Jillianne Code

Assistant Professor

Research Interests

Educational Context
Educational Technologies
Formative assessment
Immersive learning
Learner agency
Learning and Memory
Learning design
Self-efficacy
Self-regulated Learning
Situated and embodied cognition
Virtual augmented and mixed reality for learning
Virtual learning environments

Relevant Degree Programs

Affiliations to Research Centres, Institutes & Clusters

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
 
 

Biography

Dr. Jillianne Code is a learning scientist, whose area of research is at the praxis of educational technology, psychology and measurement. Before coming to the University of British Columbia, Jillianne was Associate Professor of Educational Technology and Psychology in the Faculty of Education at the University of Victoria (UVic), and a Post-doctoral Research Fellow at the Harvard Graduate School of Education in Assessment and Learning Technologies. Dr. Code holds a Ph.D in Educational Psychology from Simon Fraser University, a M.Ed in Educational Psychology with a specialization Instructional Technology and a B.Ed in Secondary Science and Art Education from the University of Alberta.

Research Methodology

Mixed methods
survey research

Recruitment

Master's students
2023
I support public scholarship, e.g. through the Public Scholars Initiative, and am available to supervise students and Postdocs interested in collaborating with external partners as part of their research.
I support experiential learning experiences, such as internships and work placements, for my graduate students and Postdocs.
I am interested in hiring Co-op students for research placements.
I am interested in supervising students to conduct interdisciplinary research.

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Graduate Student Supervision

Master's Student Supervision (2010 - 2021)
Social network analysis as a progressive tool for learning analytics : a sample of teacher education students’ course interactions with Threadz on the canvas platform (2020)

This thesis investigates social network analysis as a progressive tool for learning analytics through the lens of curriculum theory. The theoretical framework is based on the Tyler rationale and Dewey’s concept of progressivism. A quasi-experiment was conducted relying on an embedded mixed-method research design. Teacher education students (n=18) participated in three online discussions. Two online discussions allowed students to access social network analysis visualizations through Threadz, a Canvas plugin. The overall inquiry focuses on how this exposure of learning analytics data influences the students and how the application of learning analytics might be related to educational ideologies. The methods of investigation rely on social network analysis, inferential statistics and content analysis. The conclusion states that exposing learning analytics data to students might have an impact on their behaviour in online discussions.

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Publications

 
 

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