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Board 69 : Work in Progress: Constructing a Prediction Model of Creativity and Cognitive Concept Connections Based on Learning Portfolio

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Conference

2018 ASEE Annual Conference & Exposition

Location

Salt Lake City, Utah

Publication Date

June 23, 2018

Start Date

June 23, 2018

End Date

July 27, 2018

Conference Session

Computers in Education Division Poster Session

Tagged Division

Computers in Education

Page Count

12

Permanent URL

https://peer.asee.org/30087

Download Count

24

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Paper Authors

biography

Ting-Ting Wu National Yunlin University of Science and Technology

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Ting-Ting Wu is currently an Associate Professor in the Graduate School of Technological and Vocational Education at National Yunlin University of Science and Technology, Taiwan. She received her Ph.D. degree from the Department of Engineering Science at National Cheng Kung University. She received the MS degree in Information and Learning Technology from National University of Tainan. Her research interests include mobile and ubiquitous learning, information technology-applied instructions and intelligent learning systems.

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biography

Yueh-Min (Ray) Huang National Cheng Kung University

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Dr. Yueh-Min Huang received his MS and Ph.D. degrees in Electrical Engineering from the University of Arizona, respectively. He is currently a chair professor of the Department of Engineering Science and associate dean of Engineering College at National Cheng-Kung University, Taiwan. His research interests include e-Learning, embedded systems and artificial intelligence. He has co-edited 3 books published by Springer Verlag and has published over 250 refereed journal papers. His works have received over 5000 Google citations in recent 5 years. Dr. Huang has received many research awards, including best paper awards, such as GCCCE2013 and national competition prizes, such as the first prize of ARM Code-O-Rama 2012. He is also a winner of the distinguished research award of the National Science Council, Taiwan in 2010 and 2013, respectively. Dr. Huang is in the editorial board of several SSCI- and SCI-indexed journals such as Interactive Learning Environments and Wireless Communications and Mobile Computing. He was the technical program chair of International Conference on Web-based Learning (2013) and the general chair of AECT International Conference on the Frontier in e-Learning Research 2013 (ICFER) and the e-Learning Forum Asia 2014. Dr. Huang became a Fellow of British Computer Society (FBCS) in 2011 and a senior member of the IEEE.

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Pei-Yu Cheng National Cheng Kung University

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Pei-Yu Cheng is a Ph.D. student in the Department of Engineering Science at National Cheng Kung University, Tainan, Taiwan. He received his Master degree from the Department of Information Engineering at Kun Shan University, Taiwan, in 2013. His main research interests include E-Learning, Learning Technology, Mobile learning, E-Books. He is working on his doctoral program under his advisor, Prof. Yueh-Min Huang.

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Abstract

The skills required of new employees by industry are increasingly interdisciplinary and creativity-related because of a paradigm shift in target markets. Engineering education should therefore focus on helping students develop their creativity and critical thinking skills. A student’s level of creativity is usually evaluated by examining his or her final projects. However, the language that students use in discussions and interactions can be analyzed to determine their cognitive processes and thus their creativity. This study collected 1 year of records of discussions and interactions on a Moodle learning platform among students in two college courses (Computer Science and Engineering). The discussions and interactions were filmed and recorded in a backend database and were later transcribed. The transcripts were arranged and analyzed. The data were divided into a training set (79 discussions; 90%) and a test set (9 discussions; 10%) before data mining was performed. The training set was used to construct a training model, and the test set was employed to examine whether the proposed model correctly predicted creativity in the students. K-means clustering was used to cluster the language in the discussion content. The level of creativity of each student was correctly predicted by the model, which can be used by teachers to provide feedback and support in a timely manner for triggering different thinking in students to enhance his or her creative thinking. The proposed model can thus identify level of creativity and assist both teachers and students.

Wu, T., & Huang, Y. R., & Cheng, P. (2018, June), Board 69 : Work in Progress: Constructing a Prediction Model of Creativity and Cognitive Concept Connections Based on Learning Portfolio Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/30087

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