Collaborative learning: Elements encouraging and hindering deep approach to learning and use of elaboration strategies.

AIM: The purpose of this research was to investigate students' approaches to learning and use of cognitive strategies in a collaborative learning environment with team-based learning. METHOD: In a mixed-methods study, 263 medical students from 6 different semesters answered the R-SPQ-2F Questionnaire and MSLQ's items that measure elaboration and rehearsal strategies. ANOVA was used to compare differences between semesters, and Pearson's correlation to investigate how approaches to learning, cognitive strategies, and academic achievement correlate. Focus groups elucidated which elements in the collaborative learning environment enhanced or hindered deep approach to learning or elaboration strategies and why. RESULTS: Students took a deep approach to learning and sometimes a surface approach. They used elaboration and rehearsal strategies. First semester's students had significantly higher deep approach than fifth and sixth semesters' students. Elaboration strategies significantly correlated with final grade. Commitment to the group, case discussions, feeling challenged by teachers, and patients' visits were perceived to enhance deep approach to learning and use of elaboration strategies, while overload in course activities hindered deep approach to learning. CONCLUSIONS: Particular elements of the learning environment triggered students to take deep approach to learning and use elaboration strategies, and this positively correlated to academic achievement.

First experience with multiple mini interview for medical school admission in Brazil: Does it work in a different cultural scenario?

PURPOSE: Evaluation of non-cognitive skills never has been used in Brazil. This study aims to evaluate Multiple Mini Interviews (MMI) in the admission process of a School of Medicine in São Paulo, Brazil. METHODS: The population of the study comprised 240 applicants summoned for the interviews, and 96 raters. MMI contributed to 25% of the applicants' final grade. Eight scenarios were created with the aim of evaluating different non-cognitive skills, each one had two raters. At the end of the interviews, the applicants and raters described their impressions about MMI. The reliability of the MMI was analyzed using the Theory of Generalization and Many-Facet Rasch Model (MFRM). RESULTS: The G-study showed that the general reliability of the process was satisfactory (coefficient G = 0.743). The MMI grades were not affected by the raters' profile, time of interview (p = 0.715), and randomization group (p = 0.353). The Rasch analysis showed that there was no misfitting effects or inconsistent stations or raters. A significant majority of the applicants (98%) and all the raters believed MMIs were important in selecting students with a more adequate profile to study medicine. CONCLUSIONS: The general reliability of the selection process was excellent, and it was fully accepted by the applicants and raters.