🏷️ student-experience

> **Synthesis:** Alsaiari et al. (2026) report a large-scale quasi-experimental cohort study (13,037 students; 51,296 student-authored resources) comparing three AI-mediated feedback workflows. Studen…

2026-08-13 · feedback-loop, formative-assessment, learning-analytics, higher-ed, self-regulated-learning

> **Synthesis:** Ahmed and Sultan (2026) investigated how perceived autonomy, competence, relatedness, expectancy, and value influence autonomy support for AI use, autonomous motivation, and ultimatel…

2026-08-13 · generative-ai, motivation, self-determination-theory, engagement-metrics, higher-ed

> **Synthesis:** Sperber et al. (2025) present the Peer and AI Review + Reflection (PAIRR) model, a human-centered approach to formative assessment that combines peer review best practices with AI rev…

2026-08-13 · ai-feedback-quality, writing-education, formative-assessment, ai-literacy, peer-review

> **Synthesis:** Sirnoorkar & Mamidpalliwar (2026) investigate the association between introductory physics students' preferences for chatbot behavior and their epistemological beliefs, using a custom…

2026-08-13 · physics-education, chatbot, socratic-method, ai-literacy, higher-ed

> **Synthesis:** Wang and Wang (2025) argue for a posthumanist reframing of AI literacy, moving beyond the humanistic view of AI as a discrete "tool" used by autonomous human agents toward understandi…

2026-08-13 · ai-literacy, writing-education, agency-gap, generative-ai, multilingual-writing

> **Synthesis:** Liu, Meng, and Zhang (2026) examined technology acceptance of text-to-image (T2I) generative AI in art and design education from both educators' and students' perspectives, using a mo…

2026-08-13 · generative-ai, creativity, ai-literacy, higher-ed, trust-calibration

> **Peer review** — the practice in which students read, evaluate, and provide feedback on one another's work, most often writing. In writing pedagogy, peer review is a long-standing best practice: st…

2026-08-13 · writing-education, formative-assessment, ai-feedback-quality, collaboration, self-regulated-learning

> **Student engagement** — the degree and quality of a learner's active involvement in the learning process, most often decomposed into behavioral, cognitive, and affective dimensions. In AI-education…

2026-08-13 · motivation, higher-ed, self-regulated-learning, generative-ai, ai-education

> **Synthesis:** This pilot study (N = 22 STEM higher-education students) evaluates AI-generated interactive fiction as an educational medium. Narrative clarity and length acceptance rated positively,…

2026-08-12 · generative-ai, ai-tutoring, engagement-metrics, curriculum-design, higher-ed

> **Synthesis:** The StudentXGenAI Project surveyed more than 7,000 students across 7 UK institutions (September–December 2025) on GenAI use in their studies, comparing findings with a companion Austr…

2026-08-12 · higher-ed, generative-ai, academic-integrity, equity, ethics

> **Synthesis:** This theoretical paper names a state it calls *metacognitively discordant completion* (MDC): a learner submits correct, complete work while holding a first-person awareness that under…

2026-08-12 · metacognition, self-regulated-learning, cognitive-offloading, over-reliance, academic-integrity

> **Creativity** — the capacity to generate novel and valuable ideas, solutions, or artifacts. In the AI era, creativity is a central educational stake: generative AI can both amplify creative work (a…

2026-08-12 · critical-thinking, divergent-thinking, generative-ai, writing-education, constructivist

> **Neurodiversity** — the framing that neurological differences such as autism, ADHD, dyslexia, and dyspraxia are natural variations in human cognition rather than deficits to be corrected. In educat…

2026-08-12 · special-education, accessible-learning, equity, inclusive-design, neurodiversity

> **Student misconceptions about AI** — the inaccurate beliefs students hold about what AI systems are, what they do, and what using them means for learning, especially in academic contexts. Misconcep…

2026-08-12 · ai-literacy, trust-calibration, metacognition, over-reliance, cognitive-offloading

> **Trust calibration** — the metacognitive capacity to align one's confidence in an AI system with its actual reliability in a given context, knowing when to trust and when to question its output. Tr…

2026-08-12 · ai-literacy, over-reliance, trust-calibration, human-ai-collaboration, metacognition

> **Universal Design for Learning (UDL)** — an educational framework that designs instruction to be accessible and effective for the widest range of learners by proactively building in flexible means …

2026-08-12 · accessible-learning, equity, special-education, instructional-design, inclusive-design

> **Synthesis:** Cheng, Chung, Chiu, Lin & Liao (2026) present Spritz, a Discord-based [[llm]] technology probe that mediates disciplinary boundaries in interdisciplinary student project teams, findin…

2026-08-11 · collaborative-learning, project-based-learning, human-ai-collaboration, conversational-agents, llm

> **Synthesis:** This paper proposes the Absent Cognitive Baseline (ACB) as a conceptual framework describing how pervasive generative AI use during secondary schooling may reduce the independent cogn…

2026-08-10 · metacognition, generative-ai, cognitive-offloading, self-regulated-learning, higher-ed

> **Synthesis:** Testa, Apuzzo, and Pittaway (2026) investigate how AI-related competencies contribute to career adaptability in business and management education. Surveying 339 university students in…

2026-08-10 · ai-literacy, career-adaptability, higher-ed, assessment, equity

> **Motivation** — the psychological processes that initiate, direct, and sustain goal-directed behavior. In AI in education, motivation research examines how AI tools affect learners' and teachers' m…

2026-08-10 · motivation, engagement-metrics, affective-computing, self-determination-theory, ai-education

> **Self-Determination Theory (SDT)** — a psychological theory of human motivation positing that intrinsic motivation and well-being depend on satisfying three basic psychological needs: autonomy, com…

2026-08-10 · self-determination-theory, motivation, affective-computing, teacher-ai-competency, ai-education

> **Synthesis:** Misiejuk, López-Pernas, Kaliisa & Saqr (2026) analyze 281 prompts from 122 student submissions across four assignments to examine how prompting strategies reveal cognitive offloading …

2026-08-09 · cognitive-offloading, prompting-literacy, higher-ed, learning-analytics, ai-literacy

> **Active Learning** — instructional approaches that engage students in doing things and thinking about what they are doing, rather than passively receiving information. In AI in education, active le…

2026-08-09 · active-learning, instructional-design, scaffolding, higher-ed, k-12

> **Assessment** is a central concept in AI in education research, connected to 8 articles in this wiki. …

2026-08-09 · ai-education, generative-ai, higher-ed

> **Cognitive offloading** — the use of external tools (including AI) to reduce internal cognitive demand, shifting mental work from the learner to the system. In AI in education, cognitive offloading…

2026-08-09 · cognitive-offloading, cognitive-load-theory, over-reliance, ai-literacy, generative-ai

> **Collaborative Learning** — instructional approaches where students work together to solve problems, complete tasks, or construct knowledge, supported or mediated by AI tools. In AI in education, c…

2026-08-09 · collaborative-learning, cscl, ai-education, scaffolding, equity

> **Design Thinking** — a key concept in AI in education research. Explored across 1 articles in this wiki.…

2026-08-09 · ai-education, generative-ai, higher-ed

> **Edtech Platform** is a central concept in AI in education research, connected to 15 articles in this wiki. …

2026-08-09 · ai-education, generative-ai, higher-ed

> **Efficacy Study** — a key concept in AI in education research. Explored across 6 articles in this wiki.…

2026-08-09 · ai-education, generative-ai, higher-ed

> **Engagement metrics** — the range of observable signals and measurement approaches researchers and systems use to operationalize [[student-engagement|student engagement]] in AI-supported learning: …

2026-08-09 · ai-education, generative-ai, higher-ed, learning-analytics, engagement-metrics

> **AI in Higher Education** — the integration of artificial intelligence into university teaching, learning, assessment, and administration. Higher education is the most-studied context in the wiki, …

2026-08-09 · higher-ed, ai-education, generative-ai, faculty-development, academic-integrity

