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ORCIDKenneth R. Koedinger
Ken Koedinger
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- affiliation: Carnegie Mellon University, Pittsburgh, USA
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2020 – today
- 2024
[j47]Ken Koedinger:
Navigating Ethical Benefits and Risks as AIED Comes of Age. Int. J. Artif. Intell. Educ. 34(1): 136-143 (2024)- [c264]Napol Rachatasumrit
, Daniel Weitekamp III, Kenneth R. Koedinger:
Good Fit Bad Policy: Why Fit Statistics Are a Biased Measure of Knowledge Tracer Quality. AIED Companion (2) 2024: 183-191 - [c263]Qianou Ma, Hua Shen, Kenneth R. Koedinger, Sherry Tongshuang Wu:
How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debugging. AIED (1) 2024: 265-279 - [c262]Danielle R. Thomas, Erin Gatz, Shivang Gupta, Vincent Aleven, Kenneth R. Koedinger:
The Neglected 15%: Positive Effects of Hybrid Human-AI Tutoring Among Students with Disabilities. AIED (1) 2024: 409-423 - [c261]Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger:
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. LAK 2024: 404-415 - [c260]Wode Ni, Sam Estep, Hwei-Shin Harriman, Kenneth R. Koedinger, Joshua Sunshine:
Edgeworth: Efficient and Scalable Authoring of Visual Thinking Activities. L@S 2024: 98-109 - [c259]Gautam Yadav, Paulo F. Carvalho, Elizabeth A. McLaughlin, Kenneth R. Koedinger:
Beyond Repetition: The Role of Varied Questioning and Feedback in Knowledge Generalization. L@S 2024: 451-455 - [c258]Danielle R. Thomas, Jionghao Lin, Shambhavi Bhushan, Ralph Abboud, Erin Gatz, Shivang Gupta, Kenneth R. Koedinger:
Learning and AI Evaluation of Tutors Responding to Students Engaging in Negative Self-Talk. L@S 2024: 481-485 - [c257]Eason Chen, Jia-En Lee, Jionghao Lin, Kenneth R. Koedinger:
GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation. L@S 2024: 539-541 - [c256]Jionghao Lin, Eason Chen, Ashish Gurung, Kenneth R. Koedinger:
MuFIN: A Framework for Automating Multimodal Feedback Generation using Generative Artificial Intelligence. L@S 2024: 550-552 - [c255]Jionghao Lin, Kenneth R. Koedinger:
HAROR: A System for Highlighting and Rephrasing Open-Ended Responses. L@S 2024: 553-555 - [c254]Clifford A. Shaffer, Peter Brusilovsky, Ken Koedinger, Thomas W. Price, Tiffany Barnes, Behrooz Mostafavi:
Ninth SPLICE Workshop on Technology and Data Infrastructure for CS Education Research. SIGCSE (2) 2024: 1904 - [i13]Sanjit Kakarla, Danielle Thomas, Jionghao Lin, Shivang Gupta, Kenneth R. Koedinger:
Using Large Language Models to Assess Tutors' Performance in Reacting to Students Making Math Errors. CoRR abs/2401.03238 (2024) - [i12]Zifei FeiFei Han, Jionghao Lin, Ashish Gurung, Danielle R. Thomas, Eason Chen, Conrad Borchers, Shivang Gupta, Kenneth R. Koedinger:
Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation. CoRR abs/2402.14594 (2024) - [i11]Jionghao Lin, Eason Chen, Zeifei Han, Ashish Gurung, Danielle R. Thomas, Wei Tan, Ngoc Dang Nguyen, Kenneth R. Koedinger:
How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses. CoRR abs/2405.00291 (2024) - [i10]Jionghao Lin, Zifei FeiFei Han, Danielle R. Thomas, Ashish Gurung, Shivang Gupta, Vincent Aleven, Kenneth R. Koedinger:
How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses. CoRR abs/2405.00970 (2024) - [i9]Gautam Yadav, Paulo F. Carvalho, Elizabeth A. McLaughlin, Kenneth R. Koedinger:
Beyond Repetition: The Role of Varied Questioning and Feedback in Knowledge Generalization. CoRR abs/2405.09655 (2024) - [i8]Eason Chen, Jia-En Lee, Jionghao Lin, Kenneth R. Koedinger:
GPTutor: Great Personalized Tutor with Large Language Models for Personalized Learning Content Generation. CoRR abs/2407.09484 (2024) - 2023
- [j46]Yun Huang, Peter Brusilovsky, Julio Guerra, Kenneth R. Koedinger, Christian Schunn:
Supporting skill integration in an intelligent tutoring system for code tracing. J. Comput. Assist. Learn. 39(2): 477-500 (2023) - [j45]Yun Huang, Steven Dang, J. Elizabeth Richey, Pallavi Chhabra, Danielle R. Thomas, Michael W. Asher, Nikki G. Lobczowski, Elizabeth A. McLaughlin, Judith M. Harackiewicz, Vincent Aleven, Kenneth R. Koedinger:
Using latent variable models to make gaming-the-system detection robust to context variations. User Model. User Adapt. Interact. 33(5): 1211-1257 (2023) - [c253]Jionghao Lin, Danielle R. Thomas, Feifei Han, Shivang Gupta, Wei Tan, Ngoc Dang Nguyen, Kenneth R. Koedinger:
Using Large Language Models to Provide Explanatory Feedback to Human Tutors. Human-AI Math Tutoring@AIED 2023: 12-23 - [c252]Daniel Weitekamp III, Kenneth R. Koedinger:
Computational Models of Learning: Deepening Care and Carefulness in AI in Education. AIED (Posters/Late Breaking Results/...) 2023: 13-25 - [c251]Vincent Aleven, Richard G. Baraniuk, Emma Brunskill, Scott Crossley, Dora Demszky, Stephen Fancsali, Shivang Gupta, Kenneth R. Koedinger, Chris Piech, Steven Ritter, Danielle R. Thomas, Simon Woodhead, Wanli Xing:
Towards the Future of AI-Augmented Human Tutoring in Math Learning. AIED (Posters/Late Breaking Results/...) 2023: 26-31 - [c250]Dollaya Hirunyasiri, Danielle R. Thomas, Jionghao Lin, Kenneth R. Koedinger, Vincent Aleven:
Comparative Analysis of GPT-4 and Human Graders in Evaluating Human Tutors Giving Praise to Students. Human-AI Math Tutoring@AIED 2023: 37-48 - [c249]Napol Rachatasumrit, Paulo F. Carvalho, Sophie Li, Kenneth R. Koedinger:
Content Matters: A Computational Investigation into the Effectiveness of Retrieval Practice and Worked Examples. AIED 2023: 54-65 - [c248]Qianou Christina Ma, Sherry Tongshuang Wu, Ken Koedinger:
Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming. LLM@AIED 2023: 64-77 - [c247]Daniel Weitekamp III, Napol Rachatasumrit, Rachael Wei, Erik Harpstead, Kenneth R. Koedinger:
Simulating Learning from Language and Examples. AIED (Posters/Late Breaking Results/...) 2023: 580-586 - [c246]Danielle R. Thomas, Shivang Gupta, Kenneth R. Koedinger:
Comparative Analysis of Learnersourced Human-Graded and AI-Generated Responses for Autograding Online Tutor Lessons. AIED (Posters/Late Breaking Results/...) 2023: 714-719 - [c245]Conrad Borchers, Paulo F. Carvalho, Meng Xia, Pinyang Liu, Kenneth R. Koedinger, Vincent Aleven:
What Makes Problem-Solving Practice Effective? Comparing Paper and AI Tutoring. EC-TEL 2023: 44-59 - [c244]Danielle Thomas, Xinyu Yang, Shivang Gupta, Adetunji Adeniran, Elizabeth A. McLaughlin, Kenneth R. Koedinger:
