provide meaning to statements through a sorting procedure (42, 43). In this type of survey, subjects are active participants who define themselves rather than being defined by a researcher's prior knowledge or understanding. Factor analysis of the data provides the means to account systematically for participant subjectivity, identifying the characteristics of each belief system in the sample (1, 4). Q-methodology was borne out of social science research, but its application has now expanded to a variety of disciplines, including higher education (37, 38), nursing education (33), and medical education (11, 26, 36, 44).

In preparing the redesign of the curriculum for the renal physiology course at the Duke University School of Medicine, we sought to evaluate our learners using Q-methodology. In addition to student interviews and mandatory course evaluations, we chose to use a Q-sort survey to assess our students' preferences across five domains: comprehension of renal physiology, personal learning preferences, course preferences, perceived clinical relevance of renal physiology, and interest in nephrology as a career. We thought that a Q-sort survey would reveal patterns of beliefs and preferences that would directly inform how to effectively redesign the renal physiology curriculum.

METHODS

Q-methodology.

To explore our students' attitudes as they entered renal physiology, we used Q-methodology, which is a quantitative-qualitative approach to measure subjectivity in humans. Using a form of multivariate analysis, a Q-study is designed to extract the number of viewpoints in a sample while identifying both the distinctions and similarities between each viewpoint. Participants in a Q-study create Q-sorts by placing a series of prepared statements onto a score sheet that has been ranked with columns representing the spectrum from most disagree (−4) to most agree (+4). In our study, participants were forced to place statement cards into the required number of spaces assigned under each column (see Fig. 1, A and B). This design requires participants to closely consider each statement carefully, which will be especially true for statements placed at each tail of the score sheet. A Q-sort is complete when all statements have been ranked. In addition to the Q-sort, participants are asked to provide narrative commentary on the two statements ranked at each extreme. All of the Q-sorts in a Q-study are then subjected to by-person factor analysis, where similar Q-sorts are correlated together into a unique factor. By looking at the defining statements within each factor, the viewpoint is easily discerned. The student narrative is then used to supplement interpretation and understand the reasons behind statement ranks. Comprehensive reviews of Q-methodology and its subsequent analysis have been written by McKeown and Thomas (25) and Watts and Stenner (45).

Fig. 1.

A: Q-sort score sheet for 37 statements with a forced pattern of distribution. Participants placed each statement card in a position of the score sheet to represent his or her level of agreement with the statement (from most disagree to most agree) until the diagram was complete (B).

Definition of the statement set.

The statements used in a Q-study need to be carefully crafted to represent the concourse of opinions present on a given topic. In our case, we created a statement set that represents a variety of issues relevant to learning renal physiology in an undergraduate medical curriculum. To inform our statement set, we first reviewed medical student course evaluations of renal physiology courses from the past 2 academic years (2011–2012 and 2012–2013) from our institution and another peer academic institution. These course evaluations included both Likert scale ratings on multiple items and unstructured student commentary. Student commentary was notable for variable preferences for live lectures, strong preferences for text/annotated supplements to slides, and attitudes about renal modules being the most difficult courses in medical school. Next, we examined peer-reviewed journal articles related to student and resident interest in nephrology. Among these, statements were informed by survey data and editorials that reflect medical student opinions of nephrology, renal physiology, and difficult concepts in preclinical renal courses (14, 18, 31, 32, 40, 41). We also included survey data related to medical student learning preferences and behaviors regarding lecture attendance and video streaming (3, 7, 13). We were also interested in self-perceived learning styles according to a learning style paradigm referred to as VARK (10). This model identifies visual and symbolic learners (V), aural learners (A), learners who prefer to read and write (R), and, finally, kinesthetic learners (K). We reviewed the current literature regarding VARK learning styles in preclinical medical students (20, 24, 28, 34). These studies found that a majority of students (range: 60–79%) have multimodal preferences, whereas the remaining students have preferences for just one of the four modalities. Because our renal physiology learning objectives pertained to medical knowledge and high-order cognitive skills rather than psychomotor skills, we were primarily interested in the visual, aural, and read/write learning styles. After reviewing all of these resources, we identified five major domains of thought for students taking renal physiology: the student's comprehension of renal physiology, learning styles/preferences, course characteristics, perceived clinical relevance of renal physiology, and perception of nephrology as a career. The primary researcher (J. K. Roberts) formulated an initial set of 10–12 statements within each domain. All statements were crafted and adjusted so that they were legible, unambiguous, and not overly positive or negative in tone. Finally, both R. W. Lehrich and J. K. Roberts refined, deleted, and combined statements to arrive at a final set of 37 statements (see Table 1). This specific number was necessary to fit within the matrix used for the sorting procedure (see Fig. 1, A and B).