> **Learning gains** — measurable improvements in student knowledge, skills, or competencies resulting from educational interventions, including AI-assisted instruction. In AI in education research, l…

2026-08-09 · assessment, ai-ed-evaluation, higher-ed, k-12

> **Math Education** — the study of how students learn mathematics and how AI can support mathematics teaching, spanning affective tutoring, cognitive diagnosis from handwritten work, productive strug…

2026-08-09 · math-education, stem-education, ai-tutoring, intelligent-tutoring, k-12

> **Multimodal** — a key concept in AI in education research. Explored across 3 articles in this wiki.…

2026-08-09 · ai-education, generative-ai, higher-ed

> **Over-reliance** — excessive or uncalibrated dependence on AI tools where students delegate cognitive work they should perform themselves, resulting in reduced learning, diminished agency, and the …

2026-08-09 · over-reliance, cognitive-offloading, ai-literacy, trust-calibration, generative-ai

> **Physics Education** — the study of how students learn physics and how to teach it more effectively, spanning Socratic AI tutoring, computational thinking assessment, student trust and AI adoption …

2026-08-09 · physics-education, stem-education, ai-tutoring, generative-ai, higher-ed

> **RCT** — a key concept in AI in education research. Explored across 2 articles in this wiki.…

2026-08-09 · ai-education, generative-ai, higher-ed

> **Socratic Method** — a pedagogical approach rooted in guided questioning and dialogue rather than direct instruction, now being adapted for generative AI tutoring systems. In AI in education, the S…

2026-08-09 · ai-education, generative-ai, higher-ed, scaffolding, intelligent-tutoring

> **Synthesis:** Becker, Bauer, Schrader, Bitzenbauer & Veith (2026) analyze 1,189 survey responses from physics students using qualitative content analysis and latent class analysis, identifying two …

2026-08-08 · physics-education, ai-literacy, higher-ed, stem-education, trust-calibration

> **Synthesis:** Fouad & Bentley (2026) survey 81 introductory physics students and find a striking 50-percentage-point trust-utility gap: 91% use AI for coursework but only 41% trust AI physics expla…

2026-08-08 · physics-education, trust-calibration, ai-literacy, higher-ed, stem-education

> **Synthesis**: Pedagogical agents are AI-driven conversational interfaces embedded in learning environments that use pedagogical strategies (eliciting, telling, scaffolding) to support learner engag…

2026-08-08 · intelligent-tutoring, llm, student-ai-interaction, scaffolding, higher-ed

> **Synthesis:** This paper presents CourseGraph, a methodology for automatically evaluating external course equivalences by modelling course content as structured knowledge graphs. Designed for stude…

2026-08-07 · cs-education, curriculum-design, edtech-platform, higher-ed, administrator

> **Synthesis:** An LLM-based interactive module teaches K-12 students prompting literacy through scenario-based deliberate practice with an AI auto-grader providing immediate, detailed feedback. Depl…

2026-08-06 · ai-literacy, prompting-literacy, k-12, llm, ai-education

> **Synthesis:** Examines AI-powered personalized learning in elementary fraction instruction through a systematic review, quantitative study (N=120), and qualitative teacher interviews. Found that AI…

2026-08-06 · ai-generated-content, personalized-learning, k-12, math-education, adaptive-learning

> **Synthesis:** Work-in-progress exploring LLMs as debugging assistants for physical hardware lab courses. Proposes 'Chat-Debugging' where students interact with an LLM to diagnose circuit faults. Ai…

2026-08-06 · llm, cs-education, higher-ed, scaffolding, stem-education

> **Synthesis:** KnowLoop, a dual-agent conversational system for post-lecture review, structures learning around three stages—Recognize (mark in-situ confusion during lectures), Resolve (Teaching Ass…

2026-08-06 · conversational-agents, personalized-learning, higher-ed, learning-by-teaching, dual-agent

> **Synthesis:** A three-semester, 999-student analysis of hint usage in a K-12 mathematics ITS finds that two simple, interpretable indicators—premature hint requests and superficial hint reading—are…

2026-08-06 · intelligent-tutoring, learning-analytics, hint-systems, k-12, math-education

> **Help-Seeking** — a key concept in AI in education research. Explored across 4 articles in this wiki.…

2026-08-06 · help-seeking, intelligent-tutoring, metacognition, higher-ed, llm

> Robinson, Gormley, Ribeiro & Loeb (2026) ran two RCTs showing that AI tutoring's binding constraint is **take-up, not capability**: despite dedicated session time, nearly half of students never used…

2026-08-03 · intelligent-tutoring, equity, engagement-metrics, k-12, ai-literacy

A randomized experiment (n = 79 medical/nursing students) examining how the **initiative design** of an AI writing agent shapes reasoning, agency, and immediate independent performance. Students compl…

2026-08-03 · generative-ai, ai-literacy, writing-education, higher-ed, agentic-ai

> Gero, Long, Schnitzler & Dhillon (2026, DIS '26) ran a between-subjects essay study (n = 253) showing that **where** AI support enters the writing process determines how much students feel they own …

2026-08-03 · writing-education, ai-generated-content, metacognition, generative-ai, llm

A qualitative study of **16 undergraduates** at a Hong Kong teacher-education university who used **ChatGPT 3.5** to obtain feedback on IELTS writing tasks. Data came from unobtrusive screen-recorded …

2026-08-03 · generative-ai, feedback-loop, higher-ed, ai-literacy, language-learning

A correlational study (N = 67 undergraduate psychology students, Bielefeld University) testing two **protective factors against uncritical GenAI overreliance**: (1) **knowledge about genAI** and (2) t…

2026-08-03 · ai-literacy, higher-ed, over-reliance, educational-theory, ai-literacy-assessment-misalignment

> The null average performance effect masks strong offsetting heterogeneity — and the exam had severe ceiling compression (control mean 89.2/100, 47% ≥ 95), which also limits power. The belief reversa…

2026-08-03 · faculty-development, teacher-role, generative-ai, k-12, cognitive-offloading

The largest study in the AEHE 51(5) special issue: a **cross-sectional survey across four Australian universities** (≈192,000 invited; 10,132 volunteered; this paper analyses **6,960 students** who an…

2026-08-03 · generative-ai, feedback-loop, higher-ed, ai-literacy, engagement-metrics

> **Araz Yusubov, Michael Bechtel, Tangiz Alizada** — arXiv preprint (2026).…

2026-08-03 · edtech-platform, active-learning, engagement-metrics, blended-learning, k-12

> Meyer, Page, Mata et al. (2026) ran two pre-registered RCTs at Georgia State University testing a **non-generative** academic chatbot that texted students 2–3 customized nudges per week in large-enr…

2026-08-03 · higher-ed, generative-ai, engagement-metrics, rct, rag

> **Shixian Zhou, Minghuan Shen, Xiaolin Wen, Zijun Qiu, Yongliang Jiang, Xiangyang Wu, Fei Wu, Yong Wang, Zhiguang Zhou** — arXiv preprint (2026).…

2026-08-03 · learning-analytics, multimodal, engagement-metrics, higher-ed, edtech-platform

> **Shuang Geng, Helen Lallos-Harrell, Jiya Ashar, Thomas J. McKenna, Annwesa Dasgupta, Caleb Farny, Emma Lejeune** — arXiv preprint (2026).…

2026-08-03 · llm, stem-education, higher-ed, teacher-role, scaffolding

> **Agentic AI** — AI systems that autonomously plan, execute, and adapt multi-step workflows to achieve learning goals, going beyond single-turn Q&A to act as persistent, goal-directed collaborators:…

2026-08-01 · agentic-ai, generative-ai, llm, intelligent-tutoring, higher-ed

> **AI tutoring** — the use of AI (especially [[llm|LLMs]] and [[intelligent-tutoring|intelligent tutoring systems]]) to provide personalized, adaptive, scalable instructional support: conversational …

