Publications

2024

Wei, Yumou, Carvalho, Paulo F, and Stamper, John (2024).  Uncovering Name-Based Biases in Large Language Models Through Simulated Trust GameIn arXiv preprint arXiv:2404.14682.

Kwon, Christine, Butler, Darren, Uchidiuno, Judith Odili, Stamper, John, and Ogan, Amy (2024).  Investigating Demographics and Motivation in Engineering Education Using Radio and Phone-Based Educational TechnologiesIn Proceedings of the CHI Conference on Human Factors in Computing Systems1-15

Xiao, Ruiwei, Hou, Xinying, and Stamper, John (2024).  Exploring How Multiple Levels of GPT-Generated Programming Hints Support or Disappoint NovicesIn Extended Abstracts of the CHI Conference on Human Factors in Computing Systems1-10

Musabirov, Ilya, Reza, Mohi, Moore, Steven, Chen, Pan, Kumar, Harsh, Tong, Li, Song, Fred Haochen, Shi, Jiakai, Choy, Koby, Price, Thomas, and Stamper, John and others (2024).  Platform-based Adaptive Experimental Research in Education: Lessons Learned from Digital Learning ChallengeIn The Fourteenth International Conference on Learning Analytics & Knowledge (LAK24): Learning Analytics in the Age of Artificial Intelligence37-40

2023

Khosravi, Hassan, Denny, Paul, Moore, Steven, and Stamper, John (2023).  Learnersourcing in the age of AI: Student, educator and machine partnerships for content creationIn Computers and Education: Artificial Intelligence100151.  Elsevier.

Moore, Steven, Nguyen, Huy A, Chen, Tianying, and Stamper, John (2023).  Assessing the quality of multiple-choice questions using gpt-4 and rule-based methodsIn European Conference on Technology Enhanced Learning229-245

Carney, John, Belmont, Nancy, King, James, Stamper, John, and Kwon, Christine (2023).  AI/ML-Driven Content Repository MaintenanceIn Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC).

Ferreira, Goncalo, Oliveira, Eva, Stamper, John, Coelho, Antonio, Paredes, Hugo, and Rodrigues, Nuno F (2023).  A Human-Computer Interaction Perspective on Clinical Decision Support Systems: A Systematic Review of Usability, Barriers, and Recommendations for ImprovementIn 2023 IEEE 11th International Conference on Serious Games and Applications for Health (SeGAH).

Oliveira, Eva, Pacheco, Paulo, Santos, Fatima, Coimbra, Joao, Stamper, John, Coelho, Antonio, Paredes, Hugo, Alves, Joana, and Rodrigues, Nuno Feixa (2023).  The Role of Kiosks on Health Services: A Systematic ReviewIn 2023 IEEE 11th International Conference on Serious Games and Applications for Health (SeGAH).

Moore, Steven, Nguyen, Huy Anh, and Stamper, John (2023).  Crowdsourcing the Evaluation of Multiple-Choice Questions Using Item-Writing Flaws and Bloom's TaxonomyIn Proceedings of the Tenth ACM Conference on Learning@ Scale.

Moore, Steven, Nguyen, Huy, Bier, Norman, Domadia, Tanvi, and Stamper, John (2023).  Who Writes Tomorrow’s Learning Activities? Exploring Community College Student Participation in LearnersourcingIn Proceedings of the 17th International Conference of the Learning SciencesInternational Society of the Learning Sciences.

Nguyen, Huy, Hou, Xinying, Stec, Hayden, Di, Sarah, Stamper, John, and McLaren, Bruce (2023).  Examining the Learning Benefits of Different Types of Prompted Self-explanation in a Decimal Learning GameIn Proceedings of the International Conference on Artificial Intelligence in EducationSpringer.

Moore, Steven, Tong, Richard, Singh, Anjali, Liu, Zitao, Hu, Xiangen, Lu, Yu, Liang, Joleen, Cao, Chen, Denny, Paul, Khosravi, Hassan, Brooks, Christopher, and Stamper, John (2023).  Empowering Education with LLMs - the Next-Gen Interface and Content GenerationIn Proceedings of the International Conference on Artificial Intelligence in EducationSpringer.

Stamper, John, Gaind, Bharat, Thankachan, Karun, Nguyen, Huy, and Moore, Steven (2023).  Hierarchical Concept Map Generation from Course DataIn AAAI 2023 Workshop on Artificial Intelligence in Education (AI4Edu).

