
MathGirls: Motivating Girls to Learn Math through Pedagogical Agents
PROCEEDINGS
Yanghee Kim, Nick Flann, Quan Wei, Youngah Ko, Sarath Alla, Utah State University, United States
EdMedia + Innovate Learning, in Orlando, FL USA ISBN 978-1-880094-60-0 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
Abstract
MathGirls is a computer-based learning environment designed for high school girls learning algebra. The primary goal of MathGirls is to provide a girl-friendly learning environment that enhances girls' self-efficacy beliefs in and motivation towards learning algebra, through persuasive messages of human-like pedagogical agents. This study investigated the impact of agent gender (male and female) and age (teacher-like and peer-like) on high school girls' choices of their agent to work with and the impact of the differing agents on the changes in the girls' math self-efficacy, math attitudes, and learning. The results indicated that the female agents were favored by the high school girls and had positive impacts on improving the girls' math self-efficacy and attitudes.
Citation
Kim, Y., Flann, N., Wei, Q., Ko, Y. & Alla, S. (2006). MathGirls: Motivating Girls to Learn Math through Pedagogical Agents. In E. Pearson & P. Bohman (Eds.), Proceedings of ED-MEDIA 2006--World Conference on Educational Multimedia, Hypermedia & Telecommunications (pp. 2025-2032). Orlando, FL USA: Association for the Advancement of Computing in Education (AACE). Retrieved December 13, 2019 from https://www.learntechlib.org/primary/p/23287/.
© 2006 Association for the Advancement of Computing in Education (AACE)
Keywords
References
View References & Citations Map- Arroyo, I., Beck, J.E., Woolf, B.P., Beal, C.R., & Schultz, K. (2000). Macroadapting animalwatch to gender and cognitive differences with respect to hint interactivity and symbolism. In Intelligent tutoring systems, proceedings (Vol. 1839, pp. 574-583).
- Arroyo, I., Murray, T., Woolf, B.P., & Beal, C.R. (2003). Further results on gender and cognitive differences in help effectiveness. Paper presented at the International Conference of Artificial Intelligence in Education, Sydney, Australia.
- Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W.H. Freeman. Bandura, A. (2001, March, 2001). Guide for constructing self-efficacy scales. Retrieved December 25, 2004, from http://www.emory.edu/EDUCATION/mfp/bgd.html
- Baylor, A.L., & Kim, Y. (2003). The role of gender and ethnicity in pedagogical agent perception. Paper presented at the ELearn, the Annual Conference of Association for the Advancement of Computing in Education., Phoenix, AZ.
- Cooper, J., & Weaver, K.D. (2003). Gender and computers: Understanding the digital divide. Mahwah, NJ: Lawrence Erlbaum Associates.
- Ethington, C.A., & Wolfe, L.M. (1988). Women's selection of quantitative undergraduate fields of study: Direct and indirect influences. American Educational Research Journal, 25, 157-175.
- Evans, E.M., Schweingruber, H., & Stevenson, H.W. (2002). Gender differences in interest and knowledge acquisition: The united states, taiwan, and japan. Sex Roles, 47(3-4), 153-167.
- Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
- Hakkarainen, K., & Palonen, T. (2003). Patterns of female and male students' participation in peer interaction in computersupported learning. Computers& Education, 40, 327-342.
- Kim, Y. (2005). Pedagogical agents as learning companions: Building social relations with learners. In C.K. Looi, G. McCalla, B. Bredeweg & J. Breuker (Eds.), Artificial intelligence in education: Supporting learning through intelligent and socially informed technology (Vol. 125, pp. 362-369). Amsterdam, The Netherlands: IOS Press.
- Passig, D., & Levin, H. (2000). Gender preferences for multimedia interfaces. Journal of Computer Assisted Learning, 16(1), 6471.
- Persson, P., Laaksolahti, J., & Lonnqvist, P. (2002). Understanding social intelligence. In K. Dautenhahn, A.H. Bond, L. Canamero & B. Edmonds (Eds.), Socially intelligent agents: Creating relationships with computers and robots. Norwell, MA: Kluwer Academic Publishers.
- Randhawa, B.S., Beamer, J.E., & Lundberg, I. (1993). Role of mathematics self-efficacy in the structural model of mathematics achievement. Journal of Educational Psychology, 85(1), 41-48.
- Schunk, D.H. (1987). Peer models and children's behavioral change. Review of Educational Research, 57(2), 149-174.
- Slotte, V., Lonka, K., & Lindblom-Ylanne, S. (2001). Study-strategy use in learning from text. Does gender make any difference? Instructional Science, 29(3), 255-272.
- Tapia, M., & Marsh, G.E. (2004). An instrument to measure mathematics attitudes. Retrieved December 24, 2004, from http://www.rapidintellect.com/AEQweb/cho25344l.htm
- Zeldin, A.L., & Pajares, F. (2000). Against the odds: Self-efficacy beliefs of women in mathematical, scientific, and technological careers. American Educational Research Journal, 37, 215-246.
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