When the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors. LAK 2023: 250-261 - [e4]Danielle R. Thomas, Jionghao Lin, Kenneth R. Koedinger:
Proceedings of the Workshop "Towards the Future of AI-augmented Human Tutoring in Math Learning" co-located with The 24th International Conference on Artificial Intelligence in Education (AIED 2023), Tokyo, Japan, July 3, 2023. CEUR Workshop Proceedings 3491, CEUR-WS.org 2023 [contents] - [i7]Qianou Ma, Tongshuang Wu, Kenneth R. Koedinger:
Is AI the better programming partner? Human-Human Pair Programming vs. Human-AI pAIr Programming. CoRR abs/2306.05153 (2023) - [i6]Jionghao Lin, Danielle R. Thomas, Feifei Han, Shivang Gupta, Wei Tan, Ngoc Dang Nguyen, Kenneth R. Koedinger:
Using Large Language Models to Provide Explanatory Feedback to Human Tutors. CoRR abs/2306.15498 (2023) - [i5]Dollaya Hirunyasiri, Danielle R. Thomas, Jionghao Lin, Kenneth R. Koedinger, Vincent Aleven:
Comparative Analysis of GPT-4 and Human Graders in Evaluating Praise Given to Students in Synthetic Dialogues. CoRR abs/2307.02018 (2023) - [i4]Qianou Ma, Hua Shen, Kenneth R. Koedinger, Tongshuang Wu:
HypoCompass: Large-Language-Model-based Tutor for Hypothesis Construction in Debugging for Novices. CoRR abs/2310.05292 (2023) - [i3]Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger:
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. CoRR abs/2312.11274 (2023) - 2022
- [j44]Christopher J. MacLellan, Kenneth R. Koedinger:
Domain-General Tutor Authoring with Apprentice Learner Models. Int. J. Artif. Intell. Educ. 32(1): 76-117 (2022) - [j43]Wayne Holmes, Kaska Porayska-Pomsta, Ken Holstein, Emma Sutherland, Toby Baker, Simon Buckingham Shum, Olga C. Santos, Maria Mercedes T. Rodrigo, Mutlu Cukurova, Ig Ibert Bittencourt, Kenneth R. Koedinger:
Ethics of AI in Education: Towards a Community-Wide Framework. Int. J. Artif. Intell. Educ. 32(3): 504-526 (2022) - [j42]Thiemo Wambsganss, Naim Zierau, Matthias Söllner, Tanja Käser, Kenneth R. Koedinger, Jan Marco Leimeister:
Designing Conversational Evaluation Tools: A Comparison of Text and Voice Modalities to Improve Response Quality in Course Evaluations. Proc. ACM Hum. Comput. Interact. 6(CSCW2): 1-27 (2022) - [c243]Nicholas Diana, John C. Stamper, Ken Koedinger, Jessica Hammer:
Debiasing Politically Motivated Reasoning with Value-Adaptive Instruction. AIED (1) 2022: 140-152 - [c242]Danielle R. Chine, Cassandra Brentley, Carmen Thomas-Browne, J. Elizabeth Richey, Abdulmenaf Gul, Paulo F. Carvalho, Lee G. Branstetter, Kenneth R. Koedinger:
Educational Equity Through Combined Human-AI Personalization: A Propensity Matching Evaluation. AIED (1) 2022: 366-377 - [c241]Thiemo Wambsganss, Matthias Söllner, Kenneth R. Koedinger, Jan Marco Leimeister:
Adaptive Empathy Learning Support in Peer Review Scenarios. CHI 2022: 227:1-227:17 - [c240]Paulo Carvalho, Napol Rachatasumrit, Kenneth R. Koedinger:
Learning depends on knowledge: The benefits of retrieval practice vary for facts and skills. CogSci 2022 - [c239]Yun Huang, Steven Dang, J. Elizabeth Richey, Michael W. Asher, Nikki G. Lobczowski, Danielle R. Chine, Elizabeth A. McLaughlin, Judith M. Harackiewicz, Vincent Aleven, Kenneth R. Koedinger:
