學術產出-Periodical Articles

Article View/Open

Publication Export

Google ScholarTM

政大圖書館

Citation Infomation

題名 Data mining for providing a personalized learning path in creativity: An application of decision trees
作者 Lin, Chun Fu ; Yeh, Yu-chu ; Hung, Yu Hsin ; Chang, Ray I
貢獻者 師培中心
關鍵詞 Intelligent tutoring systems; Architectures for educational technology systems; Teaching/learning strategies
日期 2013
上傳時間 31-Mar-2014 17:04:17 (UTC+8)
摘要 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.
關聯 Computers & Education,68, 199-210
資料類型 article
DOI http://dx.doi.org/10.1016/j.compedu.2013.05.009
dc.contributor 師培中心en_US
dc.creator (作者) Lin, Chun Fu ; Yeh, Yu-chu ; Hung, Yu Hsin ; Chang, Ray Ien_US
dc.date (日期) 2013en_US
dc.date.accessioned 31-Mar-2014 17:04:17 (UTC+8)-
dc.date.available 31-Mar-2014 17:04:17 (UTC+8)-
dc.date.issued (上傳時間) 31-Mar-2014 17:04:17 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/65048-
dc.description.abstract (摘要) 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.en_US
dc.format.extent 1505585 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Computers & Education,68, 199-210en_US
dc.subject (關鍵詞) Intelligent tutoring systems; Architectures for educational technology systems; Teaching/learning strategiesen_US
dc.title (題名) Data mining for providing a personalized learning path in creativity: An application of decision treesen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.compedu.2013.05.009en_US
dc.doi.uri (DOI) http://dx.doi.org/10.1016/j.compedu.2013.05.009en_US