Title

Identifying Students' Persistence Profiles in Problem Solving Task

Document Type

Conference Proceeding

Publication Date

7-2018

Abstract

This study explores task persistence in the context of Learning by Teaching. Using features extracted from students' interaction logs, a centroid based clustering algorithm derived two well-separated groups describing two types of students, Cluster 1 which is characterized by the more persistent students and Cluster 0 which is characterized by the less persistent students. The more persistent students demonstrated effective help-seeking behavior, and greater level of task engagement and resourcefulness compared to the less persistent students.

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