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Evaluating students’ engagement with an online learning environment during and after COVID-19 related school closures: A survival analysis approach

journal contribution
posted on 23.11.2021, 13:47 authored by Markus Wolfgang Hermann Spitzer, Raphael Gutsfeld, Maria Wirzberger, Korbinian MoellerKorbinian Moeller
Background: Due to the COVID-19 pandemic schools all over the world were closed and thereby students had to be instructed from distance. Consequently, the use of online learning environments for online distance learning increased massively. However, the perseverance of using online learning environments during and after school closures remains to be investigated. Method: We examined German students’ (n ≈ 300,000 students; ≈ 18 million computed problem sets) engagement in an online learning environment for mathematics by means of survival analysis. Results: We observed that the total number of students who registered increased considerably during and after school closures compared to the previous three years. Importantly, however, the proportion of students engaged also decreased more rapidly over time. Conclusion: The application of survival analysis provided valuable insights into students’ engagement in online learning - or conversely students’ increased dropout rates - over time. Its application to educational settings allows to address a broader range of questions on students’ engagement in online learning environments in the future.

History

School

  • Science

Department

  • Mathematics Education Centre

Published in

Trends in Neuroscience and Education

Volume

25

Publisher

Elsevier BV

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Trends in Neuroscience and Education and the definitive published version is available at https://doi.org/10.1016/j.tine.2021.100168

Acceptance date

14/11/2021

Publication date

2021-11-18

Copyright date

2021

ISSN

2211-9493

Language

en

Depositor

Prof Korbinian Moeller. Deposit date: 22 November 2021

Article number

100168