Hello, I'm Yu Yan
Pronouns: she/her
I grew up in a small, quiet city in northeastern China. I was a track and field athlete in primary school, and that early passion for sports has translated into my current hobbies of running and hiking. Building this physical and mental resilience from a young age has been incredibly beneficial to me as an educator and researcher who values curiosity and patience.
After completing my undergraduate studies, I moved to Japan as an international student, where I earned my Master’s and PhD in Computer Science, completed a postdoc, and served as an assistant professor before coming to Canada in 2024. These experiences opened my eyes to the world and helped me develop a critical appreciation for diverse cultures and perspectives, which I believe is a crucial skill as a university educator.
I am currently a tenure-track Assistant Teaching Professor in the Computer Science department at the University of Victoria. My main research interests lie in developing effective teaching and learning methods in STEM education using supporting systems and tools. To achieve this, my work spans multiple areas of computer science and data science, including adaptive and personalized learning, affective engineering, human-computer interaction, software engineering, machine learning, and fuzzy systems.
Academic Appointments
Assistant Teaching Professor
University of Victoria, Canada
Department of Computer Science
Assistant Professor
Ritsumeikan University, Japan
Department of Information Science and Engineering
Postdoctoral Researcher
University of Aizu, Japan
Department of Computer Science and Engineering
Education
Ph.D. in Computer Science and Engineering
University of Aizu, Japan
Department of Computer Science and Engineering
M.S. in Computer Science and Engineering
University of Aizu, Japan
Department of Computer Science and Engineering
B.S. in Computer Science and Technology
Harbin Normal University, China
Department of Computer Science and Technology
Teaching Experience
Assistant Teaching Professor
University of Victoria, Canada
- Database Systems (Spring 2026)
- Computers and Information Processing (Spring 2025, Fall 2025)
Assistant Professor
Ritsumeikan University, Japan
- Operating Systems (Fall 2020 – Fall 2024)
- Introduction to OOA, OOD and UML (Spring 2021 – Spring 2024)
- Information Science in Action (Spring 2020 – Spring 2023)
- Databases (Fall 2021, Fall 2023)
- Introduction to Information Systems Engineering (Spring 2020, Spring 2021)
- Boolean Algebra & Logic Design (Fall 2023)
- Imperative Programming / C Programming Language (Fall 2020)
Student Thesis Advisor and Co-Researcher
Ritsumeikan University, Japan
Provided comprehensive research mentorship and thesis advising
- Graduate Research: Co-advised and conducted joint research with approximately 5 graduate students per semester, guiding the development and execution of their advanced thesis projects.
- Undergraduate Research: Co-advised approximately 12 undergraduate students per year, providing structured mentorship for their final graduation research and academic writing.
Research & Projects
Primary Research Areas
My primary research focuses on developing innovative tools and methodologies to support the teaching and learning of computer programming. I am specifically interested in designing adaptive environments that assist beginners in comprehending complex computer languages and concepts across lectures, exercises, and self-study. During my doctoral studies, I addressed challenges in existing programming education environments by proposing two novel support frameworks:
- Lecture Oriented Program Visualization (LOPV): This framework represents a new avenue in programming learning support. Its efficacy in enhancing lecture-based instruction was formally validated through a two-year experimental application using PROVIT—an implementation of the LOPV tool—in a standard computer programming course.
- Syntactic Knowledge Point (SKP) based Personalized E-learning: SKP introduces a quantitative and precise method for representing syntactic information within program source code. I developed algorithms capable of extracting SKPs from code, analyzing a student's SKP-based learning status, and recommending tailored learning content. Together, these algorithms form the foundation of a fully automated, adaptive learning environment.
Current Research Interests
Building upon my the primary research forcues, I currently am actively integrating artificial intelligence, machine learning, affective engineering and human-computer interaction into educational analytics on helping finding more effective ways to support STEM education.