🏷️ learning-analytics

> **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, higher-ed, student-experience, self-regulated-learning

> **Synthesis:** Niousha, Kang, & Norouzi (2026) introduce **INTERNAL STUDENT DIALOGUE (INSIDE)**, a student modeling framework that fine-tunes LLMs to both *act* like students and *think* like them. …

2026-08-13 · student-modeling, llm, intelligent-tutoring, personalized-learning, ai-education

> **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 · student-experience, motivation, higher-ed, self-regulated-learning, generative-ai

> **Synthesis:** This dissertation develops an AI-guided learning framework that supports three interconnected stages — Consume, Understand, and Imitate — with three deep-learning systems for audio/vi…

2026-08-12 · personalized-learning, language-learning, feedback-loop, self-regulated-learning, multimodal

> **Cognitive diagnosis** — the inference of a learner's latent knowledge state — the specific concepts, skills, and misconceptions they have or lack — from their responses or behavior. It is the asse…

2026-08-12 · student-modeling, educational-measurement, knowledge-tracing, assessment, intelligent-tutoring

> **Synthesis:** A systematic review of AI-powered collaborative learning in higher education: Trends and outcomes from the last decade…

2026-08-11 · collaborative-learning, generative-ai, higher-ed, systematic-review

> **Synthesis:** Yan, Xiong, Li & Chen (2026) reposition LLMs from benchmark targets to auxiliary evidence sources for interpreting programming-exam difficulty, showing that AI difficulty estimates co…

2026-08-11 · computing-education, programming-education, assessment, automated-assessment, llm-evaluation

> **Synthesis:** Grounded in social presence theory, this study introduces the concept of identity anthropomorphism and adopts multimodal learning analytics (MMLA) combining questionnaires, EEG and ey…

2026-08-10 · affective-computing, agent, multimodal, ai-education, ai-tutoring

> **Synthesis:** Dawson and Pardo (2026) argue that generative AI (GenAI) is precipitating a systemic, paradigmatic transformation of education — not a passing fad — and that traditional bureaucratic …

2026-08-10 · generative-ai, higher-ed, leadership, institutional-change, governance

> **Synthesis:** Rienties et al. (2026) examine how the Open University (UK) — a large-scale distance learning institution teaching 200K+ learners across 50+ countries — designed, implemented, and eva…

2026-08-10 · generative-ai, higher-ed, distance-learning, design-based-research, ai-chatbots

> **Synthesis:** Isaeva et al. (2026) examine undergraduate students' engagement with generative AI (GenAI) in academic learning at an English-medium university, using self-determination theory (SDT) …

2026-08-10 · generative-ai, student-experience, self-regulated-learning, ai-literacy, academic-integrity

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

2026-08-09 · cognitive-offloading, prompting-literacy, higher-ed, student-experience, ai-literacy

> **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

> **Adaptive learning** — AI-driven educational systems that adjust content, pacing, and instructional strategies based on individual learner characteristics and performance. Adaptive learning is the …

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

> **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, student-experience, engagement-metrics

> **Feedback loop** — the cyclical process where AI systems assess student work, deliver feedback, observe the student's response, and adapt subsequent instruction. Effective feedback loops close the …

2026-08-09 · formative-assessment, ai-feedback-quality, automated-grading, scaffolding, self-regulated-learning

> **Knowledge graph** — a structured representation of concepts and their relationships used to model domain knowledge, student understanding, and learning dependencies in AI in education systems. Kno…

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

> **Privacy** — the protection of student data, identity, and autonomy in AI-augmented learning environments. Privacy concerns intensify as AI systems collect increasingly granular behavioral data for…

2026-08-09 · personalized-learning, k-12, ethics, regulation, equity

> **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, adaptive-learning, personalized-learning, intelligent-tutoring

> **Synthesis:** Graf et al. (2026) transformed a conventional Learning Analytics Dashboard (LAD) into an interactive ILAD by adding an LLM-powered pedagogical agent and a Judgement of Learning (JoL) …

2026-08-08 · metacognition, llm, higher-ed, engagement-metrics, self-regulated-learning

> **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 · adaptive-learning, student-modeling, personalized-learning, higher-ed, predictive-modeling

> **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, hint-systems, k-12, math-education, gaming-the-system

> **Beyond Compliance: A Proposed Framework for Ethical Governance of Student Data in Learning Analytics** — Proposes LEAGUE framework (Lawfulness, Equity, Agency, Governance, Utility, Ethics by Desig…

2026-08-05 · privacy, equity, ethics, regulation, higher-ed

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

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

> **Lan Anh Do, Hanling Jiang, Shuchin Aeron, Ayanna K. Thomas** — CogSci 2026 (accepted full paper).…

2026-08-03 · llm, collaborative-learning, student-ai-interaction, nlp-education, collaborative-ai-tutoring

> **Dimitris Tsirmpas, Katerina Korre, John Pavlopoulos** — arXiv preprint (2026).…

