Are surface and deep learning approaches associated with study patterns and choices among medical students? A cross-sectional study
AUTOR(ES)
Delgado, Álvaro Henrique de Almeida, Almeida, João Paulo Rodrigues, Mendes, Larissa Souza Borowski, Oliveira, Isabella Noceli de, Ezequiel, Oscarina da Silva, Lucchetti, Alessandra Lamas Granero, Lucchetti, Giancarlo
FONTE
Sao Paulo Med. J.
DATA DE PUBLICAÇÃO
22/10/2018
RESUMO
ABSTRACT BACKGROUND: Different approaches to learning can exert considerable influence on the teaching-learning process in medical education. This study aimed to investigate the association of surface and deep learning with study patterns, preferred type of assessment, practices of cheating and quality of sleep among medical students. DESIGN AND SETTING: Cross-sectional study on medical students enrolled in all six years of a medical school in Juiz de Fora, Brazil. METHODS: Questionnaires were applied to evaluate learning approaches (R-SPQ-2F), study patterns, sources and choices, and quality of sleep. Students’ learning approaches (deep or surface) were assessed in relation to their study patterns, study resources, quality of sleep and whether they cheated in tests. RESULTS: Among the 710 students included, 43% frequently studied on the night before an exam, 65% had used psychostimulants to study and more than 46% had cheated in an exam. Regarding quality of sleep, most students (53.4%) reported that their quality of sleep was poor, such that 45.3% slept for fewer than five hours before an exam. Those who studied just prior to an exam, used class summaries, preferred multiple-choice questions and cheated during the test had a more surface-learning approach. On the other hand, those who read books, preferred practical exams and slept better had a deeper approach. CONCLUSION: The type of learning approach was associated with study patterns and choices among medical students. Educators need to be attentive to the type of learning their students use and think of measures that impact teaching and assessment methods.
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