Summer Undergraduate Research Fair (SURF 2025)
Beginning this year, the Summer Undergraduate Research Fair (SURF) will transition from the OVPRI to the Office of the Vice-Principal, Academic and Dean (OVPAD).
The event will be integrated into their flagship Experiential Education Fair. SURF took place September 24–25, 2025, in the Kaneff Centre Rotunda. Below are pictures from the events and a summary of abstracts.
Using GrahpRAG to Design an Intelligent Tutoring System for Computer Science Courses
Tsien Hsin Chang, Devanshu Singvi, Rohan Sunilkumar Nair, Takia Talha, and Yvonne Tov (Supervisor: Professor Rutwa Engineer)
Advisory is an intelligent tutoring platform designed to convert passive, lecture-based learning into an interactive, personalized experience. At its core, Advisory uses Neo4j knowledge graphs and a GraphRAG pipeline to merge vector and keyword retrieval. The system then uses a chain-of-thought prompt engineering to generate responses.
R Activities and Applied Concepts to Support Students' Learning Experience in Introductory Statistics
Sinan Ma (Supervisor: Professor Asal Aslemand)
This study examines how integrating R activities and applied concepts enhances students’ learning experiences in an introductory statistics course. Drawing on post-course survey data from 359 students enrolled in STA107: Introduction to Probability and Modelling at the University of Toronto Mississauga, we investigated changes in students’ confidence and communication skills related to statistical reasoning and R usage. Quantitative results indicated significant gains in students’ confidence in communicating statistical ideas and in using R for analysis and visualization. Thematic analyses of open-ended responses revealed that students valued R as a practical learning tool, highlighting tutorials, assignments, and teaching assistant support as valuable contributors to their conceptual understanding. While some students noted challenges with course pacing and assignment difficulty, the overall feedback reflected strong engagement and appreciation for the applied learning approach. Findings from this study inform future course design aimed at strengthening communication, computation, and confidence in statistics education.
Student–Faculty Co-Creation of Open Educational Resources for Learning Applied Statistics with Open Source Software Tools
Nurlana Alili, Xi (Bryan) Su (Supervisor: Professor Nishan Mudalige, Co-Supervisor: Professor Masoud Ataei)
In most university courses, students learn from textbooks which they are not involved in developing. In this Independent Statistics Research Project, two undergraduate students collaborated with faculty to create an open-access, interactive e-book for STA258: Statistics with Applied Probability, which is an applied statistics course at UTM which provides students with their first in‐depth exposure to statistical inference techniques.
In this project, undergraduate students developed content, explained concepts, designed plots and figures using code blocks, built interactive apps embedded in the e-book, and created illustrative examples, including those with a coding component. The e-book was created using R and Bookdown, it is maintained with version control (Git) and is hosted on GitHub pages with source files available on GitHub. The entire project was completed with open-source tools which are sustained by the open-source community, making it a future-proof sustainable resource for instructors and students. All content created in this research project is available to the broader statistics education community as an open educational resource.
The process in which students became co-authors rather instead of simply being passive readers, allowed them to appreciate independent reproducible research, work collaboratively with faculty and external partners, obtain skills in project management workflows, and gain opportunities to independently learn and apply new skills. Faculty benefit from fresh ideas and new perspectives from students involved in developing content for their peers. The poster presented discusses the development of the e-book, the methodology and software tools used, and discuss the experience of undergraduate participants in the independent research process.
The project was conducted by undergraduate students Nurlana Alili and Xi (Bryan) Su, under the co-supervision of Professor Nishan Mudalige (UTM) and Professor Masoud Atai (UTM), with Professor Stephen Tully (Okanagan College, BC) and Avanti Coonghe (United Nations – World Health Organization, UK) as external partners who provided guidance and feedback.
The e-book is available for access at: https://nishanmudalige.github.io/STA258/
This research resulted in a paper published in the Journal of Computing, Data, and Exploration (CODEX): https://doi.org/10.33137/codex.v1i1.45881