2026-08-03 · llm, collaborative-learning, student-ai-interaction, engagement-metrics, nlp-education

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

2026-08-03 · multimodal, student-experience, 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, student-experience, teacher-role

> **Authors:** Kamila Misiejuk, Sonsoles López-Pernas, Eduardo Araujo Oliveira, Brendan Eagan, Mohammed Saqr **Source:** Computers and Education: AI, Vol 11 — Open Access (CC BY 4.0)…

2026-08-01 · automated-grading, educational-theory, ground-truth-reliability-aied, llm, llm-in-education

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, student-experience, stem-education, higher-ed, ai-education

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, student-experience, 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, academic-integrity, edtech-platform

> **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, student-experience, human-in-the-loop-ai, higher-ed

> **Synthesis:** A custom Socratic AI chatbot deployed in a large-enrollment introductory mechanics course with 150 first-year STEM majors, demonstrating that AI-driven Socratic dialogue can foster ex…

2026-07-29 · socratic-method, physics-education, generative-ai, intelligent-tutoring, socratic-questioning

Anindho, Venkatesha, Ocumpaugh and Blanchard apply Ordered Network Analysis to trace how epistemic emotions such as confusion and frustration persist and transition during co-situated collaborative pr…

2026-07-28 · affective-computing, human-in-the-loop, affective-tutoring, llm

> **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, k-12

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, stem-education, higher-ed, student-experience

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, student-experience, personalized-learning, self-regulated-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, adaptive-learning

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, formative-assessment, cs-education, higher-ed, feedback-loop

**Manuel Alonso-Carracedo, Ruben Fernandez-Boullon, Pedro Celard, Francisco J. Rodriguez-Martinez, Lorena Otero-Cerdeira (2026)** This paper presents an [[llm]]-based grading system for Linux/bash com…

2026-07-03 · llm, automated-grading, cs-education, formative-assessment, higher-ed

**Mengqian Wu (2026)** Epistemic thinking — understanding how knowledge is constructed and justified — plays a central role in [[ai-literacy]], particularly when students co-program with generative AI…

2026-07-03 · ai-literacy, cs-education, student-ai-interaction, scaffolding, higher-ed

Data comics combine sequential visual narratives with data visualization to improve student engagement with [[generative-ai]] in educational settings. This paper evaluates the effectiveness of AI-assi…

2026-07-03 · ai-generated-content, k-12, active-learning, ai-literacy, llm

While [[llm]]s now enable rapid generation of learning materials like [[generative-ai]], evaluating the pedagogical quality of these materials remains an open challenge. This paper proposes an automat…

2026-07-03 · ai-generated-content, formative-assessment, higher-ed, llm, automated-grading

The rapid integration of [[llm]]s into [[intelligent-tutoring]] threatens to reduce mathematical learning to mere answer generation. This paper presents a design framework for AI tutors that act as re…

2026-07-03 · intelligent-tutoring, llm, scaffolding, formative-assessment, higher-ed

**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, student-experience, ai-literacy, student-ai-interaction

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, llm, student-experience, ai-literacy

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, higher-ed, student-modeling, benchmark

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 · student-modeling, higher-ed, engagement-metrics, efficacy-study, self-regulated-learning

Gheisari and Salarian (2026) apply supervised machine learning classification to identify at-risk students before they withdraw from higher education programs. The study evaluates Logistic Regression,…

2026-06-23 · higher-ed, dropout-reduction, student-modeling, rct, llm

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, adaptive-learning, 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, intelligent-tutoring, adaptive-learning, student-modeling, personalized-learning

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 · k-12, higher-ed, qualitative-research, edtech-platform, student-experience

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, student-experience, teacher-role

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, student-experience, equity

> 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, student-experience

> 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, student-experience, teacher-role

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 · llm, k-12, personalized-learning, assessment, student-experience

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, student-experience, stem-education

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 · edtech-platform, higher-ed, engagement-metrics, student-experience, 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 · student-experience, higher-ed, academic-integrity, over-reliance, hallucination-risk

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, student-experience, intelligent-tutoring, efficacy-study

**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, teacher-role, 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, student-modeling, benchmark, higher-ed, llm

**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, student-experience, llm, higher-ed, scaffolding

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, generative-ai

> **Synthesis:** Fair and explainable educational recommendations with a hybrid Graph-GRU framework…

2026-06-03 · ai-education, bias-mitigation, personalized-learning

> Identifies interaction signatures of LLM literacy using Epistemic Network Analysis (ENA) on logs from 162 students. High-literacy students exhibit iterative, strategic refinement and dense cognitive…

2026-06-02 · ai-literacy, higher-ed, prompt-engineering, writing-education, scaffolding

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

2026-06-01 · teacher-role, higher-ed, student-experience, 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 · edtech-platform, personalized-learning, higher-ed, feedback-loop, student-experience

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, student-experience, 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, student-experience, higher-ed, writing-education

**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 · adaptive-learning, automated-grading, intelligent-tutoring, llm, personalized-learning

