Tzu-Wei Tsai
ABSTRACT
E-learning has been the mainstream in the field of education. Nowadays, many children use the game-based learning materials for leaning. However, the difficulty and frustration of the materials usually decrease learners' pleasure and interests. Learners' facial emotions intuitionally respond to their learning condition. Accordingly, the aim of the study is developing the affective interface of the game-based adaptive learning to enhance children's learning motivation. The various difficulty levels of a puzzle game and learning contents are designed to adapt in accordance to the learner's facial emotion which is recognized and classified by Ekam's FACS. Three groups of the elementary school students are recruited to separately participate in the evaluation experiments. One group is for the adaptive game, another for the adaptive learning content, and the other one is the control group for no adaptive learning. Afterword the subjects use the affective usability scale to evaluate the system. The results reveal the game-based learning system could enhance learners' learning motivation and satisfaction. Conclude that the affective interface developed by facial affective computing is proposed to apply on the adaptive learning.
- Zhuang, C. 1997. Education Psychology, Donghua Publisher, TaipeiGoogle Scholar
- Mehrabian, A., & James, A. R. 1974. The basic emotional impact of environments. Perceptual and Motor Skills, 38(1), 283--301.Google ScholarCross Ref
- Vesterinen, E. 2001. Affective Computing. Tik-111.590 Digital media research seminar, Helsinki, Finland.Google Scholar
- Guo, B.2006. Research on the Relationship between the Product's Form and Emotion---A. Case Study of Electric Kettles. Master Thesis, National Yun-lin university of science and technology, TaiwanGoogle Scholar
- Ekman, P., Friesen, W. V., & Hager, J. C. 2002. Facial Action Coding System Manual. Salt Lake: A Human Face.Google Scholar
- Gee, J. P. 2004. Learning by design: Games as learning machines. Interactive Educational Multimedia, number 8, p.15--23Google Scholar
- Pekrun, R., Goetz, T., Titz, W. & Perry, R. P. 2002. Academic Emotions in Students' Self-Regulated Learning and Achievement: A Program of Qualitative and Quantitative Research, Educational Psychologist, 37(2), 91--105.Google ScholarCross Ref
- Vesterinen, E. 2001. Affective Computing. Tik-111.590 Digital media research seminar, Helsinki, Finland.Google Scholar
- Mao X., & Li Z. 2010. Agent based affective tutoring systems: A pilot study. Computers & Education 55, 202--208. Google ScholarDigital Library
- Picard, R. W. (1997). Affective computing. Cambridge: The MIT Press. Google ScholarDigital Library
- Gilleade, Kiel, Dix, Alan & Allanson, Jen 2005. Affective Videogames and Modes of Affective Gaming: Assist Me, Challenge Me, Emote Me, Changing Views -- Worlds in Play.Google Scholar
- Malone, T., & Lepper, M. 1987. Making learning fun: A taxonomy of intrinsic motivations for learning. In R. Snow & M. Farr (Eds.), Aptitude, learning, and instruction, Vol. 3, p. 223--253.Google Scholar
- Garris, R. & Ahlers, R. 2002. Games, Motivation, and Learning: A Research and Practice Model. Simulation Gaming December 2002 vol. 33, 4, 441--467.Google Scholar
- Brooke, J. (1996). SUS: A "quick and dirty" usability scale. In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & I. L. McClelland (Eds.), Usability evaluation in industry (pp. 189--194). London: Taylor & Francis.Google Scholar
- Zaharias, P. 2009. Comprehensive Usability Design in the context of e-Learning: A Framework augmenting 'traditional' usability constructs with instructional design and motivation to learn. International Journal of Technology and Human Interaction vol 5 (4), 37--59.Google ScholarCross Ref
- Yu, F.-Y., Chang, L.-J., Liu, Y.-H. & Chan, T.-W. 2002. Learning preferences towards computerised competitive modes, Journal of Computer Assisted Learning, 18: 341--350.Google ScholarCross Ref
- Atchariyachanvanich, K., Okada, H. & Sonehara, N. 2006. What keeps online customers repurchasing through the internet? ACM SIGecom Exchanges, 6(2): 47--57. Google ScholarDigital Library
- Sebe, N., Lew, M. S., Sun, Y., Cohen, I., Gevers, T., & Huang. 2006. T. S.: Authentic facial expression analysis. The Journal of Image and Vision Computing, 25, 856--1863 Google ScholarDigital Library
Index Terms
- An affective computing approach to develop the game-based adaptive learning material for the elementary students
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