🏷️ adaptive-learning

> Ye et al. (2026) introduce **AgentSchool**, an LLM-driven multi-agent [[simulating-students|simulator]] that models learning as **state transition rather than prompted behavior**. It couples cogniti…

2026-08-12 · simulating-students, agentic-ai, multi-agent, zone-of-proximal-development, knowledge-graph

> Pardos & Bhandari (2024) report a randomized efficacy study (N=274) comparing ChatGPT-generated hints to human tutor-authored hints and a no-help control across four mathematics subject areas. Only …

2026-08-12 · generative-ai, llm, ai-tutoring, intelligent-tutoring, scaffolding

> OATutor (Open Adaptive Tutor) is the first open-source adaptive tutoring system built on Intelligent Tutoring System (ITS) principles, developed at UC Berkeley's CAHL Lab. It combines an MIT-license…

2026-08-12 · intelligent-tutoring, open-source, knowledge-tracing, math-education, higher-ed

> Marquez-Carpintero, Lopez-Sellers & Cazorla (2025) present a thematic review of empirical and methodological studies using LLMs to [[simulating-students|simulate student behavior]] in education. The…

2026-08-12 · simulating-students, generative-ai, llm, student-modeling, agentic-ai

> Yuan et al. (2026) present a conceptual and methodological framework for valid LLM-based [[simulating-students|student simulation]]. They identify the **competence paradox** — broadly capable LLMs a…

2026-08-12 · simulating-students, llm, student-modeling, epistemic-state, evaluation

> **Simulation** — the use of modeled environments, agents, or scenarios to support learning through practice and feedback in contexts that are safe, repeatable, and often otherwise inaccessible. Simu…

2026-08-12 · active-learning, pedagogical-agent, skill-development, reinforcement-learning, experiential-learning

> **Synthesis:** This paper introduces an evidence-grounded multimodal pipeline that constructs provenance-rich [[knowledge-tracing|knowledge graphs]] from lecture videos by integrating speech transcr…

2026-08-09 · multimodal, ai-education, knowledge-tracing, student-modeling, generative-ai

> **Synthesis:** ProPRL advances [[adaptive-learning|prerequisite relation learning]] by going beyond conventional link prediction to adaptively integrate complementary educational evidence from conce…

2026-08-09 · knowledge-tracing, student-modeling, ai-education, personalized-learning, llm

> **Synthesis:** TACT (Taxonomy-Aligned Conversational Tutor) presents a human-grounded framework for training and evaluating pedagogically adaptive ESL tutors powered by [[llm|LLMs]]. Built on a Tuto…

2026-08-09 · tutoring, tutoring-systems, scaffolding, ai-tutoring, llm

> **Synthesis:** Xie, Yang, Zhang, Li, Wang, Yang & Gao (2026) propose HiLLM-CD, a tree-structured framework for cognitive diagnosis that represents student proficiency as node-wise values on a concep…

2026-08-09 · cognitive-diagnosis, knowledge-tracing, student-modeling, llm, generative-ai

> **Computational thinking** — a problem-solving approach involving decomposition, pattern recognition, abstraction, and algorithmic design. In AI education, computational thinking is both a prerequis…

2026-08-09 · cs-education, stem-education, ai-literacy, k-12, prompt-engineering

> **Intelligent Tutoring Systems (ITS)** — a well-established subfield of AI in education that uses AI to model student knowledge, adapt instruction, and provide personalized feedback, typically throu…

2026-08-09 · ai-education, ai-tutoring, scaffolding, student-modeling, knowledge-tracing

> **Student modeling** — the broad practice of representing learner characteristics including knowledge, skills, affective states, engagement, and preferences in computational form. Student modeling i…

2026-08-09 · student-modeling, knowledge-tracing, personalized-learning, learning-analytics, intelligent-tutoring

> **Synthesis:** This paper proposes a precision education framework that adapts precision medicine's predictive, preventive approach to higher education. It envisions AI-powered student digital twins…

2026-08-07 · student-modeling, personalized-learning, higher-ed, predictive-modeling, learning-analytics

> **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, student-experience

> **Behaviorally Adaptive Visual Diversion for Inclusive and Resilient Digital Assessment Delivery** — Proposes BAVD, a theoretical framework for adaptive visual diversion in digital assessment that r…

