Title: The mixed teaching reform and empirical analysis of MOOC localisation curriculum

Authors: Yu Cao; Hui-sheng Zhu; Chao Li

Addresses: School of Physics and Information Engineering, Jiangsu Second Normal University, Nanjing, 210013, China; Jiangsu Province Engineering Research Center of Basic Education Big Data Application, Nanjing, 210013, China ' School of Physics and Information Engineering, Jiangsu Second Normal University, Nanjing, 210013, China; Jiangsu Province Engineering Research Center of Basic Education Big Data Application, Nanjing, 210013, China ' School of Physics and Information Engineering, Jiangsu Second Normal University, Nanjing, 210013, China; Jiangsu Province Engineering Research Center of Basic Education Big Data Application, Nanjing, 210013, China

Abstract: In order to solve the problems of low interest in learning and unsatisfactory improvement of learning results in traditional methods, the mixed teaching reform and empirical analysis of MOOC localisation curriculum is proposed. Firstly, SPSS statistical software is used to conduct exploratory factor analysis on the data, and alpha coefficient is used to analyse the credibility of each dimension of teaching reform. Then, take the three dimensions of peer relationship, teacher-student relationship and classroom involvement as independent variables, and the total score of learning gains as dependent variables to establish a regression model. Finally, fuzzy comprehensive evaluation is used to evaluate the effect of teaching reform, and a targeted teaching reform strategy is given. The experimental results show that after using this method, students' interest in learning can be improved by 0.57, and the score can be improved by about 142 points, the practical application effect is good.

Keywords: SPSS statistical software; MOOC localisation; factor load value; alpha coefficient; multiple linear regression analysis.

DOI: 10.1504/IJISD.2025.149103

International Journal of Innovation and Sustainable Development, 2025 Vol.19 No.5/6, pp.572 - 591

Received: 09 Jan 2023
Accepted: 21 Apr 2023
Published online: 14 Oct 2025 *

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