Table 1.

Q-sort statements organized by domain of interest, with overall mean rank score for all responses, and the number of times each statement was ranked in the extremes

Q-Sort Statements	Mean Score for All Q-Sorts	Number With Strong Agreement (+4)	Number with Strong Disagreement (−4)
Personal understanding of renal physiology
I am satisfied with how well I understand physiology	−0.53	2	6
The kidney makes sense	−0.12	0	2
Nothing is too difficult for me to learn	+1.22	8	0
The kidney is a black box	−1.35	0	3
I do not understand acid-base disorders	+0.10	2	0
I enjoy thinking about electrolyte problems	−0.43	0	3
I usually feel prepared for class	−0.95	0	2
Relevance of renal physiology
By graduation, I should know how to interpret lab tests correctly	+2.55	14	0
I will likely have to care for patients with kidney disease	+0.87	10	2
Too much of what we are taught is not clinically relevant	−1.35	1	1
It is important for me to understand the kidney	+2.28	14	1
After this course, I can forget about the kidney	−2.78	0	28
Learning preferences
I prefer to learn trough reading or writing notes	+1.50	9	0
I am a visual learner	+1.48	8	0
I am an auditory learner	−0.47	1	9
I learn much of what is needed for class from attending the lectures	−0.95	1	5
I learn much of what is needed for class from textbooks	+0.73	10	2
I learn much of what is needed for class from online lectures and videos	−0.48	4	3
Interactions during class help me understand concepts	+0.57	6	2
I learn better when I'm by myself	+0.98	2	1
It is worth my time to come to class	−0.25	1	3
I learn better when I'm around other students	−0.2	1	2
I learn in my own unique way	0.75	4	0
Going to class is a waste of my time	−0.77	1	6
Course characteristics
Our lectures are stimulating	+0.15	1	1
Our instructors don't seem to enjoy teaching	−2.30	0	13
Physiology is easier than other courses	−1.28	1	4
The school supports students with different learning styles	+2.03	9	0
Our lectures are well organized	+0.30	0	2
All of my questions get answered	+0.22	1	0
I wish other courses were taught like this one	−0.47	0	2
I have enough to time to keep up with everything	−1.43	0	12
Interest in nephrology
I have a good idea of what a nephrologist does	−1.47	0	2
I would like to learn more about nephrology as a career	−0.15	2	2
I would be willing to shadow a nephrologist	+0.62	0	1
I am unfamiliar with the procedures a nephrologist performs	+1.02	4	0
I would like to hear about kidney disease research	+0.37	3	0

n = 60 responses.

Study participants.

The target audience was first-year medical students at Duke University School of Medicine. We administered the survey to the entire first-year class (class of 2017) in November 2013 while they were taking a course on normal body physiology. The survey was administered on the first day of the Renal Physiology module. Students had already completed cardiovascular, pulmonary, and gastrointestinal physiology modules. This class was composed of 113 students, with roughly equal numbers of male students (52%) and female students (48%).

Q-sorting procedure and student commentary.

