Predicting high-level student responses using conceptual clustering

• المؤلفون الرئيسيون: Legaspi, Roberto S., Sison, Raymund C., Fukui, Ken Ichi, Numao, Masayuki
• التنسيق: text
• منشور في: Animo Repository 2005
• الموضوعات: Cluster analysis—Computer programs; Machine learning; Forecasting; Computer Sciences
• الوصول للمادة أونلاين: https://animorepository.dlsu.edu.ph/faculty_research/2948
• المؤسسة: De La Salle University

A conceptual clustering algorithm can search through huge amounts of data looking for multi-dimensional structures, where each structure or cluster represents a relevant concept in the problem-solving domain. We investigated on the effect of cluster knowledge for a learning agent to improve its prediction of higher level student response aspects. Our empirical results show that when cluster knowledge is utilized by a function approximator, prediction is improved as compared to treating the entire data population as a single cluster. © 2005 Asia-Pacific Society for Computers in Education.