Evaluation of Affective Intervention Process in Development of Affect-aware Educational Video Games
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 1675–1679 (2016)
Abstract. In this paper initial experiences are presented on implementing specific methodology of affective intervention design (AFFINT) for development of affect-aware educational video games. In the described experiment, 10 student teams are to develop affect-aware educational video games using AFFINT to formalize the whole process. Although all projects are still in progress, first observations and conclusions may already be presented.
- A. Landowska, M. Szwoch, W. Szwoch, “Methodology of Affective Intervention Design for Intelligent Systems,” Interact. Comput. 2016, http://dx.doi.org/10.1093/iwc/iwv047.
- R.Baker, “Modeling and understanding students’ off-task behavior in intelligent tutoring systems,” Proc. of the SIGCHI conference on Human factors in computing systems, ACM 2007, pp. 1059-1068.
- M. Szwoch, “Design Elements of Affect Aware Video Games,” roceedings of the Mulitimedia, Interaction, Design and Innnovation Article No. 18, 2015.
- H. Gunes, B. Schuller, “Categorical and dimensional affect analysis in continuous input: Current trends and future directions,” Image and Vision Computing, vol. 31, 2013, pp. 120-136
- J. N. Bailenson, E. D. Pontikakis, I. B. Mauss, J. J. Gross, M. E. Jabon, C. A. C. Hutcherson, C. Nass, O. John, “Real-time classification of evoked emotions using facial feature tracking and physiological responses,” International Journal of Human-Computer Studies, 66(5), 2008, 303-317.
- M. Szwoch, P. Pieniążek, “Facial Emotion Recognition Using Depth Data,” The 8th Int. Conf. on Human System Interaction, pp. 271-277, IEEE, 2015.
- Z. Zeng, M. Pantic, G. Roisman, T.S.Huang, “A survey of affect recognition methods: Audio, visual, and spontaneous expressions,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, 31(1), 2009, pp.39-58.
- S. H. Fairclough, Fundamentals of physiological computing, Interact. Comput. 21 (1-2), 2009, pp. 133-145.
- W. Szwoch, “Using Physiological Signals for Emotion Recognition”, Proc 6th International Conference on Human Systems Interaction, 2013, pp. 556-561.
- H. Binali, C. Wu, V. Potdar, “A new significant area: Emotion detection in e-learning using opinion mining techniques,” proc. of 3rd IEEE International Conference on Digital Ecosystems and Technologies, 2009, pp. 259-264.
- A. Kołakowska, “Recognizing emotions on the basis of keystroke dynamics,” Proc. of the 8th International Conference on Human System Interaction, 2015, pp.291-297.
- A. Kołakowska, “A review of emotion recognition methods based on keystroke dynamics and mouse movements,” Proc. of 6th International Conference on Human System Interaction, 2013, pp.548-555.
- H. Gunes, M. Piccardi, "Affect Recognition from Face and Body: Early Fusion versus Late Fusion," Proc. IEEE International Conference on Systems, Man and Cybernetics (SMC ',05), pp. 3437-3443, 2005.
- T. Partala, A. Kallinen, “Understanding the Most Satisfying and Unsatisfying User Experiences: Emotions, Psychological Needs, and Context”. Interacting with Computers, 24, 1, 2012, pp. 25–34.
- K. Hone, “Empathic Agents to Reduce User Frustration: The Effects of Varying Agent Characteristics,” Interacting with Computers, 18, 2, 2006, pp. 227–245.
- K. Höök, “User-Centred Design and Evaluation of Affective Interfaces,” From Brows to Trust, Springer, 2005, pp. 127–160.
- L. Chittaro L., R. Sioni, “Affective Computing vs. Affective Placebo: Study of a Biofeedback-Controlled Game for Relaxation Training,” International Journal of Human-Computer Studies, 72, 8–9, 2014, pp. 663–673.