AI in Higher Education

Meta Releases Muse Glimmer, an Open-Weight AI Model Designed to Run on Consumer Hardware

Meta is returning to open-weight artificial intelligence with Muse Glimmer, a new AI model designed to run on consumer hardware, as CEO Mark Zuckerberg argues that increasingly capable AI should be widely available rather than controlled by a small number of institutions.

OpenAI Pumps Brakes on Frontier AI Training After Hugging Face Breach

OpenAI is changing how it trains, monitors and contains frontier AI models after its July cybersecurity evaluation breach reached Hugging Face's production infrastructure.

EvoCurr: Self-evolving Curriculum with Behavior Code Generation for Complex Decision-making

Complex decision-making often requires agents to progress through intermediate tasks rather than solve the final target directly. Existing LLM self-refinement methods typically iterate on a fixed target, while curriculum-learning methods often rely on hand-designed schedules, training-time optimization, or…

From National Curricula to Cultural Awareness: Constructing Open-Ended Culture-Specific Question Answering Dataset

Large language models (LLMs) achieve strong performance on many tasks, but their progress remains uneven across languages and cultures, often reflecting values latent in English-centric training data. To enable practical cultural alignment, we propose a scalable approach that leverages national social studies…

Lightweight Machine Learning-Driven Monocular Sidewalk Path Extraction for Embedded Micromobility Navigation

Sidewalk-scale path extraction demands perception and planning that run reliably on compact, low-power hardware in cluttered, map-sparse environments. We present a monocular vision pipeline for sidewalk path extraction in micromobility systems that progresses through three design iterations, from a skeleton-graph…

A Framework for Assessing Information Literacy in Interactions with AI Chatbots

Axel Bruns , Snurblog , Sept 15, 2026 This is another conference session report from Axel Bruns (who I think we should recognize more widely for his ongoing coverage). He writes, "Variables that can be used to assess user approaches here include query design features, output control features, prompting strategies…

Mitigating LLM biases toward spurious social contexts using direct preference optimization

LLMs are increasingly used for high-stakes decision-making, yet their sensitivity to spurious context can introduce harmful biases. This is a critical concern when models are deployed for tasks like evaluating teachers' instructional quality, where biased assessment can affect teachers' professional development and…

UCO: A Multi-Turn Interactive Reinforcement Learning Method for Adaptive Teaching with Large Language Models

Large language models (LLMs) are shifting from answer providers to intelligent tutors in educational settings, yet current supervised fine-tuning methods only learn surface teaching patterns without dynamic adaptation capabilities. Recent reinforcement learning approaches address this limitation but face two critical…

Beyond the Chatbot: Co-Learning and Co-Teaching through a Dual-Persona Generative-AI Assistant

In this paper we present a generative AI application developed to support both teachers and students in secondary education. The system employs two Large Language Models-LLMs, Gemini and DeepSeek, and a Small Language Model-SLM, Gemma, integrated within a Retrieval Augmented Generation - RAG framework, creating a…

GenAIT: Development and Validation of an Objective Generative AI Literacy Test for High School Students

There is growing international interest in generative AI (GenAI) literacy and its assessment among high school students, but objective assessment in this population remains underdeveloped. This article reports the iterative development and validation of the GenAI Literacy Test (GenAIT), an 18-item multiple-choice test…

Learning to Prompt: Improving Student Engagement with Adaptive LLM-based High-School Tutoring

LLMs can personalize education, although current static-prompt tutoring systems struggle to adapt to diverse academic disciplines. We develop and test a system with subject-aware prompting, based on 14 pedagogical features (e.g., tutor scaffolding, student understanding) extracted from raw transcripts. We first train…

Giving Mechanical Engineers Intelligent Tools: A Project-Based AI Education Curriculum in Thermal Engineering

Mechanical engineering (ME) requires a broad knowledge base across several disciplines. However, ME students often have insufficient training in electrical and computer engineering, complex challenges in traditional thermal system modeling, and endure heavy course loads with limited class hours. To help address these…

