Analyzing How E-Learning Activities Affect Student Engagement in Mathematics through Artificial Intelligence Analytics

Authors

  • Ferawati Ferawati Institut Teknologi dan Bisnis Bina Sarana Global, Indonesia
  • Rudi Setiyanto Institut Teknologi dan Bisnis Bina Sarana Global, Indonesia
  • Hasbullah Hasbullah Universitas Indraprasta PGRI, Indonesia, Indonesia

DOI:

https://doi.org/10.33394/mpm.v13i2.18437

Abstract

This study aimed to examine the influence of e-learning activity variables on students’ engagement in online mathematics learning.  The ex post facto design was selected because data were collected from existing Learning Management System (LMS) activity logs without experimental manipulation, allowing the analysis of naturally occurring relationships between variables. The population consisted of 350 senior high school students in Tangerang, Indonesia, during the 2024/2025 academic year, with a proportional stratified random sample of 180 students across Grades 10–12 to ensure representativeness. The study investigated four independent variables: login frequency (X1), learning duration (X2), assignment submission punctuality (X3), and forum participation activity (X4), with student engagement (Y) as the dependent variable. Multiple linear regression analysis was conducted after confirming that the data met classical assumptions, including normality, multicollinearity, and homoscedasticity. The results indicated that all four e-learning activity variables significantly and positively influenced student engagement. The regression equation was: Y = 35.214 + 0.426X1 + 0.321X2 + 0.214X3 + 0.178X4. T-test results confirmed the partial effects of each variable: Login Frequency (t = 5.195, p < 0.001), Learning Duration (t = 4.280, p < 0.001), Assignment Submission (t = 4.115, p < 0.001), and Forum Participation (t = 2.825, p = 0.005). These findings suggest that active participation in e-learning activities enhances student engagement in online mathematics learning, providing practical implications for teachers and school administrators to optimize LMS-based instructional strategies

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Published

2025-12-13

How to Cite

Ferawati, F., Setiyanto, R., & Hasbullah, H. (2025). Analyzing How E-Learning Activities Affect Student Engagement in Mathematics through Artificial Intelligence Analytics. Media Pendidikan Matematika, 13(2), 782–796. https://doi.org/10.33394/mpm.v13i2.18437

Issue

Vol. 13 No. 2 (2025): J-MPM

Section

Articles

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