We delivered our survey using FlashQ (version 1.0, Hackert and Braehler), a free, web-based program designed to both administer a Q-sort and electronically record the data. We invited students to take the survey on the morning of the first day of the renal physiology course. Participation in the survey was voluntary and separate from Duke School of Medicine-mandated course evaluations administered at the conclusion of the course. After an introduction with instructions for the survey, FlashQ randomly presented each of the 37 statements as a card to be sorted into 1 of 3 initial piles: agree, neutral, or disagree. Next, the student was asked to pull cards from these piles and place them into Q-sort diagram columns rated from strongly agree (−4) to strongly disagree (+4). Participants were given one last option to swap card positions across the diagram so they more closely match his or her subjective viewpoint. At the conclusion of the survey, all columns on the score sheet were fully occupied by statement cards (see Fig. 1B). Finally, participants had the opportunity to provide written commentary on the most agreed and most disagreed statement selected from the Q-sample. We stored the data from FlashQ in a deidentified text file on a secure server within our institution's information technology department. The Duke Institutional Review Board deemed this survey exempt from review (Project 00049444).

Factor analysis.

We used PQMethod software (version 2.33, Schmolck), which permits by-person factor analysis. We transformed the data file containing 60 sorts from FlashQ into a format compatible with PQMethod software, which then created an intercorrelation matrix for the participants. We extracted four factors using the centroid method and performed varimax rotation on all four factors to simplify the factor structure. A “defining factor” was any sort that loaded significantly (γ > 0.32 for a 95% confidence interval) on only one unique factor.

RESULTS

A total of 113 students received the invitation to the Q-sort by e-mail, and 60 unique surveys were submitted (53% response rate). The mean rank score for each statement (on a scale from −4 to +4) is shown in Table 1, along with the number of times each statement was placed in the strongly agree (+4) and strongly disagree (−4) columns. Agreed statements with the highest overall means pertained to the relevance of renal physiology: “By graduation, I should know how to interpret lab tests correctly” (+2.55) and “It is important for me to understand the kidney” (+2.28). Disagreeable statements with the lowest mean scores were “After this course, I can forget about the kidney” (−2.78) and “Our instructors don't seem to enjoy teaching” (−2.30).

Fifty-three students (88%) provided commentary on the four statements ranked at the strongly agree (+4) and strongly disagree (−4) columns. This resulted in a total of 210 unique comments (one student left two comments instead of four). Table 2 shows these statements with examples of the associated student commentary. The most frequent statements that were ranked with in the +4 column indicated favorable attitudes toward the renal system, the desire to interpret laboratory tests correctly, and caring for patients with kidney disease in the future. Other statements ranked as +4 agreement showed that students have diverse preferences for different learning styles. The most frequent statements that were ranked in the −4 column are also shown in Table 2. Many students again showed a favorable disposition toward learning about the renal system, and they had very favorable attitudes toward their instructors. Students also indicated having difficulty with time management, and some found attending lectures to be inefficient or ineffective for learning.

Table 2.