2026-08-05 · assessment, accessible-learning, privacy, academic-integrity, equity

> **A fully open-source agentic tutoring framework that closes the loop between citation-grounded problem tutoring and difficulty-calibrated question generation**, powered by a hybrid personalization …

2026-08-04 · llm, agentic-ai, personalized-learning, intelligent-tutoring, rag

> **Authors:** Viola Deutscher, Herbert Thomann, Olga Zlatkin-Troitschanskaia, Ulrike Weyland, Stephan Abele, Amory H. Danek, Samuel Greiff, Andreas Rausch, Susan Seeber, Jürgen Seifried, Esther Winth…

2026-08-01 · professional-training, efficacy-study, intelligent-tutoring, generative-ai, simulation-based-learning

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, mastery-learning, student-experience

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, student-experience, affective-computing, personalized-learning

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, feedback-loop, student-experience, 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, student-experience, 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, student-experience, 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

> **ProPACT** (Proactive AI-Driven Adaptive Collaborative Tutor) is an AI-driven adaptive tutoring system for pair programming that **treats collaboration itself as the object of instruction.** Unlike…

2026-07-29 · pair-programming, collaborative-learning, cs-education, adaptive-learning-systems, rag

> **Comprehensive Review of Intelligent Tutoring Systems** — Journal of Computers in Education (2025). A systematic literature review covering 2010–2025 that analyzes the deployment and effectiveness …

2026-07-29 · intelligent-tutoring, literature-review, pedagogical-llm-training, educational-nlp, socratic-questioning

> **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 · student-experience, higher-ed, llm, generative-ai, learning-analytics

> **Reinforcement learning** trains AI tutors and agents through reward signals: [[special-r1-rl-special-education]], [[singh-eduqwen-pedagogical-rl-2026]], [[pedagogical-safety-rl]], and [[ai-coachin…

2026-07-28 · llm, pedagogical-safety, intelligent-tutoring, special-education, personalized-learning

Kutti AI addresses a persistent equity gap in educational technology: nearly all edtech assumes a visual interface, excluding an estimated 1.4 million blind children worldwide. The system inverts this…

2026-07-27 · intelligent-tutoring, special-education, k-12, equity, personalized-learning

STEM education faces challenges in personalization and interdisciplinary integration. AI technology has brought new possibilities, but the mechanisms by which AI reshapes the STEM education ecosystem …

2026-07-09 · stem-education, generative-ai, intelligent-tutoring, scaffolding, learning-analytics

Introductory programming instruction relies on hands-on practice and short learning activities to support mastery of foundational concepts. Although many such learning resources exist, organizing and …

2026-07-09 · knowledge-tracing, personalized-learning, intelligent-tutoring, programming-its, rag

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

2026-07-02 · generative-ai, k-12, student-experience, affective-computing, llm-in-education

> **Lawrence Obiuwevwi, Krzysztof J. Rechowicz, Jessica M. Johnson, Erika Frydenlund, Vikas Ashok, Sachin Shetty, Sampath Jayarathna** — IEEE IRI 2026, submitted 1 Jul 2026…

2026-07-02 · special-education, equity, k-12, higher-ed, llm-in-education

This paper introduces Epi2Diff (Episode to Difficulty), a framework that maps LLM reasoning traces into cognitively grounded episode sequences for predicting human item difficulty in [[assessment|educ…

2026-06-29 · assessment, llm, learning-analytics, higher-ed, student-modeling

This paper explores how an embodied AI agent can act as a [[scaffolding|coach]] that accelerates human motor-skill development using [[adaptive-learning|reinforcement learning]]. The authors argue tha…

2026-06-25 · intelligent-tutoring, personalized-learning, scaffolding, professional-training, generative-ai

This study examines the [[student-modeling]] validity of **delayed start behavior** — when students begin assignments or practice sessions past a recommended start time — as a predictor of learning-ga…

2026-06-25 · learning-analytics, student-modeling, higher-ed, engagement-metrics, efficacy-study

Akgun and Toker (2026) examine whether learning gains from GenAI-enabled adaptive pretesting persist over a seven-week retention period. Undergraduate participants completed adaptive AI-assisted prete…

