Contact Info News Publications Undergraduate Research Group

Brian Harrington

Associate Professor, Teaching Stream
Department of Computer and Mathematical Sciences
University of Toronto Scarborough
brian.harrington@utoronto.ca

I am an Associate Professor, Teaching Stream in the Department of Computer and Mathematical Sciences at the University of Toronto Scarborough. My research focuses on Computer Science Education and Pedagogy, with a special emphasis on involving undergraduate students in research.

I completed my Doctorate in Computer Science at the Oxford University Department of Computer Science under the supervision of Dr. Stephen Clark. My research focused on the intersection of Artificial Intelligence and Natural Language Processing, in particular, the automated construction of Semantic Network with the ASKNet system.

Prior to joining UTSC, I held a Research and Tutorial Fellowship in Computer Science at Keble College, Oxford. And worked as a Research Scientist in the Medical Informatics Group at the University of Wisconsin Milwaukee.



URG Students Present at WCCCE
Undergrad research group members Anand Kakri and Anis Saha came to UBC to present at WCCCE'23 and tell us all about their work on evaluating solo vs pair programming in an online environment.

SIGCSE Comes to Toronto: URG Students go to SIGCSE
SIGCSE 2023 was held in Toronto. With 3 posters from the current group, former group member Angela Zavaleta Bernuy presenting her paper Prior Programming Experience: A Persistent Performance Gap in CS1 and CS2, and a slew of student volunteers, our URG had a very strong representation. Thanks everyone for an amazing conference!



For a complete list of my publications, click here.

Finding and Categorizing COVID-19 Papers in CS Education

Brian Harrington, Aditya Kulkarni, Zixiao Ren, Conroy Trinh, Raha Gharadaghi, Thezyrie Amarouche, Ansh Aneel, Anand Karki, Seemin Syed, and David Yue. 2023. Finding and Categorizing COVID-19 Papers in CS Education. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 1342. https://doi.org/10.1145/3545947.3576288

Evaluating Solo vs Pair Programming in an Online Setting for Introductory Programming Students

Mustafa Hafeez, Anand Karki, Yara Radwan, Anis Saha, Angela Zavaleta Bernuy, and Brian Harrington. 2023. Evaluating Solo vs Pair Programming in an Online Setting for Introductory Programming Students. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 1333. https://doi.org/10.1145/3545947.3576279

Virtual Exam Wrappers: A Pilot Study for Online Replication

Abhivyakti Ahuja, Varun Datta, William Song, and Brian Harrington. 2023. Virtual Exam Wrappers: A Pilot Study for Online Replication. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2023). Association for Computing Machinery, New York, NY, USA, 1424. https://doi.org/10.1145/3545947.3576368

Exploring Lightweight Practices to Support Students' Well-being

Oluwakemi Ola and Brian Harrington. 2022. Exploring Lightweight Practices to Support Students' Well-being. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 2 (SIGCSE 2022). Association for Computing Machinery, New York, NY, USA, 1070–1071. DOI:https://doi.org/10.1145/3478432.3499031

Evidence for Teaching Practices that Broaden Participation for Women in Computing

Briana B. Morrison, Beth A. Quinn, Steven Bradley, Kevin Buffardi, Brian Harrington, Helen H. Hu, Maria Kallia, Fiona McNeill, Oluwakemi Ola, Miranda Parker, Jennifer Rosato, and Jane Waite. 2022. Evidence for Teaching Practices that Broaden Participation for Women in Computing. In Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '21). Association for Computing Machinery, New York, NY, USA, 57–131. DOI:https://doi.org/10.1145/3502870.3506568

PyBuggy: Testing the Effects of Enhanced Error Messages on Novice Programmers

Rachel D'souza, Angela Zavaleta Bernuy, and Brian Harrington. 2021. PyBuggy: Testing the Effects of Enhanced Error Messages on Novice Programmers. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE '21). Association for Computing Machinery, New York, NY, USA, 1346. DOI:https://doi.org/10.1145/3408877.3439652