Summary of commentary from statements ranked at both extremes

Statements	Number	%	Sample Student Comments
Strong agreement (+4)
It is important for me to understand the kidney	14	12	Renal physiology impacts a lot of organ systems simultaneously, and so it's important for me to understand it.
By graduation, I should know how to interpret lab tests correctly.	14	12	We will have to interpret lab tests correctly as future interns/residents, and I think it would therefore be imperative that we learn it as early as we can so we can do well in residency
I learn much of what is needed for class from a textbook	10	8	Reading a textbook is better for me than lectures because the textbook doesn't assume that you have any previous knowledge of the material, whereas lectures tend to only help if I have an idea about the subject.
I will likely have to care for patients with kidney disease.	10	8	Kidney disease is a real and common problem that, no matter what specialty I choose to enter, I will likely have to deal with.
I prefer to learn through reading or writing notes	9	8	I remember things most when I write them down or draw them out.
I am a visual learner	8	7	I need to draw pictures or concept maps in order to understand what I am taught. Watching videos that explain concepts visually (i.e., a “cartoon” with moving colors and shapes) is vital for me to internalize an idea.
Nothing is too difficult for me to learn	8	7	I think as long as I have good learning materials and enough time I can understand any concept
I learn much of what is needed for class from online lectures and videos	4	3	Streaming allows me to go back to points that I miss or don't understand which prevents episodes of misunderstanding a whole lecture because of missing a certain important point.
Strong disagreement (−4)
After this course, I can forget about the kidney	28	23	The renal system is important in filtering the blood and many/most/all systems will be affected by kidney problems.
Our instructors don't seem to enjoy teaching	13	11	I think all of our instructors are very passionate and extremely engaged in teaching. This is very evident.
I have enough time to keep up with everything	12	10	The rapid pace often means that I have to skip over certain details and lectures in order to "stay afloat" and understand the bigger picture.
I am an auditory learner	9	8	I drift off in class and end up missing something that was supposed to connect two pieces of information. Then it's a complete train wreck.
Going to class is a waste of my time	6	5	I enjoy going to class mainly because being present with the lecturer and everyone somehow makes this more memorable and more special experience, instead of just staring at a recording at home.
I learn much of what is needed for class from attending the lectures	5	4	Sometimes I don't even remember what was said in lecture immediately after lecture when I take notes and when I don't take notes.
Physiology is easier than other courses	4	3	Physiology integrates all of the sciences and demands that we fully understand concepts. This is the most difficult part about medicine.
It is worth my time to come to class	3	3	Lectures are posted online and I can stream them at my own pace. This allows me to pause if I need to process information and to look up additional information if I am confused, which allows me to get the most out of the lectures.

n = 60 students submitted Q-sorts; 53 students provided ≤4 comments each.

Factor analysis.

Factor analysis of the Q-sort data was performed to identify which statements correlated together and to distinguish students into different viewpoints (or factors). The 60 submitted Q-sorts supported the extraction of four factors. The first, second, and third factors were the dominant viewpoints defined by 18, 17, and 8 unique sorts, respectively. Despite having moderate correlation between these three factors (0.44, 0.55, and 0.58), each factor represented distinct viewpoints in the sample. The fourth factor was defined by five sorts and correlated less with the other three factors (0.22, 0.26, and 0.29). In total, these four factors explained 55% of the total variance in the 60 Q-sorts.

Table 3 shows the statements that define the first factor, which we have identified as the “social-auditory learners.” These students value attending class and prefer to learn from interactions that occur during class. They are satisfied with current lecture organization, they find lectures stimulating, and they think their instructors enjoy teaching. These students feel they are able to efficiently learn by attending lecture. Furthermore, these students think they learn better when interacting with peers. In addition to lectures, however, they also prefer to learn by reading or writing their own notes associated with the course. They initially have poor understanding of kidney function, but they value the importance of the kidney to their future careers.

Table 3.

Defining statements of the social-auditory learner

Statement	Sort Value	Z-Score
5. I learn much of what is needed for class from attending lectures	3	1.14*
14. Interactions during class help me understand concepts	2	0.87*
32. Our lectures are well organized	2	0.74*
2. I prefer to learn through reading or writing notes	1	0.52*
28. I learn better when I'm around other students	1	0.51*
4. Our lectures are stimulating	1	0.49
18. I learn better when I'm by myself	0	−0.03*
19. I do not understand acid-base disorders	−1	−0.50*
9. I learn much of what is needed for class from a textbook	−1	−0.62*
23. The kidney makes sense	−2	−0.72
1. I am satisfied with how well I understand physiology	−2	−0.72*
12. Too much of what we are taught is not clinically relevant	−3	−1.45*
30. Going to class is a waste of my time	−3	−1.64*
10. Our instructors don't seem to enjoy teaching	−4	−2.01*
36. After this course, I can forget about the kidney	−4	−2.42

n = 18 students. All were significant at P < 0.05;

^*significance at P < 0.01.