Meyers, Peter, Han, Peter, Grewala, Razik, Potnisa, Mitali, and Stamper, John (2023).  Focal: A Proposed Method of Leveraging LLMs for Automating AssessmentsIn 31st International Conference on Computers in Education Conference Vol II, ICCE 2023349-358

Okimoto, Tomoko, Johnson, Matthew, Nguyen, Huy, Moore, Steven, Eagle, Michael, and Stamper, John (2023).  Tracking Knowledge for Learning Japanese as a 2nd LanguageIn 31st International Conference on Computers in Education Conference Vol I, ICCE 2023766-768

Kwon, Christine, Stamper, John, King, James, Lam, Joanie, and Carney, John (2023).  Multimodal Data Support in Knowledge Objects for Real-time Knowledge SharingIn Proceedings of CROSSMMLA Workshop at the 13th International Conference on Learning Analytics & Knowledge.

Kwon, Christine, Butler, Ren, Stamper, John, Ogan, Amy, Forcier, Angela, Fitzgerald, Erin, and Wambuzi, Samson (2023).  Learning Analytics for Last Mile Students in AfricaIn Companion Proceedings 13th International Conference on Learning Analytics & Knowledge153-155

Moore, Steven, Nguyen, Huy, and Stamper, John (2023).  Students’ Domain Confidence and their Participation in Optional Learnersourcing ActivitiesIn Companion Proceedings 13th International Conference on Learning Analytics & Knowledge147-149

Moore, Steven, Tong, Richard, Singh, Anjali, Liu, Zitao, Hu, Xiangen, Lu, Yu, Liang, Joleen, Cao, Chen, Khosravi, Hassan, Denny, Paul, Brooks, Chris, and Stamper, John (2023).  Workshop on Empowering Education with LLMs-the Next-Gen Interface and Content Generation. In CEUR Workshop Proceedings3487 ,  32-37

Bier, Norman, Stamper, John, Moore, Steven, Siegel, Darren, and Anbar, Ariel (2023).  OLI Torus: a next-generation, open platform for adaptive courseware development, delivery, and researchIn Companion Proceedings 13th International Conference on Learning Analytics & Knowledge57-60

2022

Bhat, Shravya, Nguyen, Huy, Moore, Steven , StamperJohn, Sakr, Majd and Nyberg, Eric (2022).  Towards Automated Generation and Evaluation of Questions in Educational Domains. In Proceedings of the 15th International Conference on Educational Data Mining701-704.  International Educational Data Mining Society.

Diana, Nicholas, Stamper, John, Koedinger, Kenneth, and Hammer, Jessica (2022).  Debiasing Politically Motivated Reasoning with Value-Adaptive InstructionIn International Conference on Artificial Intelligence in EducationSpringer.

Diana, Nicholas, and Stamper, John (2022).  Reducing Bias in a Misinformation Classification Task with Value-Adaptive InstructionIn International Conference on Artificial Intelligence in EducationSpringer.

Moore, Steven, Nguyen, Huy, and Stamper, John (2022).  Leveraging Students to Generate Skill Tags that Inform Learning AnalyticsIn Proceedings of the 16th International Conference of the Learning Sciences791-798.  International Society of the Learning Sciences.

Moore, Steven, Nguyen, Huy, and Stamper, John (2022).  Participation and Success with Optional Self-Explanation for Students in Online Undergraduate Chemistry CoursesIn Proceedings of the 16th International Conference of the Learning Sciences1381-1384.  International Society of the Learning Sciences.

Moore, Steven, Nguyen, Huy A., Bier, Norman, Domadia, Tanvi, and Stamper, John (2022).  Assessing the Quality of Student-Generated Short Answer Questions Using GPT-3In Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption243-257.  Springer International Publishing.

Nguyen, Huy A., Bhat, Shravya, Moore, Steven, Bier, Norman, and Stamper, John (2022).  Towards Generalized Methods for Automatic Question Generation in Educational DomainsIn Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption272-284.  Springer International Publishing.

Moore, Steven, Stamper, John, Brooks, Christopher, Denny, Paul, and Khosravi, Hassan (2022).  Learnersourcing: Student-Generated Content @ ScaleIn Proceedings of the Ninth ACM Conference on Learning @ Scale259–262.  Association for Computing Machinery.

Carmichael, Ted, Stamper, John, and Carney, John (2022).  Developing a Continuous, Rather Than Binary, Classification for Measuring STEM Jobs. In 6th APSCE International Conference on Computational Thinking and STEM Education 2022 (CTE-STEM 2022).

