Scholar
Jionghao Lin
Google Scholar ID: l7oy8qMAAAAJ
University of Hong Kong | Carnegie Mellon University | Monash University
Citations & Impact
Citations
1,399
H-index
19
i10-index
32
Publications
20
Co-authors
46
list available
Publications
Resume (English only)
Academic Achievements
- Recent academic achievements include several accepted papers:
- - "Learning Analytics for Early Identification of At-Risk Students and Feedback Intervention" accepted by the Journal of Learning Analytics
- - "Enhancing the De-identification of Personally Identifiable Information in Educational Data" accepted by the Journal of Educational Data Mining
- - "Starting Seatwork Earlier as a Valid Measure of Student Engagement" received the Best Paper Nomination at EDM2025
- - "Automatic Large Language Models Creation of Interactive Learning Lessons" accepted by the 20th European Conference on Technology Enhanced Learning (ECTEL)
- - "LDFacilitator: A System for Facilitating Learning Design Using Large Language Models" accepted by the 26th International Conference on Artificial Intelligence in Education
Research Experience
- Currently an Assistant Professor in Learning Technologies at the Faculty of Education, University of Hong Kong; a postdoc at Carnegie Mellon University; Special Faculty (by courtesy) at HCII, Carnegie Mellon University; Research Affiliate at CoLAM, Monash University; and Tech. & Outreach Officer at IAIED Society.
Education
- Received a Ph.D. in Computer Science from Monash University, advised by Prof. Dragan Gašević, Prof. Guanliang Chen, and Prof. Sharon L. Oviatt; was a postdoc at Carnegie Mellon University, advised by Prof. Kenneth R. Koedinger; a visiting doctoral student at the Institute for Intelligent Systems, University of Memphis, mentored by Prof. Xiang-En Hu; and a visiting graduate student (coursework) at the Information School at the University of California, Berkeley.
Background
- Currently an Assistant Professor in Learning Technologies at the Faculty of Education, University of Hong Kong. Research interests include learning analytics, artificial intelligence in education, educational data mining, educational feedback, dialogue-based intelligent tutoring systems, and natural language processing. Focuses on developing computational methods to understand and enhance learning and teaching.
Miscellany
- Email: jionghao [at] hku [dot] hk; Office: Room 216, Runme Shaw Building, The University of Hong Kong, Pokfulam Road, Hong Kong; ORCID: 0000-0003-3320-3907; Personal interests not detailed
