arXiv AI
Jul 20
A Scaffolded GenAI Lab in Early Undergraduate CS: A Mixed-Methods, Multi-Course Evaluation
arXiv:2505. 00100v2 Announce Type: replace-cross Abstract: Background and Context.
The impact of generative artificial intelligence on academic development of Chinese students in humanities and social sciences
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.
Related stories
arXiv AI
Sep 17
The Uneven Impact of Generative AI on Student Learning: Examining the Roles of Reliance, Evaluation Literacy, and Course Policy in AI-related Courses
The study investigates how generative AI (GenAI) affects student learning in AI-related courses, using survey data from 118 students across 12 courses. Four distinct user clusters were identified—high-use, light-use, and two moderate-use groups—each showing varying benefits and reliance patterns. The research highlights that early reliance, evaluation literacy, and instructor policies significantly influence perceived academic benefits and negative impacts, underscoring the need for institutional policies to address inequities in AI use.
arXiv AI
Aug 25
A Survey Instrument to Assess Students' AI and Generative AI Knowledge
arXiv:2608.21391v1 Announce Type: cross Abstract: In this research-to-practice paper we present a survey that can be used to assess students' AI knowledge. As the use of artificial intelligence (AI),...
arXiv AI
Jun 2
Beyond Tool Adoption: A Practical Five-Stage Developmental Continuum for AI Literacy in Higher Education
arXiv:2606. 00038v1 Announce Type: cross Abstract: Artificial intelligence (AI) literacy is increasingly recognized as a foundational competency for all university graduates.
arXiv AI
Jun 30
Four Types of LLM Reliance and Their Predictors Among Undergraduate Writers: A Mixed-Methods Study at a Minority-Serving R1 University
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.
arXiv AI
Jul 23
Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education
arXiv:2607. 19699v1 Announce Type: cross Abstract: The rise of generative AI (GenAI) in higher education has prompted urgent debates surrounding academic integrity and ethical use.
arXiv AI
Aug 3
Scaffolding Critical Engagement with GenAI: Transforming Ethnic Minority Preparatory Students' Collaborative Discourse in Prompt Engineering Tasks
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.
arXiv AI
Jul 8
The GenAI Skill Bypass: Mapping Divergent Pathways of University Students and Staff AI Literacy
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.
Hugging Face Trending Papers
Aug 3
Rethinking Generative AI Literacy: An Integrative, Developmental, and Dialectical Framework for K-12 Teacher Education
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 AI
Jul 17
Measuring How Students Rely on Generative AI in Academic Writing: Development and Multi-Source Validation of the Generative AI Reliance Types Scale (GenAI-RTS)
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.
arXiv AI
Jul 1
Artificial Intelligence in Sports: Insights from a Quantitative Survey among Sports Students in Germany about their Perceptions, Expectations, and Concerns regarding the Use of AI Tools
arXiv:2503. 05785v2 Announce Type: replace-cross Abstract: Generative Artificial Intelligence (AI) tools such as ChatGPT, Copilot, or Gemini have a crucial impact on academic research and teaching.
arXiv AI
Sep 7
Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education
The study explores how undergraduate computing students in Saudi Arabia perceive AI‑generated writing feedback when they are explicitly told that ChatGPT, not a human instructor, produced the score and comments. Through qualitative reflections, four themes emerged: students found the feedback useful for surface‑level revisions, recognized AI’s contextual and pedagogical limits, trusted the feedback conditionally—separating its utility from its authority—and reaffirmed the human instructor’s role as the ultimate grading authority. The findings highlight a clear distinction students make between feedback usefulness and evaluative authority, treating them as separate judgments rather than opposing ends of a single approval scale.