Investigating Help-Giving Behavior in a Cross-Platform Learning Environment
- 2.2k Downloads
A key promise of adaptive collaborative learning support is the ability to improve learning outcomes by providing individual students with the help they need to collaborate more effectively. These systems have focused on a single platform. However, recent technology-supported collaborative learning platforms allow students to collaborate in different contexts: computer-supported classroom environments, network based online learning environments, or virtual learning environments with pedagogical agents. Our goal is to better understand how students participate in collaborative behaviors across platforms, focusing on a specific type of collaboration - help-giving. We conducted a classroom study (N = 20) to understand how students engage in help-giving across two platforms: an interactive digital learning environment and an online Q&A community. The results indicate that help-giving behavior across the two platforms is mostly influenced by the context rather than by individual differences. We discuss the implications of the results and suggest design recommendations for developing an adaptive collaborative learning support system that promotes learning and transfer.
KeywordsAdaptive collaborative learning support Intelligent collaborative support Help-giving-behavior Motivation
This work is supported by the National Science Foundation under Grant No 1736103.
- 6.Gweon, G., Rose, C., Carey, R., Zaiss, Z.: Providing support for adaptive scripting in an on-line collaborative learning environment. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 251–260. ACM, April 2006Google Scholar
- 7.Jackson, J., Dukerich, L., Hestenes, D.: Modeling instruction: an effective model for science education. Sci. Educ. 17(1), 10–17 (2008)Google Scholar
- 8.Kumar, R., Rosé, C.P., Wang, Y.C., Joshi, M., Robinson, A.: Tutorial dialogue as adaptive collaborative learning support. Front. Artif. Intell. Appl. 158, 383 (2007)Google Scholar
- 9.Liu, X., Koirala, H.: The effect of mathematics self-efficacy on mathematics achievement of high school students (2009)Google Scholar
- 11.Ogan, A., Finkelstein, S., Walker, E., Carlson, R., Cassell, J.: Rudeness and rapport: insults and learning gains in peer tutoring. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds.) ITS 2012. LNCS, vol. 7315, pp. 11–21. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30950-2_2CrossRefGoogle Scholar
- 13.Paramythis, A.: Adaptive support for collaborative learning with IMS learning design: are we there yet. In: Proceedings of the Workshop on Adaptive Collaboration Support, Held in Conjunction with the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Hannover, Germany, pp. 17–29, July 2008Google Scholar
- 18.Tapia, M., Marsh, G.E.: An instrument to measure mathematics attitudes. Acad. Exch. Q. 8(2), 16–22 (2004)Google Scholar
- 23.Wu, D., Hiltz, S.R.: Predicting learning from asynchronous online discussions. J. Asynchronous Learn. Netw. 8(2), 139–152 (2004)Google Scholar