🏷️ knowledge-tracing
35 pages tagged with knowledge-tracing(27 articles, 8 concepts)
📄 OATutor: An Open-source Adaptive Tutoring System and Curated Content Library for Learning Sciences Research
> 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…
🏷️ Cognitive Diagnosis
> **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…
🏷️ Simulating Students
> **Simulating students** — using LLM-based agents to model learner behavior, cognition, and social dynamics for educational research, design, and training. Simulated students let researchers evaluate…
📄 Evidence-Grounded Multimodal Knowledge Graph Construction for Multi-Lecture Educational Reasoning
> **Synthesis:** This paper introduces an evidence-grounded multimodal pipeline that constructs provenance-rich [[knowledge-tracing|knowledge graphs]] from lecture videos by integrating speech transcr…
📄 ProPRL: Property-Aware Prerequisite Relation Learning in Educational Knowledge Graphs
> **Synthesis:** ProPRL advances [[adaptive-learning|prerequisite relation learning]] by going beyond conventional link prediction to adaptively integrate complementary educational evidence from conce…
📄 HiLLM-CD: LLM-Enhanced Hierarchical Cognitive Diagnosis
> **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…
🏷️ Adaptive Learning
> **Adaptive learning** — AI-driven educational systems that adjust content, pacing, and instructional strategies based on individual learner characteristics and performance. Adaptive learning is the …
🏷️ Intelligent Tutoring
> **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…
🏷️ Knowledge Graph
> **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…
🏷️ Learning Analytics
> **Learning analytics** — the measurement, collection, analysis, and reporting of data about learners and their contexts for the purpose of understanding and optimizing learning. AI has transformed l…
🏷️ Student Modeling
> **Student modeling** — the broad practice of representing learner characteristics including knowledge, skills, affective states, engagement, and preferences in computational form. Student modeling i…
📄 Can LLMs Effectively Simulate Human Learners? Teachers' Insights from Tutoring LLM Students
> **Synthesis:** Semi-structured interviews with 12 teachers who tutored LLM-simulated students (MathDial dataset) reveal key authenticity gaps: overly complex language, lack of emotions, unnatural at…
📄 EduClaw-Bench: A Long-Horizon Benchmark for Pedagogical LLM Agents with Simulated Learners
> **EduClaw-Bench: A Long-Horizon Benchmark for Pedagogical LLM Agents with Simulated Learners** — Introduces a 30-day long-horizon benchmark for pedagogical LLM agents using simulated learners ground…
📄 Aligning LLM-Simulated and Human Examinees for Psychometric Calibration: A Cognitive Diagnostic Profiling Approach
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 …
📄 Archetypes or ability? Clustering for modelling student mathematical competence
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…
📄 Interpretable Knowledge Tracing
> **Interpretable Knowledge Tracing** — A novel framework for dialogue-based Knowledge Tracing that explicitly models both student ability and tutor-turn difficulty using Item Response Theory, produci…
📄 Learning Engagement Assistant (LEA): Cross-Course Scalability and Classroom Evaluation of an Agentic AI Tutoring System
LEA (Learning Engagement Assistant) is an **agentic AI tutoring system** that couples course-specific retrieval-augmented generation (RAG) with structured [[knowledge-tracing]] / Knowledge Component (…
📄 Automated Recommendation of Programming Learning Content Using Pattern-based Knowledge Components
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 …
📄 Cognitive Episodes in LLM Reasoning Traces Enable Interpretable Human Item Difficulty Prediction
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…
📄 Estimating Learners' Skill Acquisition Without Temporal Information
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…
🏷️ Knowledge Tracing
> **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…
📄 Reexamining the Cold-Start Problem in Knowledge Tracing Models and Implications for SafeInsights
**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…
📄 Detecting Knowledge Gaps from Conversational AI Interactions Using Curriculum Prerequisite Graphs
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…
📄 Benchmarking Large Language Models for Diagnosing Students' Cognitive Skills from Handwritten Math Work
> **MathCog** benchmark (3,036 teacher-annotated diagnostic verdicts, 639 handwritten responses, 18 LLMs): all models severely underperform (macro F1 < 0.5) — over-attributing evidence, overthinking m…
📄 StanBKT: Rethinking Parameter Estimation in Bayesian Knowledge Tracing
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…
📄 Simulating Learners' Task-Selection Strategies and System Constraints in Mastery Learning
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
📄 CLARA: An AI-Augmented Analytics Dashboard for Collaboration Literacy
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…
📄 Interpretable Difficulty-Aware Knowledge Tracing in Tutor-Student Dialogues
This paper bridges LLM-based dialogue tutoring and interpretable student modeling. By mapping opaque LLM representations to **Item Response Theory** parameters — student ability (θ) and question diffi…
📄 Explainable Knowledge Tracing via Probabilistic Embeddings and Pattern-based Reasoning
This paper introduces **PLKT** (Probabilistic Logical Knowledge Tracing), which replaces deterministic vector embeddings with **beta-distributed probabilistic embeddings**, allowing explicit represent…
📄 MBP-KT: Learning Global Collaborative Information from Meta-Behavioral Pattern for Enhanced Knowledge Tracing
This paper proposes **MBP-KT**, which transforms raw learner interaction sequences into structured **meta-behavioral patterns** before extracting collaborative signals. Raw sequences contain redundant…
📄 Ensuring Reliability in Programming Knowledge Tracing: A Re-evaluation of Attention-augmented Models and Experimental Protocols
This ITS 2026 paper challenges claims about attention-augmented Programming Knowledge Tracing (PKT) superiority. The authors identify three critical protocol flaws: **attention dimension misconfigurat…
📄 Temporal Smoothness Doubly Robust Learning for Debiased Knowledge Tracing
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…
📄 Reinforcement Learning Measurement Model
Interactive assessments generate sequential process data that conventional item response models (IRT) cannot adequately handle. This paper proposes a **reinforcement learning measurement model** that …
📄 The Missing Evaluation Axis: What 10,000 Student Submissions Reveal About AI Tutor Effectiveness
> A framework for evaluating AI tutoring systems that extends beyond pedagogical quality of feedback to measure what students actually *do* with that feedback — whether they act on it and whether they…
📄 Quantum Education Intelligent Tutoring
> **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…