2021

Moore, Steven, Nguyen, Huy Anh, and Stamper, John (2021).  Examining the Effects of Student Participation and Performance on the Quality of Learnersourcing Multiple-Choice Questions. In Proceedings of the Eighth ACM Conference on Learning@ Scale. 209-220

Nguyen, Huy, Lim, Michelle, Moore, Steven, Nyberg, Eric, Sakr, Majd, and Stamper, John (2021).  Exploring Metrics for the Analysis of Code Submissions in an Introductory Data Science Course. In LAK21: 11th International Learning Analytics and Knowledge Conference. 632-638

Moore, Steven, Stamper, John, Bier, Norman, and Blink, Mary Jean (2021).  A Human-Centered Approach to Data Driven Iterative Course Improvement. In International Conference on Remote Engineering and Virtual Instrumentation. 742-761

2020

Diana, Nicholas, Hammer, Jessica, Stamper, John, and Koedinger, Kenneth (2020).  Persuasion Invasion: Reducing Bias with Value-Adaptive Instruction. In Extended Abstracts of the 2020 Annual Symposium on Computer-Human Interaction in Play. 50-53

Diana, Nicholas, Stamper, John, and Koedinger, Kenneth (2020).  Towards Value-Adaptive Instruction: A Data-Driven Method for Addressing Bias in Argument Evaluation TasksIn Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1-11

Moore, Steven, Nguyen, Huy, and Stamper, John (2020).  Utilizing Crowdsourcing and Topic Modeling to Generate Knowledge Components for Math and Writing Problems. In Proceedings of the 28th International Conference on Computers in Education31-40

Nguyen, Huy, Guo, Yuqing, Stamper, John, and McLaren, Bruce (2020).  Improving Students’ Problem-solving Flexibility in Nonroutine MathematicsIn International Conference on Artificial Intelligence in Education409-413.  Springer.

Nguyen, Huy, Hou, Xinying, Stamper, John, and McLaren, Bruce (2020).  Moving beyond Test Scores: Analyzing the Effectiveness of a Digital Learning Game through Learning AnalyticsIn Proceedings of the International Conference on Educational Data Mining487-495

Moore, Steven, Nguyen, Huy, and Stamper, John (2020).  Evaluating Crowdsourcing and Topic Modeling in Generating Knowledge Components from ExplanationsIn Proceedings of the International Conference on Artificial Intelligence in Education398-410.  Springer.

Moore, Steven, Nguyen, Huy, and Stamper, John (2020).  Crowdsourcing Explanations for Improving Assessment Content and Identifying Knowledge ComponentsIn Proceedings of the 15th International Conference of the Learning Sciences2627-2628.  International Society of the Learning Sciences.

Moore, Steven, Nguyen, Huy, and Stamper, John (2020).  Towards Crowdsourcing the Identification of Knowledge ComponentsIn Proceedings of the Seventh (2020) ACM Conference on Learning @ Scale245-248

2019

Liu, Ran, Stamper, John, Davenport, Jodi, Crossley, Scott, McNamara, Danielle, Nzinga, Kalonji, and Sherin, Bruce (2019).  Learning linkages: Integrating data streams of multiple modalities and timescales. In Journal of Computer Assisted Learning. 35 (1),  99-109 Wiley Online Library.

Stamper, John, and Moore, Steven (2019).  Exploring Teachable Humans and Teachable Agents: Human Strategies Versus Agent Policies and the Basis of ExpertiseIn Artificial Intelligence in Education269-274.  Springer International Publishing.

Moore, Steven, and Stamper, John (2019).  Exploring Expertise through Visualizing Agent Policies and Human Strategies in Open-Ended Games.. In EDM (Workshops)30-37

Moore, Steven, and Stamper, John (2019).  Decision Support for an Adversarial Game Environment Using Automatic Hint Generation. In Intelligent Tutoring Systems. 82-88 Springer International Publishing. [Best Short Paper Finalist]

Zhang, Chuankai, Huang, Yanzun, Wang, Jingyu, Lu, Dongyang, Fang, Weiqi, Stamper, John, Fancsali, Stephen, Holstein, Kenneth, and Aleven, Vincent (2019).  Early Detection of Wheel Spinning: Comparison across Tutors, Models, Features, and Operationalizations.. In International Conference on Educational Data Mining. EDM2019.

Diana, Nicholas, Stamper, John, and Koedinger, Kenneth (2019).  Online Assessment of Belief Biases and Their Impact on the Acceptance of Fallacious ReasoningIn Artificial Intelligence in Education62-66.  Springer International Publishing.

Diana, Nicholas, Stamper, John, and Koedinger, Ken (2019).  Predicting Bias in the Evaluation of Unlabeled Political Arguments.. In CogSci1640-1646

Nguyen, Huy, Wang, Yeyu, Stamper, John, and McLaren, Bruce M (2019).  Using Knowledge Component Modeling to Increase Domain Understanding in a Digital Learning Game. In International Conference on Educational Data Mining.

