Modeling e-Learning System Performance Evaluation with Agent-Based Approach
Rapidly evolving information technology has dramatically changed the knowledge dissemination process. A proper e-learning environment is one of the most important knowledge tools in modern organizations. However, many of them lack a generic evaluation process to verify performance. In an attempt to solve this problem, this study propose an agent-based model which compose learning model, balanced scorecard and the option pricing approach to provide an dynamic, flexible framework for e-learning project’s performance evaluations.
KeywordsE-learning performance evaluation option-pricing approach Black-Scholes model balanced scorecard approach information agent systems
Unable to display preview. Download preview PDF.
- 1.Kaplan, R., Norton, D.: The balanced scorecard: measures that drive performance. Harvard Business Review 70(1), 71–80 (1992)Google Scholar
- 2.Kaplan, R., Norton, D.: Putting the balanced scorecard to work. Harvard Business Review 71(5), 134–147 (1993)Google Scholar
- 3.Kaplan, R., Norton, D.: Using the balanced scorecard as a strategic management system. Harvard Business Review 74(1), 75–85 (1996)Google Scholar
- 4.Forbes, L., Hamilton, J.: Building an international student market: educational-balanced scorecard solutions for regional Australian cities. International Education Journal 5(4), 502–520 (2003)Google Scholar
- 5.Kirkpatrick, D.L.: Techniques for evaluating training programs. Journal of the American Society of Training Directors 13, 3–26 (1959)Google Scholar
- 6.Kirkpatrick, D.L., Kirkpatrick, J.D.: Evaluating Training Programs: The Four Levels (3rd), Berrett-Koehler Publishers (1994)Google Scholar
- 8.Myers, S.C., Majd, S.: Abandonment Value and Project Lift, Advances in Futures and Option Research 4, 1 (1990)Google Scholar
- 9.Brach, M.A. (ed.): Real Options in Practice, pp. 218–223. John Wiley & Sons, Inc, Chichester (2003)Google Scholar
- 12.Chiu, H.Y., Sheng, C.C., Chen, A.P.: Designing a Dynamic E-learning Project Performance Evaluation Framework. In: The 7th IEEE International Conference on Advanced Learning Technologies (accepted)Google Scholar
- 14.Preece, A.D., Hui, K.-Y., Gray, W.A., Marti, P., Bench-Capon, T.J.M., Jones, D.M., Cu, Z.: The KRAFT architecture for knowledge fusion and transformation. In: 19th SGES International conference on knowledge-based systems and applied artificial intelligence (ES’99), Springer, Heidelberg (1999)Google Scholar
- 15.Beer, M., Huang, W., Sixsmith, A.: Using agents to build a practical implementation of the INCA system. In: Intelligent agents and their applications, Springer, Heidelberg (2002)Google Scholar