Tampa, Florida
June 15, 2019
June 15, 2019
June 19, 2019
Computing and Information Technology
15
10.18260/1-2--32901
https://peer.asee.org/32901
571
Postdoctoral Fellow of Institute of China's Science, Technology and Education Strategy, Zhejiang University; Lecturer, School of Public Administration, Zhejiang University of Finance & Economics
Postgraduate of Institute of China's Science,Technology and Education Strate, Zhejiang University
Hanbing Kong, PhD
Deputy Director, the Research Center for S&T, Education Policy, and Associate Professor of Management, Zhejiang University, and JEE Liaison for Research in Higher Education of Engineering.
Professor of Institute of China's Science,Technology and Education Strategy;Deputy Director of the Institute of Engineering Education, Zhejiang University.
Computational Thinking (CT) is typically construed as an essential competence in solving problems and designing complex systems in the digital world. Robotics programs provide learning environments for acquiring core computational thinking skills. This study first proposes a framework of computational thinking in the context of engineering (CT-ENG), using qualitative content analysis on industry interviews. The authors then introduce the program of the Robotics Class of Zhejiang University in China, providing an integrative approach to teaching computational thinking effectively. The Robotics Class engages students in project-based computing-aided engineering activities throughout the four-year bachelor’s program, and improves their computational thinking skills through engineering engagement. The findings in this study could have some implications for non-CS engineering majors to promote computing education and equip students with computational thinking at digital era.
Key Words: Computational Thinking, Engineering with Big E, Robotics, Case Study
Wu, J., & Wang, Y., & Kong, H., & Zhu, L. (2019, June), How to Cultivate Computational Thinking-Enabled Engineers: A Case Study on the Robotics Class of Zhejiang University Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32901
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