
Improving the effectiveness of interactive learning environments through facilitation: An experimental study
PROCEEDINGS
Hassan Qudrat-Ullah, Walden University, United States
E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Quebec City, Canada ISBN 978-1-880094-63-1 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA
Abstract
The effectiveness of computer simulation based interactive learning environments (ILEs) in promoting decision making and learning in complex, dynamic tasks has rarely been evaluated. This paper describes an empirical, laboratory-experiment-based evaluation of the effectiveness of facilitation based ILE. Subjects' performance is evaluated on 4 criteria: task performance, structural knowledge, heuristics knowledge, and cognitive effort. It is found that the subjects provided with post-task facilitation performed the best, followed by those provided with in-task facilitation. Contrary to the hypothesis, subjects provided with pre-task facilitation performed poorly.
Citation
Qudrat-Ullah, H. (2007). Improving the effectiveness of interactive learning environments through facilitation: An experimental study. In T. Bastiaens & S. Carliner (Eds.), Proceedings of E-Learn 2007--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 414-427). Quebec City, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved December 13, 2019 from https://www.learntechlib.org/primary/p/26362/.
© 2007 Association for the Advancement of Computing in Education (AACE)
Keywords
References
View References & Citations Map- Argyris, C. (1993). Knowledge for action: A guide to overcoming barriers to
- Bakken, B.E. (1993). Learning and Transfer of Understanding in Dynamic Decision
- Briggs, P. (1990). Do they know what they are doing? An evaluation of word-processor
- Dörner, D. (1980). On the difficulties people have in dealing with complexity. Simulations and Games, 11, 8-106.
- Edwards, W. (1962). Dynamic decision theory and probabilistic information processing. Human Factors, 4, 59-73.
- Elsom-Cook, M.T. (1993). Environment design and teaching intervention. In D.M.
- Forrester, J.W. (1961). Industrial Dynamics. Cambridge, MA: Productivity Press. Gaming. Simulation& Gaming, 29, 7-19.
- Gonzalez, M., Machuca, J., & Castillo, J. (2000). A transparent-box multifunctional simulator of competing companies. Simulation& Gaming, 31(2): 240-256.
- Goodyear, P. (1992). The provision of tutorial support for learning with computer-based simulations. In E. Corte, M. Lin, H. Mandal, & L. Verschaffel. (Eds). ComputerBased Learning Environments and Problem Solving:391-409. Berlin: SpringerVerlag. Grö bler, A, Maier, F.H., & Milling, P.M. (2000). Enhancing learning capabilities by providing transparency in transparency. Simulation& Gaming, 31(2), 257-278.
- Hayes, N.A. & Broadbent, D.E. (1988). Two modes of learning for interactive tasks. Cognition, 28: 249-276.
- Hirsch, G.B., Immediato, J.M, & Kemeny, M. (1997). Creating Integrated Care and
- Holweg, M., & Bicheno, J. (2002). Supply chain simulation– a tool for education,
- Hsiao, N. (2000). Exploration of Outcome Feedback for Dynamic Decision Making. Unpublished doctoral dissertation, State University of New York at Albany, Albany.
- Huber, O. (1995). Complex problem solving as multistage decision making. In P. Frensch
- Issacs, W., & Senge, P. (1994). Overcoming limits to learning in computer-based learning environments. In J. Morecroft and J. Sterman (Eds), Modeling for learning organizations: 267-287. Portland, Or.: Productivity Press
- Jansson, A. (1995). Strategies in Dynamic Decision Making: Does Teaching Heuristic Strategies By Instructors Affect Performance? In J. Caverni, M. Bar-Hillel, F.Barron, & H. Jungermann (Eds). Contributions to Decision Making-I: 213-253.
- Kleinmuntz, D. (1985). Cognitive heuristics and feedback in a dynamic decision environment. Management Science, 31: 680-701.
- Kriz, W.C. (2003). Creating effective learning environments and learning organizations through gaming simulation design. Simulation& Gaming, 34(4), 495-511.
- Lane, D.C. (1995). On a resurgence of management simulations and games. Journal of the Operational Research Society, 46, 604-625 Learning, 30, 159-176.
- Ledrman, L.C. (1992). Debriefing: towards a systematic assessment of theory and practice. Simulation& Gaming, 23(2), 145-160.
- Njoo, M. & De Jong, T. (1993). Supporting exploratory learning by offering structured overviews of hypotheses. In D.M. Town, T. De Jong, & H. Spada. (Eds). Simulation-Based Experiential Learning: 207-223. Berlin: Springer-Verlag. Organizational change. San Francisco: Jossey-Bass.
- Paich, M., & Sterman, J.D. (1993). Boom, bust, and failures to learn in experimental markets. Management Science, 39(12), 1439-1458.
- Qudrat-Ullah, H. & Davidsen, P. (2001). Understanding the dynamics of electricity supply, resources, and pollution: Pakistan ’ s case. Energy 26 (6), 595-606.
- Qudrat-Ullah, H. (2005). Improving Dynamic Decision Making through HCI Design Principles, In C. Ghaoui, (Ed.), The Encyclopedia of Human Computer Interaction, USA: Information Science Publishing, pp. 311-316.
- Qudrat-Ullah, H., & Karakul, M. (2007). Decision Making in Interactive Learning Environments: Towards an Integrated Model. Journal of Decision Systems, (forthcoming).
- Qudrat-Ullah, H., Saleh, M.M., & Bahaa, E.A. (1997). Fish Bank ILE: An interactive
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