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Autor/inn/enAlonso-Fernández, Cristina; Martínez-Ortiz, Iván; Caballero, Rafael; Freire, Manuel; Fernández-Manjón, Baltasar
TitelPredicting Students' Knowledge after Playing a Serious Game Based on Learning Analytics Data: A Case Study
QuelleIn: Journal of Computer Assisted Learning, 36 (2020) 3, S.350-358 (9 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Alonso-Fernández, Cristina)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0266-4909
DOI10.1111/jcal.12405
SchlagwörterCase Studies; Teaching Methods; Game Based Learning; Student Motivation; Prediction; Data Analysis; Pretests Posttests; Accuracy; First Aid; Peer Relationship; Models; Knowledge Level; Comparative Analysis; Student Evaluation
AbstractSerious games have proven to be a powerful tool in education to engage, motivate, and help students learn. However, the change in student knowledge after playing games is usually measured with traditional (paper) prequestionnaires-postquestionnaires. We propose a combination of game learning analytics and data mining techniques to predict knowledge change based on in-game student interactions. We have tested this approach in a case study for which we have conducted preexperiments-postexperiments with 227 students playing a previously validated serious game on first aid techniques. We collected student interaction data while students played, using a game learning analytics infrastructure and the standard data format Experience API for Serious Games. After data collection, we developed and tested prediction models to determine whether knowledge, given as posttest results, can be accurately predicted. Additionally, we compared models both with and without pretest information to determine the importance of previous knowledge when predicting postgame knowledge. The high accuracy of the obtained prediction models suggests that serious games can be used not only to teach but also to measure knowledge acquisition after playing. This will simplify serious games application for educational settings and especially in the classroom easing teachers' evaluation tasks. (As Provided).
AnmerkungenWiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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