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In recent years, technology developments are more rapidly. How to learn and obtain desired knowledge efficiently has become an important but complicated problem. We hope that there are methods can give us some suggestions about how to learn knowledge efficiently. In this paper, we introduced some learning behavior of people, and then use our designed Effective Learning Curve Model to imitate this learning phenomenon. Using our learning function model, we can imitate people¡¦s learning behavior through pretesting. Every one has different learning behavior functions on learning distinct courses. Different learning sequence of courses will cause different learning efficiency. From this view, we proposed Max Learning Efficiency Slope First Algorithm (MLESFA) by differential learning functions to give people some suggestions about courses learning sequence and obtain desired knowledge efficiently. These algorithms also can help us to understand how much time we have to spend on each course in order to get better learning efficiency under time limitation. Finally, we make some learning example and compare simulation results with other courses learning algorithms. From the simulation results, we can see that our MLESFA algorithm has better learning efficiency than others.

Keywords: e-learning, learning algorithm, learning function, learning model, learning efficiency, learning behavior

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Received August 31, 2005; revised January 18, 2006; accepted March 9, 2006.
Communicated by Pau-Choo Chung.
^* This research was supported in part by the National Science Council (Taiwan), Bestwise International Computing Co., CAISER (National Chiao Tung University, Taiwan) and Ta Hwa Institute of Technology. Shih -Jung Peng and Pi-Feng Liang are the teachers of Ta-Hwa Institute of Technology (THIT).