2026-08-01 · intelligent-tutoring, generative-ai, llm, scaffolding, feedback-loop

Studies student perceptions of AI-generated instructional videos in computing education. Finds students value personalization and rapid production but express concerns about accuracy and the loss of i…

2026-07-31 · generative-ai, stem-education, higher-ed

Examines the integration of deep generative models into architectural design education. The findings, based on students' views and observations in design studios, suggest that GenAI supports the explo…

2026-07-31 · generative-ai, higher-ed, active-learning

Examines how different forms of learner-AI interaction relate to learning outcomes in object-oriented programming courses. Identifies distinct patterns of GenAI use among students and correlates them …

2026-07-31 · generative-ai, stem-education, higher-ed, learning-analytics, ai-education

Pre-registered study auditing whether general-purpose helpfulness rubrics can distinguish direct answer-giving from pedagogical guidance in LLM tutors. Uses deterministic detectors for answer leakage …

2026-07-31 · llm, intelligent-tutoring, automated-grading, benchmark, feedback-loop

Presents Memdora, a cross-platform AI spaced repetition system that addresses limitations of binary flip-and-rate flashcard interactions. Grounded in cognitive science evidence on retrieval practice, …

2026-07-31 · generative-ai, adaptive-learning, mastery-learning

Argues that as AI systems become capable of producing the artifacts through which institutions recognize competence, existing ethical frameworks centered on AI failures become insufficient. Develops t…

2026-07-31 · generative-ai, educational-theory, over-reliance, ai-literacy

Randomized A/B crossover study (N=220) in a junior-level algorithms course comparing solution evaluation/critique tasks against traditional solution generation. Finds that evaluation-centered tasks pr…

2026-07-31 · generative-ai, stem-education, higher-ed, efficacy-study

Survey of 206 engineering students: AI chatbots provide greatest perceived benefit as relief from competence frustration, smaller benefits for autonomy, weakest for relatedness. Baseline motivational …

2026-07-30 · higher-ed, stem-education, affective-computing, personalized-learning, scaffolding

LLMs systematically underestimate the difficulty of misconception-driven items ('The Easy Trap'). While LLM ratings show moderate rank correlation with empirical student difficulty (rho=0.52-0.70), th…

2026-07-30 · llm, formative-assessment, adaptive-learning, feedback-loop, stem-education

Proposes Cognitive Diagnostic Profiling (CDP), a zero-shot framework that dramatically improves LLM-simulated examinee alignment with human test-takers. With CDP, IRT difficulty Spearman correlations …

2026-07-30 · llm, formative-assessment, adaptive-learning, benchmark, higher-ed

On 119,034 students across 13 UK national exams, Bernoulli Mixture Models found few distinct skill clusters — overall ability dominates. A simple explainable model achieved 78% accuracy, competitive w…

2026-07-30 · personalized-learning, stem-education, learning-analytics, adaptive-learning, k-12

Describes rapid development of a Thonny log visualizer using AI-assisted 'vibe coding' to make student programming processes visible to teachers. Piloted in a 160-student introductory programming cour…

2026-07-30 · stem-education, higher-ed, teacher-role, learning-analytics, academic-integrity

> **AICoFE** (AI-based Collaborative Feedback) is a multi-LLM feedback generation system for higher education that combines independently fine-tuned language models with **teacher-in-the-loop mediatio…

2026-07-29 · ai-ed-evaluation, feedback-loop, human-in-the-loop-ai, higher-ed, learning-analytics

> **Critical AI Tutors: Empower or Enslave?** — A position paper presented at the AIED 2025 workshop that issues a stark warning: unchecked use of AI tutors risks creating a generation of cognitively …

2026-07-29 · intelligent-tutoring, critical-thinking, over-reliance, ai-assistance-reduces-persistence, regulation

A **randomized 2×2 full-factorial field experiment** (N = 179 German university students, 22 days of app use, 12-week follow-up) testing two design principles for a **mobile chatbot-based learning jou…

2026-07-29 · self-regulated-learning, generative-ai, higher-ed, engagement-metrics, efficacy-study

> **Affective computing** in education uses physiological and behavioral signals to sense learner emotion and adapt instruction — see [[affective-text-wearable-student-health]], [[multimodal-affective…

2026-07-28 · higher-ed, llm, generative-ai, learning-analytics, k-12

> **Prompt engineering** — the practice of designing and refining inputs to large language models to achieve desired outputs. In education, prompt engineering serves dual roles: as a learner skill (st…

2026-07-28 · ai-literacy, higher-ed, generative-ai, scaffolding, llm

This experience report introduces trio-ethnography — structured dialogue between two computing educators with differing teaching philosophies and one undergraduate CS student — as a method for surfaci…

2026-07-27 · generative-ai, stem-education, teacher-role, higher-ed, scaffolding

This large-scale observational study tests the "GenAI substitution hypothesis" — the concern that students offload cognitive effort to [[generative-ai]] and earn inflated grades without learning. Usin…

2026-07-24 · generative-ai, higher-ed, efficacy-study, learning-gains, llm

A scenario-based survey (Fall 2024) comparing how computing students at Canadian and South Korean universities judged the ethicality and policy compliance of AI-assisted coding practices. Despite func…

2026-07-23 · generative-ai, higher-ed, cs-education, policy-maker

A quasi-experimental, short-term longitudinal study with 126 first-year engineering students comparing two ways of teaching students how to learn with generative AI: an experiential, hands-on session …

2026-07-23 · generative-ai, higher-ed, efficacy-study, scaffolding, self-regulated-learning

Tabletop exercises (TTXs) let learner teams rehearse high-stakes workplace tasks such as cybersecurity incident response, but their open-ended, collaborative nature makes [[formative-assessment]] diff…

2026-07-22 · formative-assessment, feedback-loop, learning-analytics, stem-education, higher-ed

This survey of design students at the Politecnico di Milano (2025/2026), paired with AI-use journals kept during research assignments, examines how [[generative-ai]] enters the design process. Reporte…

2026-07-22 · generative-ai, higher-ed, ai-literacy, academic-integrity, writing-education

As LLMs take over task execution, a central worry is that everyday AI use becomes cognitive offloading that erodes people's own capability development. This study analyses 128,569 naturalistic human-L…

2026-07-22 · llm, generative-ai, ai-literacy, over-reliance, self-regulated-learning

This short paper provides rare descriptive classroom evidence on what happens when students repeatedly use generative-AI feedback across a full semester of writing coursework. Drawing on 2,988 reflect…

2026-07-20 · generative-ai, llm, higher-ed, writing-education, feedback-loop

This quasi-experimental study directly compares **AI-generated feedback** (two LLMs: **GPT-o4-mini** and **DeepSeek R1**) with **expert human-teacher feedback** in a project-based university course (A…

2026-07-19 · generative-ai, feedback-loop, higher-ed, learning-gains, formative-assessment

This landmark field experiment is among the first randomized controlled trials to causally demonstrate that **unguarded generative-AI tutoring can harm skill acquisition**, not merely fail to help. Co…

2026-07-19 · generative-ai, over-reliance, stem-education, k-12, rct

As generative AI (GenAI) becomes embedded in undergraduate academic writing, *how* students rely on these tools — not merely whether they use them — has emerged as a core question for [[academic-integ…

2026-07-17 · generative-ai, academic-integrity, higher-ed, writing-education, over-reliance

Analyzes how students specify intended behavior in natural language to AI code tools (Copilot) across multiple years, deriving a taxonomy of code-generation specifications expressed through comments. …

2026-07-14 · llm, stem-education, higher-ed, reshaping-cs-education-genai, ai-literacy

Investigates why AI-for-education shows inconsistent average effects, arguing that learning behavior explains background-related advantage: students from advantaged backgrounds engage with AI tools in…