2026-06-23 · rct, formative-assessment, learning-gains, higher-ed, personalized-learning

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, student-experience, engagement-metrics

Nagai et al. (2026) tackle the practical problem that many real-world educational datasets contain only single-time-point assessments (snapshots) without temporal information, making standard time-ser…

2026-06-23 · student-modeling, knowledge-tracing, learning-analytics, formative-assessment, personalized-learning

> **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, student-modeling, personalized-learning

> **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

AdaPT uses transformers to adapt lesson plans across regional and differentiated instruction contexts; improves teacher efficiency while maintaining pedagogical alignment with local curricula. AdaPT: …

2026-06-18 · personalized-learning, k-12, teacher-role, generative-ai, ai-literacy-assessment-misalignment

ASTRA uses autonomous AI sim-pilots for scalable air traffic control training; reduces dependency on human role-players while maintaining realistic scenario complexity. ASTRA: A Scalable Next-Generati…

2026-06-18 · intelligent-tutoring, professional-training, active-learning, llm, adaptive-virtual-patient-psychotherapy-training

> 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, ai-literacy, higher-ed, engagement-metrics, student-experience

> 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, edtech-platform, student-experience, equity, learning-analytics

**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, personalized-learning, formative-assessment, intelligent-tutoring, edtech-platform

**KT4EQG: Personalized Exercise Question Generation via Knowledge Tracing** bridges two key AI-in-education paradigms: [[personalized-learning]] through question generation and [[learning-analytics]] …

2026-05-28 · automated-grading, intelligent-tutoring, learning-analytics, llm, personalized-learning

📄 DOI: 10.32473/flairs.39.1.141554 Codify (also called AI Tutor) is an [[intelligent-tutoring]] system that leverages [[llm|LLMs]], competency tracking, and adaptive assessment to provide Socratic, d…

2026-05-26 · intelligent-tutoring, llm, stem-education, higher-ed, self-regulated-learning

This paper addresses a fundamental gap in [[metacognition]] research: the lack of systematic integration of metacognitive theories into scenario taxonomies capable of guiding AI-enhanced professional …

2026-05-26 · metacognition, professional-training, lifelong-learning, scaffolding, self-regulated-learning

StanBKT introduces an open-source Python package for Bayesian Knowledge Tracing (BKT) that moves beyond traditional expectation-maximization (EM) point estimates to full Bayesian inference via Stan. T…

2026-05-25 · intelligent-tutoring, learning-analytics, benchmark, open-source, adaptive-learning-systems

Serious games are widely used for learning and training across domains such as healthcare, defense, and education. This chapter examines how contemporary AI approaches may support real-time instructio…

2026-05-22 · intelligent-tutoring, generative-ai, edtech-platform, professional-training, llm

**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, student-experience, 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, engagement-metrics, simulation, k-12

📄 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

> LearnMate^2: Design and Evaluation of an LLM-powered Personalized and Adaptive Support System for Online Learning **Wang, Lee, & Mutlu (2026)** — University of Wisconsin-Madison. CHI-related publica…

2026-05-15 · personalized-learning, llm, generative-ai, higher-ed, scaffolding

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, student-experience, adaptive-learning-systems

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 · assessment, engagement-metrics, learning-analytics, student-experience, adaptive-learning-systems

**Cognitive Agent Compilation (CAC)** is a framework that uses a strong teacher LLM to compile problem-solving knowledge into an explicit, inspectable target agent. Unlike end-to-end LLM tutoring appr…

2026-05-11 · intelligent-tutoring, llm, personalized-learning, pedagogical-llm-training, adaptive-learning-systems

> **Authors:** Kirk Vanacore, Ryan S. Baker, Avery H. Closser, Jeremy Roschelle **Year:** 2026 **Venue:** arXiv (cs.HC) > Synthesizes intelligent tutoring systems research and generative AI into a kee…

2026-05-11 · intelligent-tutoring, generative-ai, llm, scaffolding, personalized-learning

> A set of 19 empirically-grounded design guidelines for AI-supported learning technologies tailored to adult learners, synthesized by Reddig et al. (2026) from longitudinal deployment data at a US na…

