Student Alignment with Expert Knowledge as a Predictor of Problem Solving Performance
Mitchell, Sheila, Education - Curry School of Education, University of Virginia
Van Hover, StephanieS, Curry School of Education, University of Virginia
Engineering education is intended to equip students with such skills as analysis and design that are necessary for success in the engineering profession even while universities are under pressure to increase the depth, breadth, and scope of material taught to students. Without drastically changing the structure of the engineering degree, teaching with efficiency is an option that ensures students receive the necessary relevant instruction. To ensure that instruction is cognitively appropriate, a first step is determining the student’s current knowledge level. The purpose of this study is to determine if the degree to which a student’s problem-solving method aligns with that of experts predicts student ability to solve those problems.
Participating students completed a survey derived from a cognitive task analysis of three engineering design experts. Those responses were analyzed, and a linear regression run to determine if the responses predicted a student’s performance on classroom design problems. Results were mixed. The results from the freshmen students demonstrated no correlation between their score on the survey and their scores on classroom design problems. However, the sophomore students did find a predictive relationship, although not completely in the direction anticipated.
The inverse nature of the predictive relationship is worthy of further research to determine if that relationship is indicative instructional procedures tailored to specific classroom objectives or if it is the result of teaching potentially maladaptive skills. Additionally, more research is necessary to determine if the nature of the predictive relationship changes throughout the engineering degree program.
PHD (Doctor of Philosophy)
expertise, cognitive load theory, engineering education
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