Online Education vs Traditional Education: Analysis of Student Performance in Computer Science using Shapley Additive Explanations Cover Image

Online Education vs Traditional Education: Analysis of Student Performance in Computer Science using Shapley Additive Explanations
Online Education vs Traditional Education: Analysis of Student Performance in Computer Science using Shapley Additive Explanations

Author(s): Małgorzata Charytanowicz
Subject(s): Higher Education , ICT Information and Communications Technologies, Distance learning / e-learning
Published by: Vilniaus Universiteto Leidykla
Keywords: higher education; online learning; XGBoost; SHAP values; COVID-19; student motivation;

Summary/Abstract: Nowadays, the rapid development of ICT has brought more flexible forms that push the boundaries of classic teaching methodology. This paper is an analysis of online teaching and learning forced by the COVID-19 pandemic, as compared with traditional education approaches. In this regard, we assessed the performance of students studying in the face-to-face, online and hybrid mode for an engineering degree in Computer Science at the Lublin University of Technology during the years 2019–2022. A total of 1827 final test scores were examined using machine learning models and the Shapley additive explanations method. The results show an average increase in performance on final tests scores for students using online and hybrid modes, but the difference did not exceed 10% of the point maximum. Moreover, the students’ work had a much higher impact on the final test scores than did the study system and their profile features.

  • Issue Year: 22/2023
  • Issue No: 3
  • Page Range: 351-368
  • Page Count: 18
  • Language: English