Author:
Baker Ryan S.,Richey J. Elizabeth,Zhang Jiayi,Karumbaiah Shamya,Andres-Bray Juan Miguel,Nguyen Huy Anh,Andres Juliana Maria Alexandra L.,McLaren Bruce M.
Abstract
AbstractDigital learning games have been increasingly adopted in classrooms to facilitate learning and to promote learning outcomes. Contrary to common beliefs, many digital learning games can be more effective for female students than male students in terms of learning and affective outcomes. However, the in-game learning mechanisms that explain these differences remain unclear. In the current study, we re-analyze three retrospective data sets drawn from three studies conducted in different years. These data sets, which involved 213, 197, and 287 students, were collected from a digital learning game that teaches late elementary and middle school students decimal concepts. We re-analyzed these data sets to understand how female and male students differ in the rates of gaming the system, a behavioral measure that reflects a form of disengagement while playing the game. Rates of gaming the system are compared between female and male students within each of the game’s two core instructional activities (i.e. problem-solving and self-explanation) as well as tested in a game vs. non-game condition. We found that female students game the system significantly less than male students in the self-explanation step in the game condition, in all three studies. This difference in the rates of gaming mediates the relationship between gender and learning outcomes, a pattern in which female students tend to learn more than male students, across all three studies. These results suggest that future design iterations of the game could focus on reducing gaming behaviors for male students, which might improve learning outcomes for female students as well. Understanding gender-based differences in game behaviors can inform future game design to promote better learning outcomes for all students.
Funder
National Science Foundation
Publisher
Springer Science and Business Media LLC
Reference140 articles.
1. Adamo-Villani, N., Wilbur, R., & Wasburn, M. (2008). Gender differences in usability and enjoyment of VR educational games: A study of SMILE™. In 2008 International conference visualisation (pp. 114–119). IEEE.
2. Ainsworth, S., & Burcham, S. (2007). The impact of text coherence on learning by self-explanation. Learning and Instruction, 17(3), 286–303.
3. Aleksić, V., & Ivanović, M. (2017). Early adolescent gender and multiple intelligences profiles as predictors of digital gameplay preferences. Croatian Journal of Education: Hrvatski Časopis Za Odgoj i Obrazovanje, 19(3), 697–727.
4. Aleven, V. A. W. M. M., Koedinger, K. R., & Popescu, O. (2003). A tutorial dialog system to support self-explanation: Evaluation and open questions. In Proceedings of the 11th international conference on artificial intelligence in education (pp. 39–46).
5. Aleven, V., McLaren, B. M., Sewall, J., Van Velsen, M., Popescu, O., Demi, S., Ringenberg, M., & Koedinger, K. R. (2016). Example-tracing tutors: Intelligent tutor development for non programmers. International Journal of Artificial Intelligence in Education, 26(1), 224–269.