Publications

2024

Stamper, John, Moore, Steven, Rose, Carolyn, Pavlik, Philip, and Koedinger, Kenneth (2024). LearnSphere: A Learning Data and Analytics CyberInfrastructure. In Journal of Educational Data Mining. 16 (1), 141-163.

Moore, Steven, Bier, Norman, and Stamper, John (2024). Assessing Educational Quality: Comparative Analysis of Crowdsourced, Expert, and AI-Driven Rubric Applications. In Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 12 , 115-125.

An, Marshall, He, Mufei, Yao, Wei, and Stamper, John (2024). Singular Action, Complex Cognition: An Intelligent Tutoring System in Riichi Mahjong. In European Conference on Technology Enhanced Learning. 51-56.

Kumar, Harsh, Xiao, Ruiwei, Lawson, Benjamin, Musabirov, Ilya, Shi, Jiakai, Wang, Xinyuan, Luo, Huayin, Williams, Joseph Jay, Rafferty, Anna, Stamper, John, and others (2024). Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms. In Proceedings of the Eleventh ACM Conference on Learning@ Scale. 86-97.

Moore, Steven, Schmucker, Robin, Mitchell, Tom, and Stamper, John (2024). Automated Generation and Tagging of Knowledge Components from Multiple-Choice Questions. In Proceedings of the Eleventh ACM Conference on Learning@ Scale. 122-133.

Moore, Steven, Singh, Anjali, Lu, Xinyi, Jin, Hyoungwook, Khosravi, Hassan, Denny, Paul, Brooks, Christopher, Wang, Xu, Kim, Juho, and Stamper, John (2024). Learnersourcing: Student-generated Content@ Scale: 2nd Annual Workshop. In Proceedings of the Eleventh ACM Conference on Learning@ Scale. 559-562.

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

Xiao, Ruiwei, Hou, Xinying, Kumar, Harsh, Moore, Steven, Stamper, John, and Liut, Michael (2024). Learner-Centered Design of LLM-Based Tutoring Systems in Education: Insights from a Large-Scale Classroom Deployment. In Proceedings of the 8th Educational Data Mining in Computer Science Education (CSEDM) Workshop.

Stamper, John, Xiao, Ruiwei, and Hou, Xinying (2024). Enhancing llm-based feedback: Insights from intelligent tutoring systems and the learning sciences. In International Conference on Artificial Intelligence in Education. 32-43.

Moore, Steven, Costello, Eamon, Nguyen, Huy A, and Stamper, John (2024). An Automatic Question Usability Evaluation Toolkit. In International Conference on Artificial Intelligence in Education. 31-46.

Kwon, Christine, King, James, Carney, John, and Stamper, John (2024). A Schema-Based Approach to the Linkage of Multimodal Learning Sources with Generative AI. In International Conference on Artificial Intelligence in Education. 3-10.

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 Technologies. In Proceedings of the CHI Conference on Human Factors in Computing Systems. 1-15.

Xiao, Ruiwei, Hou, Xinying, and Stamper, John (2024). Exploring How Multiple Levels of GPT-Generated Programming Hints Support or Disappoint Novices. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. 1-10.

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 Challenge. In The Fourteenth International Conference on Learning Analytics & Knowledge (LAK24): Learning Analytics in the Age of Artificial Intelligence. 37-40.

2023

Khosravi, Hassan, Denny, Paul, Moore, Steven, and Stamper, John (2023). Learnersourcing in the age of AI: Student, educator and machine partnerships for content creation. In Computers and Education: Artificial Intelligence. 100151. 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 methods. In European Conference on Technology Enhanced Learning. 229-245.

Carney, John, Belmont, Nancy, King, James, Stamper, John, and Kwon, Christine (2023). AI/ML-Driven Content Repository Maintenance. In 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 Improvement. In 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 Review. In 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 Taxonomy. In 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 Learnersourcing. In Proceedings of the 17th International Conference of the Learning Sciences. International 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 Game. In Proceedings of the International Conference on Artificial Intelligence in Education. Springer.

