Abstract
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.
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Cheng, SC., Huang, YM., Chen, JN., Lin, YT. (2005). Automatic Leveling System for E-Learning Examination Pool Using Entropy-Based Decision Tree. In: Lau, R.W.H., Li, Q., Cheung, R., Liu, W. (eds) Advances in Web-Based Learning – ICWL 2005. ICWL 2005. Lecture Notes in Computer Science, vol 3583. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11528043_27
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DOI: https://doi.org/10.1007/11528043_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27895-5
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