You are here:

Sequence Analysis of Learning Behavior in Different Consecutive Activities.
PROCEEDING

, , University of Pittsburgh, United States

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Las Vegas, NV, United States ISBN 978-1-939797-35-3 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

Abstract

The purpose of this research is to study the possibility of identifying students, statistically, by analyzing their behavior in different consecutive activities. In this project, there are three different sorts of activities: animated example, basic example, and parameterized exercises. We extracted the behavior of each student from the log activities of the Mastery Grids platform. Additionally, we investigate by using unsupervised learning technique, whether there are common patterns, that students share or not while performing these activities. We conclude that we are able to identify students from their behavior, besides that there are some common patterns.

Citation

Abuabat, A. & Brusilovsky, P. (2018). Sequence Analysis of Learning Behavior in Different Consecutive Activities. In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 817-822). Las Vegas, NV, United States: Association for the Advancement of Computing in Education (AACE). Retrieved April 6, 2020 from .

References

View References & Citations Map

These references have been extracted automatically and may have some errors. Signed in users can suggest corrections to these mistakes.

Suggest Corrections to References