Medical Students Mix Effective and Ineffective Study Strategies, New Research Reveals

Every autumn, thousands of first-year biomedical students arrive at university carrying a private toolkit of study habits: flashcards, highlighted textbooks, late-night summary sheets, group sessions with classmates. A new study from researchers at Leiden University Medical Center in the Netherlands suggests that what students actually do with those tools is far more structured, and far more surprising, than educators have typically assumed. The research, published in BMC Medical Education, examined which cognitive learning strategies first-year students use across three undergraduate biomedical programmes, and how those strategies combine into distinct patterns of study behaviour.

The team, led by Jolande Disser, with Arnout Jan de Beaufort and Paul Steendijk, surveyed first-year students in Medicine (n = 187), Clinical Technology (n = 28), and Biomedical Sciences (n = 40) at Leiden University Medical Center and collaborating institutions. Students reported their use of twelve commonly studied cognitive learning strategies, ranging from practice testing and summarisation to peer learning and self-explanation. The survey approach was deliberately broad: rather than asking students to rate a single recommended technique, the researchers asked them to describe their actual study behaviour across the full spectrum of strategies documented in the cognitive psychology literature.

The results revealed a clear hierarchy of strategy use that held remarkably steady across all three programmes. Practice testing and summarisation dominated the top of the ranking, appearing among the most frequently used strategies in every programme surveyed. At the opposite end of the spectrum, peer learning was the least used strategy across the board. This finding is notable because practice testing, often called retrieval practice, is one of the most robustly supported techniques in cognitive psychology, with decades of evidence showing that actively recalling information strengthens long-term retention far more effectively than passive review. Summarisation, by contrast, occupies a more contested position in the literature, with effectiveness depending heavily on how well students execute it.

But the study’s most striking contribution lies in what came next. Rather than treating each strategy as an isolated variable, the researchers analysed how strategies cluster together within individual students. Using principal component analysis with varimax rotation, applied to the Medicine cohort due to sample size limitations in the other programmes, the team identified five distinct combinations of learning strategy use. Each combination represents a characteristic pattern: strategies that tend to travel together in the study behaviour of individual students.

The five patterns were labelled Deep learning, Surface learning, Creative learning, Distributed repetition, and Interleaved repetition. The deep learning combination groups strategies associated with meaningful engagement, such as elaboration and connecting new material to existing knowledge. The surface learning combination, by contrast, clusters strategies associated with rote processing and minimal cognitive transformation. The creative learning combination captures more generative approaches, while the two repetition patterns distinguish between distributed practice, where review sessions are spread over time, and interleaved practice, where different topics are mixed within a study session. Both repetition patterns align with well-established principles from cognitive science: spacing effects and interleaving have both been shown to enhance retention and transfer, though they remain underused by most students.

This combinatorial approach challenges a persistent assumption in educational research. Previous studies of learning strategies have often been inconsistent, showing substantial differences in use and effectiveness depending on level of education and learning domain. The authors argue that part of the inconsistency may stem from the analytical habit of studying strategies in isolation. Students typically use multiple strategies simultaneously, and the effectiveness of any single strategy may depend on which other strategies accompany it. A student who combines practice testing with elaboration may extract different benefits than one who pairs the same testing routine with pure rereading. The researchers hypothesise that these combinations may affect overall effectiveness in ways that isolated analyses cannot capture.

When the researchers compared strategy use across the three programmes, the overall ranking of individual strategies proved similar, but subtle differences emerged at the programme level. Biomedical Sciences students appeared to use slightly more deep-learning strategies, while Clinical Technology students used fewer surface-learning strategies. These differences emerged despite considerable overlap in course content across the programmes, suggesting that instructional design, the way courses are structured, assessed, and delivered, may be associated with individual learning strategy preferences. The finding carries practical weight for curriculum developers: if the architecture of a programme nudges students toward more effective strategies, then pedagogical choices may shape study behaviour in measurable ways.

The study also highlights a persistent gap between what cognitive psychology recommends and what students actually do. The coexistence of both effective and ineffective strategies in students’ repertoires, the authors note, stresses the need to help students choose learning strategies that support long-term retention. Many students arrive at university with habits formed through secondary education, where short-term performance on frequent assessments can reward strategies that fail to produce durable learning. Without explicit guidance, students may continue relying on techniques that feel productive in the moment but do not survive contact with the forgetting curve.

The researchers emphasise that these insights are needed to support educators in designing curricula and personalised, targeted learning-to-learn interventions, ultimately guiding students toward effective strategies aimed at long-term learning. The study was approved by the LUMC Educational Research Review Board and the Human Research Ethics Committee of TU Delft, and conducted in accordance with the Declaration of Helsinki. Participation was voluntary, with students providing informed consent before completing the questionnaire.

For the wider field, the study opens a concrete research agenda. If strategy combinations matter, then future studies should examine how specific patterns of use relate to academic performance, retention over time, and transfer to clinical practice. The authors suggest that biomedical learning behaviour deserves sustained investigation, particularly as educators seek evidence-based ways to foster lifelong learning in future healthcare professionals. The five combinations identified here provide a starting framework, but the authors caution that their analysis was limited to the Medicine cohort for combinatorial analysis, and that larger samples across programmes would strengthen future comparisons. What the study establishes beyond doubt is that students’ study behaviour is not a random assortment of techniques but a structured system, one that educators can now begin to map, measure, and, with the right interventions, improve.

Subject of Research: Cognitive learning strategy use and their combinations in first year biomedical programmes

Article Title: Cognitive learning strategy use and their combinations in first year biomedical programmes

Article References: Disser, J., de Beaufort, A. J., & Steendijk, P. (2026). Cognitive learning strategy use and their combinations in first year biomedical programmes. BMC Medical Education. https://doi.org/10.1186/s12909-026-10408-2

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10408-2

Keywords: Cognitive, learning, strategy, combinations, first, year, biomedical, programmes, scientific research