Modeling Student Behavior and Affect in Different Learning Environments

Abstract

In this paper, the author describes a summary of her early career research, this includes work in building and empirically validating student cognitive and affective models using sample sets from various locations in the Philippines. These student models have extended the operationalization of similar models of researchers from other Universities in western cultures like the U.S. In constructing these models, the methods used include supervised, unsupervised and semi-supervised machine learning using the appropriate machine learning algorithms as required by the characteristics of the feature sets and the research problems. The author’s research findings corroborate, and to some extent, expand existing models that allow generalization of prior findings to Philippine sample sets.