Hui Shi
Introduction
Hui Shi is a doctoral student in Instructional Systems and Learning Technologies program at Florida State University. She earned her B.S. in Computer Education at Jiangnan University and M.S. in Education Information Technology at East China Normal University. She went to Auburn University as a short-term visiting student during her master’s program.
Research Interests
Her first research interest focuses on exploring student self-regulated learning, participation, and interactive behaviors in online learning contexts using data mining techniques. Specifically, she is interested in investigating what behavioral factors can determine successful academic performance and how students behave differently between successful and unsuccessful groups. Her second research interest focuses on building student performance prediction models to improve automatic evaluation and the quality of teaching support in large-scale online courses.
Publications
- Shi, H., Dennen, V. P., Hur, J. (in process). From unsuccessful to successful learning: Profiling behavior patterns of online learners in an open university.
- Dennen, V. P., Shi, H., Rutledge, S. A., Bagdy, L. M., Jung, D., Bunn, S., Cargill, C., Cosgrove, C., & Hedquist, A. (2022). Teen social media use during COVID-19: Parent perceptions and oversight. In P. Kommers, I. A. Sánchez, & P. Isaias (Eds.), Proceedings of the International Conferences e-Society 2022 and Mobile Learning 2022 (pp. 155-162). IADIS Press.
Conferences
- Shi, H., Hur, J., Dennen, V. P., Zhou, Y. (2022). From unsuccessful to successful learning: Mining behavioral patterns of distance learners in open and online universities. Paper presented as Concurrent Presentation at the 2022 AECT International Convention, October 24-28, 2022, Las Vegas, NV, USA.
- Dennen, V. P., Tang, Y. M., Hur, J., Shi, H. (2022). Instructors’ Perceptions and Interventions in Students’ Active and Passive Participation in Online Teaching. Paper presented as Roundtable at the 2022 AECT International Convention, October 24-28, 2022, Las Vegas, NV, USA.
- Jung, D., Dennen, V.P., Bagdy, L., Rutledge, S., Bunn, S., Cargill, C., Cosgrove, C., Hedquist, A., Shi, H. (2022). Social media, schools, and teen life: An umbrella of learning spaces. Paper presented as Concurrent Presentation at the 2022 AECT International Convention, October 24-28, 2022, Las Vegas, NV, USA.
- Dennen, V. P., Rutledge, S., Shi, H., Bagdy, L., Jung, D., Bunn, S., Hedquist, A., Cosgrove, C., Cargill, C. (2022). Teen engagement with current events and social issues on social media: A survey of American youth. Paper presented at the 12th International Conference on Social Media & Society, July 18-19, 2022, online.
- Dennen, V. P., Shi, H., Rutledge, S. A., Bagdy, L. M., Jung, D., Bunn, S., Cargill, C., Cosgrove, C., & Hedquist, A. (2022). Teen social media use during COVID-19: Parent perceptions and oversight. Paper presented at the 20th International Conference e-Society, March 12-14, 2022, online.
Projects
- From unsuccessful to successful learning: Profiling behavior patterns of online learners in an open university
Hui Shi, Vanessa Dennen, Jaesung Hur.
The purpose of this project is to investigate what kind of behavior patterns lead to successful performance and how learners behave differently between successful and unsuccessful learning groups.
- Multi-horizon Time-series Prediction in Online Learning: Using Interpretable Deep Neural Networks for Precision Education
Hui Shi
The purpose of this project is to develop a Time-Series Deep Neural Network Ensemble Learning (TDNN-EL) model to predict student online performance. The predictive model can not only accomplish a state-of-the-art accuracy for student performance prediction but also improve interpretability through selecting important predictors and identifying critical junctures in student learning trajectories, which can support effective intervention design for at-risk students and eventually achieve precision education.
CV
