1. Curriculum mapping and assessment
Co-lead: prof. Alex Rennet (MAT), Collaborators: prof. Lisa Zhang (CSC Co-lead), prof. Andrew Petersen (CSC), prof. Tyler Holden (MAT)
This project involved creating a new curriculum map for each of our MCS disciplines as a first step, followed by identifying target program learning outcomes (PLOs) with inter-disciplinary potential for curriculum assessment. This work is in progress and involves various interventions, data collection and analysis. This work is supported by a LEAF Impact Grant.
2. Embedding writing skill development across the curriculum
Co-lead: prof. Lisa Zhang, Collaborators: prof. Michael Kaler (ISUP), prof. Andrew Petersen (MCS)
This project aims to embed writing instruction and assessment across the curriculum in our core CSC courses, in a variety of writing genres (e.g., documentation, proofs, user guides, etc.). This effort in CSC courses is done with the support of the Writing Development Initiative (TA training and writing specialist support), as well as support from a TDI grant and the LEAF Impact Grant for curriculum assessment (research assistants, quantitative and qualitative data analysis, etc.).
2. Embedded Ethics topics in the CS curriculum at UTM
Co-leads: prof. Rutwa Engineer (MCS), prof. Andrew Petersen (MCS), in collaboration with prof. Elliot Carter (Department of Philosophy)
This project involves a recent initiative to introduce and develop Ethics topics in the context of Computer Science courses, by embedding Ethics modules contextualized to CS courses. This is aligned with a new program learning outcome (PLO) in our curriculum, which is being developed in collaboration with the Department of Philosophy at UTM, and drawing from the experiences of the E3I initiative at the Department of Computer Science and the Department of Philosophy at UTSG. Topics currently being introduced via Ethics modules include accessibility in software design, energy considerations and e-waste, data privacy considerations in application design, etc.
1. Visualizations for Aiding Learning and Multiple External Representations (MERs)
With: Naaz Sibia (lead PhD student), Jessica Wen, Amber Richardson, Yashika Jain, prof. Angela Zavaleta Bernuy, prof. Andrew Petersen (co-lead PI), prof. Carolina Nobre (lead PI), and prof. Michael Liut (lead PI)
Novice programming students often struggle to connect low-level memory operations with high-level structural understanding, particularly with recursion and linked data structures. Visualizations can aid learning by making underlying relationships more visible and helping students track complex behavior. While such tools exist, most emphasize procedural flow without scaffolding abstraction. This project explores whether multiple external representations (MERs), which are a well-established approach in other STEM fields that is underutilized in computing education, can support structural abstraction through synchronized, layered visualizations.
2. Generative AI, Small and Large Language Models (SLMs/LLMs) in Computer Science Education
Current & past students and collaborators: Suqing Liu (lead MSc student), Valeria Ramirez Osorio (lead undergraduate student), Alisha Hasan (lead undergraduate student), Ido Ben Haim, prof. Michael Liut (University of Toronto Mississauga), prof. Angela Zavaleta Bernuy (McMaster University), prof. Florin Pop (Politehnica Bucharest National University of Science and Technology)
This work spawns several projects involving getting a better understanding of the impact of Generative AI and SLMs/LLMs in Computer Science education. For instance, one step was to seek how students use GenAI tools in various contexts, and their perceptions on these tools, working towards generating insights into productive uses of such tools and how they can be integrated into an educational context while limiting potential pitfalls of their use on learners.
3. OnTrack: Investigating Email Prompt Design for Student Engagement
With: Angela Zavaleta Bernuy (lead PhD student), Naaz Sibia, Elexandra Tran, Runlong Ye, prof. Andrew Petersen, prof. Michael Liut, prof. Joseph Jay Williams
This projects draws from behavioral design strategies in a pedagogic context, in order to understand student engagement and make decisions that are likely to lead to improved learning outcomes. One of the current efforts is to incorporate customized weekly email reminders to keep students on track with a course, and analyze the efficacy of various email prompt design. This effort is under the umbrella of a larger OnTrack project, in collaboration with several faculty members and graduate students affiliated with the IAI lab. The larger project involves employing various A/B testing methods and analyzing a variety of factors such as email subject lines, personalized email reminder content and several other strategies.
