Analytics for Game-Based Learning

Authors

DOI:

https://doi.org/10.18608/jla.2022.7929

Keywords:

game-based assessment , learning analytics, editorial

Abstract

The purpose of this special section is to collect in one place how data in game-based learning environments may be turned into valuable analytics for student assessment, support of learning, and/or improvement of the game, using existing or emerging empirical research methodologies from various fields, including computer science, software engineering, educational data mining, learning analytics, learning sciences, statistics, and information visualization. Four contributions form this special section, which will inspire future high-quality research studies and contribute to the growing knowledge base of learning analytics and game-based learning research and practice.

References

Alonso-Fernández, C., Calvo-Morata, A., Freire, M., Martínez-Ortiz, I., & Fernández-Manjón, B. (2019). Applications of data science to game learning analytics data: A systematic literature review. Computers & Education, 141, 103612. https://doi.org/10.1016/j.compedu.2019.103612

Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016). Digital games, design, and learning: A systematic review and meta-analysis. Review of Educational Research, 86(1), 79–122. https://doi.org/10.3102/0034654315582065

Ifenthaler, D., & Gibson, D. C. (2019). Opportunities of analytics in challenge-based learning. In A. Tlili & M. Chang (Eds.), Data analytics approaches in educational games and gamification systems (pp. 55–68). Springer. https://doi.org/10.1007/978-981-32-9335-9_3

Kim, Y. J., & Ifenthaler, D. (2019). Game-based assessment: The past ten years and moving forward. In D. Ifenthaler & Y. J. Kim (Eds.), Game-based assessment revisited (pp. 3–12). Springer. https://doi.org/10.1007/978-3-030-15569-8_1

Loh, C. S., Sheng, Y., & Ifenthaler, D. (Eds.). (2015). Serious games analytics: Methodologies for performance measurement, assessment, and improvement. Springer. https://doi.org/10.1007/978-3-319-05834-4

Downloads

Published

2022-12-16

How to Cite

Kim, Y. J. ., Valiente, J. A. R., Ifenthaler, D., Harpstead, E., & Rowe, E. (2022). Analytics for Game-Based Learning. Journal of Learning Analytics, 9(3), 8-10. https://doi.org/10.18608/jla.2022.7929

Issue

Vol. 9 No. 3 (2022): Analytics for Game Based Learning

Section

Special Section on Analytics for Game-based Learning

License

Copyright (c) 2022 Journal of Learning Analytics

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Authors who publish with this journal agree to the following terms:
  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons License, Attribution - NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) license that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).