2026-07-14 · generative-ai, learning-gains, personalized-learning, equity, rag

A systematic API audit of four LLMs acting as history tutors evaluates 1,800 responses about the 1989 Romanian Revolution, exposing a 'paternalistic filter': models differentially refuse or soften ans…

2026-07-14 · llm, equity, higher-ed, bias-mitigation

This study investigates how students conceptualize generative AI (GenAI) and how those mental models shape their academic integration. A student's mental model of GenAI — their beliefs about what it c…

2026-07-14 · ai-literacy, generative-ai, metacognition, higher-ed, human-ai-collaboration

> **Bias mitigation** in educational AI requires auditing models across the pipeline: [[gender-bias-transfer-llm-writing]], [[ai-scoring-language-bias-physics]], [[llm-cultural-relevance-k12]], and [[…

2026-07-14 · bias-mitigation, equity, ethics, higher-ed, ai-literacy

Presents a large-scale descriptive analysis of an AI learning assistant (Syntea) using objective log data from 77,543 higher-education students, characterizing real usage patterns, adoption, and engag…

2026-07-10 · llm, higher-ed, learning-analytics, personalized-learning, self-regulated-learning

Introduces a Bloom-aligned framework for measuring 'educational control' in LLMs: the ability to preserve a task's instructional intent while shifting its cognitive demand toward higher-order Bloom le…

2026-07-10 · llm, generative-ai, scaffolding, higher-ed, feedback-loop

Uses epistemic network analysis of multimodal YouTube metadata (transcripts, titles, thumbnails, comments) to show how different creator groups frame ChatGPT use in education, revealing divergent narr…

2026-07-10 · ai-literacy, academic-integrity, higher-ed, generative-ai, self-regulated-learning

The widespread availability of general-purpose AI that can perform complex cognitive tasks threatens to undermine education at scale. This effortless bypass dilemma sharpens a challenge AIED has long …

2026-07-09 · over-reliance, self-regulated-learning, metacognition, teacher-role, formative-assessment

Building upon found examples is a popular way people learn to code, especially in creative coding communities where sharing projects and remixing are common practices. But effectively doing so require…

2026-07-09 · scaffolding, generative-ai, feedback-loop, active-learning, programming-its

Debugging exercises are usually graded from final code and test outcomes, which hide *how* students reproduced failures, formed hypotheses, inspected evidence, edited code, and verified fixes. The aut…

2026-07-08 · programming-its, learning-analytics, formative-assessment, cs-education, higher-ed

Nearly all prior research on LLMs in computing education has used text input, yet voice-enabled interfaces are becoming common. This exploratory study investigated how introductory programming student…

2026-07-08 · ai-literacy, cs-education, generative-ai, llm, programming-its

As generative AI becomes central to software development, CS education is shifting toward prompt-centered workflows where students describe intended behavior in natural language to elicit code. But pr…

2026-07-07 · generative-ai, cs-education, over-reliance, metacognition, higher-ed

Learning to communicate with code-generating AI is an emerging skill for novice programmers. 'Prompt Problems' — having students solve computational tasks by writing natural-language prompts for code-…

2026-07-07 · ai-literacy, cs-education, generative-ai, higher-ed, programming-its

**Tomohiro Nagashima, Lisa Siegrist, Niklas Scholz, Shintaro Sato, Martina Vincoli, Man Su (2026)** As AI technologies enter [[k-12]] classrooms, understanding how different stakeholders perceive thes…

2026-07-03 · k-12, teacher-role, ai-literacy, student-ai-interaction, automated-grading

> **Margaret Ellis, Nikitha Donekal Chandrashekar, Sehrish Basir Nizamani, Mohammed Farghally, Jake O'Brien, Naren Ramakrishnan** — SIGCSE Virtual 2026, submitted 29 Jun 2026…

2026-07-02 · llm, higher-ed, academic-integrity, stem-education, llm-in-education

> **Zekun Wu, Man Su, Huiyong Li, Tomohiro Nagashima, Anna Maria Feit** — submitted 1 Jul 2026…

2026-07-02 · generative-ai, k-12, affective-computing, adaptive-learning, llm-in-education

> **Sehrish Basir Nizamani, Zannah Ziew, Saad Nizamani, Khyati Goyal** — ACM SIGCSE Virtual 2026, submitted 29 Jun 2026…

2026-07-02 · llm, collaborative-learning, higher-ed, engagement-metrics, llm-in-education

> **Mohammad Abu Nasir Rakib, Sharmin Akter, Eshwara Prasad Sridhar, Somik Biswas, Md Rassel Raihan, Mahmudur Rahman** — submitted 1 Jul 2026…

2026-07-02 · stem-education, higher-ed, personalized-learning, active-learning, blended-learning

**Tran, Harper & Price (2026)** examine a pressing motivational paradox in contemporary computing education: the ready availability of AI tools that can complete programming assignments undermines stu…

2026-06-30 · academic-integrity, higher-ed, llm, over-reliance, ai-assistance-reduces-persistence

Karidi, Amir & Roll (2026) present one of the largest empirical analyses to date of authentic (rather than lab-based) interactions between college students and generative AI tools. By analyzing intera…

2026-06-30 · generative-ai, higher-ed, learning-analytics, llm, ai-literacy

Hutchison et al. (2026) develop and validate a method for measuring critical engagement with AI code completion tools in educational settings. Using behavioral signals (time-to-accept, edit distance f…

2026-06-30 · formative-assessment, higher-ed, llm, stem-education

Siyan et al. (2026) conduct a carefully controlled experiment isolating the effect of empathetic language in LLM-powered physical activity coaching chatbots over a longitudinal deployment. While the e…

2026-06-30 · affective-computing, feedback-loop, llm, personalized-learning, affective-tutoring

Abdelghani, Kaiser & Murayama (2026) trace how middle and high school students' interactions with AI math tutors evolve over time, identifying a trajectory from superficial prompting ('tell me the ans…

2026-06-30 · ai-literacy, k-12, metacognition, stem-education, self-regulated-learning

Bernstein, Denny, Leinonen et al. (2026) investigate whether providing students with multiple, diverse LLM-generated explanations of code (rather than a single 'best' explanation) improves comprehensi…

2026-06-30 · feedback-loop, higher-ed, llm, scaffolding, stem-education

Hossain (2026) develops a typology of LLM reliance among undergraduate writers at a minority-serving R1 institution, identifying four distinct profiles: strategic scaffolders who use AI for idea gener…

2026-06-30 · ai-literacy, higher-ed, over-reliance, writing-education, llm

DysLexLens is a low-resource LLM framework designed to analyze how [[special-education|dyslexic learners]] experience AI tools by mining online forum discussions. The framework employs dictionary-driv…

2026-06-29 · special-education, llm, ai-literacy, equity, language-learning

📄 [PDF](https://arxiv.org/pdf/2606.26579) This study investigates how different modes of AI interaction affect cognitive engagement and learning outcomes in high school students. Using a within-subje…

2026-06-26 · k-12, llm, generative-ai, engagement-metrics, affective-computing

📄 [PDF](https://arxiv.org/pdf/2606.26565) This case study reports on a community-based participatory research project that co-designed an [[ai-literacy|AI literacy]] program for 54 adults (48 in-pers…

2026-06-26 · ai-literacy, lifelong-learning, equity, edtech-platform, faculty-development

This large-scale survey of humanities and social sciences (HSS) students in China examines how [[generative-ai]] reshapes academic development across four dimensions: usage patterns, effects on learni…

2026-06-24 · generative-ai, higher-ed, llm, ai-literacy, personalized-learning

Scheinberg et al. (2026) analyze 78 university learners of German across four sites completing a counterbalanced spot-the-difference task with both a human peer and a real-time AI partner. Using diari…

2026-06-23 · language-learning, llm, intelligent-tutoring, personalized-learning

Castillo Ventura et al. (2026) address the gap between instructional design of digital mathematics resources and their pedagogical use in classrooms. Their work-in-progress framework translates learni…

