Assessing Aptitude for Learning with a Serious Game for Foreign Language and Culture
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Realtime Knowledge Space Skill Assessment for Personalized Digital Educational Games
ICALT '09 Proceedings of the 2009 Ninth IEEE International Conference on Advanced Learning Technologies
Computers & Education - Virtual learning? Selected contributions from the CAL 05 symposium
Case retrieval in ontology-based CBR systems
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Easing assessment of game-based learning with and LAMS
Proceedings of the second ACM international workshop on Multimedia technologies for distance leaning
Annie: Automated Generation of Adaptive Learner Guidance for Fun Serious Games
IEEE Transactions on Learning Technologies
Petri Nets and Ontologies: Tools for the "Learning Player" Assessment in Serious Games
ICALT '11 Proceedings of the 2011 IEEE 11th International Conference on Advanced Learning Technologies
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Serious games are increasingly used in schools, universities or in vocational training. When they are used in the classroom, teachers often have to deal with the lack of tools for monitoring the students during the game and assessing them after the game. So they often tend to add assessment questionnaires to the fun sequence of "learning by playing", to ensure that students have learned during the session. Our goal is to enable the teacher to do without this type of questionnaires by providing them an automated tool for monitoring and analyzing the actions performed by learners. The system combines an "expert Petri Net" and a domain and game action ontology. Our first experiment conducted on a sample of fifteen students showed that the diagnostic tool gives relatively close results to those of an online assessment questionnaire proposed by the teacher.