New Special Section in the Journal of Learning Analytics published, including an open access editorial introduction by the Guest Editors.
Kim, Y. J., Ruipérez Valiente, J. A., 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
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.
