%0 Conference Proceedings %T Adapting to When Students Game an Intelligent Tutoring System %+ Learning Sciences Research Institute %+ Human-Computer Interaction Institute %+ School of Design %+ North Hills Junior High %+ Machine Learning Department [Carnegie Mellon Univ.] %A Baker, Ryan %A Koedinger, Kenneth R. %A Corbett, Albert T. %A Wagner, Angela Z. %A Evenson, Shelley %A Roll, Ido %A Naim, Meghan %A Raspat, Jay %A Beck, Joseph E. %< avec comité de lecture %( Proceedings of the 8th International Conference on Intelligent Tutoring Systems, 26-30 June 2006. %B International Conference on Intelligent Tutoring Systems %C Jhongli, Taiwan %8 2006 %D 2006 %K game systems %Z Computer Science [cs]/Technology for Human LearningConference papers %X It has been found in recent years that many students who use intelligent tutoring systems game the system, attempting to succeed in the educational environment by exploiting properties of the system rather than by learning the material and trying to use that knowledge to answer correctly. In this paper, we introduce a system which gives a gaming student supplementary exercises focused on exactly the material the student bypassed by gaming, and which also expresses negative emotion to gaming students through an animated agent. Students using this system engage in less gaming, and students who receive many supplemental exercises have considerably better learning than is associated with gaming in the control condition or prior studies. %G English %2 https://telearn.hal.science/hal-00190177/document %2 https://telearn.hal.science/hal-00190177/file/Baker_2006.pdf %L hal-00190177 %U https://telearn.hal.science/hal-00190177 %~ TELEARN %~ TICE %~ LORIA2 %~ TEL