Longitudinal changes of student engagement in social annotation

Abstract

The purpose of the study was to examine (a) students’ social annotation behaviors and engagement change in an undergraduate course throughout the semester, and (b) which social annotation behaviors impact active engagement time. A total of 91 university students’ social annotation behaviors, as well as their active engagement time in readings, were collected from a social annotation system named Perusall. Longitudinal growth modeling analysis revealed that (a) students’ active engagement time on readings declined over the course of the semester with a significant variation in the changes among individual students, and (b) all social annotation behaviors, except for the number of question upvotes given by students, were positive predictors of active engagement time. These findings are discussed in terms of the implications, limitations, and future directions.

Keywords:

• social annotation
• engagement
• longitudinal growth model
• online learning

Disclosure statement

No potential conflict of interest was declared by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Notes on contributors

Lijia Lin

Lijia Lin is an assistant professor in the Faculty of Education at the University of Macau. He obtained his PhD from the Educational Technology Program at Arizona State University.

Shan Li

Shan Li is an assistant professor in the College of Health at Lehigh University. He is also an affiliated faculty in the Department of Education and Human Services at Lehigh University. He received his PhD in learning sciences from McGill University.

Xiaoshan Huang

Xiaoshan Huang is a PhD candidate in learning sciences in the Department of Educational and Counseling Psychology at McGill University.

Fu Chen

Fu Chen is an assistant professor in the Faculty of Education at the University of Macau. He obtained his PhD in measurement, evaluation, and data science from University of Alberta.