arXiv:2607. 14301v1 Announce Type: new Abstract: As generative AI (GenAI) becomes increasingly embedded in undergraduate academic writing, how students rely on these tools, rather than simply whether they use them, has become a central question for learning, academic integrity, and educational equity.
By Shahin Hossain, Tukhbita Afroz Nawmi
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:2505. 00100v2 Announce Type: replace-cross Abstract: Background and Context.
By Ethan Dickey, Andres Bejarano, Rhianna Kuperus, B\'arbara Fagundes
arXiv:2606. 24104v1 Announce Type: cross Abstract: Generative artificial intelligence(GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and social sciences(HSS), where learning outcomes are commonly expressed through written and interpretive forms that align closely with GenAI's capabilities.
By Lei Fan, Fangxue Liu
arXiv:2606. 28749v1 Announce Type: cross Abstract: Although most undergraduates now use large language models (LLMs), a form of generative artificial intelligence (GenAI) for academic writing, no validated method distinguishes the qualitatively different ways students rely on them.
By Shahin Hossain
arXiv:2607. 28650v1 Announce Type: cross Abstract: While industry discourse often emphasizes immediate productivity gains and frames GenAI primarily as a tool for automation, the integration of GenAI into system administration may involve deeper shifts in professional practice that are not yet fully understood.
By Rana Abou Khamis, Hala Assal, Ashraf Matrawy
arXiv:2512. 12413v2 Announce Type: replace Abstract: Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that users must critically evaluate AI outputs rather than accept them at face value.
By Gabriel R. Lau, Wei Yan Low, Louis Tay, Ysabel Guevarra, Dragan Ga\v{s}evi\'c, Andree Hartanto
arXiv:2606. 00040v1 Announce Type: cross Abstract: As Generative AI (GenAI) becomes integral to education, fostering GenAI literacy is critical.
By Angxuan Chen, Jiyou Jia
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. 10881v1 Announce Type: new Abstract: Learner agency and autonomy are foundational to personal development, yet a pervasive "jingle-jangle" fallacy (i.
By Fei Qin, Xiaobo Liu, Yaowen Zhang, Xuming Li, Fei Wang, Mutlu Cukurova, Jingjing Chen, Yu Zhang
arXiv:2607. 28630v1 Announce Type: cross Abstract: Generative AI (GenAI) holds significant promise for advancing educational equity among ethnic minority students by broadening access to learning resources and mitigating linguistic barriers.
By Deliang Wang, Cunling Bian
High-stakes English proficiency tests treat standardized, unaided performance as evidence for score interpretations about academic English proficiency. This interpretation remains meaningful, but as target language use domains increasingly involve generative AI, the extrapolation from unaided test performance to academic communicative readiness becomes less self-evident.