Active Learning Strategies in Veterinary MedicineA Literature Review

Picture a first-year veterinary student sitting in a darkened lecture hall, watching slides scroll past while a professor talks through the pathophysiology of diabetes mellitus. She's taking notes. She might remember forty percent of it by Friday. Then she walks into the clinic a year later and meets an actual Beagle with polyuria and polydipsia, and suddenly she needs to reason, decide, and act. The question Bridget Garner and colleagues set out to answer is: what happens in between? What teaching strategies actually build the bridge from passive reception to clinical competence? Their 2024 literature review searched PubMed and ERIC using terms covering active learning, active teaching, and student-centered education, returning over five thousand articles. After screening, one hundred forty-seven references underwent full-text review. The findings are organized into three domains: collaborative activities, individual tasks, and educational gaming and simulation. That taxonomy is the backbone of what follows. Active learning, as Garner and colleagues frame it, is not simply doing things in class. It requires intentional engagement, purposeful observation, and critical reflection — students must not only act on material but think about what they're doing. The case for it draws on multiple lines of evidence. Students in active learning environments show better knowledge acquisition, improved long-term retention, stronger performance in the sciences, and higher attendance. There's even physiological evidence: student heart rate, used as a proxy for mental effort, tends to plateau during passive lectures and spikes during active segments — a re-engagement signal that appears in both morning and afternoon sessions. Active learning also aligns with the Competency-Based Veterinary Education framework, which was established in 2015 and outlines nine measurable domains of competence including self-directed learning, clinical reasoning, collaboration, and decision-making. These aren't skills you can lecture someone into. The barriers are real, though. Garner and colleagues document a familiar list: financial constraints, larger class sizes, reduced staff, insufficient preparation time, lack of pedagogical training, student resistance, and unequal access to technology. These don't disappear just because the research supports active learning. They shape what's actually feasible in a given school at a given moment. Now into the strategies themselves. Start with collaborative approaches, which make up the densest part of the review. Case-based learning is probably the most familiar. Students work through realistic clinical scenarios using prior foundational knowledge — Garner and colleagues describe a small-animal internal medicine activity where groups of five students receive the history and exam of a nine-year-old Beagle with polyuria and polydipsia, decide which diagnostics to run, and interpret results to differentiate diabetes mellitus from hyperadrenocorticism while the instructor releases new information progressively. The advantages are meaningful: case-based learning highlights clinical relevance, integrates basic and clinical science, and builds diagnostic confidence. The limitation is also real: large-group discussions can suppress participation, and early-year students sometimes lack the background knowledge to engage productively. Team-based learning runs deeper than a single case. It's a semester-long structure with permanent teams and a recurring three-phase cycle: individual preparation, individual and team readiness tests — often called iRAT and tRAT — and then clinical application. A pharmacology use case in the review involves five-person teams designing an anesthetic plan for a renal patient after completing individual and group quizzes. Team-based learning scales well, requires only one facilitator for many teams, and tends to produce higher team scores than individual scores. The trade-off is front-loaded investment: careful team formation, skilled facilitation, and significant student orientation. The flipped classroom inverts the traditional sequence — foundational content delivered before class through videos or readings, with in-person time reserved for active application. Garner and colleagues cite a study replacing roughly fifty percent of a pathology course with online content; students who completed at least ninety percent of the online modules scored significantly higher. The limitation the review flags most clearly is instructor workload. Creating reusable video materials is expensive in time, and when multiple instructors flip simultaneously, students can feel overwhelmed by the pre-class burden. Two lighter-lift strategies round out the collaborative picture. Think-pair-share gives students sixty seconds to consider a question — say, identifying a leukocyte on a blood smear — then discuss with a neighbor before a few pairs report to the class. It's low-prep, re-engages attention, and lowers the barrier for students reluctant to speak in large groups. The jigsaw method assigns each student one segment of a topic, has them meet with same-topic peers to become experts, then return to teach their home group. Garner and colleagues report high satisfaction and improved communication skills from jigsaw exercises, though students found them time-consuming, and disengaged members can undercut the whole group. Audience response systems — clickers, or now platforms like Kahoot!, Socrative, and Poll Everywhere — offer real-time formative assessment in large lectures and make participation effectively anonymous. Technology dependence and equity of device access remain the recurring caveats. Shifting to individual strategies, the key distinction Garner and colleagues draw is between problem-based learning and case-based learning. In case-based learning, students arrive with foundational knowledge and work through a structured scenario. In problem-based learning, the problem itself is the trigger; students search for information to resolve it without a pre-supplied solution path. That structural difference matters for how much scaffolding students receive. Self-directed learning, at its most independent, has students assessing their own needs, setting objectives, choosing resources, and evaluating progress. Directed self-learning adds instructor scaffolding and predefined objectives. A systematic review cited in the paper found self-directed learning moderately more effective than traditional methods for knowledge, skills, and attitudes, with larger gains when students chose their own learning objectives. The veterinary literature on these individual formats is largely qualitative — the outcomes data mostly comes from student surveys, not controlled comparisons. Gaming and simulation form the third domain, and they're where the evidence becomes most interesting and the trade-offs most visible. On the gaming side, Garner and colleagues describe escape rooms used in veterinary contexts, Kahoot!-based quizzes, crossword puzzle competitions, and a role-playing video game for complete blood count interpretation that produced significant pretest-to-posttest gains, with the largest improvements concentrated among lower-performing students. Meta-analyses cited in the review support positive effects of game-based learning on motivation and retention, with quests and missions singled out as particularly effective game elements. Simulation covers a wider and more expensive spectrum. The review lists the types explicitly: full-body manikins, single-skill body-part models, multimedia computer simulations, augmented reality, virtual reality with head-mounted displays, scenario-based role play, and hybrid combinations. A canine CPR mannequin equipped with sensors provides real-time feedback on compression depth, rate, intubation success, and heart rhythms. Augmented reality examples include QR-code-triggered microscope videos linking physical model work to slide review. Objective Structured Clinical Examinations, known as OSCEs, function as the assessment and feedback loop in simulation-based training, giving students structured, individualized feedback at each station. The evidence for simulation is promising but uneven. Simulation training has been shown to reduce complication rates in real clinical and surgical procedures, and in some studies outperforms video-only instruction and even case-based learning for specific skills. But here's the finding that complicates the enthusiasm: increasing simulator complexity doesn't reliably improve basic skills acquisition. Studies cited in the review found no major differences in suture skills and cerebrospinal fluid collection when complexity increased, and fine-needle aspiration performance was similar whether students trained on live animals or manikins. The core advantage simulation offers is irreducible: repeated, safe practice without risk to live animals or psychological distress to students. The core constraint is equally clear: complex simulators require space, personnel, and instructor training, and even low-fidelity models take time to build. What does Garner and colleagues' review ultimately tell us? The breadth of available strategies is real — collaborative, individual, and simulation-based methods each have documented advantages and specific use cases in veterinary education. But the evidence base is thin where it matters most. Most veterinary-specific studies are qualitative, descriptive, and survey-based, often lacking control groups or reproducible outcome measures. The authors state plainly that no single method is a panacea. What the review provides is a map of existing practice and a clear directive: the field needs controlled, quantitative studies that measure performance over time and compare approaches directly, rather than single-intervention reports describing student satisfaction. That Beagle in the clinic is waiting. The strategies to prepare students for her exist. What veterinary education still needs is the evidence to know which ones work best, for which students, and under which conditions. This lecture was created by ennepō. Go to https://ennepo.ai to Discover, Create and Follow the latest research in your field. Read when you can. Listen when you want to.