Title: Modelling and analysis of the influence of affective factors on students' learning efficiency improvement based on big data

Authors: Humin Yang; Henry Loghej

Addresses: Education Science College, Fuyang Normal College, Fuyang 236037, China ' College of Education, The University of Alabama, Tuscaloosa, AL 35487, USA

Abstract: In order to improve learning efficiency and quantify the quality of teaching, a method of modelling the influence of emotional factors on students' learning efficiency is proposed. The statistical feature analysis object model is constructed. The quantitative regression analysis method is used to construct the big data model of emotional factors and learning efficiency. The association rule decomposition method is used to decompose and model the big data samples, and analyse the influence factors of emotion on learning efficiency. The fuzzy constraint control method clusters and mines big data association rules, and analyses the promotion factors of emotional factors to students' learning efficiency, calculates the level of promotion contribution, and adopts adaptive evolutionary game method to realise emotional factors under big data. Modelling the impact of student learning efficiency, experiments show that the proposed method has high confidence level and small error in analysing subject problems.

Keywords: big data; affective factor; students' learning efficiency; information fusion; data mining.

DOI: 10.1504/IJCEELL.2019.102765

International Journal of Continuing Engineering Education and Life-Long Learning, 2019 Vol.29 No.4, pp.362 - 373

Received: 19 Dec 2018
Accepted: 21 Feb 2019
Published online: 02 Oct 2019 *

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