arXiv:2606. 00038v1 Announce Type: cross Abstract: Artificial intelligence (AI) literacy is increasingly recognized as a foundational competency for all university graduates.
By J. Paul Liu, Rachel Levy
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
The article applies an Education-Centered AI Policy Framework to Ghana’s National Artificial Intelligence Strategy 2025‑2035, examining six key components such as teacher agency, curriculum, and responsible AI. It finds the strategy ambitious in promoting AI literacy, youth skills, and rural outreach, yet it falls short on school‑level implementation, teacher preparation, and culturally responsive pedagogy. The authors highlight concerns about transparency, coherence, and the need for a sector‑specific policy that links workforce readiness with classroom practice and learner protection.
By Matthew Nyaaba, Vida Awinime Bugri, Eric Kojo Majialuwe, Bismark Nyaaba Akanzire, Ibrahim Nantomah, Felicia Boateng, Patrick Kyeremeh, Benjamin Quarshie, Ellen Kwarteng, Macharious Nabang
arXiv:2507. 03162v2 Announce Type: replace-cross Abstract: The rapid advancement of Large Language Models (LLMs) has transformed various domains, particularly computer science (CS) education.
By Adrian Marius Dumitran, Theodor-Pierre Moroianu, Mihnea-Vicentiu Buca
Generative artificial intelligence (GenAI) has entered classrooms faster than teachers have been prepared to use it well, producing a GenAI literacy lag in which technological diffusion outpaces educators' conceptual, pedagogical, and ethical readiness. Established AI literacy frameworks predate the widespread adoption of large language models and, while acknowledging ethics, position it as a discrete competency rather than a constitutive commitment, with equity and agency as supplementary design principles.
arXiv:2606. 30655v1 Announce Type: cross Abstract: AI-native course assessments in senior computer science courses and related fields should grade students by \emph{AI-resilient skill}: the ability to achieve outcomes beyond a strong AI baseline.
By Anshumali Shrivastava