Applying cluster techniques of data mining to analysis the game-based digital learning work

Abstract

Clustering is the most important task in unsupervised learning and applications is a major issue in cluster analysis. Digital learning, which arises in recent years, has become a trend of learning method in the future. The environment of digital learning may enable the learners work anytime and everywhere without the limitation of time and space. Another great improvement of digital learning is the ability of recording complete portfolio. These portfolios may be used to gain critical factors of learning if they are analyzed by data mining methods. Therefore, in this research will to analyze the records of students' portfolios of game-based homework by using Clustering Algorithm Based on Histogram Threshold (HTCA) method of data mining. The HTCA method combines a hierarchical clustering method and Otsu's method. The result indicates that the attributes or categories of impacting factors and to find conclusions of efficiency for the learning process. © 2013 Springer Science+Business Media Dordrecht.