Table 4 shows the ranked statements that define the second factor, who we call the “readers.” These students value learning from a textbook or written notes. From the commentary provided, students in this factor thought that textbooks provide the “big picture” and assume less about prior knowledge, as opposed to lecturers (see Table 2). This student is also quite confident about their learning because they feel “Nothing is too difficult for me to learn.” They do not identify as an auditory learner, they do not prefer attending lectures, and interactions during class are less helpful in understanding concepts. These learners value having long-term knowledge of the renal system as they also think they will have to care for patients with kidney disease.

Table 4.

Defining statements of the reader

Statement	Sort Value	Z-Score
9. I learn much of what is needed for class from a textbook	4	1.83*
24. Nothing is too difficult for me to learn	2	0.89*
22. I will likely have to care for patients with kidney disease	1	0.58
23. The kidney makes sense	0	0.15
20. I enjoy thinking about electrolyte problems	0	0.10*
1. I am satisfied with how well I understand physiology	0	−0.19*
14. Interactions during class help me understand concepts	−2	−0.82*
5. I learn much of what is needed for class from attending lectures	−3	−1.64*
7. I am an auditory learner	−4	−1.86*
36. After this course, I can forget about the kidney	−4	−2.01

n = 17 students. All were significant at P < 0.05;

^*significance at P < 0.01.

Table 5 shows the ranked statements that define the third factor, the “visual learners.” This student self-identifies as a visual learner and primarily prefers to learn from online videos related to the course. Compared with the others, students in this factor feel distinctive by agreeing with the statement “I learn in my own unique way.” In addition, students in this factor feel like they are falling behind in class, as they strongly disagreed with the statements “I usually feel prepared for class” and “I have enough time to keep up with everything.” Both of these statements did not significantly rank within any of the other factors identified, making this a characteristic of visual learners. Compared with the readers and social-auditory learners, this group was the least satisfied with their understanding of physiology (see Table 5).

Table 5.

Defining statements of the visual learner

Statement	Sort Value	Z-Score
3. I am a visual learner	4	1.88*
13. I learn much of what is needed for class from online lectures	3	1.14*
29. I learn in my own unique way	2	1.09
8. It is important for me to understand the kidney	1	0.91*
17. I am unfamiliar with the procedures a nephrologist performs	0	−0.10*
28. I learn better when I'm around other students	0	−0.15
23. The kidney makes sense	−1	−0.30
5. I learn much of what is needed for class from attending lectures	−2	−1.06*
36. After this course, I can forget about the kidney	−2	−1.29*
6. I usually feel prepared for class	−3	−1.33*
1. I am satisfied with how well I understand physiology	−4	−1.60*
35. I have enough time to keep up with everything	−4	−2.00*

n = 8 students. All were significant at P < 0.05;

^*significance at P < 0.01.

The fourth factor we extracted was a viewpoint shared by a minority of students we call “predestined students.” The ranked statements in Table 6 show that these students indicated a high comprehension of renal physiology at the start of the course and they slightly agreed with the statement “After this course, I can forget about the kidney.” They do not anticipate caring for patients with kidney disease, and they are not interested in shadowing a nephrologist or learning more about nephrology as a career.

Table 6.

Defining statements of the predestined student

Statement	Sort Value	Z-Score
2. I prefer to learn through reading or writing notes	4	2.17*
24. Nothing is too difficult for me to learn	3	1.67*
1. I am satisfied with how well I understand physiology	2	1.01*
23. The kidney makes sense	2	0.77
36. After this course, I can forget about the kidney	1	0.35*
12. Too much of what we are taught is not clinically relevant	1	0.16*
5. I learn much of what is needed for class from attending lectures	0	−0.04*
8. It is important for me to understand the kidney	0	−0.21*
30. Going to class is a waste of my time	−2	−0.89*
16. I would be willing to shadow a nephrologist	−3	−0.95*
15. I would like to learn more about nephrology as a career	−4	−1.76*
22. I will likely have to care for patients with kidney disease	−4	−2.29*

n = 5 students. All were significant at P < 0.05;

^*significance at P < 0.01.

