Abstract:
Teaching evaluation is a difficult task because of the difficulty of transforming teaching behavior into a quantitative problem. In this paper, an improved classification...Show MoreMetadata
Abstract:
Teaching evaluation is a difficult task because of the difficulty of transforming teaching behavior into a quantitative problem. In this paper, an improved classification algorithm is proposed into the field of teaching evaluation by contrast with the traditional methods. Firstly, the key concepts of algorithms using in teaching evaluation are introduced, including the actual process of mining knowledge. Secondly, an improved decision tree algorithm is presented to analyze the data by fuzzy clustering. Thirdly, after the analysis by this new way, the potential rules are found and can be as the objective basis for teaching evaluation. The improved method can overcome the shortage of traditional methods on data integration and aggregation. The results show that this method for decision-making on teaching evaluation is feasible and effective.
Published in: 2009 IEEE International Conference on Granular Computing
Date of Conference: 17-19 August 2009
Date Added to IEEE Xplore: 22 September 2009
Print ISBN:978-1-4244-4830-2