2026-06-23 · teacher-role, k-12, stem-education, scaffolding, ai-literacy

Borchers (2026) reports on a 90-minute participatory design workshop with 12 U.S. middle school mathematics teachers using i-Ready Math weekly. Thematic analysis identified four recurring dimensions o…

2026-06-23 · k-12, teacher-role, engagement-metrics, adaptive-learning

Graf et al. (2026) identify a new challenge in collaborative programming education: AI use is now an invisible yet consequential dimension of collaboration, and partners often misread ability and effo…

2026-06-23 · cs-education, collaborative-ai-tutoring, over-reliance, higher-ed, ai-tutoring

> **Knowledge tracing** — modeling what learners know over time by tracking their performance on exercises and predicting future mastery. It is the wiki's richest modeling thread, spanning Bayesian, d…

2026-06-23 · knowledge-tracing, learning-analytics, intelligent-tutoring, adaptive-learning, student-modeling

> **Naaz Sibia, Jessica Wen, Amber Richardson, Yashika Jain, Khushi Malik, Bogdan Simion, Carolina Nobre, Angela Zavaleta Bernuy, Andrew Petersen, Michael Liut** (2026). ICER 2026…

2026-06-19 · cs-education, scaffolding, active-learning, feedback-loop, multi-representational-tools

> **Po-Chin Chang, Nicholas Hogan, Aske Plaat, Michiel T. van der Meer** (2026). arXiv cs.AI preprint…

2026-06-19 · intelligent-tutoring, llm, k-12, personalized-learning, scaffolding

Computing students show inconsistencies between confidence in cybersecurity knowledge and actual safe practices; educational interventions are needed to close the gap. Confident yet Concerned: Inconsi…

2026-06-18 · higher-ed, ai-literacy, academic-integrity, engagement-metrics

> Engagement intensity during AI ethics instruction serves as an effective learner-modeling signal for adaptive instruction; prior LLM experience influences engagement patterns.…

2026-06-18 · personalized-learning, adaptive-learning, ai-literacy, higher-ed, engagement-metrics

Revisits WordStream (2009) as a quantitative encoding for qualitative learning analytics; demonstrates how structured coding can surface cohort-level trends while preserving individual narrative conte…

2026-06-18 · learning-analytics, k-12, higher-ed, qualitative-research, edtech-platform

> **Ariyan Hossain, Kazi Kamruzzaman Rabbi, Farig Sadeque, S M Taiabul Haque** (2026). arXiv cs.CL…

2026-06-17 · llm, generative-ai, bias-mitigation, writing-education, higher-ed

> **Alexandra Neagu, Jeffrey T. H. Wong, Marcus Messer, Rhodri Nelson, Peter B. Johnson** (2026). Pluralistic Alignment Workshop @ ICML 2026…

2026-06-17 · scaffolding, intelligent-tutoring, llm, benchmark, efficacy-study

> **Xinfei Cen, Vincent Aleven, Kenneth R. Koedinger, Conrad Borchers, Paulo F. Carvalho** (2026). EC-TEL 2026…

2026-06-17 · intelligent-tutoring, personalized-learning, efficacy-study, higher-ed, self-regulated-learning

> **Farnaz Baksh, Matevz B. Zorec, Feiazie Baksh, Karl Kruusamae** (2026). ICSR + ART 2026, London…

2026-06-17 · k-12, higher-ed, intelligent-tutoring, stem-education, human-ai-collaboration

Based on a questionnaire of 100 higher-education engineering students and a critical literature review, examines how students use and perceive LLMs. Students value LLMs for writing support, conceptual…

2026-06-16 · higher-ed, llm, stem-education, teacher-role, ai-literacy

Argues that epistemic vigilance — the human evaluation of AI output calibrated to how far a fallible source can be trusted — is the binding constraint on productive augmentation. AI's fluent, confiden…

2026-06-16 · personalized-learning, scaffolding, k-12, higher-ed, hallucination-risk

Evaluates cross-dataset generalization of ML/DL methods and LLMs for automatic Bloom's taxonomy classification of assessment questions across five datasets. Supervised ML/DL models degraded substantia…

2026-06-16 · automated-grading, llm, formative-assessment, higher-ed, teacher-role

Team-based projects are a cornerstone of engineering and computing courses, but unstructured team formation often leads to poor project outcomes due to misaligned student interests and inadequate skil…

2026-06-16 · intelligent-tutoring, edtech-platform, higher-ed, stem-education, personalized-learning

> Argues the dominant paradigm of runtime GenUI adaptation in EdTech is insufficient. Proposes design-time card-based GenUI where educational content is encoded as modality-agnostic semantic units and…

2026-06-16 · personalized-learning, adaptive-learning, edtech-platform, equity, learning-analytics

> Examines gender differences in AI literacy, safety awareness, and STEM career aspirations among Australian secondary students (Years 7, 8, 10; N=199) from two co-educational government schools after…

2026-06-16 · ai-literacy, k-12, stem-education, equity, learning-analytics

> Asks what is gained and lost when 'collaboration' is applied freely to human-AI interaction. Argues true collaboration requires symmetric/negotiated relationship, shared goals, low and shifting divi…

2026-06-16 · intelligent-tutoring, scaffolding, active-learning, teacher-role, learning-analytics

Standardized examinations are typically treated as uniform syllabus coverage problems. LearnOpt recovers stable latent cognitive structures diverging systematically from official syllabi, using LLM-ta…

2026-06-16 · learning-analytics, llm, k-12, personalized-learning, assessment

Investigates LLM chatbots' performance on 70 MCQs for a university CS lecture on interactive visual data analysis, comparing with student performance. GPT-4o and GPT-5 significantly outperformed small…

2026-06-16 · higher-ed, llm, automated-grading, stem-education, learning-analytics

Studies whether public LLM tutoring benchmarks distinguish learning-supportive behavior from mere answer production. Proposes a lightweight diagnostic based on the gap between solving-oriented and ped…

2026-06-16 · intelligent-tutoring, llm, feedback-loop, scaffolding, benchmark

> Investigates ML models to predict exam outcomes from physiological data (electrodermal activity, heart rate, skin temperature) collected during exams. Evaluates logistic regression, random forest, S…

2026-06-16 · learning-analytics, edtech-platform, higher-ed, engagement-metrics, rag

> An interview study with 19 computing students through a functionalist perspective of shame and guilt. Findings show these emotions regulate when and how students make their AI use visible, engaging …

2026-06-16 · higher-ed, academic-integrity, over-reliance, hallucination-risk, learning-analytics

This paper investigates whether [[llm|large language models]] can serve as scalable proxies for students by simulating realistic logical errors in code submissions. Using the CodeWorkout dataset of 74…

2026-06-15 · llm, stem-education, intelligent-tutoring, learning-analytics, efficacy-study

**Ravi, Stevens, Hurt, Hanks, Lin & Anderson (2026)**. Ravi et al. investigate how the voice accent of a [[generative-ai]] conversational peer agent shapes learners' perceptions, trust, and interactio…

2026-06-12 · equity, generative-ai, human-in-the-loop, k-12, llm

As [[generative-ai]] disrupts [[higher-ed]], institutions increasingly require students to declare AI use. However, generic binary declarations (e.g., "I used GenAI") fail to capture the nuanced appli…

2026-06-12 · generative-ai, higher-ed, academic-integrity, policy-maker, ai-literacy

Bischof et al. investigate how students' awareness of [[generative-ai]] regulations relates to their perceived compliance and actual usage behavior in [[higher-ed]]. While previous research mainly exa…

2026-06-12 · generative-ai, higher-ed, policy-maker, regulation, academic-integrity

> **Shravika Mittal, Su Lin Blodgett, Q. Vera Liao**…

2026-06-11 · generative-ai, llm, over-reliance, metacognition, higher-ed

**Angela Chen, Siwei Jin, Catherine Bao, Canwen Wang, Robert E. Kraut, Tongshuang Wu, Haiyi Zhu** — cs.CY, cs.HC The Adaptive Virtual Patient (AVP) is an LLM-driven simulated patient for psychotherapy…

