The dynamics of affective transitions in simulation problem-solving environments

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4738 LNCS, Issue , 2007, Pages 666-677

  Baker, Ryan S J D ^a   Rodrigo, Ma Mercedes T ^a   Xolocotzin, Ulises E ^a,b  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^b ATENEO DE MANILA UNIVERSITY   (Philippines)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; PROBLEM SOLVING; STUDENTS;

AFFECTIVE TRANSITIONS; INCREDIBLE MACHINE; QUANTITATIVE FIELD OBSERVATIONS;

DYNAMICS;

EID: 38049083678     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74889-2_58     Document Type: Conference Paper

References (20)

1. Amershi, S., Conati, C., Maclaren, H.: Using feature selection and unsupervised clustering to identify affective expressions in educational games. Proceedings of the Workshop. Motivational and Affective Issues in ITS. In: conjunction with ITS, 8th International Conference on Intelligent Tutoring Systems (2006), Jhongli, Taiwan (2006)
2. Baker, R.S.J.d., Corbett, A.T., Koedinger, K.R., Evenson, E., Roll, I., Wagner, A.Z., Naim, M., Raspat, J., Baker, D.J., Beck, J. Adapting to When Students Game an Intelligent Tutoring System. In: Proceedings of the 8th International Conference on Intelligent Tutoring Systems, pp. 392-401 (2006)
3. Baker, R.S., Corbett, A.T., Koedinger, K.R., Wagner, A.Z.: Off-Task Behavior in the Cognitive Tutor Classroom: When Students Game the System. In: Proceedings of ACM CHI: Computer-Human Interaction, pp. 383-390 (2004)
4. Chaffar, S., Frasson, C.: Using and Emotional Intelligent Agent to Improve the Learner's Performance. In: Proceedings of the Workshop on Social and Emotional Intelligence in Learning Environments, In conjuction with Intelligent Tutoring Systems, Maceio, Brazil (2004)
5. Cohen, J.A.: Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement-20, 37-46 (1960)
6. Conati, C., Chabbal, R., Maclaren, H.: A: study on using biometric sensors for detecting user emotions in educational games. In: Proceedings of the Workshop Assessing and Adapting to User Attitude and Affects: Why, When and How? In: conjunction with UM '03, 9th International Conference on User Modeling, Pittsburgh, PA, U.S.A (2003)
7. Craig, S.D., Graesser, A.C., Sullins, J., Gholson, B.: Affect and learning: an exploratory look into the role of affect in learning with AutoTutor. Journal of Educational Media-29(3), 241-250 (2004)
8. Csikszentmihalyi, Flow, M.: The Psychology of Optimal Experience. Harper and Row, New York (1990)
9. D'Mello, S.K., Craig, S.D., Witherspoon, A., McDaniel, B., Graesser, A.: Integrating affect sensors in an intelligent tutoring system. In: Affective Interactions: The Computer in the Affective Loop Worksho. In: conjunction with International conference on Intelligent User Interfaces, pp. 7-13 (2005)
10. D'Mello, S., Taylor, R.S., Graesser, A.: Monitoring Affective Trajectories during Complex Learning. In: Proceedings of the 29th Annual Meeting of the Cognitive Science Society (in press),
11. de Vicente, A., Pain, H.: Informing the detection of the students' motivational state: an empirical study. In: Proceedings of the 6th International Conference on Intelligent Tutoring Systems, pp. 933-943 (2002)
12. Guastello, S.J., Johnson, E.A., Rieke, M.L.: Nonlinear Dynamics of Motivational Flow. Nonlinear dynamics, psychology, and life sciences-3(3), 259-274 (1999)
13. Johnson, W.L., Kole, S., Shaw, E., Pain, H.: Socially Intelligent Learner-Agent Interaction Tactics. In: Proceedings of Artificial Intelligence in Education: Shaping the Future of Learning through Intelligent Technologies, pp. 431-433 (2003)
14. Metropolis, N., Ulam, S.: The Monte Carlo Method. Journal of the American Statistical Association-44, 335 (1949)
15. Mota, S., Picard, R.W.: Automated posture analysis for detecting learner's interest level. Workshop on Computer Vision and Pattern Recognition for Human-Computer Interaction, CVPR HCI (2003)
16. Rodrigo, M., Baker, R., Lagud, M., Lim, S., Macapanpan, A., Pascua, S., Santillano, J., Sevilla, R., Sugay, J., Tep, S., Viehland, N.: Affect and Usage Choices in Simulation Problem-Solving Environments. In: Proceedings of the 13th International Conference on Artificial Intelligence in Education (in press). Available online via Google Scholar,
17. Rosenthal, R., Rosnow, R.L.: Essentials of Behavioral Research: Methods and Data Analysis, 2nd edn. McGraw-Hill, Boston (1991)
18. Sierra Online, Inc, The Incredible Machine: Even More Contraptions (2001)
19. Thayer, R.E.: The biopsychology of mood and arousal. Oxford University Press, New York (1989)
20. Ziemek, T.: Two-D or not Two-D: gender implications of visual cognition in electronic games. In: Proceedings of the 2006 Symposium on Interactive 3D graphics and games, pp. 183-190 (2006)