"I'm not sure, but...": Expert Practices that Enable Effective Code Comprehension in Data Science - Christopher Lum; Guoxuan Xu; Sam Lau (Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1, SIGCSE TS 2025, Pittsburgh, PA, USA, 26 February 2025 - 1 March 2025, 2025)

How Novices Use Program Visualizations to Understand Code that Manipulates Data Tables - Ylesia Wu; Qirui Zheng; Sam Lau (Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1, SIGCSE TS 2025, Pittsburgh, PA, USA, 26 February 2025 - 1 March 2025, 2025)

How Instructors Incorporate Generative AI into Teaching Computing - James Prather; Juho Leinonen; Natalie Kiesler; Jamie Gorson Benario; Sam Lau; Stephen MacNeil; Narges Norouzi; Simone Opel; Virginia Pettit; Leo Porter; Brent N. Reeves; Jaromír Savelka; et al. (Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 2, ITiCSE 2024, Milan, Italy, July 8-10, 2024, 2024)

Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools - James Prather; Juho Leinonen; Natalie Kiesler; Jamie Gorson Benario; Sam Lau; Stephen MacNeil; Narges Norouzi; Simone Opel; Vee Pettit; Leo Porter; Brent N. Reeves; Jaromír Savelka; et al. (2024 Working Group Reports on Innovation and Technology in Computer Science Education, ITiCSE 2024, Milan, Italy, 8 July 2024, 2024)

Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools - James Prather; Juho Leinonen; Natalie Kiesler; Jamie Gorson Benario; Sam Lau; Stephen MacNeil; Narges Norouzi; Simone Opel; Vee Pettit; Leo Porter; Brent N. Reeves; Jaromír Savelka; et al. (CoRR, 2024)

Teaching Data Science by Visualizing Data Table Transformations: Pandas Tutor for Python, Tidy Data Tutor for R, and SQL Tutor - Sam Lau; Sean Kross; Eugene Wu; Philip J. Guo (Proceedings of the 2nd International Workshop on Data Systems Education: Bridging education practice with education research, DataEd 2023, Seattle, WA, USA, 23 June 2023, 2023)

From "Ban It Till We Understand It" to "Resistance is Futile": How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot - Sam Lau; Philip J. Guo (Proceedings of the 2023 ACM Conference on International Computing Education Research - Volume 1, ICER 2023, Chicago, IL, USA, August 7-11, 2023, 2023)

The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses - Sam Lau; Justin Eldridge; Shannon Ellis; Aaron Fraenkel; Marina Langlois; Suraj Rampure; Janine Tiefenbruck; Philip J. Guo (L@S'22: Ninth ACM Conference on Learning @ Scale, New York City, NY, USA, June 1 - 3, 2022, 2022)

How Computer Science and Statistics Instructors Approach Data Science Pedagogy Differently: Three Case Studies - Sam Lau; Deborah Nolan; Joseph Gonzalez; Philip J. Guo (SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education, Providence, RI, USA, March 3-5, 2022, Volume 1, 2022)

Codehound: Helping Instructors Track Pedagogical Code Dependencies in Course Materials - Sam Lau; Philip J. Guo (Proceedings of the 2022 ACM SIGPLAN International Symposium on SPLASH-E, SPLASH-E 2022, Auckland, New Zealand, 5 December 2022, 2022)

TweakIt: Supporting End-User Programmers Who Transmogrify Code - Sam Lau; Sruti Srinivasa Ragavan; Ken Milne; Titus Barik; Advait Sarkar (CHI '21: CHI Conference on Human Factors in Computing Systems, Virtual Event / Yokohama, Japan, May 8-13, 2021, 2021)

The Design Space of Computational Notebooks: An Analysis of 60 Systems in Academia and Industry - Sam Lau; Ian Drosos; Julia M. Markel; Philip J. Guo (IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2020, Dunedin, New Zealand, August 10-14, 2020, 2020)