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Ken Koedinger
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- affiliation: Carnegie Mellon University, Pittsburgh, USA
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2020 – today
- 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) - [c251]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 - [c250]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 - [c249]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 - [c248]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 - [c247]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 - [c246]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 - [c245]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 - [c244]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 - [c243]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 - [c242]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] - [i6]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) - [i5]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) - [i4]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) - [i3]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) - 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) - [c241]Nicholas Diana, John C. Stamper, Ken Koedinger, Jessica Hammer:
Debiasing Politically Motivated Reasoning with Value-Adaptive Instruction. AIED (1) 2022: 140-152 - [c240]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 - [c239]Thiemo Wambsganss, Matthias Söllner, Kenneth R. Koedinger, Jan Marco Leimeister:
Adaptive Empathy Learning Support in Peer Review Scenarios. CHI 2022: 227:1-227:17 - [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]Kelly Rivers, Erik Harpstead, Kenneth R. Koedinger:
Learning Curve Analysis for Programming: Which Concepts do Students Struggle With? ICER 2016: 143-151 - [c185]Noboru Matsuda, Nikolaos Barbalios, Zhengzheng Zhao, Anya Ramamurthy, Gabriel J. Stylianides, Kenneth R. Koedinger:
Tell Me How to Teach, I'll Learn How to Solve Problems. ITS 2016: 111-121 - [c184]Ran Liu, Rony Patel, Kenneth R. Koedinger:
Modeling common misconceptions in learning process data. LAK 2016: 369-377 - [c183]Kenneth R. Koedinger, Elizabeth A. McLaughlin, Julianna Zhuxin Jia, Norman L. Bier:
Is the doer effect a causal relationship?: how can we tell and why it's important. LAK 2016: 388-397 - [c182]Judith Uchidiuno, Amy Ogan, Kenneth R. Koedinger, Evelyn Yarzebinski, Jessica Hammer:
Browser Language Preferences as a Metric for Identifying ESL Speakers in MOOCs. L@S 2016: 277-280 - [c181]Ken Koedinger:
Practical Learning Research at Scale. L@S 2016: 429 - 2015
- [j30]Nan Li, Noboru Matsuda, William W. Cohen, Kenneth R. Koedinger:
Integrating representation learning and skill learning in a human-like intelligent agent. Artif. Intell. 219: 67-91 (2015) - [j29]Noboru Matsuda, William W. Cohen, Kenneth R. Koedinger:
Teaching the Teacher: Tutoring SimStudent Leads to More Effective Cognitive Tutor Authoring. Int. J. Artif. Intell. Educ. 25(1): 1-34 (2015) - [j28]Philip I. Pavlik, Michael Yudelson, Kenneth R. Koedinger:
A Measurement Model of Microgenetic Transfer for Improving Instructional Outcomes. Int. J. Artif. Intell. Educ. 25(3): 346-379 (2015) - [j27]Karrie E. Godwin, Derek Lomas, Kenneth R. Koedinger, Anna V. Fisher:
Monster Mischief: Designing a Video Game to Assess Selective Sustained Attention. Int. J. Gaming Comput. Mediat. Simulations 7(4): 18-39 (2015) - [c180]Kenneth R. Koedinger, Noboru Matsuda, Christopher J. MacLellan, Elizabeth A. McLaughlin:
Methods for Evaluating Simulated Learners: Examples from SimStudent. AIED Workshops 2015 - [c179]Christopher J. MacLellan, Erik Harpstead, Eliane Stampfer Wiese, Mengfan Zou, Noboru Matsuda, Vincent Aleven, Kenneth R. Koedinger:
Authoring Tutors with Complex Solutions: A Comparative Analysis of Example Tracing and SimStudent. AIED Workshops 2015 - [c178]Nesra Yannier, Kenneth R. Koedinger, Scott E. Hudson:
Learning from Mixed-Reality Games: Is Shaking a Tablet as Effective as Physical Observation? CHI 2015: 1045-1054 - [c177]Danny Koh, Kenneth R. Koedinger, Carolyn P. Rosé, David F. Feldon:
Expertise in Cognitive Task Analysis Interviews. CogSci 2015 - [c176]Rony Patel, Kenneth R. Koedinger:
Does Learning Magnitude Knowledge help Students Learn Procedural Knowledge or Vice Versa? CogSci 2015 - [c175]Eliane Wiese, Rony Patel, Jennifer K. Olsen, Kenneth R. Koedinger:
Transitivity is Not Obvious: Probing Prerequisites for Learning. CogSci 2015 - [c174]Christopher J. MacLellan, Ran Liu, Kenneth R. Koedinger:
Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning. EDM 2015: 53-60 - [c173]Xu Wang, Diyi Yang, Miaomiao Wen, Kenneth R. Koedinger, Carolyn P. Rosé:
Investigating How Student's Cognitive Behavior in MOOC Discussion Forum Affect Learning Gains. EDM 2015: 226-233 - [c172]Mohammad Hassan Falakmasir, Michael Yudelson, Steven Ritter, Kenneth R. Koedinger:
Spectral Bayesian Knowledge Tracing. EDM 2015: 360-363 - [c171]Ran Liu, Kenneth R. Koedinger:
Variations in Learning Rate: Student Clustering Based on Systematic Residual Error Patterns Across Practice Opportunities. EDM 2015: 420-423 - [c170]Kenneth R. Koedinger, Jihee Kim, Julianna Zhuxin Jia, Elizabeth A. McLaughlin, Norman L. Bier:
Learning is Not a Spectator Sport: Doing is Better than Watching for Learning from a MOOC. L@S 2015: 111-120 - 2014
- [j26]Erin Walker, Nikol Rummel, Kenneth R. Koedinger:
Adaptive Intelligent Support to Improve Peer Tutoring in Algebra. Int. J. Artif. Intell. Educ. 24(1): 33-61 (2014) - [j25]