Ken Koedinger
Hillman University Professor
Studies the cognitive science of learning and intelligent tutoring systems, including educational data mining.
Ken Koedinger's lab at CMU works on learning & education technology, interfaces & interaction techniques and computational neuroscience & cognition. 86 papers since 2023, 4 at top venues, mostly IJCAI and AAAI. Applications close .
At a glance
- papers, 2023–2026
- 22/ year
- at T1 venues
- 5%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 18 papers2026 · T1 2 · collecting
- 36 papers2025 · T1 1
- 20 papers2024 · T1 1
- 12 papers2023 · T1 0
T1 venuesOtherVenues: IJCAI, AAAI, CHI, SIGCSE
Research focuspaper titles that use each topic's words
- Learning & education technology30 papers
- tutoring systems4 papers
- Computational neuroscience & cognition3 papers
- intelligent tutoring2 papers
- Interfaces & interaction techniques1 paper
Paper list
From DBLP.
202618 papers
- LAKActive Learning Beyond Borders: PEOE Enhancement of Explanatory Understanding in Japanese Undergraduates (opens in a new tab)
- LAKAI Knows Best? The Paradox of Expertise, AI-Reliance, and Performance in Educational Tutoring Decision-Making Tasks (opens in a new tab)
- EC-TELAI-Driven Assessment of Human Tutors: Linking Training Performance to Real-Life Practice (opens in a new tab)
- LAKBrief but Impactful: How Human Tutoring Interactions Shape Engagement in Online Learning (opens in a new tab)
- AIEDChat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learning (opens in a new tab)
- L@SCoasting Through Class: Learning Opportunity Loss from Practice Avoidance During Individual Seatwork (opens in a new tab)
- AIEDCross-Subject Predictive Validity for Learning Outcomes of Delayed Start Behavior (opens in a new tab)
- AIEDDoes the TalkMoves Codebook Generalize to One-on-One Tutoring and Multimodal Interaction? (opens in a new tab)
- EC-TELDosage and Dialogue: Understanding Human Support in Hybrid Human-AI Math Tutoring (opens in a new tab)
- AIEDEvaluating a Data-Driven Redesign Process for Intelligent Tutoring Systems (opens in a new tab)
- LAKHow to Assess AI Literacy: Misalignment Between Self-Reported and Objective-Based Measures (opens in a new tab)
- IEEE Trans. Learn. Technol.Improving Automated Feedback Systems for Tutor Training in Low-Resource Scenarios Through Data Augmentation (opens in a new tab)
202536 papers
- EDM9th Educational Data Mining in Computer Science Education (CSEDM) Workshop (opens in a new tab)
- L@SAdvancing the Science of Teaching with Tutoring Data: A Collaborative Workshop with the National Tutoring Observatory (opens in a new tab)
- AIED CompanionAI Literacy For All: 1st International Workshop on AI Literacy Education For All (opens in a new tab)
- GenAI-LA@LAKAugmenting Human-Annotated Training Data with Large Language Model Generation and Distillation in Open-Response Assessment (short paper) (opens in a new tab)
- EC-TEAutomatic Large Language Models Creation of Interactive Learning Lessons (opens in a new tab)
- AIED CompanionAvalon: A Human-in-the-Loop LLM Grading System with Instructor Calibration and Student Self-assessment (opens in a new tab)
- Commun. ACMBeyond Benchmarks: Responsible AI in Education Needs Learning Sciences (opens in a new tab)
- CogSciDecomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency (opens in a new tab)
- L@SDemo of VTutor for High-Impact Tutoring at Scale: A Real-Time Multi-Screen Tutor Support System with P2P Connections (opens in a new tab)
- EC-TEDetecting LLM-Generated Short Answers and Effects on Learner Performance (opens in a new tab)
- LAKDo Tutors Learn from Equity Training and Can Generative AI Assess It? (opens in a new tab)
- LAKDoes Multiple Choice Have a Future in the Age of Generative AI? A Posttest-only RCT (opens in a new tab)
202420 papers
- EDM8th Educational Data Mining in Computer Science Education (CSEDM) Workshop (opens in a new tab)
- EC-TELActiveAI: The Effectiveness of an Interactive Tutoring System in Developing K-12 AI Literacy (opens in a new tab)
- Int. J. Artif. Intell. Educ.AI Adaptivity in a Mixed-Reality System Improves Learning (opens in a new tab)
- EDMBeyond Accuracy: Embracing Meaningful Parameters in Educational Data Mining (opens in a new tab)
- L@SBeyond Repetition: The Role of Varied Questioning and Feedback in Knowledge Generalization (opens in a new tab)
- EDMCombining Dialog Acts and Skill Modeling: What Chat Interactions Enhance Learning Rates During AI-Supported Peer Tutoring? (opens in a new tab)
- IJCAI (T1)Content Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples (Extended Abstract) (opens in a new tab)
- L@SEdgeworth: Efficient and Scalable Authoring of Visual Thinking Activities (opens in a new tab)
- AIED CompanionGood Fit Bad Policy: Why Fit Statistics Are a Biased Measure of Knowledge Tracer Quality (opens in a new tab)
- L@SGPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation (opens in a new tab)
- L@SHAROR: A System for Highlighting and Rephrasing Open-Ended Responses (opens in a new tab)
- EDMHow Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses (opens in a new tab)
202312 papers
- Human-AI Math Tutoring@AIEDComparative Analysis of GPT-4 and Human Graders in Evaluating Human Tutors Giving Praise to Students (opens in a new tab)
- AIEDComparative Analysis of Learnersourced Human-Graded and AI-Generated Responses for Autograding Online Tutor Lessons (opens in a new tab)
- AIEDComputational Models of Learning: Deepening Care and Carefulness in AI in Education (opens in a new tab)
- AIEDContent Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples (opens in a new tab)
- LLM@AIEDIs AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming (opens in a new tab)
- AIEDSimulating Learning from Language and Examples (opens in a new tab)
- J. Comput. Assist. Learn.Supporting skill integration in an intelligent tutoring system for code tracing (opens in a new tab)
- AIEDTowards the Future of AI-Augmented Human Tutoring in Math Learning (opens in a new tab)
- Human-AI Math Tutoring@AIEDUsing Large Language Models to Provide Explanatory Feedback to Human Tutors (opens in a new tab)
- User Model. User Adapt. Interact.Using latent variable models to make gaming-the-system detection robust to context variations (opens in a new tab)
- EC-TELWhat Makes Problem-Solving Practice Effective? Comparing Paper and AI Tutoring (opens in a new tab)
- LAKWhen the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
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