2026-06-10 · professional-training, llm, generative-ai, intelligent-tutoring, higher-ed

**Misan Paul Etchie, Taiwo Olutosin** — cs.CY, cs.AI, cs.HC This paper proposes an AI-integrated LMS designed specifically for middle school instruction, addressing the gap between current LMS platfor…

2026-06-10 · k-12, adaptive-learning, personalized-learning, formative-assessment, intelligent-tutoring

**Yuchen Liu, Roberto Martinez-Maldonado, Riordan Alfredo, Paola Mejia-Domenzain, Dwi Rahayu, Sadia Nawaz** — AIED 2026 — cs.HC, cs.AI This paper presents an AI-based speech processing approach to ana…

2026-06-10 · active-learning, ai-education, higher-ed, learning-analytics, teacher-role

**Oleksandra Poquet, Mani Shankar Nanduri, Maria Ximena Salinas Loyer, Matthias Stadler, Michael Sailer, Jelena Jovanovic** — Accepted at EC-TEL 2026 — cs.HC, cs.ET This study compares two approaches …

2026-06-10 · writing-education, llm, higher-ed, ai-literacy, generative-ai

**Jiayi Zhang, Ryan S. Baker, Debshila Basu Mallick, Cristina Heffernan, Neil Heffernan** — cs.HC This paper replicates and extends prior work on the cold-start problem in knowledge tracing — the chal…

2026-06-10 · knowledge-tracing, learning-analytics, student-modeling, benchmark, higher-ed

**Jingzhe Lin, Hengbin Yu, Yongdan Zeng, Fangwei Zhong** — ICML 2026 — cs.MA, cs.CY EduMirror introduces a multi-agent simulator for studying educational social dynamics, addressing the dilemma that o…

2026-06-10 · intelligent-tutoring, llm, higher-ed, scaffolding, generative-ai

**Yifan Liu, Jaime Arguello, Orland Hoeber, Chang Liu et al.** — cs.IR, cs.AI, cs.HC This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS), which examined how Ge…

2026-06-10 · generative-ai, llm, ai-literacy, policy-maker, higher-ed

**Hartwig Grabowski, Michael Canz** — cs.AI, cs.CV, cs.CY This paper identifies the didactic narrowing caused by fully digital e-assessment (overuse of closed question formats) and proposes a hybrid a…

2026-06-10 · automated-grading, assessment, higher-ed, generative-ai, formative-assessment

This paper introduces a pipeline that maps student questions directed at a conversational AI teaching assistant to curriculum topics using a few-shot text classifier, grounded in a GPT-4-extracted pre…

2026-06-10 · knowledge-tracing, llm, student-modeling, higher-ed, learning-analytics

> This paper develops a VR-based immersive learning environment using Photon Fusion that allows teachers and students to be present in the same virtual space regardless of physical locations. The syst…

2026-06-10 · edtech-platform, active-learning, higher-ed, engagement-metrics, generative-ai

**Yi-Chieh Lee, Nattapat Boonprakong, Yugin Tan, Harold Soh et al.** — Workshop report from NUS-Google Workshops — cs.CY This white paper synthesizes findings from two international NUS-Google Worksho…

2026-06-10 · cs-education, generative-ai, curriculum-design, higher-ed, llm

**Yibo Meng, Ruiqi Chen, Zhiming Liu, Xiaolan Ding** — Accepted at MobileHCI 2026 — cs.HC TibetCPR is a low-cost, self-guided CPR training system that pairs depth-driven electrotactile feedback with r…

2026-06-10 · professional-training, llm, formative-assessment, edtech-platform, higher-ed

Reports on cross-boundary Community-Based Learning where undergraduate students develop AI-enabled solutions for cultural heritage preservation and sustainable development. The paper argues that AIED …

2026-06-09 · higher-ed, ai-literacy, equity, teacher-role, intelligent-tutoring

Examines how 98 Grade-9 students across three German Gymnasium schools regulated their use of a Mistral-Large GenAI tutor while preparing for a math exam. Despite overwhelmingly selecting scaffolded s…

2026-06-09 · llm, k-12, self-regulated-learning, metacognition, scaffolding

> **Synthesis:** Recent work in Technology-Enhanced Learning and HumanComputer Interaction highlights the importance of transparency and trust calibration in AI-supported learning environments as they…

2026-06-03 · intelligent-tutoring, hallucination-risk, trust-calibration, llm, help-seeking

Proposes a five-stage developmental continuum (Not Engaged, Uncritical Use, Informed Use, Critical Evaluation, Improvement) for AI literacy at NC State; the continuum doubles as a diagnostic tool for …

2026-06-03 · ai-literacy, higher-ed, curriculum-design, ethics, instructional-design

> **Synthesis:** Conversational AI as a catalyst for informal learning: An empirical large-scale study on LLM use in everyday learning…

2026-06-03 · generative-ai, informal-learning, llm, lifelong-learning

> **Synthesis:** Human-AI collaboration in higher education: Exploring the impact of technology expectations and distrust…

2026-06-03 · human-in-the-loop, generative-ai, higher-ed

> **Authors:** Junsoo Park, Youssef Medhat, Htet Phyo Wai, Ploy Thajchayapong, Ashok K. Goel (2026) — Georgia Tech…

2026-06-01 · learning-analytics, teacher-role, higher-ed, feedback-loop, ai-literacy

Artificial intelligence assistants deployed in online learning environments create new opportunities to collect large volumes of learner interaction data and generate insights to improve student outco…

2026-05-29 · learning-analytics, edtech-platform, personalized-learning, higher-ed, feedback-loop

A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor model evaluation and …

2026-05-29 · intelligent-tutoring, llm, learning-analytics, personalized-learning, reinforcement-learning

The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large language models (LLMs) might have access to sources …

2026-05-29 · llm, intelligent-tutoring, scaffolding, teacher-role, over-reliance

Generative AI challenges academic integrity not only by enabling students to delegate substantial portions of their academic work, but also by blurring the ethical boundaries by which students disting…

2026-05-29 · academic-integrity, llm, higher-ed, writing-education, ai-literacy

Technologies and methods for detecting AI-generated content in academic submissions, including classifier-based approaches, watermarking, and stylistic analysis. The effectiveness and reliability of t…

2026-05-29 · academic-integrity, ai-detection, higher-ed, generative-ai, ai-literacy

**LLM-Assisted Sentiment Analysis for Mixed-Methods Education Research** demonstrates how LLMs can serve as scalable qualitative research assistants, enabling researchers to investigate multiple demog…

2026-05-28 · llm, edtech-platform, higher-ed, learning-analytics, formative-assessment

This paper argues that [[generative-ai]] systems in [[higher-ed]] are not epistemically neutral — they actively marginalize non-hegemonic ways of knowing. Drawing on educational sciences, critical tec…

2026-05-27 · generative-ai, higher-ed, special-education, equity, bias-mitigation

This is the first empirical study of what happens when AI agents are embedded **persistently** in a real academic research environment — with durable memory, local files, external tools, scheduled rou…

2026-05-27 · llm, generative-ai, higher-ed, agentic-ai, faculty-development

SlidesQAQA is a Flask-based system that extracts text and rendered images from PDF lecture slides and processes them through a four-stage [[llm]] pipeline: **window planning** (segment extraction), **…

2026-05-27 · prompt-engineering, generative-ai, llm, higher-ed, scaffolding

This paper presents a fine-grained taxonomy categorizing novice programmers' difficulties with reading and understanding control flow constructs — specifically conditionals (selection) and loops (iter…

2026-05-27 · cs-education, stem-education, higher-ed, benchmark, llm

This multicenter study (N=243 European secondary students) systematically challenges the 'Digital Native' paradigm by demonstrating a severe confidence-competence gap in digital and AI literacy. Stude…

