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:2602. 09907v3 Announce Type: replace-cross Abstract: College students increasingly use AI chatbots to support academic reading, yet we lack granular understanding of how these interactions shape their reading experience and cognitive engagement.
By Yue Fu, Joel Wester, Niels Van Berkel, Alexis Hiniker
arXiv:2602. 09907v2 Announce Type: replace-cross Abstract: College students increasingly use AI chatbots to support academic reading, yet we lack granular understanding of how these interactions shape their reading experience and cognitive engagement.
By Yue Fu, Joel Wester, Niels Van Berkel, Alexis Hiniker
arXiv:2607. 01255v1 Announce Type: cross Abstract: Universities have responded to generative artificial intelligence (GenAI) in noticeably different ways, both internationally and within Spain.
By Jessica D\'iaz, Sonia Linio, Fernando Pescador, Daniel Martin-Fabiani
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.
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: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. 05411v1 Announce Type: cross Abstract: Higher education institutions are increasingly expected to ensure that both students and staff develop Generative AI (GenAI) literacies.
By Eduardo Oliveira, Narelle English, Tracii Ryan, Kamila Misiejuk, Cory dal Ponte, Sonsoles L\'opez-Pernas, Mohammed Saqr
arXiv:2607. 11314v1 Announce Type: cross Abstract: The promise of AI literacy ``for all'' confronts a structural challenge embedded in how nations organise secondary computer science education.
By Adrian-Marius Dumitran, Iulia-Maria Popescu
arXiv:2606. 14718v1 Announce Type: cross Abstract: As Artificial Intelligence (AI) literacy initiatives expand in K-12 settings, understanding how gender shapes student baseline perceptions, tool-use, and responsiveness to interventions is essential for equitable curriculum design.
By Jake Renzella, Christian Bergh, Natasha Banks, Alexandra Vassar
arXiv:2505. 00100v2 Announce Type: replace-cross Abstract: Background and Context.
By Ethan Dickey, Andres Bejarano, Rhianna Kuperus, B\'arbara Fagundes