期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：89
期号：1
出版社：Journal of Theoretical and Applied
摘要：Teaching effectiveness is a multidimensional construct in which teacher questioning skill is one of its key indicators. This paper explores the feasibility of applying data mining techniques to analyze teaching effectiveness using a data set of teachers questions. More specifically, the performance of nine data mining techniques is investigated for the classification of teachers classroom questions into the six Blooms cognitive levels. To this end, a data set has been collected, annotated with Bloom�s cognitive levels, transformed into a suitable representation, and the data mining techniques have been applied. The results confirm the feasibility of applying data mining techniques to analyze teaching effectiveness. Moreover, the results show that the performances of these techniques vary, depending on the sensitivity of each technique to the curse of dimensionality problem. Most remarkably, Support Vector Machine and Random Forest techniques show a striking performance, whereas Adabost and J48 show a sharp deterioration in their performances as the dimensionality grows.