2026-05-26 · k-12, ai-literacy, equity, efficacy-study, genai-minoritized-knowledges-disability

This comparative user study (n=48) examines how the temporal and visual dimensions of AI collaboration shape the experience of [[writing-education|writing tasks]], revealing that humanlike design feat…

2026-05-26 · generative-ai, writing-education, llm, higher-ed

This preregistered between-subjects study (N=559) provides the first rigorous evidence that [[llm]] reasoning traces — increasingly common in AI interfaces — do not improve performance and can activel…

2026-05-26 · llm, metacognition, efficacy-study, over-reliance, self-regulated-learning

This grounded theory study analyzed open-ended responses from 1,054 university students across three Philippine universities to define **AI fatigue** as a distinct construct — separate from technostre…

2026-05-25 · over-reliance, ai-literacy, higher-ed, affective-computing, self-regulated-learning

This preregistered large-scale study (N = 1,237) investigates whether people are well-calibrated in estimating the time savings from AI assistance on simple cognitive tasks. The key finding is a **spe…

2026-05-25 · over-reliance, metacognition, efficacy-study, cognitive-offloading, ai-assistance-reduces-persistence

This study surveyed 24 neurodivergent computing students (autistic and/or ADHD) and 20 neurotypical peers, supplemented by 4 in-depth interviews, to understand how collaborative active learning struct…

2026-05-25 · cs-education, special-education, equity, collaborative-learning, equity-in-ai-education

This study embedded undisclosed AI agents as teammates in synchronous text-based group interactions across analytical, creative, and ethical tasks with 786 participants making 1,572 identity judgments…

2026-05-25 · ai-literacy, over-reliance, llm, affective-computing, rag

Across three pre-registered studies (N=2,691), this paper documents systematic miscalibration in how people perceive their own [[generative-ai|AI]] usage. The authors find that people not only use AI …

2026-05-23 · generative-ai, over-reliance, ai-literacy, ai-assistance-reduces-persistence, rag

This landmark study provides the **first large-scale behavioral and outcome evidence** that [[generative-ai]] has fundamentally altered how students study and what they retain. Using a ten-year panel …

2026-05-23 · generative-ai, over-reliance, stem-education, k-12, higher-ed

**Annie Yuan (2026)**. arXiv preprint (cs.HC). Current AI-driven educational systems primarily rely on behavioural analytics and performance metrics, lacking the ability to model expert cognition used…

2026-05-22 · learning-analytics, intelligent-tutoring, adaptive-learning, teacher-role, ai-literacy

Intelligent Tutoring Systems often grant learners shared control over skill and problem selection. We propose a simulation-based framework to examine how learner task-selection strategies and system c…

2026-05-22 · intelligent-tutoring, mastery-learning, adaptive-learning, engagement-metrics, simulation

📄 [Full article](https://edtechinsiders.substack.com/p/how-ai-is-changing-teaching-workflows) AI saves teachers roughly 30% of lesson preparation time with no measurable quality loss — but whether th…

2026-05-21 · generative-ai, teacher-role, faculty-development, efficacy-study, rct

Benedetti (2026) introduces a theoretically grounded framework for AI-enabled pedagogical accompaniment that explicitly centers human agency — an approach described as "human-in-command" rather than m…

2026-05-21 · intelligent-tutoring, scaffolding, human-in-the-loop, pedagogical-safety, ai-literacy

Oral code reviews paired with a flipped classroom represent a pragmatic harm-reduction approach to generative AI in CS education. Rather than banning LLMs, Fowles et al. (2026) designed weekly formati…

2026-05-21 · generative-ai, higher-ed, cs-education, over-reliance, academic-integrity

Kapsalis (2026) presents one of the first empirical studies of generative AI integration in architectural design education, using a locally executed, discipline-specific tool within a mixed-methods fo…

2026-05-21 · generative-ai, higher-ed, creative-thinking, ai-literacy, personalized-learning

Yang et al. (2026) tackle a fundamental tension in AI-augmented classrooms: how to balance teacher orchestration with student agency during dynamic transitions between individual and collaborative wor…

2026-05-21 · intelligent-tutoring, teacher-role, k-12, human-in-the-loop, collaborative-learning

📄 DOI: 10.1016/j.caeai.2022.100074 This paper introduces **XAI-ED**, a framework for explainable AI that is purpose-built for education. It argues that while XAI in education shares common ground wit…

2026-05-21 · intelligent-tutoring, learning-analytics, bias-mitigation, equity, privacy

This paper presents a striking longitudinal finding: as AI becomes a routine educational tool, students systematically revalue **human intelligence (HI) over artificial intelligence (AI)**. Drawing on…

2026-05-20 · ai-literacy, higher-ed, stem-education, over-reliance, efficacy-study

LLM sycophancy creates a feedback loop where user errors propagate into AI advice, degrading outcomes; AI literacy training reduces but doesn't eliminate this contextual sycophantic dependence. This A…

2026-05-19 · llm, generative-ai, ai-literacy, hallucination-risk, bias-mitigation

Socratic questioning, reflection prompts, misconception checks, and mandatory pauses produce better K-12 engagement than directive answer-giving AI tutors. SocratiCode demonstrates a participatory des…

2026-05-19 · intelligent-tutoring, llm, generative-ai, k-12, scaffolding

In a year-long study of 458 university students (3,610 person-waves) using Oura rings for passive physiological sensing, researchers examined whether **ultra-brief affective text prompts** (median 3-w…

2026-05-17 · affective-computing, higher-ed, learning-analytics, affective-tutoring, llm

This dissertation presents an integrated AI framework for campus well-being spanning prevention (improving feedback collection) and intervention (advancing mental health detection). It represents an i…

2026-05-16 · higher-ed, llm, generative-ai, affective-computing, edtech-platform

This paper presents a systematic two-stage methodology for surfacing student misconceptions at scale. Drawing on 3,802 medical student enrollments across 5 biomedical science courses (9 course periods…

2026-05-16 · llm, generative-ai, formative-assessment, higher-ed, learning-analytics

This paper exposes a critical failure mode in using LLMs as simulated students for [[intelligent-tutoring]] development and evaluation. The authors introduce **misconception faithfulness** — the prope…

2026-05-16 · intelligent-tutoring, llm, generative-ai, benchmark, hallucination-risk

> Understanding How International Students in the U.S. Are Using Conversational AI to Support Cross-Cultural Adaptation **Nourian et al. (2026)** — Multiple institutions. arXiv cs.HC.…

2026-05-15 · higher-ed, generative-ai, llm, equity, culturally-relevant-pedagogy

> Evaluating Prompt Injection Defenses for Educational LLM Tutors: Security-Usability-Latency Trade-offs **Maiorano (2026)** — arXiv cs.CR/cs.AI.…

2026-05-15 · intelligent-tutoring, llm, generative-ai, regulation, hallucination-risk

> Characterizing Students' LLM Usage Behaviors and Their Association with Learning in Critical Thinking Tasks **Park, Orozco Vasquez, & Conati (2026)** — University of British Columbia. Accepted at ED…

2026-05-15 · higher-ed, llm, generative-ai, learning-analytics, ai-literacy

This study evaluated five generative AI tools for creating instructional slides from instructor-authored course notes: NotebookLM, Claude, M365 Copilot, Cursor, and Claude Code. Educators assessed sli…

2026-05-14 · generative-ai, higher-ed, faculty-development, ai-literacy, faculty-development-genai

This paper uses a clever identification strategy: measure the **seasonal drop in ChatGPT activity during non-school summer months** (2023 and 2024). Areas with larger summer dropoffs have heavier scho…

2026-05-14 · generative-ai, k-12, over-reliance, academic-integrity, efficacy-study

> Perl-Nussbaum & Finkelstein (2026) adapt institutional-change models to generative AI as an **arrival technology** — one that entered classrooms before pedagogical evidence existed — yielding a six-…

