Using Comparative Behavior Analysis to Improve the Impact of Serious Games on Students’ Learning Experience
| Autor: | Dominique Jaccard, Ariane Dumont, Jarle Hulaas |
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| Rok vydání: | 2016 |
| Předmět: |
Multimedia
Process (engineering) business.industry Deep learning 05 social sciences Learning analytics 050301 education 02 engineering and technology computer.software_genre Open source Software deployment 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Statistical analysis Artificial intelligence Student learning business Psychology 0503 education computer TRACE (psycholinguistics) |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319501819 GALA BASE-Bielefeld Academic Search Engine |
| DOI: | 10.1007/978-3-319-50182-6_18 |
| Popis: | In the last decade, the use of serious games as a teaching and learning tool has steadily increased in many disciplines. Nevertheless, serious games are still facing crucial challenges, such as their integration in the global learning process. On the other hand, with the increased adoption of online applications and courses, it is becoming possible to collect and centralize large amounts of trace data generated by players. Such data may be used to produce statistics on students’ behaviors inside pedagogical serious games, both as individuals and aggregated as groups (e.g., classrooms). In this paper we propose a classification of potential uses of statistics in serious games and give new insights into how statistical analysis of groups’ behavior may impact positively on the learning process. We also present experimental results obtained during a large-scale game deployment using the Wegas platform, our open source platform for game authoring and execution. |
| Databáze: | OpenAIRE |
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