DISCUSSION

This is the first report of a successful application of Q-sort to understand the learning preferences of medical students to guide the reorganization of medical school curriculum. We constructed our Q-sort survey to assess attitudes in the domains we thought were relevant to learning physiology; however, we did not know which were the most important or relevant to a current student's experience. Exploratory factor analysis with a Q-sort is notable in that it does not require a priori hypothesis testing. It is constructed to let the students define themselves by sorting a series of statements. In this case, it revealed that the most discriminating opinions among first-year medical students related to the students' self-identified learning preferences, rather than any of the other domains we prespecified.

The majority of respondents value learning about renal physiology and kidney disease, they anticipate caring for patients with kidney disease, and they value being able to interpret laboratory tests correctly. We are reassured that the majority of students enter the course with the belief that renal physiology is highly relevant to their future. For these students, expanding the learning process through different learning styles may be more valuable than addressing attitudes toward the course content. On the other hand, we did identify a minority of students who appear to not share these favorable feelings. These predestined students may have very specific career plans that (they perceive) do not require knowledge of the renal system. For these students, we are unsure if they already have required knowledge for the course or if they have developed negative learning attitudes that have implications for other courses. This suggests that in many preclinical courses, there may be a minority of students with predetermined beliefs and/or career plans that could impact engagement and motivation. Thus, teaching innovations and curriculum redesign should consider instructional methods to activate these students.

Many educators have studied the learning process with regard to student learning preferences or “styles.” Although learning style theories seem intuitive, it has not been proven that style-based instruction improves learning ability. In fact, the available evidence suggests that there is no relationship between learning styles and academic performance (30, 39, 46). Within medical education, a randomized, crossover trial of residents and medical students found no effect of learning styles or cognitive styles on test performance after a web-based module (8). One critique to learning style theories is the certain fact that some subjects are best taught visually, verbally, or both (39). Thus, as the content, context, or course instructor changes, any effect of style-based instruction may be difficult to quantify, should it even exist.

Despite the sobering evidence regarding learning styles and learning ability, students continue to have strong feelings about their own learning preferences and self-perceived learning efficacy. Under the VARK paradigm, the majority of medical students are unsurprisingly multimodal; they are able to use many styles simultaneously (20, 24, 28, 34). It is plausible that high-achieving students like medical and graduate students need to be multimodal to succeed in a variety of academic contexts, independent of whatever preferences they actually hold. Despite this, the self-identified preference for visual or verbal modes has been shown to correlate in real time with modality-specific cortical activity during a visual-verbal cognitive task (22). In other words, preferences for visual or verbal stimuli are not just “in our heads,” they are literally in our heads.

Even though the majority of medical students describe themselves as multimodal, many will show preferences for a single mode if given the opportunity to rank order choices, as we have shown through our Q-study. In conjunction with the students' statement-specific commentary, we are also more apt to understand context-specific preferences of our students and perhaps move closer to an optimal preclinical physiology curriculum. In undergraduate physiology, VARK learning styles do not correlate with exam performance (9, 15). One study found that lecture attendance was weakly correlated with academic performance, and the use of alternative learning resources to substitute lecture attendance was associated with improved exam performance (15). Thus, for content that can reasonably be presented via different modalities, such as physiology, there could be important benefits to providing materials in multiple formats. As exam performance may not be dependent on style-based instruction, other factors, such as learning efficiency or long-term retention, may be impacted significantly.

Curriculum redesign.

The current generation of medical students desires an individualized learning process. One study found that some medical students prefer video-recorded lectures to live lectures because they can learn more efficiently with videos (save time), watch them at any time of the day (provide flexibility), and watch at a customized pace (watch at accelerated 2× pace or pause to look up information) (7). A separate study at a single medical school found that 17% of students routinely attend all lectures, whereas the remaining 83% perform a cost-benefit analysis to determine attendance (3). Students are constantly appraising the quality of the lecturer, the presence or absence of active learning methods, and characteristics of the subject matter to decide whether it is worth their time to attend or not (3, 13). However, there appears to be a minority of students who consistently attend all lectures. These students appear to uniquely benefit from attending lectures and interacting with peers, but other factors, such as the desire to socialize and the fear of missing important information, are also present (7, 13). In light of these results, it is easy to appreciate the frustrations of today's medical student. With each new course or instructor, they must immediately appraise the time and energy cost of different learning resources with the perceived learning benefits. As courses, instructors, and available learning resources change over time, so does student behavior.