Item Response Theory-Based Gaming Detection. EDM 2022 - [c238]Danielle R. Chine, Pallavi Chhabra, Adetunji Adeniran, Shivang Gupta, Kenneth R. Koedinger:
Development of Scenario-based Mentor Lessons: An Iterative Design Process for Training at Scale. L@S 2022: 469-471 - 2021
- [j41]Xu Wang, Meredith M. Thompson, Kexin Yang, Dan Roy, Kenneth R. Koedinger, Carolyn P. Rosé, Justin Reich:
Practice-Based Teacher Questioning Strategy Training with ELK: A Role-Playing Simulation for Eliciting Learner Knowledge. Proc. ACM Hum. Comput. Interact. 5(CSCW1): 51:1-51:27 (2021) - [c237]Peter Schaldenbrand, Nikki G. Lobczowski, J. Elizabeth Richey, Shivang Gupta, Elizabeth A. McLaughlin, Adetunji Adeniran, Kenneth R. Koedinger:
Computer-Supported Human Mentoring for Personalized and Equitable Math Learning. AIED (2) 2021: 308-313 - [c236]Daniel Weitekamp III, Erik Harpstead, Kenneth R. Koedinger:
Toward Stable Asymptotic Learning with Simulated Learners. AIED (2) 2021: 390-394 - [c235]Xu Wang, Carolyn P. Rosé, Ken Koedinger:
Seeing Beyond Expert Blind Spots: Online Learning Design for Scale and Quality. CHI 2021: 51:1-51:14 - [c234]Judith Odili Uchidiuno, Jessica Hammer, Ken Koedinger, Amy Ogan:
Fostering Equitable Help-Seeking for K-3 Students in Low Income and Rural Contexts. CHI 2021: 684:1-684:14 - [c233]Judith Uchidiuno, Ken Koedinger, Amy Ogan:
Teacher Perspectives on Peer-Peer Collaboration and Education Technologies in Rural Tanzanian Classrooms. COMPASS 2021: 14-26 - [c232]Napol Rachatasumrit, Kenneth R. Koedinger:
Toward Improving Student Model Estimates through Assistance Scores in Principle and in Practice. EDM 2021 - [c231]Yun Huang, Nikki G. Lobczowski, J. Elizabeth Richey, Elizabeth A. McLaughlin, Michael W. Asher, Judith M. Harackiewicz, Vincent Aleven, Kenneth R. Koedinger:
A General Multi-method Approach to Data-Driven Redesign of Tutoring Systems. LAK 2021: 161-172 - [i2]Daniel Weitekamp III, Christopher MacLellan, Erik Harpstead, Kenneth R. Koedinger:
Decomposed Inductive Procedure Learning. CoRR abs/2110.13233 (2021) - 2020
- [j40]Nesra Yannier, Scott E. Hudson, Kenneth R. Koedinger:
Active Learning is About More Than Hands-On: A Mixed-Reality AI System to Support STEM Education. Int. J. Artif. Intell. Educ. 30(1): 74-96 (2020) - [c230]Yun Huang, Vincent Aleven, Elizabeth A. McLaughlin, Kenneth R. Koedinger:
A General Multi-method Approach to Design-Loop Adaptivity in Intelligent Tutoring Systems. AIED (2) 2020: 124-129 - [c229]J. Elizabeth Richey, Nikki G. Lobczowski, Paulo F. Carvalho, Kenneth R. Koedinger:
Comprehensive Views of Math Learners: A Case for Modeling and Supporting Non-math Factors in Adaptive Math Software. AIED (1) 2020: 460-471 - [c228]Daniel Weitekamp III, Zihuiwen Ye, Napol Rachatasumrit, Erik Harpstead, Kenneth R. Koedinger:
Investigating Differential Error Types Between Human and Simulated Learners. AIED (1) 2020: 586-597 - [c227]Nicholas Diana, John C. Stamper, Ken Koedinger:
Towards Value-Adaptive Instruction: A Data-Driven Method for Addressing Bias in Argument Evaluation Tasks. CHI 2020: 1-11 - [c226]Daniel Weitekamp III, Erik Harpstead, Kenneth R. Koedinger:
An Interaction Design for Machine Teaching to Develop AI Tutors. CHI 2020: 1-11 - [c225]Nicholas Diana, Jessica Hammer, John C. Stamper, Kenneth R. Koedinger:
Persuasion Invasion: Reducing Bias with Value-Adaptive Instruction. CHI PLAY (Companion) 2020: 50-53 - [c224]Steven Dang, Kenneth R. Koedinger:
The Ebb and Flow of Student Engagement: Measuring motivation through temporal pattern of self-regulation. EDM 2020 - [c223]Xu Wang, Meredith M. Thompson, Kexin Yang, Dan Roy, Kenneth R. Koedinger, Carolyn Penstein Rosé, Justin Reich:
Practice-Based Teacher Education With ELK: A Role-Playing Simulation for Eliciting Learner Knowledge. ICLS 2020 - [c222]Peter Brusilovsky, Ken Koedinger, David A. Joyner, Thomas W. Price:
Building an Infrastructure for Computer Science Education Research and Practice at Scale. L@S 2020: 211-213 - [e3]Thomas W. Price, Peter Brusilovsky, Sharon I-Han Hsiao, Ken Koedinger, Yang Shi:
Proceedings of 4th Educational Data Mining in Computer Science Education (CSEDM) Workshop co-located with the 13th Educational Data Mining Conference (EDM 2020), Virtual Event, July 10, 2020. CEUR Workshop Proceedings 2734, CEUR-WS.org 2020 [contents]
2010 – 2019
- 2019
- [j39]Carolyn P. Rosé, Elizabeth A. McLaughlin, Ran Liu, Kenneth R. Koedinger:
Explanatory learner models: Why machine learning (alone) is not the answer. Br. J. Educ. Technol. 50(6): 2943-2958 (2019) - [c221]Nicholas Diana, John C. Stamper, Kenneth R. Koedinger:
Online Assessment of Belief Biases and Their Impact on the Acceptance of Fallacious Reasoning. AIED (2) 2019: 62-66 - [c220]Nicholas Diana, John C. Stamper, Ken Koedinger:
Predicting Bias in the Evaluation of Unlabeled Political Arguments. CogSci 2019: 1640-1646 - [c219]Yugo Hayashi, Ken Koedinger:
What are you talking about?: A Cognitive Task Analysis of how specificity in communication facilitates shared perspective in a confusing collaboration task. CogSci 2019: 1887-1893 - [c218]Judith Uchidiuno, Evelyn Yarzebinski, Emilio Vargas-Vite, Ken Koedinger, Amy Ogan:
The Effectiveness of Publicly vs. Privately Assigned Group Leaders Among Learners in Rural Villages in Tanzania. CSCL 2019 - [c217]Judith Uchidiuno, Evelyn Yarzebinski, Emily Keebler, Kenneth R. Koedinger, Amy Ogan:
Learning from african classroom pedagogy to increase student engagement in education technologies. COMPASS 2019: 99-110 - [c216]Steven Dang, Ken Koedinger:
Exploring the Link Between Motivations and Gaming. EDM 2019 - [c215]Daniel Weitekamp III, Erik Harpstead, Christopher J. MacLellan, Napol Rachatasumrit, Kenneth R. Koedinger:
Toward Near Zero-Parameter Prediction Using a Computational Model of Student Learning. EDM 2019 - [c214]Khushboo Thaker, Paulo Carvalho, Kenneth R. Koedinger:
Comprehension Factor Analysis: Modeling student's reading behaviour: Accounting for reading practice in predicting students' learning in MOOCs. LAK 2019: 111-115 - [c213]Xu Wang, Srinivasa Teja Talluri, Carolyn P. Rosé, Kenneth R. Koedinger:
UpGrade: Sourcing Student Open-Ended Solutions to Create Scalable Learning Opportunities. L@S 2019: 17:1-17:10 - 2018
- [j38]Judith Uchidiuno, Ken Koedinger, Jessica Hammer, Evelyn Yarzebinski, Amy Ogan:
How Do English Language Learners Interact with Different Content Types in MOOC Videos? Int. J. Artif. Intell. Educ. 28(4): 508-527 (2018) - [c212]Erik Harpstead, Christopher J. MacLellan, Robert P. Marinier, Kenneth R. Koedinger:
Towards Natural Cognitive System Training Interactions: A Preliminary Framework. AAAI Spring Symposia 2018 - [c211]Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, Kenneth R. Koedinger:
Learning Cognitive Models Using Neural Networks. AIED (1) 2018: 43-56 - [c210]Nicholas Diana, John C. Stamper, Ken Koedinger:
An Instructional Factors Analysis of an Online Logical Fallacy Tutoring System. AIED (1) 2018: 86-97 - [c209]Paulo F. Carvalho, Kody Manke, Ken Koedinger:
Not all Active Learning is Equal: Predicting and Explaining Improves Transfer Relative to Answering Practice Questions. CogSci 2018 - [c208]Judith Uchidiuno, Evelyn Yarzebinski, Michael A. Madaio, Nupur Maheshwari, Ken Koedinger, Amy Ogan:
Designing Appropriate Learning Technologies for School vs Home Settings in Tanzanian Rural Villages. COMPASS 2018: 9:1-9:11 - [c207]Paulo F. Carvalho, Min Gao, Benjamin A. Motz, Ken Koedinger:
Analyzing the relative learning benefits of completing required activities and optional readings in online courses. EDM 2018 - [c206]Kenneth R. Koedinger, Richard Scheines, Peter Schaldenbrand:
Is the Doer Effect Robust Across Multiple Data Sets? EDM 2018 - [c205]Clifford A. Shaffer, Peter Brusilovsky, Kenneth R. Koedinger, Stephen H. Edwards:
CS Education Infrastructure for All: Interoperability for Tools and Data Analytics (Abstract Only). SIGCSE 2018: 1063 - [e2]Rose Luckin, Scott R. Klemmer, Kenneth R. Koedinger:
Proceedings of the Fifth Annual ACM Conference on Learning at Scale, London, UK, June 26-28, 2018. ACM 2018 [contents] - [i1]Devendra Singh Chaplot, Christopher MacLellan, Ruslan Salakhutdinov, Kenneth R. Koedinger:
Learning Cognitive Models using Neural Networks. CoRR abs/1806.08065 (2018) - 2017
- [j37]Kelly Rivers, Kenneth R. Koedinger:
Data-Driven Hint Generation in Vast Solution Spaces: a Self-Improving Python Programming Tutor. Int. J. Artif. Intell. Educ. 27(1): 37-64 (2017) - [j36]Eliane Stampfer Wiese, Kenneth R. Koedinger:
Designing Grounded Feedback: Criteria for Using Linked Representations to Support Learning of Abstract Symbols. Int. J. Artif. Intell. Educ. 27(3): 448-474 (2017) - [c204]Nicholas Diana, Michael Eagle, John C. Stamper, Kenneth R. Koedinger:
Teaching Informal Logical Fallacy Identification with a Cognitive Tutor. AIED 2017: 605-608 - [c203]James Derek Lomas, Kenneth R. Koedinger, Nirmal Patel, Sharan Shodhan, Nikhil Poonwala, Jodi L. Forlizzi:
Is Difficulty Overrated?: The Effects of Choice, Novelty and Suspense on Intrinsic Motivation in Educational Games. CHI 2017: 1028-1039 - [c202]Paulo F. Carvalho, Elizabeth A. McLaughlin, Ken Koedinger:
Is there an explicit learning bias? Students beliefs, behaviors and learning outcomes. CogSci 2017 - [c201]Nicholas Diana, John C. Stamper, Kenneth R. Koedinger:
Teaching Informal Logical Fallacy Identification with a Cognitive Tutor. EDM 2017 - [c200]Ran Liu, Kenneth R. Koedinger:
Closing the loop: Automated data-driven cognitive model discoveries lead to improved instruction and learning. EDM 2017 - [c199]Ran Liu, Kenneth R. Koedinger:
Towards reliable and valid measurement of individualized student parameters. EDM 2017 - [c198]Ran Liu, Kenneth R. Koedinger, John C. Stamper, Philip I. Pavlik Jr.:
Sharing and Reusing Data and Analytic Methods with LearnSphere. EDM 2017 - [c197]Ken Koedinger, Ran Liu, John C. Stamper, Candace Thille, Phil Pavlik:
Community based educational data repositories and analysis tools. LAK 2017: 524-525 - [c196]Steven Dang, Michael Yudelson, Kenneth R. Koedinger:
Detecting Diligence with Online Behaviors on Intelligent Tutoring Systems. L@S 2017: 51-59 - [c195]Judith Uchidiuno, Jessica Hammer, Evelyn Yarzebinski, Kenneth R. Koedinger, Amy Ogan:
Characterizing ELL Students' Behavior During MOOC Videos Using Content Type. L@S 2017: 185-188 - 2016
- [j35]Kenneth R. Koedinger, Vincent Aleven:
An Interview Reflection on "Intelligent Tutoring Goes to School in the Big City". Int. J. Artif. Intell. Educ. 26(1): 13-24 (2016) - [j34]Vincent Aleven, Ido Roll, Bruce M. McLaren, Kenneth R. Koedinger:
Help Helps, But Only So Much: Research on Help Seeking with Intelligent Tutoring Systems. Int. J. Artif. Intell. Educ. 26(1): 205-223 (2016) - [j33]Vincent Aleven, Bruce M. McLaren, Jonathan Sewall, Martin Van Velsen, Octav Popescu, Sandra Demi, Michael A. Ringenberg, Kenneth R. Koedinger:
Example-Tracing Tutors: Intelligent Tutor Development for Non-programmers. Int. J. Artif. Intell. Educ. 26(1): 224-269 (2016) - [j32]Nesra Yannier, Scott E. Hudson, Eliane Stampfer Wiese, Kenneth R. Koedinger:
Adding Physical Objects to an Interactive Game Improves Learning and Enjoyment: Evidence from EarthShake. ACM Trans. Comput. Hum. Interact. 23(4): 26:1-26:31 (2016) - [j31]Kenneth R. Koedinger, Michael Yudelson, Philip I. Pavlik Jr.:
Testing Theories of Transfer Using Error Rate Learning Curves. Top. Cogn. Sci. 8(3): 589-609 (2016) - [c194]James Derek Lomas, Jodi Forlizzi, Nikhil Poonwala, Nirmal Patel, Sharan Shodhan, Kishan Patel, Kenneth R. Koedinger, Emma Brunskill:
Interface Design Optimization as a Multi-Armed Bandit Problem. CHI 2016: 4142-4153 - [c193]Rony Patel, Ran Liu, Kenneth R. Koedinger:
When to Block versus Interleave Practice? Evidence Against Teaching Fraction Addition before Fraction Multiplication. CogSci 2016 - [c192]Eliane Wiese, Rony Patel, Kenneth R. Koedinger:
Benefits for Grounded Feedback over Correctness in a Fraction Addition Tutor. CogSci 2016 - [c191]Eliane Wiese, Rony Patel, Kenneth R. Koedinger:
Why Sense-Making through Magnitude May Be Harder for Fractions than for Whole Numbers. CogSci 2016 - [c190]Christopher J. MacLellan, Erik Harpstead, Rony Patel, Kenneth R. Koedinger:
The Apprentice Learner architecture: Closing the loop between learning theory and educational data. EDM 2016: 151-158 - [c189]Devendra Singh Chaplot, Yiming Yang, Jaime G. Carbonell, Kenneth R. Koedinger:
Data-driven Automated Induction of Prerequisite Structure Graphs. EDM 2016: 318-323 - [c188]Kenneth R. Koedinger, Elizabeth A. McLaughlin:
Closing the Loop with Quantitative Cognitive Task Analysis. EDM 2016: 412-417 - [c187]Nicholas Diana, Michael Eagle, John C. Stamper, Kenneth R. Koedinger:
Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC Data. EDM 2016: 583-584 - [c186]