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By Kimito Funatsu and Kiyoshi Hasegawa

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They showed that when we learn new data, we always start with our prior knowledge and try to modify it. If the new concepts are inconsistent with our prior knowledge, the new knowledge will likely be distorted or even rejected. Data mining method are based on human-computer interaction, where user interacts with a decision tree learner to improve the trees in performance and meaning to him/her. Knowledge acquisition should be processed in a systematic way, where humans lead the data mining by comparing multiple trees constructed on different subsets of the data set and through several forms of attribute selection.

4, pp. 410-417. Utgoff, P. (1989) Incremental induction of decision trees. Machine Learning. pp. 161-186. ; Berkman, N. and Clouse, J. (1997). Decision tree induction based on efficient tree Restructuring. Machine Learning. 5-44. Utgoff, P. and Brodley, C. (1990). An Incremental Method for Finding multivariate splits for decision trees. 7th International Conference on Machine Learning. pp. 58-65. Utgoff, P. and Brodley, C. (1995). Multivariate decision trees. Machine Learning. pp. 45-77. Vallez, M.

They developed different kinds of courses like a GNU/Linux course, a Basic Math Operation course, and learning material for preparation to the Mexico’s AdmissionTest for College EXANI-II. The students participated by reading, evaluating and adding material (Web resources) to the courses. Next, we present an example of how an author creates/updates learning material for a Basic Math course (figure 12). We first create the structure of the course (left-top). Then, we add learning material for each learning style (right-top and left-bottom).

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