Modeling agent-based performance evaluation for e-learning systems

Abstract

Purpose - The purpose of this paper is to show how rapidly evolving information technology has dramatically changed the knowledge dissemination process. However, many of them lack a generic evaluation process to verify the system's performance. In an attempt to solve this problem, this study seeks to propose an agent-based model to provide a dynamic, flexible framework for performance evaluations of e-learning projects. Design/methodology/approach - The paper proposes an agent-based model which comprises a learning model, balanced scorecard and option-pricing approach to evaluate the performance of an e-learning project. Findings - E-learning could be the paradigm shift of traditional education. Thus, the paper provides organizations with a methodology to deliberately evaluate their e-learning projects by treating it as a continuous improvement process. Originality/value - The original contributions in this paper are: application of a balance scorecard to weigh different perspectives; application of a real options approach for risk management of e-learning projects; construction of an agent-based system for autonomous qualitative/quantitative information gathering.