In this paper, we propose an automatic leveling system for e-learning examination pool using the algorithm of the decision tree. The automatic leveling system is built to automatically level each question in the examination pool according its difficulty. Thus, an e-learning system can choose questions that are suitable for each learner according to individual background. Not all attributes are relevant to the classification, in other words, the decision tree tells the importance of each attribute. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Cheng, S. C., Huang, Y. M., Chen, J. N., & Lin, Y. T. (2005). Automatic leveling system for e-learning examination pool using entropy-based decision tree. In Lecture Notes in Computer Science (Vol. 3583, pp. 273–278). Springer Verlag. https://doi.org/10.1007/11528043_27
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