2026-05-09 · lifelong-learning, personalized-learning, faculty-development, edtech-platform, human-in-the-loop-ai

> 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, metacognition, student-experience, self-regulated-learning

> Stub — pending source ingestion. Lifelong learning and AI support for continuous education beyond formal schooling.…

2026-05-09 · lifelong-learning, personalized-learning, professional-training, llm, intelligent-tutoring

> **EduGage** (Leng et al., 2026) addresses a core challenge: in online/video-based learning, **learners must self-regulate** their engagement with instructional materials. > Sensor-based momentary as…

2026-05-08 · learning-analytics, affective-computing, higher-ed, feedback-loop, 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, pedagogical-safety, mastery-learning, pedagogical-llm-training

> As reinforcement learning personalizes instruction in intelligent tutoring systems, there is no formal framework for pedagogical safety — a critical gap. > First formal framework for defining and de…

2026-05-08 · intelligent-tutoring, pedagogical-safety, reinforcement-learning, adaptive-learning-systems, metacognition

> **SCRIPT** (Deriyeva, Dannath, Paassen, 2026) implements an intelligent tutoring system for **Python programming** in a German university context, filling a gap in prior ITS which rarely supported P…

2026-05-08 · intelligent-tutoring, stem-education, higher-ed, formative-assessment, student-misconceptions-conditionals-loops-taxonomy

> **From Prototype to Classroom** (Elhaimeur & Chrisochoides, 2026) describes a tutoring system for quantum computing that bridges the gap between dense mathematical formalism and limited qualified in…

2026-05-08 · higher-ed, intelligent-tutoring, knowledge-tracing, stem-education, adaptive-learning-systems

> **MuTSE** (Roscan et al., 2026) addresses a critical need in **Intelligent Tutoring Systems (ITS)**: delivering content at the right reading level for each learner. > Human-in-the-loop evaluation fr…

2026-05-08 · intelligent-tutoring, nlp-education, human-in-the-loop, generative-ai, human-in-the-loop-ai

> Conventional LLM safety benchmarks focus on toxic outputs, jailbreaks, and bias. In education, the primary risks are quieter: > "Solving problems correctly and avoiding toxic language does not make …

2026-05-07 · pedagogical-safety, intelligent-tutoring, k-12, higher-ed, llm

> ProPACT constructs a real-time model of pair collaboration using three signals: > Most adaptive learning systems are individual-centric and reactive. **ProPACT** treats **collaboration itself as the…

2026-05-07 · intelligent-tutoring, scaffolding, higher-ed, formative-assessment, learning-analytics

> Two critical gaps in dialogue-based Knowledge Tracing (KT): > Most LLM-based dialogue tutoring systems produce opaque predictions. Huang et al. map raw LLM logits into **student ability (θ)** and **…

2026-05-07 · intelligent-tutoring, personalized-learning, learning-analytics, k-12, llm

> 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, student-experience, ai-education, generative-ai, benchmark

> Current AI tutoring systems treat each session as independent. Adaptive systems use real-time knowledge tracing (e.g., [[knowledge-tracing-irt|IRT-based models]]) but rarely retain a longitudinal st…

2026-05-07 · llm, personalized-learning, intelligent-tutoring, generative-ai, lifelong-learning

> Ostrowska, Kukla & Majstrak (2026) present an AI tutoring system **integrated into the Moodle LMS** designed to scaffold students from surface-level fact recall to deep conceptual understanding thro…

2026-05-07 · intelligent-tutoring, higher-ed, edtech-platform, llm, scaffolding

> 1. **Desirable difficulties** — General-purpose AI removes productive struggle; tutoring tools preserve it via graduated hints. 2. **Germane load** — Effective learning requires processing that feel…

2026-05-07 · intelligent-tutoring, llm, generative-ai, personalized-learning, scaffolding

> 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, scaffolding, 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, benchmark, ai-education, higher-ed

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, ai-education, llm, higher-ed

> **Synthesis:** Raza & Farooq (2025) conduct a comprehensive content analysis of AI in education from 2020-2025, examining 100+ peer-reviewed articles through a three-layer framework: the genome laye…

2025-10-31 · ai-education, systematic-review, personalized-learning, generative-ai, learning-analytics