Quan Nguyen
Pronouncing /kwan/ /new-yen/

Ph.D. candidate in Education Technology, Institute of Educational Technology, The Open University UK .

Email: quan.nguyen@open.ac.uk
Twitter: @QuanNguyen3010
Curriculum Vitae

Quan Nguyen
 holds a BSc and a MSc in Economics and Information Management (cum laude) from Maastricht University, Netherlands. He is currently doing his PhD at the Open University UK (2016-2019) and working part-time as a Lecturer in Applied Statistics in MSc. Cosmetic Science Programme, University of Arts London (Jan 2018 – now).

His research focuses on the use of learning analytics on a large scale to understand and improve learning design in Virtual Learning Environment. In particular, this research visualizes and analyzes how learning designs were configured longitudinally, how educators mix & match different types of learning activities while designing for learning, compare and contrast learning design with actual student engagement on VLE, pass rates, retention, and satisfaction. He leverages a mixed of qualitative (e.g. interview), and quantitative techniques such as network analysis, multi-level modelling, and machine learning.

Quan’s research has been published in leading international peer-reviewed journals such as Computers and Human Behavior, IEEE Transactions on Learning Technologies, Journal of Computer Assisted Language Learning, and in the proceedings of well-established conference such as the International conference on  Human-Computer Interaction (HCII), Learning Analytics & Knowledge (LAK), The European Association for Research on Learning and Instruction (EARLI). His research has been widely recognized by practitioners, researchers, and management both within the Open University and at international context (best paper award in HCII17, best paper award in LAK18), together with a doctoral fellowship from the Leverhulme Trust.

By connecting the two emerging fields of Learning Design & Learning Analytics, Quan’s research strives to advocate a shift from ‘static’ to ‘dynamic’ learning design approach through continuously fine-tuning the design based on feedback from learner during their learning process. His research brings together multiple stakeholders (IT staff, learning designers, instructors, researchers from other disciplines) to ensure a strong alignment between theory and practice, which could increase the research impact on real-world problems.