With our mixed-methods approach to assessing student preferences, we quantified the viewpoints in our course using the Q-sort survey. Within each viewpoint, intercorrelations between statements as well as the associated commentary provided us a rich and detailed understanding of our medical students' experiences. For example, the social-auditory learners were the only factor who had favorable attitudes toward lecturers, active learning methods, and learning with peers. Thus, they were the only group who thought it worth their time to attend lecture. On the other hand, the readers felt strongly about not attending lectures and they felt like they did not learn best from auditory information. In the associated commentary, these students praise textbooks/notes for both not assuming prior knowledge and giving them the opportunity to move at their own pace. The visual learners also felt strongly about not attending lectures and instead preferred watching online videos. The corresponding student narrative showed that they valued adjusting video speed and using pause/rewind functions to personalize learning (see Table 2). Interestingly, the visual learners were the only students who did not “feel prepared for class,” and they disagreed with having “enough time to keep up with everything.” This suggested to us that the visual learners may be having the most difficulty finding appropriate learning resources and navigating the cost-benefit analysis of lecture attendance. These insights directly informed how we were to proceed with course reorganization.

The individualized physiology curriculum.

At our medical school, physiology is traditionally taught via large group lectures, video-recorded lectures, and clinically oriented sessions, such as team-based learning activities. To better foster individualization, we created a renal physiology course that will simultaneously cater to various students. We are now providing the foundational content in three different formats: lectures delivered by course instructors, mini-chapters written by the same instructors, and online video tutorials (or “pencasts”) that heavily use drawings, diagrams, and graphs to explain core physiological concepts. Students can use whatever content they prefer, and all of the notes and videos are available at the start of the course. In addition to the lectures, we created interactive in-class experiences where we will use active learning methods such as in-class assignments, case discussions, and simulation to connect the content to clinical practice. These case-based sessions are the optimal venues to demonstrate the importance of physiology on seemingly unrelated specialties or disciplines.

This approach is innovative in that students can choose to learn fundamental content according to personal learning preferences while reaping the benefits of both interactive sessions and clinically oriented teaching. Because the instructors share authorship in all of the fundamental course materials, students can choose to use one or any combination of resources and not miss important information. The social-auditory students can continue to attend lectures as they desire, but students who find it inefficient to attend lectures can substitute them with alternative materials (notes or video tutorials), which has been correlated with improved exam performance (15). With this degree of freedom, some students may elect to read the notes or view the pencast tutorials before lectures, a format known as the “flipped” classroom (35).

Limitations.

It is important to highlight the limitations and unique features of our study. It should be noted that Q-methodology is a methodology that can be difficult to understand. Many criticisms of Q-methodology relate to poor understanding of the procedure, and these have been comprehensively addressed by Brown et al. (6). The purpose of a Q-study is not to estimate population statistics, but rather to identify and explore the various perspectives on a given topic present in a group (4). The design of a Q-study is such that the participants' subjectivity is front and center; only the participant of a Q-study has access to his or her subjective experience during the card sorting activity, and the role of the researcher is thus minimized (4, 6). Because of this unique design, Q-methodology is thought to be a highly valid measure of subjectivity, and test-retest reliability of Q-sorts has been shown to be 0.8 or higher (4, 5). However, since our results are based on subjectivity, it should be emphasized that perceptions of learning or value do not equate to actual learning or value. On the other hand, because our student participants were 4 mo into the first-year of medical school, they had enough experience to develop meaningful preferences from accurate self-assessment. Because our Q-sort data were deidentified, we were unable to correlate Q-sort results to measures of academic performance, such as grade point average or standardized test scores. Next, our response rate was 53%, and our analysis may not necessarily be representative of the entire class. One benefit of Q-methodology is that the results are less dependent on the number of participants but more dependent on the characteristics of the statement set (4). For example, the true concourse of opinions on learning renal physiology is theoretically infinite, and our statement set is a limited sample of this concourse. We developed a quasinaturalistic statement set as it was derived from sources (publications, editorials, and course evaluations) external to our study (25). It is likely that our statement set did not cover all possible issues or subissues related to learning renal physiology, and it is possible that unintentional bias could have been introduced into the statement structure. Imbalance in the statements (too many overtly positive or negative statements) can also introduce bias into the results of a Q-study. In our study, we found that initial card sorting into agree, neutral, and disagree piles produced a mean of 15, 11, and 10 cards, respectively, which reflects reasonable overall balance. One statement, “After this course, I can forget about the kidney,” was a strongly disagreed statement (ranked at −4) in 28 of the sorts. This statement was likely worded too strongly as it represents a very extreme viewpoint. This did not impact factor analysis as the presence of a strong statement in the sample does not detract from identifying other important differences between viewpoints. Finally, this study was completed at a single medical school, where our students' attitudes may be specific to our student population and not as generalizable to other student cohorts.

