Active Learning Among Health Professions’ Educators: Perceptions, Barriers, and Use

Abstract

Introduction

Active learning engages students in the learning process through meaningful learning activities. Despite evidence that active learning can improve student’s comprehension and problem solving, many educators remain reluctant to adopt it. The goal of this study was to explore health professions’ educators’ perceptions of active learning and identify implementation barriers.

Materials and Methods

We developed a 25-question survey based on the Miller and Metz “perceptions of active learning” survey. We added 12 single-response demographics questions to the original 13 survey questions.

Results

One hundred three respondents completed the survey. We found positive perceptions of active learning significantly correlated with gender, rank, teaching FTE, and full-time employment. The use of specific active learning modalities significantly correlated with gender, terminal degree, institutional appointment, academic rank, and role. Lack of time to develop materials and lack of class time were the most common personal barriers identified, while being lecture-accustomed and lack of training were the most common perceived barriers to the implementation of active learning by their peers.

Conclusion

Despite overwhelmingly positive perceptions of active learning among US health professions’ educators and desire to incorporate it, a gap still exists between institutional and educators’ support of active learning due to implementation barriers for resource-intensive active learning.

Introduction

Active learning is defined as any instructional method in which students become engaged participants in the learning process through the use of meaningful learning activities [1, 2]. The primary goal of active learning is to create a student-focused environment where higher-order cognitive tasks are promoted through engagement with content [1]. The term active learning can be applied to a multitude of instructional strategies; however, there are notable commonalities among them. In active learning, students play a role beyond passive recipients of knowledge, rather, they engage in activities that prioritize critical reasoning, skills development, and exploration of the affective domain [3]. Correspondingly, faculty become more than purveyors of information, instead playing the roles of organizer, facilitator, motivator, and partner in learning [4]. Therefore, in active learning, learners and educators are both actively involved in the learning process.

Due to the shift in professional identity, faculty must be highly motivated to adopt active learning. Some may be motivated by learning theory or empirical data. Active learning is based on the constructivist theory of learning. Constructivism is widely accepted and supported by extensive evidence within the educational psychology and neurocognitive behavior literature. According to constructivism, knowledge is actively built upon prior knowledge and experiences through sensory input and cognition. Active learning supports the cognitive work required to build knowledge according to this theory [5]. Further, active learning provides opportunities to learn through social interaction and promotes the type of conceptual understanding that allows learners to apply knowledge to different contexts [6].

Substantial evidence suggests that active learning improves student’s comprehension and problem solving [1]. In a meta-analysis of 225 studies of undergraduate science, technology, engineering, and math (STEM) courses that incorporated some active learning, students demonstrated an average of 6% improvement in exam scores, while students in traditional lecture courses were 1.5 times more likely to fail [7]. Another meta-analysis of undergraduate STEM courses reported an effect size mean of 0.47 when comparing the impact of active learning innovations on student learning [8]. Active learning has been shown to enhance motivation and positive attitudes toward learning [9]. Of note, multiple studies have demonstrated closure of the achievement gap for underrepresented and economically disadvantaged students [10–12].

Studies of undergraduate medical education programs demonstrated the effectiveness of active learning when delivered via problem-based learning (PBL), team-based learning (TBL), and case-based learning (CBL) [13–15]. In medical residency programs, active learning has been shown to promote achievement of learning outcomes and reduce the time spent in lecture with no detrimental effects to learning [16–18].

Based on evidence, one might assume that active learning has increased in acceptance in health professions’ education. However, many have pointed to a lack of reform regarding active learning in medical education, some noting any current progress toward implementation as “cosmetic rather than substantive” [19–21]. In 2012 and 2013, Prober et al. published seminal calls for reform of the lecture-based model in medical education. In it, they describe evidence from K-12 and undergraduate natural science classrooms to justify the need for active learning in medical school. They emphasize the ability of active learning to promote “stickiness” of the educational content and to fully utilize the increasingly limited curricular time [22, 23].

Despite substantial evidence for the effectiveness of active learning and calls for reform, many educators are reluctant to adopt it in the classroom. Although barriers to the implementation of active learning have been proposed, the majority of publications are based on data gathered from K-12 or undergraduate educators and learners. Therefore, a better understanding of the perceptions, use, and barriers to implementation of active learning among health professions educators is needed. This study aims to address this gap in the literature.