Mapping the Landscape of Peer Review in Computing Education Research

Marian Petre, Kate Sanders, Robert McCartney, Marzieh Ahmadzadeh, Cornelia Connolly, Sally Hamouda, Brian Harrington, Jérémie Lumbroso, Joseph Maguire, Lauri Malmi, Monica M. McGill, and Jan Vahrenhold. 2020. Mapping the Landscape of Peer Review in Computing Education Research. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '20). Association for Computing Machinery, New York, NY, USA, 173–209. https://doi.org/10.1145/3437800.3439207

What are We Asking our Students? A Literature Map of Student Surveys in Computer Science Education

Angela Zavaleta Bernuy and Brian Harrington. 2020. What are We Asking our Students? A Literature Map of Student Surveys in Computer Science Education. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '20). Association for Computing Machinery, New York, NY, USA, 418–424. https://doi.org/10.1145/3341525.3387383

An Analysis of Student Preferences for Inverted vs Traditional Lecture

Harrington, Brian, Mohamed Moustafa, Jingyiran Li, Marzieh Ahmadzdeh, and Nick Cheng. "An Analysis of Student Preferences for Inverted vs Traditional Lecture." Psychology of Programming Interest Group Workshop 2020.

Developing Testing-First Labs For a Less Intimidating Introductory CS Experience.

Bernuy, Angela M. Zavaleta, and Brian Harrington. "Developing Testing-First Labs For a Less Intimidating Introductory CS Experience." Psychology of Programming Interest Group Workshop 2020.

Compiler error messages considered unhelpful: The landscape of text-based programming error message research

Brett A. Becker, Paul Denny, Raymond Pettit, Durell Bouchard, Dennis J. Bouvier, Brian Harrington, Amir Kamil, Amey Karkare, Chris McDonald, Peter-Michael Osera, Janice L. Pearce, and James Prather. 2019. Compiler Error Messages Considered Unhelpful: The Landscape of Text-Based Programming Error Message Research. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '19). Association for Computing Machinery, New York, NY, USA, 177–210. https://doi.org/10.1145/3344429.3372508

On the Effect of Question Ordering on Performance and Confidence in Computer Science Examinations

Brian Harrington, Jingyiran Li, Mohamed Moustafa, Marzieh Ahmadzadeh, and Nick Cheng. 2019. On the Effect of Question Ordering on Performance and Confidence in Computer Science Examinations. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19). Association for Computing Machinery, New York, NY, USA, 620–626. https://doi.org/10.1145/3287324.3287398

A Statistical Analysis of Drop Rates in Introductory Computer Science by Gender and Partial Grade

Jikai Long and Brian Harrington. 2019. A Statistical Analysis of Drop Rates in Introductory Computer Science by Gender and Partial Grade. In Proceedings of the Western Canadian Conference on Computing Education (WCCCE '19). Association for Computing Machinery, New York, NY, USA, Article 13, 1–2. https://doi.org/10.1145/3314994.3325081

A Mixed-Methods Study of Novice Programmer Interaction with Python Error Messages

Rachel D'souza, Mahima Bhayana, Marzieh Ahmadzadeh, and Brian Harrington. 2019. A Mixed-Methods Study of Novice Programmer Interaction with Python Error Messages. In Proceedings of the Western Canadian Conference on Computing Education (WCCCE '19). Association for Computing Machinery, New York, NY, USA, Article 15, 1–2. https://doi.org/10.1145/3314994.3325090

Immediate Feedback Collaborative Code Tracing

Jun Zheng, Sohee Kang, and Brian Harrington. 2019. Immediate Feedback Collaborative Code Tracing. In Proceedings of the Western Canadian Conference on Computing Education (WCCCE '19). Association for Computing Machinery, New York, NY, USA, Article 12, 1–2. https://doi.org/10.1145/3314994.3325087

Identity Atheneum: Combining User Management, Analytics and Gamification in a Multi Tool Hub

Jun Zheng and Brian Harrington. 2019. Identity Atheneum: Combining User Management, Analytics and Gamification in a Multi Tool Hub. In Proceedings of the 5th ACM SPLICE Project Workshop in conjunction with ICER2019 (SPLICE ’19), August 11, 2019, Toronto Canada