Implications.

It is common knowledge that students are heterogeneous in many attributes. Using a self-sorting procedure, we found that the current medical students are best distinguished according to different preferences for visual, social-auditory, and read/write learning styles. Even though students adapt to different learning modes, our results reinforce the fact that students do place different values on the different learning modalities. To optimize and individualize learning, we redesigned our renal physiology course by replicating foundational material in three different formats to simultaneously cater to disparate learning styles. We made lecture attendance optional, provided detailed course notes, and created new pencast tutorials that heavily use visual stimuli. Offloading content from live lecture into these other formats could potentially free up class time for unique and active learning experiences. In this format, we have planned interactive clinical correlations and simulation sessions to foster active learning and place the physiology into a clinical context.

To implement such a change requires the upfront creation of these new resources. In our case, each hour of lecture required us to create 8–12 pages of notes and 2–4 video tutorials (each 8–12 min in length). This duplication of content can be time intensive and require new resources or technology. However, we have found this process to be complementary rather than additive with regard to time. An experienced lecturer for a given topic can likely create notes or subchapters with minimal effort. Instructional tutorial videos can be easily created with free or inexpensive software, and one recent study (12) has already identified the best practices to enhance student engagement with instructor-guided videos. Updating a large course or curriculum would certainly require faculty development, administrative, and technical support. The courses that would benefit the most from a multimodal approach would be knowledge-stable subjects that could reasonably be taught in different formats. Physiology is prototypical; we do not expect current physiology knowledge to be outdated anytime soon (ensuring the longevity of resources), and the integration of biochemistry, cell biology, and multiple organ systems makes physiology visually captivating and clinically important.

It has been shown that intrinsic learning ability is not dependent on learning styles, but supplementing courses with alternative materials appears to improve performance (15). Providing multimodal learning resources in a physiology course could allow students to customize learning and potentially improve learning efficiency, long-term retention, and overall course satisfaction in a way that transforms the quality of undergraduate medical education. Our Q-sort defined medical student viewpoints, which helped us create an individualized learning curriculum, which can possibly impact the overall learning process. We plan further studies to determine if these changes will have an impact on performance, learning outcomes, learning efficiency, and student satisfaction.

GRANTS

This work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases and Duke Training Grant in Nephrology 5-T32-DK-007731.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the author(s).

AUTHOR CONTRIBUTIONS

Author contributions: J.K.R., C.W.H., E.J., and R.L. conception and design of research; J.K.R. performed experiments; J.K.R., C.W.H., and R.L. analyzed data; J.K.R., C.W.H., and R.L. interpreted results of experiments; J.K.R. prepared figures; J.K.R. drafted manuscript; J.K.R., C.W.H., A.N., E.J., and R.L. edited and revised manuscript; J.K.R., C.W.H., A.N., E.J., and R.L. approved final version of manuscript.