Recent (Detailed) News
Recent (Detailed) News
New publication out! π Our latest article in Interactive Learning Environments explores how students co-construct knowledge with generative AI, and what it really means to see AI as a collaborator in learning. π Read the article here
Jung, Y. & Jin, S. (2025). Questioning the role of AI as collaborator: A Systematic Literature Review of studentsβ discourse with generative AI for knowledge co-construction. Interactive Learning Environments. [SSCI-indexed; IF = 5.3]
Presented a webinar, "Expanding Learning Assessment through the Lens of Learning Analytics". The talk explored how learning analytics can expand approaches to evaluating learning processes, with a focus on automated feedback to understanding collaborative discourse in authentic contexts.
Moderated/facilitated a webinar, βData Collection Standardization for AI and Software-Based Education Advancementβ, hosted by Korea Universityβs National Center of Excellence in Software. The session highlighted collaborative efforts in South Korea to establish standardized practices for educational data collection.
Co-presented a webinar, βLifelong Learning Analytics: Research and Teaching in Adult Education.β We explored how learning analytics can deepen understanding of adult learners, their learning contexts, and their transitions across the lifespan.
Began a new chapter as an Assistant Professor in the Learning Technologies and Performance Systems (LTPS) program, College of Education and Human Development, Texas A&M University. I am excited to contribute to this innovative program and collaborate with colleagues and students on advancing technology-enhanced education!
New article out in Computers & Education! π We examined how students use learning analytics messages to take action and build better collaboration routines in online annotation learning. π Read the article here
Jung, Y. & Wise, A. F. (2025). How students engage with learning analytics: Access, action-taking, and learning routines with message-based information to support collaborative annotation. Computers & Education. [SSCI-indexed; IF = 10.5]Β
Our latest article in Innovations in Education and Teaching International documents a multi-case study, examining how AI chatbots are integrated into three asynchronous online courses with different course designs, reshaping socio-material interactions between learners and technology. π Read the article here
Moon, J., Jung, Y., Bae, H., Kim, K., & Lee, U. (2025). Socio-material interactions: A multi-case study on AI chatbot integration in asynchronous online learning. Innovations in Education and Teaching International. [SSCI-indexed; IF = 4.9]
Co-chaired the symposium βTowards Actionable Collaborative Discourse Analysis: Bridging Advanced Computational Analysis with Practical Implementationβ at the International Society of the Learning Sciences Annual Meeting
Presented the poster βDynamics of Student Engagement in Collaborative Discourseβ at the American Educational Research Association Annual Meeting, and led a roundtable on AI chatbot-supported knowledge building, which received πBest Conference Paper Award from the Korean-American Educational Research Association.
Presented a poster on AI tutor proactiveness in enhancing self-paced learning during online lectures, and presented a case in a pre-conference workshop on designing and launching learning analytics courses, offering perspectives from two public universities in the U.S.
New article published in Journal of Computing in Higher Education! 𧩠Our study highlights how instructors interpret and use learning analytics, and why pedagogy is key to meaningful analytics-informed teaching practices. π Read the article here
Li, Q., Jung, Y.*, & Wise, A. F. (2025). How instructors use learning analytics: The pivotal role of pedagogy. Journal of Computing in Higher Education. [SSCI-indexed; IF = 4.9]Β
Co-chaired the symposium βBridging Social Annotation Practice with Perspectives from the Learning Sciences and CSCLβ, which brought together diverse viewpoints on how social annotation can support collaborative learning.
Our paper, βProbing Actionability in Learning Analytics: The Role of Routines, Timing, and Pathways,β was presented and published in the conference proceedings (pp. 871β877, ACM) at the 14th International Conference on Learning Analytics & Knowledge (LAK 2024). The study investigates how the timing of analytics and learnersβ established routines shape their ability to take meaningful, actionable steps in technology-enhanced learning environments.π Read the proceedings here
Jung, Y., & Wise, A. F. (2024, March). Probing Actionability in Learning Analytics: The Role of Routines, Timing, and Pathways. In Proceedings of the 14th International Conference on Learning Analytics & Knowledge (pp. 871-877). ACM. Acceptance rate: 30%
Presented a paper and co-chaired a workshop at LAK 2024, both focusing on advancing actionability in learning analytics by incorporating student learning workflow and diverse stakeholder perspectives. The workshop created space for educators, researchers, and technologists to envision actionable analytics that could serve learners and instructors in practical, context-sensitive ways.