AI in Higher Education
Wednesday, 9 September 2026
What crossed the desk today, gathered from 58 sources.
A scoping review of generative AI-powered agentic AI in education: Research landscape, agentic capabilities, and insights from the frontier agent paradigm, exemplified by OpenClaw
Computers and Education: Artificial Intelligence, Volume 11
Generative AI in scenario-based healthcare education: A systematic review of applications, validation practices, and pedagogical integration
Computers and Education: Artificial Intelligence, Volume 11
Artificial intelligence in vocational education and training: A systematic review of educational purposes, theoretical conceptualizations, and empirical effectiveness
Computers and Education: Artificial Intelligence, Volume 11
Measuring Acceptance of Age-Tiered AI Literacy Guidebooks: A Developmentally Informed Study of K-12 Students and Teachers
Computers and Education: Artificial Intelligence
Preferred Scaffolding Does Not Lead to Better Learning Performance: Empirical Evidence from AI-Supported Mathematical Modelling
Computers and Education: Artificial Intelligence
Applying IRT to distinguish between human and generative AI responses to multiple-choice assessments
Computers and Education: Artificial Intelligence
Developing L2 writing student self-assessment literacy through AI-generated feedback and AI chain-of-thought: An action research study with lower-proficiency university EFL learners
Computers & Education, Volume 254
LLMs in text linguistics teaching: an exploratory study with genAI novices in higher education
Computers and Education Open, Volume 11
AI-assisted, instructor-supervised grading and feedback in higher education: Design and evaluation of an end-to-end pipeline
Computers and Education Open, Volume 11
Rethinking data privacy for AI Adoption in African Higher Education: A meta-synthesis of stakeholder perceptions and policy implications
Computers and Education Open, Volume 11
AI training and science student teachers’ TPACK in campus-based and distance education: a comparative study
Computers and Education Open, Volume 11
Institutional structures, digital inequality, and AI integration in higher education
Computers and Education Open, Volume 11
Junior high school student perspectives on the use of ChatGPT in music education
Computers and Education Open, Volume 11
Navigating the challenges of Gen-AI in Chinese higher education: Balancing technological innovation with academic integrity and intellectual engagement
Computers and Education Open
The double-edged sword effect of AI use on college students' learning engagement
The Internet and Higher Education, Volume 71
Stressed minds, smart tools: How academic expectation stress fuels generative AI dependency in Chinese higher education
The Internet and Higher Education, Volume 71
Self-regulated learning strategy transitions and academic performance in blended learning: Insights from learning analytics
The Internet and Higher Education
GPT-4 feedback increases student activation and learning outcomes in higher education
International Journal of Artificial Intelligence in Education, Volume 36, Issues 1–2
Making machine learning findings accessible to teachers in blended classrooms
International Journal of Artificial Intelligence in Education, Volume 36, Issues 1–2
Assistive generative AI for visually impaired learners: Personalization and inclusion in higher education
International Journal of Artificial Intelligence in Education, Volume 36, Issues 1–2
Facilitative Teaching for Transformational Learning in the Age of AI
Higher education institutions can better prepare students for an artificial intelligence–augmented workforce by shifting from teacher-centered models to facilitative instructional approaches that develop the enduring professional capacities that become more, not less, valuable as AI transforms work: critical thinking…
Listening to Skepticism: What Faculty Concerns About Generative AI Reveal
Listening to faculty concerns about generative AI can help institutions respond with more clarity, precision, and trust.
Building AI Initiatives with Bottom-Up Champions
Driven by a bottom-up partnership between the Faculty Center for Teaching and Learning and the Division of Digital Learning, the University of Central Florida established an evolving campus infrastructure of policies, training, and a national conference to guide the ethical and effective integration of generative AI…
Can AI truly recognise student needs?
Unis are using AI for a range of purposes. From a student’s perspective, most uses fall into four familiar functions: tutoring, lecturing, feedback provision, and marking. These are all core parts of teaching traditionally done by humans.
The convergent laboratory: when AI reasoning, autonomous experiments, high performance and quantum computing reshape chemistry
This Comment emerges from TPC26 (https://tpc26.org), a conference convening leaders from academia, national laboratories, and industry who are reshaping materials science discovery. The meeting explored how AI, autonomous agents, self-driving labs, higher performance and quantum computing converge to amplify their…
A Translational Note on AI Safety Evaluation
Recent studies report that automated red-teaming finds more vulnerabilities, at lower cost, than human red-teaming on standard AI safety benchmarks, and some read this as evidence that human evaluators are becoming dispensable. The comparison measures one thing and the conclusion claims another. A benchmark measures…
Context-Masked Truncated Reasoning Audits for Answer-Key Dependence in LLM Tutors
Large language model (LLM) tutors may have access to teacher notes, answer keys, rubrics, or retrieved solutions while producing student-facing explanations. We study whether truncated reasoning probes can distinguish direct access to such private context from answer information carried by the written explanation…
Ordinary, Reasonable Chatbots: Do AI Models Track Human Legal Judgments?
As people increasingly rely on artificial intelligence (AI) for guidance in their own lives, scholars, lawyers, and even judges have begun to consider the role of AI in legal decision-making. As "silicon sampling" -- the use of generative AI models in social science research -- is now impacting academia, "silicon…
From Sensor Data to Classroom Inquiry: GenAI-Supported Exploration of School Digital Twin Data
Digital Twins for educational buildings can support sustainability-oriented learning, but their use in schools remains limited. This paper presents a GenAI-based chatbot built on top of an existing Digital Twin for two school buildings in Greece, using real IoT data from environmental sensors and energy meters. The…
Flawed but Memorable: Student Critical Reception of Interest-Personalized GenAI Analogies in Computing Education
Motivation: Undergraduate computing students increasingly turn to generative AI (GenAI) tools to understand abstract concepts through analogies. Analogies compare an unfamiliar concept to something familiar, but judging whether the comparison holds requires knowledge of both. GenAI may also embed assumptions about who…
Building an everyday equitable practice for AI in schools
AI technology is advancing rapidly in schools, but research is increasingly showing that Large Language Models (LLMs) lack the common sense, morality, and knowledge of individual classroom dynamics needed to be truly equitable. The post Building an everyday equitable practice for AI in schools appeared first on…
Students who use AI generally score worse at school
Students who use AI to help them study tend to perform worse at school than those who don't, according to data from a global OECD educational report. The situation is more complex than it sounds though, with certain types of AI use giving learners a slight boost, especially among students taught to critically assess…