Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/65048


Title: Data mining for providing a personalized learning path in creativity: An application of decision trees
Authors: Lin, Chun Fu;Yeh, Yu-chu;Hung, Yu Hsin;Chang, Ray I
Contributors: 師培中心
Keywords: Intelligent tutoring systems;Architectures for educational technology systems;Teaching/learning strategies
Date: 2013
Issue Date: 2014-03-31 17:04:17 (UTC+8)
Abstract: Customizing a learning environment to optimize personal learning has recently become a popular trend in e-learning. Because creativity has become an essential skill in the current e-learning epoch, this study aims to develop a personalized creativity learning system (PCLS) that is based on the data mining technique of decision trees to provide personalized learning paths for optimizing the performance of creativity. The PCLS includes a series of creativity tasks as well as a questionnaire regarding several key variables. Ninety-two college students were included in this study to examine the effectiveness of the PCLS. The experimental results show that, when the learning path suggested by a hybrid decision tree is employed, the learners have a 90% probability of obtaining an above-average creativity score, which suggests that the employed data mining technique can be a good vehicle for providing adaptive learning that is related to creativity. Moreover, the findings in this study shed light on what components should be accounted for when designing a personalized creativity learning system as well as how to integrate personalized learning and game-based learning into a creative learning program to maximize learner motivation and learning effects.
Relation: Computers & Education,68, 199-210
Data Type: article
DOI 連結: http://dx.doi.org/10.1016/j.compedu.2013.05.009
Appears in Collections:[師資培育中心] 期刊論文

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