Wang, Yeyu, Nguyen, Huy, Harpstead, Erik, Stamper, John, and McLaren, Bruce M (2019).  How does order of gameplay impact learning and enjoyment in a digital learning game?. In International Conference on Artificial Intelligence in Education.

Stamper, John, Carvalho, Paulo, Moore, Steven, and Koedinger, Kenneth (2019).  Tigris: An Online Workflow Tool for Sharing Educational Data and Analytic Methods. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 183

Baik, Jason, Stamper, John, and Rangwala, Huzefa (2019).  MOOC Effort Dashboard: An Interactive Web Dashboard Built in R. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 167

Soniya, Gadgil, Moore, Steven, and Stamper, John (2019).  How does Performance in an Online Primer Predict Achievement in a Future Computer Science Course?. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 300-306

Koedinger, Kenneth and Stamper, John, and Carvalho, Paulo (2019).  Sharing and Reusing Data and Analytic Methods with LearnSphere. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 328-331

Moore, Steven, Stamper, John, and Soniya, Gadgil (2019).  Human-Centered Data Science for Educational Technology Improvement using Crowd Workers. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 341-347

Koedinger, Kenneth and Stamper, John, and Carvalho, Paulo (2019).  LearnSphere: Learning Analytics Development and Sharing Made Simple. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 996

Carmichael, Ted and Blink, Mary Jean, and Stamper, John (2019).  TutorGen SCALE ® - Student Centered Adaptive Learning Engine. In Companion Proceedings 9th International Conference on Learning Analytics & Knowledge. 964-973

2018

Liu, Ran, Stamper, John, and Davenport, Jodi (2018).  A Novel Method for the In-Depth Multimodal Analysis of Student Learning Trajectories in Intelligent Tutoring Systems. In Journal of Learning Analytics. 5 (1),  41-54

Diana, Nicholas, Stamper, John, and Koedinger, Ken (2018).  An Instructional Factors Analysis of an Online Logical Fallacy Tutoring System. In International Conference on Artificial Intelligence in Education. 86-97

Diana, Nicholas, Eagle, Michael, Stamper, John, Grover, Shuchi, Bienkowski, Marie, and Basu, Satabdi (2018).  Data-driven Generation of Rubric Criteria from an Educational Programming Environment. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge. 16-20 ACM.

Eagle, Michael, Corbett, Albert, Stamper, John, and Mclaren, Bruce (2018).  Predicting Individualized Learner Models across Tutor Lessons. In Proceedings of the 11th International Conference on Educational Data Mining. 474-478

Eagle, Michael, Carmichael, Ted, Stokes, Jessica, Blink, Mary Jean, Stamper, John, and Levin, Jason (2018).  Predictive Student Modeling for Interventions in Online Classes. In Proceedings of the 11th International Conference on Educational Data Mining. 619-624

Diana, Nicholas, Eagle, Michael, Stamper, John, Grover, Shuchi, Bienkowski, Marie, and Basu, Satabdi (2018).  Measuring Transfer of Data-Driven Code Features Across Tasks in Alice. In Proceedings of the Educational Data Mining in Computer Science Education (CSEDM) Workshop in conjuction with the 11th International Conference on Educational Data Mining (EDM2018).

Jiang, Bo, Li, Zhixuan, and Stamper, John (2018).  Programming Pathway Clustering Using Tree Edit Distance. In Proceedings of the Educational Data Mining in Computer Science Education (CSEDM) Workshop in conjuction with the 11th International Conference on Educational Data Mining (EDM2018).

Diana, Nicholas, Eagle, Michael, Stamper, John, Grover, Shuchi, Bienkowski, Marie, and Basu, Satabdi (2018).  Peer Tutor Matching for Introductory Programming: Data-Driven Methods to Enable New Opportunities for Help. In Proceedings of the 13th International Conference of the Learning Sciences (ICLS 2018). 1377-1378

Carmichael, Ted, Blink, Mary Jean, Stamper, John, and Gieske, Elizabeth (2018).  Linkage Objects for Generalized Instruction in Coding (LOGIC). In The Thirty-First International Flairs Conference. 442-446

2017

Grover, Shuchi, Basu, Satabdi, Bienkowski, Marie, Eagle, Michael, Diana, Nicholas, and Stamper, John (2017).  A Framework for Using Hypothesis-Driven Approaches to Support Data-Driven Learning Analytics in Measuring Computational Thinking in Block-Based Programming Environments. In ACM Trans. Comput. Educ.. 17 (3),  14:1-14:25 ACM.