Materials and Methods

Survey Instrument

We created a survey based upon the “perceptions of active learning” instrument developed by Miller and Metz [2]. The 25-item survey included ranking, Likert-scale, single-response, and open response questions. The Likert-scale responses were “strongly disagree,” “disagree,” “neither agree nor disagree,” “agree,” and “strongly agree.” The survey included 12 demographic and characterizing questions and 13 survey questions adapted from the Miller and Metz survey [2]. These questions surveyed knowledge and familiarity, current use, perceptions, and barriers to implementation of active learning. To ensure that all participants understood the term “active learning,” we included the following definition in the survey:

• “Active learning is an instructional method in which students become engaged participants in the classroom. Students are responsible for their own learning through the use of in-class: written exercises, games, problem sets, i-clickers, debates, class discussions, etc.” [2]

Survey Administration

The survey was distributed by email through DR-ED, a health science profession Listserv sponsored by Michigan State University, and, with permission, to educators within graduate health science programs at individual institutions. Respondents consented to participate, voluntarily, by completing the survey and could withdraw consent by discontinuing a survey at any time. No identifying information was collected, and no incentives were offered. Qualtrics software (Qualtrics LLC, Provo, Utah) was used to construct and administer the survey. Responses were collected during between August 2019 and May 2020. This study was granted exempt approval by the University Institutional Review Board, Approval Number M-1904-102-1905.

Inclusion and Exclusion Criteria

To be included, participants needed to be appointed as faculty within a graduate health sciences education program with a percentage of effort dedicated to teaching/instructional/educational responsibilities. We defined graduate health sciences education to include medical school, osteopathic medical school, medical residency, dental school, pharmacy school, veterinary school, physical therapy or occupational therapy school, chiropractic school, graduate nursing programs, and other similar graduate-level health professions academic programs. Persons under 18 years of age were excluded from the study.

Data Analysis

Exploratory factor analysis using principal component analysis and varimax rotation was performed. No confounding variables were identified, so all analyses were performed separately. Continuous data was analyzed between two groups using the Mann–Whitney U test. Continuous data was compared between three or more groups using the Kruskal–Wallis Z test, and the Tukey–Kramer test was used for pairwise comparisons. Categorical variables were analyzed using Chi-square or Fisher’s exact test. Correlation analysis was performed using simple linear regression. All p values were considered significant at < 0.05. Data was analyzed using NCSS 2021 (ICSS 2021 Statistical Software, NCSS, LLC. Kaysville, UT, USA).

Results

Participant Demographics and Characteristics

Survey responses were collected from participants in 35 states. Of 137 respondents who consented to participate, 103 (75%) completed the survey. Sixty-three percent of respondents identify as female. 85.4% of respondents were aged 40 years or older. Rank was distributed, with 29% staff, 27% assistant professor, 28% associate professor, and 15% full professor. 73.5% reported 10 years or more teaching experience.

A majority of respondents held a PhD terminal degree (52.9%), while 27.5% held an MD or DO terminal degree. 11.7% held a graduate-level degree in education. A minority of respondents reported holding other degrees such as DVM, JD, MBA, MPH, and RN (8.8%). Eighty-eight percent of respondents were employed full-time, defined as 40 h a week. Seventy-seven percent reported 0.5 full-time equivalent 9FTE) or more dedicated to teaching.

Among respondents, 58.3% were employed at allopathic medical schools, 14.5% at osteopathic medical schools, and 4.9% at medical residency programs. A minority of participants reported appointments within other programs (16.5%), such as audiology, dental, graduate nursing, occupational therapy, pharmacy, physical therapy, physician assistant, and veterinary.

Respondents reported involvement in multiple educator activities, including curriculum development and modification (79.6%), developing or implementing new teaching methods (72.8%), and faculty development (71.8%) (Table 1).

Table 1.

Demographics of survey respondents

Demographic	N (%)
Age
21–29	2 (1.9%)
30–39	13 (12.6%)
40–49	32 (31.1%)
50–59	29 (28.2%)
60 or older	27 (26.2%)
Gender
Female	65 (63.1%)
Male	38 (36.9%)
Terminal degree
Master’s	6 (5.9%)
PhD	59 (57.8%)
MD/DO	34 (33.3%)
Other	3 (2.9%)
Employment status
1–39 h	8 (7.8%)
40+	91 (88.4%)
Retired	4 (3.7%)
Rank
Staff/lecturer	30 (29.41%)
Assistant professor	28 (27.45%)
Associate professor	29 (28.43%)
Full professor	15 (14.71%)
% effort teaching
< 25%	9 (9.1%)
25–50%	13 (13.1%)
51–75%	32 (32.3%)
75–100%	45 (45.5%)
Role
Curriculum development	82 (78.9%)
New teaching methods	75 (72.1%)
Education research	70 (67.3%)
Faculty development	74 (71.2%)
Online learning	32 (30.8%)
Course director	49 (47.1%)

Apart from a significant correlation between age and rank (p < 0.001), we found no associations between independent variables describing demographics and characteristics. Demographic data such as race, ethnicity, and nationality were not collected.

