Title: Analysis of the learners' learning behaviours in MOOC informationisation leadership

Authors: Mei Liu; Shusheng Shen; Changsheng Chen

Addresses: School of Education Science, Nanjing Normal University, Ninghai Road 122, Gulou, Nanjing, Jiangsu, 210097, China; School of Education Science, Linyi University, Middle of Shuangling Road, Linyi, 276005, China ' School of Education Science, Nanjing Normal University, Ninghai Road 122, Gulou, Nanjing, Jiangsu, 210097, China ' School of Modern Service Management, Shandong Youth University of Political Science, Jingshi Road 31699, Licheng, Jinan, Shandong, 250100, China

Abstract: For better adapting the course to different learners' needs, this study analysed the learners' online learning behaviours. Through using data mining technology to mine the learning behaviours from five dimensions: video watching, text reading, discussion and communication, test and assignments taking, we draw the following conclusions: the demographic characteristics of learners show that the learners are mainly composed of principals, middle-level educational managers and key teachers. The learner's general learning behaviour characteristics are mainly expressed by the facts that the learners' interest in practical cases, and few participants can last more than four weeks, and the learners like videos and texts but they do not like to speak in the discussion forum. Learners can be divided into three clusters: certificate-oriented learners, practice oriented learners and browsers. The value of MOOC should not be evaluated on the basis of certification rates but on whether the learner's learning needs are met.

Keywords: online learning behaviour analysis; massive open online course; MOOC; informationisation leadership; clustering; data mining.

DOI: 10.1504/IJCEELL.2021.115979

International Journal of Continuing Engineering Education and Life-Long Learning, 2021 Vol.31 No.3, pp.281 - 297

Received: 30 Jun 2019
Accepted: 10 Oct 2019

Published online: 27 Apr 2021 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article