Dr. Luc Paquette

Associate Professor

Build a Statement of Purpose

Generate a tailored SOP for Dr. Luc Paquette. Improve your application with a focused, well-structured draft.

Biography

Luc Paquette is an associate professor in the Department of Curriculum & Instruction at the University of Illinois, Urbana-Champaign. He completed his PhD in Computer Science at the Université de Sherbrooke, where he focused on designing knowledge representations for intelligent tutoring systems and their applications in generating pedagogical content. Subsequently, he worked as a post-doctoral research associate at Teachers College, Columbia University, employing educational data mining and knowledge engineering techniques to investigate student behaviors in digital learning environments. His research interests include educational data mining, learning analytics, and the development of digital learning environments to enhance pedagogical practices. Professor Paquette studies various behaviors in digital contexts, including misuse of such environments and self-regulated learning. His teaching involves courses on digital learning environments and computer science education, emphasizing practical and theoretical aspects of these fields. He has received the NSF CAREER Award in 2020 for his contributions to education research and service.

Research Interests

Experience

Associate Professor

— Present

University of Illinois, Urbana-Champaign • Champaign, IL

Teaching digital learning environments and computer science courses, conducting research in educational data mining and learning analytics.

Awards

#2020

NSF CAREER Award

Courses

CI 210: Introduction Digital Learning Environments CI 492: Discrete Mathematics CS Teachers CI 480: Introduction Computer Science CS Teachers CI 488: Capstone Project Computer Science Teachers CI 487: Data Structures Computer Science Teachers CI 438: Computer Programming Classroom CI 483: Computer Systems CS Teachers

Requirements for University of Illinois

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:7
Reading
Required:7
Writing
Required:7
Speaking
Required:7
Overall
Required:7.5
TOEFL
Listening
Required:17
Reading
Required:19
Writing
Required:21
Speaking
Required:20
Total
Required:103
GRE General
Prerequisites
Mathematical background Linear Algebra Calculus
Application Checklist
  • Online application
  • Unofficial transcripts
  • 3 Letters of Recommendation
  • Academic Statement of Purpose
  • Resume/CV
Specialization Notes

GRE is optional for admission to all graduate programs in Statistics. Full status admission requires higher language scores than limited status.