Empirical Evidence on Gamification and Learning Analytics (GaLA): What is Missing?

Empirical Evidence on Gamification and Learning Analytics (GaLA): What is Missing?

Empirical Evidence on Gamification and Learning Analytics (GaLA): What is Missing?

By Ahmed Hosny Saleh Metwally, Ahmed Tlili, Ahmed Mohamed Fahmy Yousef, Ronghuai Huang, and Lennart E. Nacke

Abstract

“The growing adoption of learning analytics (LA) approaches and data mining (DM) techniques using educational gamification data sets is reflected in increased publications on this topic. However, with different gamified contexts and a variety of LA methods available, no comprehensive review summarized the obtained findings. Therefore, this research aims to identify studies’ characteristics, objectives, and methods used in gamification learning analytics (GaLA) research. To identify these, this study comprehensively reviewed the literature of 24 studies selected from an initial pool of 221 search results. The findings show that GaLA methods can be categorized into: visualization, data mining, social network analysis (SNA), statistics, and correlations. In conclusion, GaLA is defined as a data-driven approach using various methods of data analysis and mining techniques in gamified contexts for collecting, analyzing, and reporting data to assess or enhance the gameful experience, understand student behaviour, and improve learning outcomes.”

Reference

Metwally, A. H., Tlili, A., Yousef, A. M., Huang, R., &; Nacke, L. E. (2022). Empirical evidence on gamification and learning analytics (gala): What is missing? 2022 International Conference on Advanced Learning Technologies (ICALT). doi:10.1109/icalt55010.2022.00040 https://www.computer.org/csdl/proceedings-article/icalt/2022/951900a106/1FUUbBkb9sc

Keyword

Gamification, learning, empirical evidence, analytics, publications, research