Xiaoshan Huang

McGill University
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Canada

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Articles (10)

Exploring behavioural patterns and their relationships with social annotation outcomes

Background Social annotation has emerged as a promising educational technology that fosters collaborative reading and discussion of digital resources among learners. While the positive impact of social annotation on students' learning process and performance is widely acknowledged, students' behavioural patterns in social annotation are underexplored. Objectives This study investigated patterns in students' use of annotation and response behaviours in social annotation activities. We also explored how students' performance in the behavioural, cognitive, emotional, and social dimensions varied based on their behavioural patterns. Methods We recruited 93 undergraduates who were enrolled in an elective course at a large North American University. Students were tasked with collaboratively annotating the class readings uploaded to Perusall, a social annotation platform, over 7 weeks. We used metaclustering to determine the optimal number of clusters pertaining to student behaviours. We compared the differences among clusters across multiple performance dimensions. Results and Conclusions Two distinct clusters were identified and defined as initiators and responders. We found that responders had significantly longer active reading time and exhibited greater social annotation effort compared to initiators. However, initiators received more peer acknowledgement, as evidenced by higher upvotes. No significant difference was found in cognitive insight between initiators and responders, but responders demonstrated significantly higher cognitive discrepancy. Additionally, there were no significant differences in positive and negative tones between initiators and responders; however, responders displayed higher levels of prosocial behaviours than initiators. This study has significant practical implications regarding promoting students' collaborative learning experience in social annotation.

Year:

2024

Collaborators (4)

Susanne Lajoie

Full Professor

McGill University

CANADA

Hanxiang Du

University of Florida

UNITED STATES

Juan Zheng

-

UNITED STATES

Shan Li

Assistant Professor

Lehigh University

UNITED STATES
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