2026-05-14 · ai-education, institutional-change, faculty-development, higher-ed, pedagogy

This book chapter presents a **text mining analysis** of how scholarly literature frames ChatGPT's role in programming education. Using term frequency analysis, phrase pattern extraction, and topic mo…

2026-05-13 · over-reliance, academic-integrity, hallucination-risk, stem-education, feedback-loop

This paper introduces **PLKT** (Probabilistic Logical Knowledge Tracing), which replaces deterministic vector embeddings with **beta-distributed probabilistic embeddings**, allowing explicit represent…

2026-05-13 · knowledge-tracing, learning-analytics, intelligent-tutoring

This paper proposes **MBP-KT**, which transforms raw learner interaction sequences into structured **meta-behavioral patterns** before extracting collaborative signals. Raw sequences contain redundant…

2026-05-13 · knowledge-tracing, learning-analytics, adaptive-learning, adaptive-learning-systems

This paper addresses a critical but under-examined issue in KT systems: **selection bias** from non-random exercise recommendations. Prior KT methods train on observed logs using standard empirical ri…

2026-05-13 · knowledge-tracing, learning-analytics, personalized-learning, intelligent-tutoring

Adaptive learning systems produce substantial learning gains, yet many students engage too briefly or superficially to benefit. This paper addresses the central challenge of **measuring student effort…

2026-05-12 · adaptive-learning, assessment, engagement-metrics, learning-analytics, adaptive-learning-systems

> **Yu, Lu, Si et al. (77 authors, 2026)** — Shanghai Jiao Tong University, SII, GAIR. Open-source benchmark.…

2026-05-11 · benchmark, higher-ed, llm, generative-ai, pedagogical-llm-training

> **Authors:** Youjie Chen, Xixi Shi, Xinyu Liu, Shuaiguo Wang, Tracy Xiao Liu, Dragan Gašević **Year:** 2026 **Venue:** arXiv (cs.CY) > Large-scale analysis (N=11,406 students, 200 classes, 10 instit…

2026-05-11 · generative-ai, intelligent-tutoring, engagement-metrics, higher-ed, learning-analytics

Most AI-based educational tools adopt a one-on-one tutoring paradigm, pairing a single LLM with a single learner. Yet decades of learning science — from Vygotsky's Zone of Proximal Development to Band…

2026-05-11 · llm, intelligent-tutoring, scaffolding, collaborative-ai-tutoring, agentic-ai-ecosystems-higher-education

**AI multimodal feedback matches educator feedback for learning while significantly outperforming it on student perceptions.** The authors built a real-time AI-facilitated multimodal feedback system i…

2026-05-11 · multimodal, feedback-loop, generative-ai, llm, learning-analytics

**Sequenced AI feedback harms learning despite boosting engagement and positive perceptions.** In a randomized experiment with 199 participants, the authors compared two types of AI-generated feedback…

2026-05-11 · feedback-loop, formative-assessment, scaffolding, generative-ai, efficacy-study

> A design framework for LLM-powered educational agents that prioritize durable learning over short-term task performance. Introduced by Khosravi et al. (2026), AI learning companions are defined as a…

2026-05-09 · llm, personalized-learning, adaptive-learning, metacognition, self-regulated-learning

> A yearlong global "premortem" by the Brookings Center for Universal Education (2026) examining generative AI's risks and benefits for students. Based on 500+ interviews across 50 countries, 400+ stu…

2026-05-09 · policy-maker, k-12, regulation, ai-literacy, llm

> Stub — pending source ingestion. AI adoption, strategy, and governance from the institutional administrator and leadership perspective.…

2026-05-09 · administrator, policy-maker, higher-ed, generative-ai, llm

>Highlights critical misalignment between self-reported AI literacy and actual performance. Teachers overestimate their AI skills by 40% on average. Performance-based assessments correlate better (r=0…

2026-05-08 · ai-literacy, assessment, assessment-validity, k-12, self-regulated-learning

> ECNUClaw is an open-source framework by Zhou, Li & Zhang (2026) for building **learner-profiled intelligent study companions** in K-12 education. The system maintains a **five-dimension learner prof…

2026-05-08 · k-12, personalized-learning, intelligent-tutoring, llm, self-regulated-learning

> Key limitations exist in both LLM-based tutoring and conventional Deep Knowledge Tracing (DKT): > Combining neural networks with symbolic educational knowledge for interpretable, data-efficient, and…

2026-05-08 · intelligent-tutoring, learning-analytics, adaptive-learning, pedagogical-safety, mastery-learning

> **Synthesis:** Rather than replacing universities, generative AI **redefines their essential functions** — this paper proposes a four-level framework of institutional AI adoption and argues that the…

2026-05-08 · higher-ed, teacher-role, administrator, policy-maker, regulation

Automated question generation leverages NLP and LLMs to create educational assessments at scale. Wei & Stamper (2025) introduced the **generate-then-validate** paradigm, reducing hallucination by 62% …

2026-05-08 · nlp-education, assessment, llm, stem-education, automated-grading

Culturally Relevant Pedagogy (CRP), introduced by Gloria Ladson-Billings (1995), centers marginalized students' cultural references in curriculum design. Wang et al. (2025) demonstrate that **LLMs can…

2026-05-08 · equity, curriculum-design, culturally-sustaining-pedagogy, k-12, ai-literacy

Equity in AI Education addresses systemic disparities in access to, representation within, and benefits from AI educational tools. Three critical dimensions emerge: Wang et al. (2025) found that **78%…

2026-05-08 · accessible-learning, culturally-sustaining-pedagogy, equity, ai-literacy, higher-ed

K-12 AI Education encompasses the integration of artificial intelligence literacy, tools, and pedagogical approaches into primary and secondary education. Recent research reveals three critical pillar…

2026-05-08 · ai-literacy, curriculum-design, equity, k-12, faculty-development

Teacher AI competency encompasses the knowledge, skills, and dispositions required for effective AI integration in educational contexts. Emerging frameworks identify three competency dimensions: Zhang…

2026-05-08 · ai-literacy, faculty-development, k-12, higher-ed, generative-ai

> Gonnermann-Müller, Haase & Leins (2026) evaluate whether **LLM-generated student personas simulating ADHD profiles** maintain stable and realistic behavioral patterns over time. This addresses a cri…

2026-05-07 · llm, ai-education, generative-ai, benchmark, learning-analytics

> Integrating emotional awareness into AI tutoring systems can yield measurable pedagogical gains, but the same affective sophistication risks amplifying harms if learner agency is eroded by empatheti…

2026-05-07 · affective-computing, intelligent-tutoring, adaptive-learning, scaffolding, k-12

> Metacognition — thinking about one's own thinking — is both a target of AI education research (can AI tools develop students' metacognitive skills?) and a risk factor (AI completing tasks may suppre…

2026-05-07 · metacognition, self-regulated-learning, formative-assessment, k-12, higher-ed

> Domain-specialized optimization can transform a mid-sized open-source model (Qwen3-32B) into a pedagogical domain expert that outperforms far larger proprietary systems — but only when training rewa…

2026-05-07 · llm, intelligent-tutoring, adaptive-learning, benchmark, ai-education

Tailoring educational experiences to individual learner profiles, including prior knowledge, learning pace, preferences, and affective states. AI enables personalization at scale, though the gap betwe…

2026-05-07 · personalized-learning, intelligent-tutoring, adaptive-learning, ai-education, llm

> Self-regulated learning (SRL) describes learners as active participants who can shape and develop their cognitive and behavioral actions in a successful way. AI tools can either scaffold SRL develop…

2026-05-07 · self-regulated-learning, metacognition, scaffolding, k-12, higher-ed

> Socratic dialogue — asking structured questions rather than providing answers — is one of the strongest pedagogical scaffolds for deep learning. When automated via AI, it produces measurable reasoni…

2026-05-07 · intelligent-tutoring, scaffolding, active-learning, higher-ed, stem-education