Familiarity with Active Learning

Overall, the population demonstrated near universal familiarity with active learning. Ninety-five percent of respondents agreed or strongly agreed that they were familiar with the definition of active learning and its use (Fig. 1). Those with part-time appointments were less familiar with the definition of active learning and the use of active learning (p < 0.007).

Fig. 1.

Faculty responses to Likert-scale questions on familiarity with and perceptions of active learning

Perceptions of Active Learning

At least 90% of respondents agreed or strongly agreed that active learning improves student learning and long-term retention of information. Eighty percent or more agreed or strongly agreed that active learning is effective, students enjoy active learning, and active learning increases student motivation. Seventy-one percent perceived that active learning improves exam performance (Fig. 1).

We identified significant correlations between positive perceptions of active learning and both junior rank and greater FTE dedicated to teaching. Assistant professors were more likely to agree or strongly agree that when they used active learning in a classroom setting, it was effective (p < 0.04). Greater FTE dedicated to teaching positively correlated with the percentage of time participants think should be dedicated to active learning (ρ = 0.3929, p < 0.0006) independent of employment status.

Significant negative relationships existed between positive perceptions of active learning and part-time employment status. Part-time faculty were more likely to strongly disagree that students enjoy active learning (p < 0.0004), students learn better from lectures that incorporate active learning (p < 0.0163), and that active learning increases students’ motivation (p < 0.001), retention (p < 0.0001), and exam performance (p < 0.0022).

We also examined the perceived effectiveness of 6 teaching methods (games, group learning, lecture, problem solving, reading, and videos). Participants ranked them from most to least effective. Overall, problem solving was ranked as the most effective, followed by group learning, educational games, online learning, and videos. Lecture was ranked the least effective. Full-time faculty ranked lecture lower on the effectiveness scale compared to part-time counterparts (p < 0.005). However, men were more likely than women to rank lecture higher in effectiveness (p < 0.002). Additionally, faculty with a PhD were more likely than faculty without a PhD to rank lecture higher in effectiveness (p < 0.04).

Use of Active Learning

43.9% of respondents reported using active learning at least 50% of the time; however, 78.7% expressed the desire to use active learning at least 50% of the time. A higher percentage of FTE dedicated to teaching positively correlated with the percentage of class time participants dedicated to active learning (ρ = 0.3148, p < 0.0019). The percentage of class time participants dedicate to active learning strongly correlated with the percentage of class time they believe should be dedicated to active learning (ρ = 0.6652, p < 0.0001) (Fig. 2).

Fig. 2.

Percent of class time that faculty dedicate to active learning strongly correlates with percent of class time that they perceive should be dedicated to active learning (ρ = 0.6652, p < 0.0001)

Participants were asked to select specific active learning modalities that they currently implement in the classroom. From a list of 17 active learning modalities derived from the Miller and Metz survey, 79% of participants reported using CBL and/or discussion in the classroom. Respondents also reported using audience response (72%), TBL (70%), oral presentations (57%), simulation (55%), and PBL (50%). Between 35 and 48% of faculty reported using concept mapping, demonstration, games, interactive modules, interview or panel, journal club, lab, peer-oriented problem solving (POPS), peer teaching, and workshops (Fig. 3).

Fig. 3.

Word cloud demonstrating the frequency of use of 17 active learning modalities

Participants also ranked 6 teaching methods (games, group learning, lecture, problem solving, reading, and videos) according to frequency of use. Participants ranked group learning and lecture as most frequently used, followed by problem solving, videos, reading, and educational games (Fig. 4). This contrasts with respondents ranking lecture as the least effective method.

Fig. 4.

Faculty responses to ranking questions on frequency of use and perceived effectiveness of teaching methods. Percent of faculty that ranked the teaching methods as the most used or most effective are shown

We identified five variables that demonstrated significant correlations with the use of and/or frequency of active learning modalities and methods: gender, terminal degree, institutional appointment, academic rank, and role.

Gender

Overall, men used a larger variety of active learning modalities than women (p < 0.0036). However, women were more likely to use certain modalities, including concept mapping (p < 0.0004), demonstration (p < 0.012), games (p < 0.048), interactive modules (p < 0.024), interview/panel (p < 0.024), oral presentation (p < 0.006), simulation (p < 0.039), and workshop (p < 0.038). Men reported using education games less frequently than women (p < 0.031).

