In many engineering subjects students learn to solve problems. Problem solving demands the transfer of knowledge from one context to another1. This requires that one’s knowledge be suitably organized in meaningful patterns, and that one be able to retrieve that knowledge, recognizing its relevance in the context of the problem solving process. This is linked to one widely appreciated dimension of expertise: metacognition or the ability to monitor one’s progress in approaching a task and to determine when understanding is inadequate. A number of researchers have successfully developed and implemented programs to support students’ metacognitive skills to improve learning and problem solving. Examples include reading comprehension, writing, mathematics, physics, statistics and computer program debugging. For example, in Brown & Palinscar’s Reciprocal Teaching method, which is used to support text comprehension, instruction is structured around encouraging students to implement four strategies: summarizing, question generating, clarifying, and predicting. The teacher initially models these comprehension strategies, asking students to summarize, predict, etc., and then students take turns assuming the role of teacher in leading this dialogue with each other. Although these instructional programs are domain dependent, each focuses on procedures or features that are generally applicable to a wide range of problems within the domain, rather than specific problem solution algorithms. This paper investigates a domain-specific metacognitive strategy that may broadly benefit problem-solving in statics.
Paul S. Steif, J. Lobue, A. L. Fay, Levent Burak Kara, S.E. Spencer. (2007). Inducing Students to Contemplate Concept-Eliciting Questions and the Effect on Problem Solving Performance. Proceedings of the 2007 American Society for Engineering Education Annual Conference and Exposition. June 24-27, 2007.