Liu, Ran, Koedinger, Kenneth, Stamper, John, and Pavlik, Philip (2017).  Sharing and reusing data and analytic methods with LearnSphereIn Workshop and Tutorials Chairs475-476.

Diana, Nicholas, Eagle, Michael, Stamper, John, Grover, Shuchi, Bienkowski, Marie, and Basu, Satabdi (2017).  An instructor dashboard for real-time analytics in interactive programming assignments. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference. 272-279

Grover, Shuchi, Bienkowski, Marie, Basu, Satabdi, Eagle, Michael, Diana, Nicholas, and Stamper, John (2017).  A Framework for Hypothesis-driven Approaches to Support Data-driven Learning Analytics in Measuring Computational Thinking in Block-based Programming. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference. 530-531 ACM.

Diana, Nicholas, Eagle, Michael, Stamper, John, and Koedinger, Kenneth (2017).  Teaching Informal Logical Fallacy Identification with a Cognitive Tutor. In Artificial Intelligence in Education. 605-608 Springer International Publishing.

Eagle, Michael, Corbett, Albert, Stamper, John, McLaren, Bruce, Baker, Ryan, Wagner, Angela, MacLaren, Benjamin, and Mitchell, Aaron (2017).  Exploring Learner Model Differences Between Students. In Artificial Intelligence in Education. 494-497 Springer International Publishing.

Diana, Nicholas, Eagle, Michael, Stamper, John, Grover, Shuchi, Bienkowski, Marie, and Basu, Satabdi (2017).  Data-Driven Generation of Rubric Parameters from an Educational Programming Environment. In Artificial Intelligence in Education. 490-493 Springer International Publishing.

Diana, Nicholas, Eagle, Michael, Stamper, John C, Grover, Shuchi, Bienkowski, Marie A, and Basu, Satabdi (2017).  Automatic Peer Tutor Matching: Data-Driven Methods to Enable New Opportunities for Help.. In Proceedings of the 10th International Conference on Educational Data Mining (EDM 2017). 372-373

Diana, Nicholas, Eagle, Michael, Stamper, John, and Koedinger, Kenneth (2017).  Teaching Informal Logical Fallacy Identification with a Cognitive Tutor. In Proceedings of the 10th International Conference on Educational Data Mining (EDM 2017). 433-435

Liu, Ran, and Stamper, John C (2017).  Multimodal Data Collection and Analysis of Collaborative Learning through an Intelligent Tutoring System. In MMLA-CrossLAK@ LAK. 47-52

Koedinger, Ken, Liu, Ran, Stamper, John, Thille, Candace, and Pavlik, Phil (2017).  Community Based Educational Data Repositories and Analysis ToolsIn Proceedings of the Seventh International Learning Analytics & Knowledge Conference524-525.  Association for Computing Machinery.

Lang, Charles, Teasley, Stephanie, and Stamper, John (2017).  Building the Learning Analytics Curriculum: WorkshopIn Proceedings of the Seventh International Learning Analytics & Knowledge Conference520-521.  Association for Computing Machinery.

2016

Stamper, John, and Pardos, Zachary A (2016).  The 2010 KDD Cup Competition Dataset: Engaging the machine learning community in predictive learning analytics. In Journal of Learning Analytics. 3 (2),  312-316

Eagle, Michael, Corbett, Albert, Stamper, John, McLaren, Bruce M., Baker, Ryan, Wagner, Angela, MacLaren, Benjamin, and Mitchell, Aaron (2016).  Predicting Individual Differences for Learner Modeling in Intelligent Tutors from Previous Learner Activities. In Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization<. 55-63 ACM. [Best Paper Award]

Eagle, Michael, Corbett, Albert, Stamper, John, McLaren, Bruce, Wagner, Angela, MacLaren, Benjamin, and Mitchell, Aaron (2016).  Estimating Individual Differences for Student Modeling in Intelligent Tutors from Reading and Pretest Data. In Intelligent Tutoring Systems. 133-143 Springer International Publishing. [Best Paper Finalist]

Liu, Ran, Davenport, Jodi, and Stamper, John (2016).  Beyond Log Files: Using Multi-Modal Data Streams towards Data-Driven KC Model Improvement. In 9th International Conference on Educational Data Mining (EDM2016). 436-441

Diana, Nicholas, Stamper, John, and Koedinger, Ken (2016).  Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC Data. In 9th International Conference on Educational Data Mining (EDM2016). 583-584

