Online Tests and Predictive Analytics

Authors

  • Andreas Helfrich-Schkarbanenko
  • Nathalie Verné University of Applied Sciences Esslingen

DOI:

https://doi.org/10.3991/ijet.v17i23.36459

Keywords:

STACK, online assessment, learning analytics, predictive analytics, multivariate nonlinear regression

Abstract


We present a framework that estimates students’ exam performance in the context of mathematics lectures. For the prediction, we apply a multi-variate nonlinear regression implemented in MATLAB based on the results of five tests acting as independent data. The electronic tests were implemented by means of online assessment system STACK. The tests cover all major topics and are evenly distributed throughout the lecture period. The performance of the approach is quantitatively tested on student groups. In the future, the insights gained in this way will serve as a starting point for prespective analytics.

Cover iJET Vol. 17 No. 23 (2022)

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Published

2022-12-08

How to Cite

Helfrich-Schkarbanenko, A., & Verné, N. (2022). Online Tests and Predictive Analytics. International Journal of Emerging Technologies in Learning (iJET), 17(23), pp. 89–93. https://doi.org/10.3991/ijet.v17i23.36459

Issue

Vol. 17 No. 23 (2022)

Section

Special Focus Papers

License

Copyright (c) 2022 Nathalie Verné, Prof. Dr. rer. nat. Andreas Helfrich-Schkarbanenko

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