Tampa, Florida
June 15, 2019
June 15, 2019
June 19, 2019
Manufacturing
10
10.18260/1-2--33507
https://peer.asee.org/33507
387
Dr. Faisal Aqlan is an assistant professor of industrial engineering at Penn State Behrend. He earned his Ph.D. in Industrial and Systems Engineering from the State University of New York at Binghamton in 2013. Dr. Aqlan is a senior member of the Institute of Industrial and Systems Engineers (IISE) and has received numerous awards and honors including the IBM Vice President award for innovation excellence.
Dr. Richard Zhao is an Assistant Professor of Computer Science and Software Engineering at the Behrend College of the Pennsylvania State University. He received his B.S. degree in Computer Science from the University of Toronto, and his M.S. and Ph.D. degrees in Computing Science from the University of Alberta in 2009 and 2015, respectively. His research focuses on the application of artificial intelligence in games and machine learning techniques in data mining.
Metacognition is the process of “thinking about thinking” such that individuals learn methods to understand the way that they learn, what they are lacking in their current learning strategies, and how to improve. Metacognition is an important dimension of problem solving because it allows problem solvers to analyze problems and find viable solutions. In design and manufacturing, problem solving focuses on optimizing the product design and improving the production process. In this paper, we discuss the development of physical simulation games to evaluate metacognitive awareness in industrial engineering students. In order to develop metacognitive awareness, students participate in group manufacturing simulations and each group evaluate the work of other groups. Metacognitive awareness inventory (MAI) is used to evaluate the metacognitive awareness of the students before and after their participation in the simulation activities. MAI is an instrument designed to assess general self-regulated learning skills. The instrument has 52 items that are classified by type of cognitive knowledge: declarative (DK), procedural (PK), and conditional (CK); or by specific metacognitive process: planning (P), information management strategies (IMS), monitoring (M), debugging strategies (DS), and evaluation (E). Results show that the students improved their metacognitive awareness for all the MAI categories. However, only the improvement in the last three categories (i.e., M, DS, and E) was statistically significant.
Aqlan, F., & Lum, H. C., & Elliott, L. J., & Zhao, R. (2019, June), Using Manufacturing Simulations to Evaluate Metacognitive Awareness in Industrial Engineering Students Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--33507
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