**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, student-experience, formative-assessment

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

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, adaptive-learning, benchmark, open-source, adaptive-learning-systems

**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 · intelligent-tutoring, adaptive-learning, student-experience, teacher-role, ai-literacy

Theodora and Tselios (2026) provide a policy-oriented synthesis of AI's dual role in adult and [[lifelong-learning]] contexts — as both an enabler of personalized, scalable education and a source of s…

2026-05-21 · lifelong-learning, policy-maker, equity, intelligent-tutoring, ai-literacy

📄 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, bias-mitigation, equity, privacy, metacognition

This paper tackles a core ITS challenge: predicting when students will disengage so tutors can intervene before it's too late. It introduces **engagement forecasting** as a supervised prediction task …

2026-05-20 · intelligent-tutoring, engagement-metrics, k-12, efficacy-study, benchmark

Agentic analytics using AI-produced concept-map artifacts as shared human-AI representations improves collaboration quality analysis and AI response grounding over transcript-only baselines. CLARA int…

2026-05-19 · generative-ai, llm, higher-ed, edtech-platform, collaborative-learning

Closed-loop ITS with multimodal affective scoring (facial, vocal, textual, oculomotor) produced significant presentation skill gains (Cohen's d = 0.39-0.90, N=204) over 30 days. This paper presents on…

2026-05-19 · intelligent-tutoring, affective-computing, multimodal, higher-ed, professional-training

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, student-experience, higher-ed, affective-tutoring, llm

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, personalized-learning

> 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, student-experience, llm, generative-ai, ai-literacy

AICoFe orchestrates a multi-LLM pipeline using GPT-4.1-mini, Gemini 2.5 Flash, and Llama 3.1 to synthesize quantitative rubric data and qualitative observations into actionable feedback for higher edu…

2026-05-14 · automated-grading, feedback-loop, higher-ed, llm, human-in-the-loop-ai

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, intelligent-tutoring, student-experience

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, student-experience, adaptive-learning, adaptive-learning-systems

This ITS 2026 paper challenges claims about attention-augmented Programming Knowledge Tracing (PKT) superiority. The authors identify three critical protocol flaws: **attention dimension misconfigurat…

2026-05-13 · knowledge-tracing, automated-grading, benchmark

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, personalized-learning, intelligent-tutoring, student-experience

Interactive assessments generate sequential process data that conventional item response models (IRT) cannot adequately handle. This paper proposes a **reinforcement learning measurement model** that …

2026-05-12 · assessment, knowledge-tracing, benchmark, llm

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, student-experience, adaptive-learning-systems

> **Authors:** Eason Chen, Ce Guan, A Elshafiey, Zhonghao Zhao, Joshua Zekeri, Afeez Edeifo Shaibu, Emmanuel Osadebe Prince **Year:** 2026 **Venue:** arXiv (cs.HC) > Mining discourse from Moltbook, a …

2026-05-11 · agentic-ai, benchmark, collaborative-ai-tutoring, engagement-metrics, llm

> **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, student-experience, engagement-metrics, higher-ed

> Stop treating κ > 0.8 as a binary stamp of approval.…

2026-05-11 · benchmark, efficacy-study, generative-ai, llm, automated-grading

**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, student-experience

> A web-based system that uses LLMs and Learning Analytics dashboards to provide automated, rubric-based feedback on student presentation slides. Developed by Becerra et al. (2026), AISSA addresses th…

2026-05-09 · automated-grading, formative-assessment, higher-ed, llm, human-in-the-loop-ai

> 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

> A bibliometric–systematic review of AI tools in STEM education: > Systematic review (2005–2025) mapping how AI tools scaffold and co-regulate metacognitive development in STEM classrooms through bib…

2026-05-08 · metacognition, stem-education, intelligent-tutoring, posthumanist, ai-literacy

> **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 · adaptive-learning, 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, adaptive-learning, pedagogical-safety, mastery-learning, pedagogical-llm-training

> Peer feedback develops critical reflection and evaluative judgment, yet: > Student peer feedback is often superficial or inconsistent. **AICoFe** (AI-based Collaborative Feedback) uses a multi-LLM p…

2026-05-07 · edtech-platform, feedback-loop, formative-assessment, teacher-role, higher-ed

> Automatic Short Answer Grading (ASAG) is never perfect. Upper bounds on accuracy arise from: > Zero-shot LLMs perform strongly on ASAG without task-specific fine-tuning, but **model-based confidence…

2026-05-07 · automated-grading, llm, formative-assessment, feedback-loop, higher-ed

> 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, adaptive-learning, scaffolding, higher-ed, formative-assessment

> 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 · adaptive-learning, intelligent-tutoring, personalized-learning, 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

Educational AI systems that strategically interleave automated generation with human expert judgment, preserving pedagogical quality while scaling production. Two recent implementations illustrate dis…

2026-05-07 · human-in-the-loop, assessment, pedagogical-safety, ai-education, llm

> **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, intelligent-tutoring