Gender, confidence, and mark prediction in CS examinations

Brian Harrington, Shichong Peng, Xiaomeng Jin, and Minhaz Khan. 2018. Gender, confidence, and mark prediction in CS examinations. In Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2018). Association for Computing Machinery, New York, NY, USA, 230–235. https://doi.org/10.1145/3197091.3197116

Fit-breaks: incorporating physical activity breaks in introductory CS lectures

Alyona Koulanova, Ary Maharaj, Brian Harrington, and Jessica Dere. 2018. Fit-breaks: incorporating physical activity breaks in introductory CS lectures. In Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2018). Association for Computing Machinery, New York, NY, USA, 260–265. https://doi.org/10.1145/3197091.3197115

Tracing vs. Writing Code: Beyond the Learning Hierarchy

Brian Harrington and Nick Cheng. 2018. Tracing vs. Writing Code: Beyond the Learning Hierarchy. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18). Association for Computing Machinery, New York, NY, USA, 423–428. https://doi.org/10.1145/3159450.3159530

TrAcademic: Improving Participation and Engagement in CS1/CS2 with Gamified Practicals

Brian Harrington and Ayaan Chaudhry. 2017. TrAcademic: Improving Participation and Engagement in CS1/CS2 with Gamified Practicals. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE '17). Association for Computing Machinery, New York, NY, USA, 347–352. https://doi.org/10.1145/3059009.3059052

The Code Mangler: Evaluating Coding Ability Without Writing any Code

Nick Cheng and Brian Harrington. 2017. The Code Mangler: Evaluating Coding Ability Without Writing any Code. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE '17). Association for Computing Machinery, New York, NY, USA, 123–128. https://doi.org/10.1145/3017680.3017704

A semantic network approach to measuring relatedness

Harrington, Brian. "A semantic network approach to measuring relatedness." Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010).

Asknet: Creating and Evaluating Large Scale Integrated Semantic Networks

Harrington, Brian, and Stephen Clark. "Asknet: Creating and evaluating large scale integrated semantic networks." International Journal of Semantic Computing 2.03 (2008): 343-364.

Interested in getting involved in research? Want to sharpen your academic skills? Just wondering what it is your professors do all day? Then come join the UTSC Computer and Mathematical Sciences Undergraduate Research Group.

The CMS Undergraduate Research Group was founded to give students in our department an opportunity to explore and participate in research. Any level of experience or commitment is welcome. We have everything from reading and discussion groups, to full-fledged research projects. We have published dozens of papers undergraduate co-authors, established an annual symposium, and had students present at local, national and international research conferences.

Research Opportunities:
If you are interested in joining our group, e-mail me at brian.harrington@utoronto.ca to find out more.


Abhivyakti Ahuja

Software Engineer at Amazon


Thezyrie Amarouche

Software Developer at Contractor Compliance Inc.


Ansh Aneel

Class of '24


Mahima Bhayana

Production Engineer at Shopify


Ayaan Chaudhry

Manager of Machine Learning at ManXMachina


Varun Datta

Class of '24


Rachel D'Souza

Class of '20


Raha Gharadaghi

Technology Specialist at Bell


Mustafa Hafeez

Class of '22


Xiaomeng (Tracy) Jin

PhD Student at University of Illinois Urbana-Champaign


Anand Karki

Class of '22


Minhaz Khan

Analyst, Business Intelligence at The Princess Margaret Cancer Foundation


Alyona Koulanova

Evaluation and Research Specialist at EveryMind


Aditya Kulkarni

Class of '23


Jingyiran Sophia Li

Data Scientist at RBC


Jikai Long

Software Development Engineer at Amazon Web Services


Ary Maharaj

Outreach & Education Coordinator at NEDIC


Mohamed Moustafa

Full Stack Engineer at eSSENTIAL Accessibility


Shichong (Nio) Peng

PhD Student at Simon Fraser University


Yara Radwan

Class of '23


Zixiao Ren

Class of '23


Anis Saha

Class of '22


Will Song

Software Engineer at Amazon


Seemin Syed

MInfo Candidate University of Toronto


Conroy Trinh

Software Engineer at Veeva Systems


David Yue

Software Engineer at Huawei


Angela Zavaleta-Burnuy

PhD Candidate - University of Toronto


Jun Zheng

Software Engineer at Google