Abstract: Data mining is a powerful tool for pedagogic intervention. When data mining is used in developing methods for discovering knowledge from data which come from educational environment and it becomes Educational Data Mining (EDM). The educational institutions can use classification for complete analysis of students characteristics. This study details the Hunts algorithm in classification technique. The Hunts algorithm builds a decision tree from a dataset. In our work we collect Teaching Assistant Evaluations (TAE) dataset from UCI machine learning repository. Then we applied Hunts Algorithm to construction of Decision Tree (DT). The implementation of this algorithm is useful to analysis of evaluations of teaching performance over three regular semesters and two summer semesters of 151 Teaching Assistant (TA).By this work we find various types of impurities measures and finding the maximum information gain at various iterations levels. This task is to extract the knowledge that describes TA performance over summer and regular semester. This work will help the institute to improve the performance.
K. Devasenapathy and S. Duraisamy, 2016. Performance Analysis of Teaching Assistant Using Decision Tree Classification Algorithm. Asian Journal of Information Technology, 15: 3820-3825.