Matsuda, Noboru, Chandrasekaran, Sanjay, and Stamper, John (2016).  How quickly can wheel spinning be detected?. In 9th International Conference on Educational Data Mining (EDM2016). 607-608

2015

Baker, Ryan, Carney, John, Mitros, Piotr, Saxberg, Bror, and Stamper, John (2015).  The Future of Practical Applications of EDM at Scale. In Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015). 11

Gasevic, Dragan, Martin, Taylor, Pardos, Zachary, Pechenizkiy, Mykola, Stamper, John, and Zaiane, Osmar (2015).  Ethics and privacy in EDM. In Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015). 13

2014

Koedinger, Kenneth R., McLaughlin, Elizabeth A., and Stamper, John C. (2014).  Data-driven Learner Modeling to Understand and Improve Online Learning: MOOCs and Technology to Advance Learning and Learning Research (Ubiquity Symposium). In Ubiquity. 2014 (May),  3:1-3:13 ACM.

Fancsali, Stephen E, Ritter, Steven, Stamper, John C, and Berman, Susan (2014).  Personalization, non-cognitive factors, and grain-size for measurement and analysis in intelligent tutoring systems: implications for GIFT. In Proceedings of the 2nd Annual GIFT Users Symposium. 123-134

Blink, Mary Jean, Stamper, John, and Carmichael, Ted (2014).  SCALE: Student Centered Adaptive Learning Engine. In Intelligent Tutoring Systems. 654-655 Springer International Publishing.

Carmichael, Ted, Hadzikadic, Mirsad, Blink, Mary Jean, and Stamper, John C. (2014).  A Multi-level Complex Adaptive System Approach for Modeling of Schools. In Intelligent Tutoring Systems. 623-624 Springer International Publishing.

2013

Koedinger, Kenneth R, Stamper, John C, Leber, Brett, and Skogsholm, Alida (2013).  LearnLab's DataShop: A Data Repository and Analytics Tool Set for Cognitive Science. In Topics in Cognitive Science. 5 (3),  668-669 Wiley Online Library.

Stamper, John, Eagle, Michael, Barnes, Tiffany, and Croy, Marvin (2013).  Experimental Evaluation of Automatic Hint Generation for a Logic Tutor. In International Journal of Artificial Intelligence in Education. 22 (1-2),  3-17 IOS Press.

Koedinger, Kenneth R, Brunskill, Emma, Baker, Ryan SJd, McLaughlin, Elizabeth A, and Stamper, John (2013).  New Potentials for Data-Driven Intelligent Tutoring System Development and Optimization. In AI Magazine. 34 (3),  27-41 Citeseer.

Koedinger, Kenneth R., Stamper, John C., McLaughlin, Elizabeth A., and Nixon, Tristan (2013).  Using Data-Driven Discovery of Better Student Models to Improve Student Learning. In Artificial Intelligence in Education. 421-430 Springer Berlin Heidelberg.

Stamper, John, Koedinger, Kenneth, and Mclaughlin, Elizabeth (2013).  A comparison of model selection metrics in datashop. In In Proceedings of the 6th International Conference on Educational Data Mining (EDM 2013).

Johnson, Matthew W, Eagle, Michael, Stamper, John, and Barnes, Tiffany (2013).  An Algorithm for Reducing the Complexity of Interaction Networks. In In Proceedings of the 6thInternational Conference on Educational Data Mining (EDM 2013).

Fancsali, Stephen E, Ritter, Steven, Stamper, John, and Nixon, Tristan (2013).  Toward Hyper-Personalized Cognitive Tutors. In AIED 2013 Workshops Proceedings Volume 7. 71-79

Spacco, Jaime, Fossati, Davide, Stamper, John, and Rivers, Kelly (2013).  Towards Improving Programming Habits to Create Better Computer Science Course Outcomes. In Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education. 243-248 ACM.

Hovemeyer, David, Hertz, Matthew, Denny, Paul, Spacco, Jaime, Papancea, Andrei, Stamper, John, and Rivers, Kelly (2013).  CloudCoder: Building a Community for Creating, Assigning, Evaluating and Sharing Programming Exercises (Abstract Only). In Proceeding of the 44th ACM Technical Symposium on Computer Science Education. 742-742 ACM.

Williams, Joseph Jay, Renkl, Alexander, and Koedinger, Ken (2013).  Online Education: A Unique Opportunity for Cognitive Scientists to Integrate Research and. In Proceedings of the Annual Meeting of the Cognitive Science Society, 35 (35).

