Title: Analysing learning behaviours of advanced mathematics in MOOCs

Authors: Jiwei Qin; Zhenghong Jia; Pei Ma

Addresses: School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China; Center of Network and Information Technology, Xinjiang University, Urumqi 830046, China ' Center of Network and Information Technology, Xinjiang University, Urumqi 830046, China ' Center of Network and Information Technology, Xinjiang University, Urumqi 830046, China

Abstract: The purpose of this study is to analyse the relationship between online learning behaviour and learning achievement, and improve academic performance of learners in MOOCs. This paper analyses the learning behaviour of 1,388 undergraduates in the online advanced mathematics course of the online platform named 'Erya' with statistical analysis and clustering methods. The results show that: 1) the lack of positive interaction between teachers and learners can affect learners' enthusiasm for learning and learners' learning outcomes; 2) the academic performance related with the ethnic, the number of access and the completion of the after-school tasks, but the correlation with the discussion is small. In addition, we also made some suggestions based on the results of the learning behaviour analysis to improve academic performance in the massive open online courses.

Keywords: massive open online courses; MOOCs; subtraction clustering; k-means clustering; learning analytics.

DOI: 10.1504/IJCEELL.2019.099251

International Journal of Continuing Engineering Education and Life-Long Learning, 2019 Vol.29 No.1/2, pp.113 - 128

Received: 13 Sep 2018
Accepted: 16 Nov 2018
Published online: 23 Apr 2019 *

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