Predicting Personality Traits by Student Learning Behaviors on Blackboard Systems

Illinois Institute of Technology, Chicago, IL, USA

^* e-mail: yong.zheng@iit.edu

Abstract

Personality has been demonstrated as influential factors in technology-enhanced learning. The collection of personality is always a challenge. Human efforts are usually required in the user surveys which is the most common and popular way to collect the personality traits. Predicting personality traits, as a result, becomes one of the research directions. Some researchers consider these personality traits as labels in the classifications, while some others consider them as numeric variables in the regressions. In this paper, we made our attempt to predict the students’ personality traits from their learning behaviors on the Blackboard system. More specifically, we tried both the classification and regression models, and evaluate them based on the same standards. Our initial experimental results discover the insights about these predictive models.