Problem-Based Learning: Exploiting Knowledge of how People Learn to Promote Effective Learning
Edward J. Wood
Abstract
Edward J. Wood
Abstract
There is much information from educational psychology studies on how people learn. The thesis of this paper is that we should use this information to guide the ways in which we teach rather than blindly using our traditional methods. In this context, problem-based learning (PBL), as a method of teaching widely used in medical schools but applicable to practically all subjects, embraces the principles of good learning and teaching. It is student-directed, provides incentives and feedback during the learning process, and encourages the experiential development of a number of skills, including team-work, finding and digesting information, peer teaching (explaining to others), reaching conclusions from data, and reflecting on the learning process. Inter alia, it encourages the accumulation of subject knowledge which is perceived to be relevant, and that is digested or compiled and organised.
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There is much information from educational psychology studies on how people learn. The thesis of this paper is that we should use this information to guide the ways in which we teach rather than blindly using our traditional methods. In this context, problem-based learning (PBL), as a method of teaching widely used in medical schools but applicable to practically all subjects, embraces the principles of good learning and teaching. It is student-directed, provides incentives and feedback during the learning process, and encourages the experiential development of a number of skills, including team-work, finding and digesting information, peer teaching (explaining to others), reaching conclusions from data, and reflecting on the learning process. Inter alia, it encourages the accumulation of subject knowledge which is perceived to be relevant, and that is digested or compiled and organised.
Key concepts: Experiential learning, Context (archaeology), Process (computing), Cooperative learning, Active learning (machine learning), Incentive, Computer science, Psychology