I Annotate 2021

the conference for open annotation practices and technologies

Program

Panel: Social Annotation Research

1–2:30pm ET, Wednesday 23 June 2021

What insights from current research shed light on the relationship between social annotation and student learning? This session will showcase three innovative research agendas and methods for studying social annotation, with implications for how social annotation can effectively support student engagement, knowledge construction, and collaborative meaning-making. The panel will be moderated by Bodong Chen, and feature speakers Chris Andrews, Yeonji Jung, and Xinran Zhu.

• Moderator: Bodong Chen, Associate Professor, University of Minnesota: Bodong Chen (he/him @bod0ng) is an associate professor, the Huebner Endowed Chair in Education & Technology, and co-director of the Learning Informatics Lab at the University of Minnesota. His research is at the intersection of computer-supported collaborative learning, learning analytics, and network science.
• Chris Andrews, PhD Candidate, Indiana University: Chris Andrews (he/him @chrisandrewsedu) is a PhD Candidate in Learning Sciences at Indiana University. He is studying how social annotation can be used to support learning in the classroom. He has taught undergraduate learning theory courses for pre-service teachers and previously was a high school teacher. He has an MA in Teacher Education.
• Yeonji Jung, PhD Candidate, New York University: Yeonji Jung (she/her @yeonji_jung) is a PhD Candidate at Educational Communication and Technology in New York University. Her research interests center on measuring, understanding, and supporting online learning engagement in higher education using learning analytics. Her recent work focuses on implementing and examining students' data-informed decision making in collaborative annotation.
• Xinran Zhu, PhD Candidate, Learning Technologies, University of Minnesota: Xinran Zhu (she/her @XinranZ1) is a PhD student in Learning Technologies at the University of Minnesota. She's interested in computer-supported collaborative learning, learning analytics, network analysis, and design based research. Her current research includes co-designing collaborative annotation activities (via Hypothesis) with university instructors and studying learners' collaborative knowledge construction facilitated by the designed activities.

Session Recording

You can also annotate the transcript of this video while watching.

Session Resources

• Xinran Zhu's presentation in annotatable PDF format.
• Check back for more resources from the session.