Pedantic Computing

This Read & Reflect focuses on the following open access paper:

Keith Tran, Colton Harper, and Thomas Price. 2026. "Why Put in This Much Effort?": How AI Availability Shapes Students' Motivation in Introductory Programming. In Proceedings of the 2026 ACM Conference on International Computing Education Research Vol. 1 (ICER '26). Association for Computing Machinery, New York, NY, USA, 189–201. https://doi.org/10.1145/3765964.3811653

As derivative work, this recording is compliant with the license for the paper listed above, which is ⁠CC-BY⁠.

This Read & Reflect focuses on the following open access paper:

Nickolas Falkner, Leo Leppänen, and Juho Leinonen. 2026. Effective Use of Large Language Models for Social Constructivism in Computer Science Education. In Proceedings of the 31st ACM Conference on Innovation and Technology in Computer Science Education V. 1 (ITiCSE 2026). Association for Computing Machinery, New York, NY, USA, 210–216. https://doi.org/10.1145/3803400.3809392

As derivative work, this recording is compliant with the license for the paper listed above, which is CC-BY.

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 8, Conclusion

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 7, Fast and Forgettable: A Controlled Study of Novices’ Performance, Learning, Workload, and Emotion in AI-Assisted and Human Pair Programming Paradigms

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 6, Beyond Efficiency: A Critical Political Economy Perspective on AI Code Generators in Computing Education

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 5, HBCU Student Perspectives on Identity, Persistence, and Code-Generating AI in CS Education: A Case Study

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 4, Relationships Between Trust, Compliance, and Performance for Novice Programmers Using AI Code Generation

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 3, Novice Interactions with GitHub Copilot Under Time Pressure: A Deductive Qualitative Interview Study

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Chapter 2, Performance, Workload, Emotion, and Self-Efficacy of Novice Programmers Using AI Code Generation

Responsible and Equitable Use of AI Code Generators in Computer Science Education, the PhD Dissertation of Nicholas Gardella | Font Matter and Chapter 1, Introduction