Title: Online course learning outcome evaluation method based on big data analysis

Authors: Hai-jie Li; Min Peng

Addresses: Academic Affairs Office, Beihua University, Jilin 132013, China ' College of Information Engineering, Wuhan Technology and Business University, Wuhan, Hubei, 430065, China

Abstract: In order to solve the low credibility and poor timeliness of the online course learning effect evaluation, a method based on big data for online course learning results evaluation is proposed, which can better solve the problems existing in traditional methods. A statistical average analysis model for big data of online course learning outcomes is constructed for learning outcome big data analysis based on the sample regression analysis method; a decision objective function of online course learning outcome evaluation is established. The experimental results show that when the method proposed in this paper is adopted to evaluate online course learning outcomes, the method has relatively high confidence and overall timeliness, and the time taken to evaluate the effectiveness of online courses is 28 s and 29 s less than that of the other two methods, so it can provide accurate and reliable evaluation results.

Keywords: big data analysis; online course learning; outcome evaluation; feature extraction; pattern recognition.

DOI: 10.1504/IJCEELL.2019.102769

International Journal of Continuing Engineering Education and Life-Long Learning, 2019 Vol.29 No.4, pp.349 - 361

Received: 29 Nov 2018
Accepted: 15 Feb 2019
Published online: 02 Oct 2019 *

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