Abstract
In this research, a teaching simulation model is built where the understanding status, knowledge structure, and collaborative effect of each learner are integrated by using a doubly structural network model. The purpose of the model is to analyse the actual conditions of understanding of learners regarding instructions given in classrooms. The influence of teaching strategies on learning effects is analysed in the model. Moreover, the influence of the seating arrangement of learners on collaborative learning effects is discussed. As a result of the simulation, the following points were found: (1) the learning effects depend on the difference in teaching strategies, and (2) a teaching strategy where learning skills, material structure, and collaborative learning are integrated on a doubly structural network model is the most effective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Durlach, P.J., Lesgold, A.M. (eds.): Adaptive Technologies for Training and Education. Cambridge University Press, New York (2012)
Sawyer, K.: Introduction, The New Science of Learning. In: Sawyer, K. (ed.) The Cambridge Handbook of the Learning Sciences, pp. 1–18. Cambridge University Press (2006)
Baker, R.S., Yacef, K.: The State of Educational Data Mining in 2009, A Review and Future Visions. Journal of Educational Data Mining 1(1), 3–17 (2009)
Johnson, D.W., Johnson, R.T., Holubec, E.J.: Circles of Learning: Cooperation in the classroom, 5th edn. Interaction Book Company (2002)
Terano, T.: A Doubly Structural Network Model. The Operations Research Society of Japan 2(1), 57–69 (2008)
Kunnigami, M., Kobayashi, M., Yamadera, S., Terano, T.: A Doubly Structural Network Model and Analysis on Emergence of Money. Information Processing Society of Japan, Mathematical Modeling and Problem Solving 53(12), 661–666 (2009)
Kunnigami, M., Kobayashi, M., Yamadera, S., Yamada, T., Terano, T.: A Doubly Structural Network Model and Analysis on Emergence of Money. In: Takadama, K., Cioffi-Revilla, C., Defuant, G. (eds.) Simulating Interacting Agents and Social Phenomena, Agent-Based Social Systems, vol. 7, pp. 137–149. Springer, Tokyo (2010)
Birnbaum, A.: Some Latent Trait Models. In: Load, F.M., Novick, M.R. (eds.) Statistical Theories of Mental Test Sores, pp. 97–424. Addison-Wesley, Reading (1968)
Ueno, M., Shojima, K.: The New Trend of Learning Evaluation. Asakura Shoten, Tokyo (2010)
Toyoda, H.: Item Latent Theory (Beginners’ Course). Asakura Shoten, Tokyo (2012)
Ueno, M.: An Extension of the IRT to a Network Model. Behaviormetrika 29(1), 59–79 (2002)
Wainer, H., Bradlow, E.T., Wang, X.: Testlet Response Theory and Its Appliations. Cambridge University Press, New York (2007)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems. Morgan Kaufmann, San Francisco (1988)
Shigemasu, K., Motomura, Y., Ueno, M.: General Information of Bayesian Network. Baifukan, Tokyo (2006)
Jensen, F.V., Nielsen, T.D.: Bayesian Networks and Decision Graphs, 2nd edn. Springer, Berlin (2007)
Koller, D., Friedman, N.: Probabilistic Graphical Models. The MIT Press, MA (2009)
Ueno, M., Onishi, M., Shigemasu, H.: An Extension of the IRT to a Network Model. Information Processing Society of Japan (A), J77-A(10), 1398–1408 (1994)
Ueno, M.: The Graphical Test Theory from Bayesian Approach. Japan Society for Educational Technology 24(1), 35–52 (2000)
Epstein, J., Axtell, R.: Growing Artificial Societies. Brookings Institution Press, Washington, D.C. (1996)
Axelrod, R.: The Complexity of Cooperation. Princeton University Press, New Jersey (1999)
R Package, http://ran.r-projet.org/web/pakages/
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Kurahashi, S., Kuniyoshi, K., Terano, T. (2014). Teaching Simulation on Collaborative Learning by the Complex Doubly Structural Network. In: Jezic, G., Kusek, M., Lovrek, I., J. Howlett, R., Jain, L. (eds) Agent and Multi-Agent Systems: Technologies and Applications. Advances in Intelligent Systems and Computing, vol 296. Springer, Cham. https://doi.org/10.1007/978-3-319-07650-8_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-07650-8_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07649-2
Online ISBN: 978-3-319-07650-8
eBook Packages: EngineeringEngineering (R0)