Terminal Degree

Faculty with a PhD were less likely to use oral presentation (p < 0.004) or case-based learning (p < 0.02). There were no significant differences in the frequency of teaching methods based on terminal degree.

Institutional Appointment

Faculty with appointments in osteopathic medicine programs were less likely to use CBL (p < 0.018) and more likely to use demonstration (p < 0.023), compared to respondents employed by other programs, regardless of terminal degree. Faculty with appointments in allopathic medical programs were less likely to use workshops (p < 0.006). Additionally, faculty in allopathic medical programs reported less frequent use of educational games (p < 0.025). Interestingly, we found that among faculty with sole appointments in medical residency programs, none reported using PBL, though small sample size precluded analysis.

Academic Rank

We found a significant negative correlation between rank and using demonstration as a technique, with assistant professors most likely to use it, and full professors least likely use it (p < 0.027). There was no significant difference in the frequency of teaching methods based on rank.

Role

Regarding institutional roles, we found those involved in curriculum development (p < 0.016), developing or implementing new teaching methods (p < 0.019), and online learning (p < 0.00005) used the largest variety of active learning modalities.

Faculty with roles in online learning were more likely to use the specific modalities of CBL (p < 0.0175), concept mapping (p < 0.008), discussion (p < 0.0016), demonstration (p < 0.0007), games (p < 0.0255), interactive module (p < 0.0002), POPS (p < 0.0025), and simulation (p < 0.032)). These participants also reported less frequent use of lecture (p < 0.022) as a teaching method and more frequent use of videos (p < 0.011).

Faculty with roles in curriculum development were more likely to use CBL (p < 0.0143), discussion (p < 0.036), journal club (p < 0.0063), and laboratory (p < 0.0395) than those without such a role. Participants with roles in developing new teaching methods and faculty development reported less frequent use of lecture (p < 0.016 and p < 0.023, respectively) and more frequent use of problem solving (p < 0.026 and p < 0.004, respectively). Uniquely, faculty involved in educational research were more likely to use peer teaching (p < 0.023) and games (p < 0.033).

Barriers to Active Learning

We obtained information related to the respondents’ personal barriers to implementation, and the barriers they perceived as limiting peers from implementation. There were significant correlations between barriers and independent variables such as role, academic rank, and/or gender.

Personal Barriers

Participants most frequently identified lack of time to develop materials (42%) and lack of class time (37%) as personal barriers. Twenty-seven percent of faculty identified lack of administrative support and class size as personal barriers. Approximately 15% of faculty are accustomed to lecture, feel they lack sufficient training, or feel that active learning is not a productive use of class time (Fig. 5). Those respondents with a role in faculty development were more likely to identify lack of administrative support as a personal barrier (p < 0.029) and less likely to identify time to develop materials as a personal barrier (p < 0.033). Respondents involved in educational research were less likely to identify class size as a personal barrier (p < 0.0073).

Fig. 5.

Faculty responses to questions on personal barriers to implementing active learning and perceived barriers to implementing active learning for others

Perceived Barriers for Peers

A majority of faculty perceived being accustomed to lecture-based methods (74%), lack of training (65%), and lack of time to develop materials (57%) as the major barriers inhibiting the implementation of active learning among their peers. Lack of class time (40%), lack of awareness of active learning (32%), class size (23%), and lack of administrative support (21%) were also frequently identified. Usefulness of active learning (19%) and ineffective use of class time (17%) were the least frequently selected.

Faculty involved in curriculum development were more likely to report familiarity with lecture-based methods (p < 0.033) and a lack of training (p < 0.040) as perceived barriers for peers. Participants who pioneer new teaching methods (p < 0.023) or with a role in faculty development (p < 0.004) were more likely to perceive a lack of awareness of active learning as a barrier for peers.

Faculty with a role in online teaching were more likely to believe that peers do not find active learning useful in the classroom (p < 0.024) and that class size is a barrier for others (p < 0.023). Rank was significantly associated with perceiving unawareness and lack of time to develop materials as a barrier for others, with instructors most likely and full professors least likely to identify these as potential barriers. Finally, women were more likely than men to perceive lack of training as a barrier for others (p < 0.04).

Discussion

In this study, we analyzed US health professions educators’ perceptions and use of active learning and personal and perceived barriers to implementing active learning. Due to a substantial lack of evidence in the literature until now, thoughts and attitudes about active learning among health professions educators, and the impact of these, remained unclear. We found overwhelming knowledge of and support for active learning among study participants that correlated with academic rank, percent FTE dedicated to teaching, and employment status. Use of active learning varied based on gender, terminal degree, institutional appointment, academic rank, and role. Our study revealed that the major barriers to active learning, perceived by health professions educators, were feasibility given class size, inadequate time to develop materials, lack of class time to deliver activities, and a lack of administrative support for resource-intensive active learning.

