Teaching-Learning Activity Modeling Based on Data Analysis

Symmetry

Kyungrog Kim¹  Yoo-Joo Choi⁴  Mihui Kim²  Jung-Won Lee⁵  Doo-Soon Park³  Nammee Moon⁶ 

[1] Department of Information Security, Hoseo University, Chungcheongnam-Do 336-795, Korea;Department of Computer and Web Information Engineering, Hankyong National University, Kyonggi-Do 456-749, Korea; E-Mail:;Department of Computer Software Engineering, Soonchunhyang University, Bucheon 420-767, Korea; E-Mail:;Department of New Media, Korean German Institute of Technology, Seoul 157-930, Korea; E-Mail:;Department of Electrical and Computer Engineering, Ajou University, Suwon 442-721, Korea; E-Mail:;Department of Mobile Software, Hoseo University, Chungcheongnam-Do 336-795, Korea

关键词: learning analytics;    learning style;    RFM technique;    learning-teaching activity model;    adaptive learning;   

DOI  :  10.3390/sym7010206

来源: mdpi

【 摘 要 】

Numerous studies are currently being carried out on personalized services based on data analysis to find and provide valuable information about information overload. Furthermore, the number of studies on data analysis of teaching-learning activities for personalized services in the field of teaching-learning is increasing, too. This paper proposes a learning style recency-frequency-durability (LS-RFD) model for quantified analysis on the level of activities of learners, to provide the elements of teaching-learning activities according to the learning style of the learner among various parameters for personalized service. This is to measure preferences as to teaching-learning activity according to recency, frequency and durability of such activities. Based on the results, user characteristics can be classified into groups for teaching-learning activity by categorizing the level of preference and activity of the learner.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland