SHS Web Conf.
Volume 77, 2020The 2nd ACM Chapter International Conference on Educational Technology, Language and Technical Communication (ETLTC2020)
|Number of page(s)
|08 May 2020
Predicting Personality Traits by Student Learning Behaviors on Blackboard Systems
Illinois Institute of Technology, Chicago, IL, USA
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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.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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