Lecturing skills as predictors of tutoring skills in a problem-based medical curriculum

Abstract

Purpose: Recruitment of tutors to work in problem-based learning (PBL) programs is challenging, especially in that most of them are graduated from discipline-based programs. Therefore, this study aims at examining whether lecturing skills of faculty could predict their PBL tutoring skills. Methods: This study included evaluation of faculty (n=69) who participated in both tutoring and lecturing within particular PBL units at the College of Medicine and Medical Sciences (CMMS), Arabian Gulf University, Bahrain. Each faculty was evaluated by medical students (n=45±8 for lecturing and 8±2 for PBL tutoring) using structured evaluation forms based on a Likert-type scale (poor to excellent). The prediction of tutoring skills using lecturing skills was statistically analyzed using stepwise linear regression. Results: Among the parameters used to judge lecturing skills, the most important predictor for tutoring skills was subject matter mastery in the lecture by explaining difficult concepts and responding effectively to students' questions. Subject matter mastery in the lecture positively predicted five tutoring skills and accounted for 25% of the variance in overall effectiveness of the PBL tutors (F=22.39, P=0.000). Other important predictors for tutoring skills were providing a relaxed class atmosphere and effective use of audiovisual aids in the lecture. Conclusion: Predicting the tutoring skills based on lecturing skills could have implications for recruiting tutors in PBL medical programs and for tutor training initiatives.