4. Productive Failure in CS Education
With: Phil Steinhorst (lead PhD student), prof. Jan Vahrenhold (Muenster University), prof. Andrew Petersen (University of Toronto Mississauga)
This project aims to explore Productive Failure (PF), a pedagogical technique previously explored in other disciplines, in the context of Computer Science education. The idea behind PF is that direct instruction may not lead to learners forming the right mental representations of concepts or problem-solving skills, because their prior experience will not afford them to understand the reasoning behind how direct instruction expects students to process the new information. In PF, learners explore for themselves representations and solution methods (RSMs) for solving various problems. Although this process often leads to initial failure to generate the instructor’s expected RSMs, it has the potential for an intrinsic benefit in being able to connect the student RSMs with the instructor’s intended RSMs, generating a better critical understanding.
5. Exploring Common Writing Issues in Computer Science Courses
Students: Niveditha Kani, Rehmat Munir, Francesco Strafforello (co-supervised with prof. Lisa Zhang and prof. Michael Kaler)
This project aims to explore common writing issues in undergraduate CS students with the goal of better developing writing-skills across the curriculum.
6. Student Help Seeking Aspects in an Online Delivery Mode in Introductory CS
Students: Andrew Jiang
This study explores how students seek help and their perception on ability to get help through various channels (lectures, labs, discussion board, office hours, etc.) during an introductory CS course delivered online using active learning pedagogy.
7. Analyzing the Effects of Active Learning Classrooms (ALCs)
Students: Ayesha Naeem Syeda and Rutwa Engineer
Active learning environments have only recently started to be analyzed in the CS discipline,
in terms of their effect on student performance. The goal of this project is to understand
the impact of the learning space, both in terms of quantitative measures such as student
success as indicated by grades, or negative measures such as failure rates or drop rates.
We also need to investigate student perception of the learning space in terms of how conducive
it is to the learning process.
8. Studying the Group Work Dynamics of Participation in ALCs and traditional classrooms
Students: Ayesha Naeem Syeda and Rutwa Engineer
This work aims to study the ways that students engage with others during active learning problem-solving
activities, in relation to their environment. The expectation is that the dynamics of participation and
engagement with group work are important factors to fruitful collaboration and implicitly, to the
development of the right mental models and problem-solving skills.
9. Active Learning Environments and the Transition to Online
Students: Andrew Siqueira
The goal of this work was to analyze the student perception differences between a traditional learning spaces and an active learning classroom (ALC) in terms of the ability to engage in active group problem-solving, and how this perception shifts when transitioning to online active learning lectures.
10. Studying the Effects of a Help Centre in Introductory Computer Science
Students: Jonathan Leung
Enrollments in introductory CS courses have increased substantially in large academic institutions
over the past few years, in part due to the perceived utility of computational skills from incoming
cohorts of students. In the face of surging enrollments, instructor office hours simply do not scale
in a manner where individualized and sufficient help is possible for a variety of students.
Introducing a Help Centre for novice CS students is in part intended to address scaling instructor
office hours but more importantly, to provide students with timely help, particularly struggling
students who may fall further behind.
This project aims to study the benefits of the introduction of a Help Centre, initially piloted in
a CS2 course, CSC148.
11. UTAP: UTM TA Application System
Initial Lead Students: Krish Chowdhary and Lance Santiago
This project was started with the goal of revamping our current teaching assistant application system,
in order to facilitate our TA hiring process. The goal is to provide a rich but simple interface for both applicants
and faculty/TA coordinators, as well as to streamline some of the key aspects of hiring (e.g., DDAH forms, midterm reviews, etc.).
The tool has been developed over time via work-study and independent study projects, where students get to
build their skills and explore new techniques, tools, and software packages, to work on a real-world application.
12. Discussion Board Analytics
Students: Katarina Chiam, Arnaud Deza, Haocheng Hu, and Vaishvik Maisuria (co-supervised with prof. Michael Liut and prof. Andrew Petersen)
The goal of this work is to analyze historic discussion board participation data and investigating
possible correlations of various levels of engagement and kinds of engagement, with student success metrics.
Another direction is to develop a machine learning model for generating predictive instructor responses
for certain categories of questions that where automated help may be suitable.