arXiv:2608. 16318v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence (GenAI) have substantially improved the ability of large language models (LLMs) to generate and explain source code.
By Marina Lepp, Joosep Kaimre
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:2505. 00100v2 Announce Type: replace-cross Abstract: Background and Context.
By Ethan Dickey, Andres Bejarano, Rhianna Kuperus, B\'arbara Fagundes
arXiv:2604. 01114v3 Announce Type: replace-cross Abstract: As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning tasks, either by requesting help or through integrated tools.
By Griffin Pitts, Neha Rani, Weedguet Mildort
arXiv:2606. 12424v1 Announce Type: cross Abstract: As generative AI and low-code workflow platforms become routine in software practice, a key educational question is whether the next generation of computer engineers will accept these tools as useful, usable, and worthy of sustained engagement.
By Aung Pyae
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:2607. 12296v1 Announce Type: cross Abstract: With the increased use of generative AI (GenAI) applications such as ChatGPT, higher education institutions (HEIs) have released a range of guidelines and policies to direct adoption within their institutions.
By Amrita Ganguly, Aditya Johri, Nora McDonald, Areej Ali, Umama Dewan, Aayushi Hingle Collier
arXiv:2607. 00211v1 Announce Type: new Abstract: Epistemic thinking plays a central role in students' learning processes when applying generative artificial intelligence (GenAI), particularly in programming contexts where learners must construct queries, evaluate and validate AI-generated outputs, and regulate problem-solving strategies.
By Mengqian Wu
arXiv:2606. 05509v1 Announce Type: cross Abstract: Generative artificial intelligence (AI) is increasingly used to support self-directed learning, yet student interaction with such systems often remains unstructured, limiting engagement in deeper cognitive processes.
By Xiaoyu Hou, Bo Xiao, Hexu Liu, Shane Mueller
arXiv:2608. 12351v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) has challenged the validity of unsupervised online assessment, especially in technical subjects where plausible answers can be produced with little effort.
By Riasat Islam (School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom), Thomas Roelleke (School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom)
arXiv:2606. 30549v1 Announce Type: cross Abstract: AI code completion tools, such as Github Copilot, provide students with code suggestions to help them write programs.
By Jessica Hutchison, Ian Tyler Applebaum, Kenneth Angelikas, Kush Rakesh Patel, Phuoc Nguyen, Antonio Lazaro, Nicholas Rucinski, Rahad Arman Nabid, Stephen MacNeil
arXiv:2606. 28882v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown the potential to generate code explanations that surpass those of peers in quality, offering promising opportunities for computer science education.
By Seth Bernstein, Paul Denny, Juho Leinonen, Kush Patel, Rayhona Nasimova, Matt Littlefield, Stephen MacNeil