2012

Stamper, J, Lomas, Derek, Ching, Dixie, Linch, K, and Ritter, S (2012).  Internet scale experimental design and deployment for educational games using BrainPOP. In Proceedings of the 8th Games+ Learning+ Society Conference (GLS 2012). 275-281

Baker, Ryan S. J. d., Duval, Erik, Stamper, John, Wiley, David, and Shum, Simon Buckingham (2012).  Educational Data Mining Meets Learning Analytics. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge. 20-20 ACM.

Koedinger, Kenneth R, McLaughlin, Elizabeth A, and Stamper, John C (2012).  Automated Student Model Improvement. In Proceedings of the 5th International Conference on Educational Data Mining (EDM 2012). 17-24 [Best Paper Award]

Stamper, John C, Lomas, Derek, Ching, Dixie, Ritter, Steve, Koedinger, Kenneth R, and Steinhart, Jonathan (2012).  The Rise of the Super Experiment. In Proceedings of the 5th International Conference on Educational Data Mining (EDM 2012). 196-200

Lomas, Derek, Stamper, John, Muller, Ryan, Patel, Kishan, and Koedinger, Kenneth R. (2012).  The Effects of Adaptive Sequencing Algorithms on Player Engagement within an Online Game. In Intelligent Tutoring Systems. 588-590 Springer Berlin Heidelberg.

Jin, Wei, Barnes, Tiffany, Stamper, John, Eagle, Michael John, Johnson, Matthew W., and Lehmann, Lorrie (2012).  Program Representation for Automatic Hint Generation for a Data-Driven Novice Programming Tutor. In Intelligent Tutoring Systems. 304-309 Springer Berlin Heidelberg.

Ritter, Steve, Nixon, Tristan, Lomas, Derek, Stamper, John, and Ching, Dixie (2012).  Using Time Pressure to Promote Mathematical Fluency. In Intelligent Tutoring Systems. 669-670 Springer Berlin Heidelberg.

2011

Stamper, John, Barnes, Tiffany, and Croy, Marvin (2011).  Enhancing the automatic generation of hints with expert seeding. In International Journal of Artificial Intelligence in Education. 21 (1-2),  153-167 IOS Press.

Barnes, Tiffany, Stamper, John, and Croy, Marvin (2011).  Using Markov decision processes for student problem-solving visualization and automatic hint generation. In Handbook of Educational Data Mining. 467-480 CRC Press.

Stamper, John C., Eagle, Michael, Barnes, Tiffany, and Croy, Marvin (2011).  Experimental Evaluation of Automatic Hint Generation for a Logic Tutor. In Artificial Intelligence in Education. 345-352 Springer Berlin Heidelberg. [Best Paper Finalist]

Stamper, John C., and Koedinger, Kenneth R. (2011).  Human-Machine Student Model Discovery and Improvement Using DataShop. In Artificial Intelligence in Education. 353-360 Springer Berlin Heidelberg.

Stamper, John C., Koedinger, Kenneth R., Baker, Ryan S. J. d., Skogsholm, Alida, Leber, Brett, Demi, Sandy, Yu, Shawnwen, and Spencer, Duncan (2011).  Managing the Educational Dataset Lifecycle with DataShop. In Artificial Intelligence in Education. 557-559 Springer Berlin Heidelberg.

Jin, Wei, Lehmann, Lorrie, Johnson, Matthew, Eagle, Michael, Mostafavi, Behrooz, Barnes, Tiffany, and Stamper, John (2011).  Towards Automatic Hint Generation for a DataDriven Novice Programming TutorIn Workshop on Knowledge Discovery in Educational Data, 17th ACM Conference on Knowledge Discovery and Data Mining.

Stamper, John (2011).  EDM and the 4th Paradigm of Scientific Discovery-Reflections on the 2010 KDD Cup Competition. In Proceedings of the 4th International Conference on Educational Data Mining (EDM 2011). 7

Koedinger, Kenneth, Pavlik Jr, Philip I, Stamper, John, Nixon, Tristan, and Ritter, Steven (2011).  Avoiding problem selection thrashing with conjunctive knowledge tracing. In Proceedings of the 4th International Conference on Educational Data Mining (EDM 2011). 91-100

Stamper, John C., Koedinger, Kenneth R., Baker, Ryan S. J. d., Skogsholm, Alida, Leber, Brett, Demi, Sandy, Yu, Shawnwen, and Spencer, Duncan (2011).  DataShop: A Data Repository and Analysis Service for the Learning Science Community (Interactive Event). In Artificial Intelligence in Education. 628 Springer Berlin Heidelberg.

2010

Tiffany Barnes, and John Stamper (2010).  Automatic Hint Generation for Logic Proof Tutoring Using Historical Data. In Journal of Educational Technology & Society. 13 (1),  3-12 International Forum of Educational Technology & Society.

