Academic Innovation at Michigan (AIM) Research: Quan Nguyen

Date: 
Fri, 11/08/2019 - 12:00pm to 1:30pm

Rackham Graduate School - East Conference Room

AIM Research (formerly AIM Analytics) is a monthly seminar series for researchers across U-M who are interested in research and learning analytics. The field of learning analytics is a multi and interdisciplinary field that brings together researchers from education, learning sciences, computational sciences and statistics, and all discipline-specific forms of educational inquiry.

Using temporal analytics to detect inconsistencies between learning design and student engagement

Abstract

Learning analytics has the potential to make the temporal dimensions of learning processes more visible using fine-grained proxies of how and when students engage with online learning activities. In this talk, I will demonstrate the extent to which students actually follow the course timeline and the subsequent effect on their academic performance. I will also discuss some on-going work and future research directions, such as the role of learning analytics in addressing the attainment gap of ethnic minority students, and outlier detection for time-on-task estimation.

Speaker Bio

Quan Nguyen is a Postdoctoral Research Fellow in Educational Data Science at the School of Information, University of Michigan. His research explores the temporal processes of learning using time-series analysis of digital traces in education. His current research project examines learning patterns in data science education by analyzing trace data collected from Jupyter Notebook. Prior to joining UM, Quan was a PhD candidate in Learning Analytics at The Open University UK and an Associate Lecturer in Applied Statistics at the University of Arts London. His research employed multilevel models and network analysis methods to understand how teachers design their course in online learning environment and how learning design influences student temporal engagement patterns. His work received multiple best paper awards at established conferences (LAK18 and HCI International 17). Quan had a background in Economics (BSc. & Msc.) at Maastricht University, Netherlands.