The AI Adaptation Gap in Higher Education: Students, Faculty, and Administrative Staff

The purpose of this study was to analyze patterns of artificial intelligence (AI) use and attitudes toward AI among students, faculty, and administrative staff at a large university specializing in teacher education. The analytical sample comprised 1809 students, 250 faculty members, and 62 administrative staff…

AI Tends to Mark Students’ Essays Higher Than Humans, Study Shows

AI Tends to Mark Students’ Essays Higher Than Humans, Study Shows Susan H. Greenberg Thu, 08/27/2026 - 03:00 AM LLMs cannot be relied on to give accurate indication of student performance, researchers find, as universities explore ways to relieve pressure on graders. Byline(s) Juliette Rowsell for Times Higher…

Better answers, broader thinking: What students gain from ChatGPT and critical-thinking training

A randomized study of more than 1,000 students examines ChatGPT, critical thinking, originality, and student performance on a real-world university assignment.

AI, humans and the university in an era of (un)becoming

The Nexus of Gen‐AI Features in Higher Education: Reducing Cognitive Load, Building Resilience, and Personalising Learning

Journal of Computer Assisted Learning, Volume 42, Issue 5, October 2026.

Artificial intelligence reshaping Belarus’ higher education, assessment practices

Are your institutions seeing changes in enrollments given the use of AI LLMs like ChatGPT and Google AI Overviews by prospective students?

I’ve been looking at what the publicly traded postsecondary companies said on their most recent earnings calls, and there seems to be a recurring theme around student acquisition and its evolution given the adoption of LLMs by prospective students. The management teams are saying that prospective students are going…

New Microsoft AI Code of Conduct Emphasizes Human Control

Microsoft has published a draft code of conduct that details how its homegrown AI models should behave, with human control taking priority over model capability, autonomy, and even task completion.

Context-sensitive learning analytics in open and distance education: Identifying students' online learning behavior patterns in a large-scale Indonesian context

The Internet and Higher Education

Higher Education Does Not Need More AI Tools but Better AI Experiences

For most colleges and universities, access to AI tools is no longer the barrier. The real work is building the clarity, confidence, and shared responsibility to use them well.

Game On Exploring the AI Arcade at Penn State

Higher education can strengthen students' artificial intelligence (AI) literacy and responsible AI use by creating low-stakes, hands-on learning spaces where students, faculty, and staff explore emerging AI tools through guided experimentation, collaboration, and reflection.

Designing the AI-Integrated Classroom: A Triadic Learning Ecosystem

Artificial intelligence (AI) will transform the classroom into an interactive ecosystem of guidance and support. The Triadic Learning Ecosystem (TLE) offers an architecture of that near future, connecting teachers, students, and AI-enabled tools in a collaborative model of learning.

The Current State of Play: AI in Higher Education and the Road Ahead

Artificial intelligence is reshaping higher education, exposing weaknesses in assessment, curriculum, and institutional strategy. Ten critical challenges reveal why incremental change will not suffice and why colleges and universities must rethink their strategy, culture, and purpose.

How the University of the Western Cape Layers a Chatbot Into Its Mental Health Support Ecosystem

Artificial intelligence–based counseling apps can address unmet mental health needs and also help those who need in-person support feel more comfortable seeking it.

ACTUAL Intelligence: Practitioner Perspectives on Centering the Human in the Age of AI

As artificial intelligence (AI) reshapes higher education, educators and technologists must rely on ACTUAL intelligence—agency, connection, trust, uniqueness, adaptability, and lifelong learning—to ensure AI enhances, rather than replaces, human judgment, relationships, and learning.

AI Giants Warn It May Be Time to Slow Down

For years, leaders in the artificial intelligence industry have warned that increasingly capable AI systems could eventually become dangerous, all the while continuing to race to build them. Now, their sentiments have changed.

Assessing ChatGPT-generated comments for video-based learning content to enhance knowledge and emotional support based on scaffolding theory

Computers and Education: Artificial Intelligence, Volume 11