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 Generation. In Proceedings of the International Conference on Artificial Intelligence in Education. Springer.

Stamper, John, Gaind, Bharat, Thankachan, Karun, Nguyen, Huy, and Moore, Steven (2023). Hierarchical Concept Map Generation from Course Data. In 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 Assessments. In 31st International Conference on Computers in Education Conference Vol II, ICCE 2023. 349-358.

Okimoto, Tomoko, Johnson, Matthew, Nguyen, Huy, Moore, Steven, Eagle, Michael, and Stamper, John (2023). Tracking Knowledge for Learning Japanese as a 2nd Language. In 31st International Conference on Computers in Education Conference Vol I, ICCE 2023. 766-768.

Kwon, Christine, Stamper, John, King, James, Lam, Joanie, and Carney, John (2023). Multimodal Data Support in Knowledge Objects for Real-time Knowledge Sharing. In 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 Africa. In Companion Proceedings 13th International Conference on Learning Analytics & Knowledge. 153-155.

Moore, Steven, Nguyen, Huy, and Stamper, John (2023). Students’ Domain Confidence and their Participation in Optional Learnersourcing Activities. In Companion Proceedings 13th International Conference on Learning Analytics & Knowledge. 147-149.

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 Proceedings. 3487 , 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 research. In Companion Proceedings 13th International Conference on Learning Analytics & Knowledge. 57-60.

2022

Bhat, Shravya, Nguyen, Huy, Moore, Steven , Stamper, John, 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 Mining. 701-704. International Educational Data Mining Society.

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

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

Moore, Steven, Nguyen, Huy, and Stamper, John (2022). Leveraging Students to Generate Skill Tags that Inform Learning Analytics. In Proceedings of the 16th International Conference of the Learning Sciences. 791-798. 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 Courses. In Proceedings of the 16th International Conference of the Learning Sciences. 1381-1384. 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-3. In Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. 243-257. 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 Domains. In Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption. 272-284. Springer International Publishing.

Moore, Steven, Stamper, John, Brooks, Christopher, Denny, Paul, and Khosravi, Hassan (2022). Learnersourcing: Student-Generated Content @ Scale. In Proceedings of the Ninth ACM Conference on Learning @ Scale. 259–262. 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 Tasks. In 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 Education. 31-40.

Nguyen, Huy, Guo, Yuqing, Stamper, John, and McLaren, Bruce (2020). Improving Students’ Problem-solving Flexibility in Nonroutine Mathematics. In International Conference on Artificial Intelligence in Education. 409-413. 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 Analytics. In Proceedings of the International Conference on Educational Data Mining. 487-495.

Moore, Steven, Nguyen, Huy, and Stamper, John (2020). Evaluating Crowdsourcing and Topic Modeling in Generating Knowledge Components from Explanations. In Proceedings of the International Conference on Artificial Intelligence in Education. 398-410. Springer.

Moore, Steven, Nguyen, Huy, and Stamper, John (2020). Crowdsourcing Explanations for Improving Assessment Content and Identifying Knowledge Components. In Proceedings of the 15th International Conference of the Learning Sciences. 2627-2628. International Society of the Learning Sciences.

Moore, Steven, Nguyen, Huy, and Stamper, John (2020). Towards Crowdsourcing the Identification of Knowledge Components. In Proceedings of the Seventh (2020) ACM Conference on Learning @ Scale. 245-248.

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 Expertise. In Artificial Intelligence in Education. 269-274. 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 Reasoning. In Artificial Intelligence in Education. 62-66. Springer International Publishing.

Diana, Nicholas, Stamper, John, and Koedinger, Ken (2019). Predicting Bias in the Evaluation of Unlabeled Political Arguments.. In CogSci. 1640-1646.

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 LearnSphere. In Workshop and Tutorials Chairs. 475-476.

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 Tools. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference. 524-525. Association for Computing Machinery.

Lang, Charles, Teasley, Stephanie, and Stamper, John (2017). Building the Learning Analytics Curriculum: Workshop. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference. 520-521. 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 Tutor. In 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.