Koedinger, Kenneth R, d Baker, Ryan SJ, Cunningham, Kyle, Skogsholm, Alida, Leber, Brett, and Stamper, John (2010).  A Data Repository for the EDM Community: The PSLC DataShop. In Handbook of Educational Data Mining. 43 CRC Press.

Stamper, John, Barnes, Tiffany, and Croy, Marvin (2010).  Enhancing the Automatic Generation of Hints with Expert Seeding. In Intelligent Tutoring Systems. 31-40 Springer Berlin Heidelberg. [Best Student Paper Award]

Stamper, John, Koedinger, Ken, Baker, Ryan S. J. d., Skogsholm, Alida, Leber, Brett, Rankin, Jim, and Demi, Sandy (2010).  PSLC DataShop: A Data Analysis Service for the Learning Science Community. In Intelligent Tutoring Systems. 455-455 Springer Berlin Heidelberg.

Koedinger, Kenneth R, and Stamper, John C (2010).  A data driven approach to the discovery of better cognitive models. In Proceedings of the 3rd International Conference on Educational Data Mining (EDM 2010). 325-326

Stamper, John, Barnes, Tiffany, and Croy, Marvin (2010).  Using a Bayesian Knowledge Base for Hint Selection on Domain Specific Problems. In Proceedings of the 3rd International Conference on Educational Data Mining (EDM 2010). 327-328

2009

Stamper, John, and Barnes, Tiffany (2009).  An unsupervised, frequency-based metric for selecting hints in an mdp-based tutor. In Proceedings of the 2nd International Conference on Educational Data Mining (EDM 2009). 180-189

Stamper, John, and Barnes, Tiffany (2009).  Utility in Hint Generation: Selection of Hints from a Corpus of Student Work. In Proceedings of the 2009 Conference on Artificial Intelligence in Education: Building Learning Systems That Care: From Knowledge Representation to Affective Modelling. 749-751 IOS Press.

2008

Stamper, John, Barnes, Tiffany, Lehmann, Lorrie, and Croy, Marvin (2008).  The hint factory: Automatic generation of contextualized help for existing computer aided instruction. In Proceedings of the 9th International Conference on Intelligent Tutoring Systems Young Researchers Track. 71-78

Barnes, Tiffany, and Stamper, John (2008).  Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data. In Intelligent Tutoring Systems. 373-382 Springer Berlin Heidelberg. [Best Paper Finalist]

Barnes, Tiffany, Stamper, John, Lehman, Lorrie, and Croy, Marvin (2008).  A pilot study on logic proof tutoring using hints generated from historical student data. In Proceedings of the 1st International Conference on Educational Data Mining (EDM 2008). 197-201

Croy, Marvin, Barnes, Tiffany, and Stamper, John (2008).  Towards an Intelligent Tutoring System for Propositional Proof Construction. In Proceedings of the 2008 Conference on Current Issues in Computing and Philosophy. 145-155 IOS Press.

2007

Stamper, John C., Barnes, Tiffany, and Croy, Marvin (2007).  Extracting Student Models for Intelligent Tutoring Systems. In Proceedings of the 22nd National Conference on Artificial Intelligence - Volume 2. 1900-1901 AAAI Press.

Barnes, Tiffany and Stamper, John (2007).  Toward the extraction of production rules for solving logic proofs. In Proceedings of the 13th International Conference on Artificial Intelligence in Education, Educational Data Mining Workshop (AIED2007). 11-20

Stamper, John and Carmichael, Ted (2007).  A Complex Adaptive System Approach to Predictive Data Insertion for Missing Student Data. In Proceedings of the 3rd International Conference on Computer Blended Learning (ICBL 2007). Kassel Press.

2006

Stamper, John (2006).  Automating the Generation of Production Rules for Intelligent Tutoring Systems. In Proceedings of the 9th International Conference on Interactive Computer Aided Learning (ICL2006). Kassel Press.

Barnes, Tiffany, Stamper, John, and Madhyastha, Tara (2006).  Comparative Analysis of Concept Derivation Using the Q-matrix Method and Facets. In Proceedings of the AAAI 21st National Conference on Artificial Intelligence Educational Data Mining Workshop (AAAI2006). AAAI Press.

2005

Howitt, Ivan, Stamper, John, Raja, Anita, and Mappillai, V. (2005).  Predictive protocol management with contingency planning for wireless sensor networks. In IEEE International Conference on Mobile Adhoc and Sensor Systems Conference (MASS2005). 3 pp.-162