Quan Nguyen

Teaching Fellow in UBC Master of Data Science

University of British Columbia

Biography

I am a Teaching Fellow at the UBC Master of Data Science where I develop and teach data science courses in statistical inference, time-series, and data science communication. Prior to UBC, I was a Postdoctoral Research Fellow in Learning Analytics at the School of Information, University of Michigan. My research applies statistical and machine learning techniques on large-scale clickstream data from learning management systems to predict student performance and interactions. My work has received multiple best paper awards at established conferences (e.g. LAK18 and HCI International 17). Prior to joining UMich, I 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. I have a background in Economics (BSc. & Msc.) at Maastricht University, Netherlands.

Interests

Learning Analytics
Data Science Education
Educational Psychology

Education

Postdoc in Learning Analytics, 2021
University of Michigan-Ann Arbor, US
PhD in Learning Analytics, 2019
Open University, United Kingdom
MSc in Economics (cum laude), 2016
Maastricht University, Netherlands
BSc in Economics, 2015
Maastricht University, Netherlands

News

Aug 01, 2021
I am excited to start a new position as a Teaching Fellow in the UBC Master of Data Science!
Jun 01, 2021
I lead a workshop on Temporal Analytics at the Learning Analytics Summer Institute 2021, hosted virtually by UBC.
Nov 10-11, 2020
I am excited give a research talk on using spatial-temporal network data to inform strategies to reopen campuses during pandemic at the Michigan Institute of Data Science (MIDAS) Annual Symposium 2020.
Oct 31, 2020
My submission on spatial-temporal network has been accepted for presentation at the AERA 21 roundtable on Advanced Statistical Methods for Complex Data.
Sep 18, 2020
My poster submission on modeling peer interactions from spatial-temporal network was presented at the AERA Sattlelitte conference in Educational Data Science hosted by Stanford. You can find the poster here
May 13, 2020
My research proposal “Students’ mobility patterns on campus and the implications for the recovery of campus activities post-pandemic” has been selected (7 out of 49 submissions) for funding through the MIDAS Propelling Original Data Science (PODS) program for a COVID-19 mini-grants.
May 4, 2020
My study “Exploring homophily in demographics and academic performance using spatial-temporal student networks”, has been accepted as a full paper at the 13th International Conference on Educational Data Mining (EDM) 2020.
Mar 22-27, 2020
I am looking forward to presenting my research paper and an on-going workshop paper in temporal network analysis at LAK20 in Frankfurt, Germany. Update: the conference was held virtually.
Jan 17th, 2020
I am excited to give a talk “Using Temporal Analytics to Detect Inconsistencies Between Learning Design and Student Engagement” at the LINK research lab, University of Texas Arlington, USA
Jan 7th, 2020
I was invited to deliver a workshop on Temporal and Sequential analysis at the Learning Analyis Summer Institute (LASI20) in New York hosted by NYU and Columbia, USA.
Dec 4th, 2019
I have successfully defended my dissertation and got awarded a PhD!
Nov 8th, 2019
I am giving a talk at the AIM series, Center of Academic Innovation, UMich.
Oct 8th, 2019
I am excited to start my postdoc at the School of Information, UMich. I will be working in the Educational Technology Collective lab, led by Dr. Chris Brooks. I am looking forward to collaborating with many brilliant learning analytics researchers and practitioners at University of Michigan!
Sep 19th, 2019
I am thrilled (and relief) to have submitted my Ph.D. thesis!
Jun 14th, 2019
I am glad to receive the Erik Duval travel scholarship to attend the Learning Analytics Summer Institute (LASI) in Vancouver, Canada, hosted by UBC and SFU. Beautiful weather!

Recent & Upcoming Talks

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

Learning analytics has the potential to make the temporal dimensions of learning processes more visible using fine-grained proxies of …

Nov 8, 2019 12:00 PM Ann Arbor, MI

Quan Nguyen

Slides