The paper presents ESSE, a self‑explanation tutor that uses a large language model to give immediate feedback on students’ line‑by‑line explanations of introductory programming worked examples. It evaluates the LLM’s judgments against a domain expert and a crowd of non‑experts, finding that the model is reliable enough to serve as the tutor’s assessment engine. In an introductory Java course, the tutor’s feedback encourages students to persist, improves the completeness and conceptual depth of their explanations, and shows evidence of learning.
By Arun-Balajiee Lekshmi-Narayanan, Mohammad Hassany, Kamil Akhuseyinoglu, Rully Hendrawan, Peter Brusilovsky
The study examined how different designs of AI teaching assistants (AI TAs) affect students in an introductory programming course. Four AI TAs were compared based on pedagogical style (Socratic vs. Direct instruction) and context awareness (no context vs. full context). Results showed that the Socratic AI TA with full context received the lowest favorability ratings, had the highest interaction stress, the most external LLM use, and the lowest comprehension outcomes, though differences were not statistically significant.
By Madeleine Eastwood, Harshith Narne, Joseph Hilby, Paul Denny, Ashish Aggarwal, Amanpreet Kapoor
arXiv:2606. 03288v1 Announce Type: cross Abstract: Introductory programming (CS1) courses often struggle to support students' understanding of program execution.
By Yuri Noviello, Naaz Sibia, Anastasiia Birillo, Thomas Overklift Vaupel Klein, Michael Liut, Gosia Migut
arXiv:2511. 13271v2 Announce Type: replace-cross Abstract: The rise of Generative AI (GenAI) tools like ChatGPT has created new opportunities and challenges for computing education.
By Rufeng Chen, Shuaishuai Jiang, Jiyun Shen, AJung Moon, Lili Wei
arXiv:2609.06095v1 Announce Type: cross
Abstract: Motivation: Undergraduate computing students increasingly turn to generative AI (GenAI) tools to understand abstract concepts through analogies. Anal...
By Seth Bernstein, Naaz Sibia
arXiv:2607. 10674v1 Announce Type: cross Abstract: As AI code tools become integrated into programming environments, students increasingly describe intended behavior in natural language and rely on these tools to generate code, shifting emphasis from code writing to specification.
By Nasser Giacaman, Valerio Terragni, Paul Denny, Viraj Kumar