At its foundation, adoption of active learning requires a change in an educator’s professional identity and the role of learners in the education process [24, 25]. Traditionally, higher learning educators approach teaching as a process of imparting information, likely because they perceive content expertise to be the major determinant in one’s success as a teacher [26, 27]. In the active learning classroom, the educator must abandon their self-identity as a purveyor of knowledge and adopt a new self-concept as a facilitator of learning who allocates a greater role to learners [24, 28]. Based on the preponderance of evidence for the benefits of active learning, this paradigm shift is necessary and potentially overdue in health professions education [29]. To do so, misconceptions about active learning and barriers to implementation must be identified and addressed.

In 1997, Paul et al. found that only 9% of higher learning educators utilized active learning methods regularly in the classroom [30]. In contrast, our findings demonstrate a sea change in the perceptions and habits of health professions educators, with nearly half of respondents reporting they dedicate at least half of their instructional time to active learning. Further, our study demonstrates increasing familiarity with and belief in active learning among health professions educators. Despite the positive perceptions and desires to incorporate more active learning into educational practices, our study found that health professions’ educators identified similar barriers as K-12 and undergraduate educators.

A review of the literature identified four categories of barriers to implementing active learning in K-12 and undergraduate classrooms: challenges arising from the system, the content, the student, and the educator [31–36]. Systemic challenges are the result of the large-scale educational system in which the educator must operate. These include large class size, limited class time, lack of administrative support, lack of time to develop active learning activities, and classroom design. Our survey included the first four systemic barriers and was the most frequently identified personal barriers, demonstrating consistently across educator’s barriers up to the graduate health professions level. Despite the common concern of class size [37], the utility of active learning in large cohorts is supported by evidence. For example, a comparison of student performance in traditional and active learning classrooms in a large, introductory biology course found that students in active learning classrooms earned on average half a letter grade higher than predicted [38]. Limited class time is another common concern. As the volume of biomedical knowledge and the breadth of subject matter that must be addressed continue to expand over time, health professions’ educators express increasing concern that there is insufficient time to cover essential concepts to the necessary depth [39]. As a result, educators may rely more on lecture than active learning, due to the perception that lecture can cover more content [34], and that content coverage should be prioritized over developing critical thinking and problem-solving skills [19]. This is supported by our finding that participants perceived lecture as the least effective teaching method, yet it was the most frequently used teaching method.

Lack of administrative support and lack of time to develop active learning materials are often intertwined. Administrative support is known to drive institutional change [40, 41]. To support effective change, administrators of health professions programs must provide sufficient time and funds for faculty to develop their knowledge, skills, and teaching materials for active learning. Further, educational change requires administrators to understand change management. Institutional change must be viewed as a process, and pedagogical change is largely dependent on faculty readiness, which includes perceptions of the new pedagogy, and motivation. Administrators must provide opportunities to address gaps in these domains as well as support the shift in professional identity formation. Administrators can also identify faculty advocates for active learning to drive curricular change [42].

Our study is limited by the amount of information that exists in the literature on how perceptions of active learning impact health professions educators’ behavior during curriculum development and delivery. The instrument selected explored both perceptions and behaviors but has not been validated for reliability and validity. Although we received a high number of responses, respondents’ roles within the institutional setting remained unclear due to question design. We remain unsure of the number of administrators with decision-making capacity who participated in the survey. Lastly, our study is limited by potential acquiescence, desirability, and non-response bias. Respondents may have been more likely to agree with some statements, due to a desire to appear to use and support active learning, when in reality they may not use it or use it infrequently. In addition, those who opted to participate in the survey may have more positive perceptions than those who did not. Lastly, despite providing a definition for active learning, some survey respondents may not have a full understanding of what active learning is and is not.

Conclusion

As health professions’ education continues to evolve, we should continue to examine the role and benefits of positive perceptions of active learning and their impact in the learning environment. It has been established that educators’ unconscious and conscious biases and decision-making influence student learning in a variety of ways. Not the least of which include perceptions on educational theory, learning modalities, and teaching techniques. Based on the positive evidence in the literature to support active learning, we feel it is imperative that institutions and individuals alike take steps to improve administrative support of active learning in the classroom. Our study provides valuable evidence that health professions’ educators’ desire to incorporate active learning into health professions’ education practices and require administrative support to do so.

Declarations

Ethics Approval

This study was granted exempt approval by the Texas Christian University Institutional Review Board, Approval Number M-1904-102-1905.

Conflict of Interest

The authors declare no competing interests.