John C. Stamper

发表

Using a Bayesian Knowledge Base for Hint Selection on Domain Specific Problems

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2010, EDM.

A Human-Centered Approach to Data Driven Iterative Course Improvement

John C. Stamper, Steven Moore, Norman Bier, 2020, REV.

Proceedings of the 4th International Conference on Educational Data Mining, Eindhoven, The Netherlands, July 6-8, 2011

Cristina Conati, Toon Calders, Mykola Pechenizkiy, 2011, Educational Data Mining.

An Algorithm for Reducing the Complexity of Interaction Networks

Michael Eagle, Tiffany Barnes, John C. Stamper, 2013, EDM.

A Multi-level Complex Adaptive System Approach for Modeling of Schools

Mirsad Hadzikadic, John C. Stamper, Mary Jean Blink, 2014, Intelligent Tutoring Systems.

Data-driven generation of rubric criteria from an educational programming environment

Shuchi Grover, Michael Eagle, John C. Stamper, 2018, LAK.

Learning linkages: Integrating data streams of multiple modalities and timescales

Danielle S. McNamara, Ran Liu, John C. Stamper, 2018, J. Comput. Assist. Learn..

Ethics and Privacy in EDM

Zachary A. Pardos, Mykola Pechenizkiy, Dragan Gasevic, 2015, EDM.

Online Assessment of Belief Biases and Their Impact on the Acceptance of Fallacious Reasoning

Kenneth R. Koedinger, John C. Stamper, Nicholas Diana, 2019, AIED.

Teaching Informal Logical Fallacy Identification with a Cognitive Tutor

Kenneth R. Koedinger, John C. Stamper, Nicholas Diana, 2017, EDM.

Proceedings of the Seventh International Conference on Educational Data Mining (EDM) (7th, London, United Kingdom, July 4-7, 2014).

Zachary A. Pardos, Manolis Mavrikis, John C. Stamper, 2014, EDM 2014.

Proceedings of the 13th International Conference on Intelligent Tutoring Systems - Volume 9684

Alessandro Micarelli, John C. Stamper, Kitty Panourgia, 2016 .

Predicting Individual Differences for Learner Modeling in Intelligent Tutors from Previous Learner Activities

Michael Eagle, Ryan Shaun Joazeiro de Baker, Albert T. Corbett, 2016, UMAP.

Educational data mining meets learning analytics

Erik Duval, Ryan Shaun Joazeiro de Baker, Simon Buckingham Shum, 2012, LAK.

A Data Driven Approach to the Discovery of Better Cognitive Models

Kenneth R. Koedinger, John C. Stamper, 2010, EDM.

An instructor dashboard for real-time analytics in interactive programming assignments

Shuchi Grover, Michael Eagle, John C. Stamper, 2017, LAK.

Using Data-Driven Discovery of Better Student Models to Improve Student Learning

Kenneth R. Koedinger, John C. Stamper, Tristan Nixon, 2013, AIED.

SCALE: Student Centered Adaptive Learning Engine

John C. Stamper, Mary Jean Blink, Ted Carmichael, 2014, Intelligent Tutoring Systems.

How quickly can wheel spinning be detected?

Sanjay Chandrasekaran, John C. Stamper, Noboru Matsuda, 2016, EDM.

Early Detection of Wheel Spinning: Comparison across Tutors, Models, Features, and Operationalizations

Vincent Aleven, Jingyu Wang, John C. Stamper, 2019, EDM.

New Potentials for Data-Driven Intelligent Tutoring System Development and Optimization

Ryan Shaun Joazeiro de Baker, Kenneth R. Koedinger, John C. Stamper, 2013, AI Mag..

A framework for hypothesis-driven approaches to support data-driven learning analytics in measuring computational thinking in block-based programming

Shuchi Grover, Michael Eagle, John C. Stamper, 2017, LAK.

The Future of Practical Applications of EDM at Scale

Ryan Shaun Joazeiro de Baker, John C. Stamper, John Carney, 2015, EDM.

Towards Modeling Students' Problem-solving Skills in Non-routine Mathematics Problems

Huy Nguyen, John C. Stamper, Bruce M. McLaren, 2019, EDM.

Enhancing the Automatic Generation of Hints with Expert Seeding

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2011, Int. J. Artif. Intell. Educ..

Unsupervised MDP Value Selection for Automating ITS Capabilities.

Tiffany Barnes, John C. Stamper, 2009, EDM 2009.

Linkage Objects for Generalized Instruction in Coding (LOGIC)

John C. Stamper, Mary Jean Blink, Ted Carmichael, 2018, FLAIRS Conference.

Data-Driven Generation of Rubric Parameters from an Educational Programming Environment

Shuchi Grover, Michael Eagle, John C. Stamper, 2017, AIED.

The Validity of Providing Automated Hints in an ITS Using a MDP

Tiffany Barnes, John C. Stamper, 2008, AAAI.

Beyond Log Files: Using Multi-Modal Data Streams Towards Data-Driven KC Model Improvement

Ran Liu, John C. Stamper, Jodi L. Davenport, 2016, EDM.

Extracting Student Models for Intelligent Tutoring Systems

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2007, AAAI.

Multimodal Data Collection and Analysis of Collaborative Learning through an Intelligent Tutoring System

Ran Liu, John C. Stamper, 2017, MMLA-CrossLAK@LAK.

A pilot study on logic proof tutoring using hints generated from historical student data

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2008, EDM.

Automatic Hint Generation for Logic Proof Tutoring Using Historical Data

Tiffany Barnes, John C. Stamper, T. Barnes, 2010, J. Educ. Technol. Soc..

Online Education: A Unique Opportunity for Cognitive Scientists to Integrate Research and Practice

Joseph Jay Williams, Alexander Renkl, Kenneth R. Koedinger, 2013, CogSci.

Extracting Measures of Active Learning and Student Self-Regulated Learning Strategies from MOOC Data

Michael Eagle, Kenneth R. Koedinger, John C. Stamper, 2016, EDM.

Sharing and Reusing Data and Analytic Methods with LearnSphere

Ran Liu, Kenneth R. Koedinger, John C. Stamper, 2017, EDM.

Utility in hint generation: Selection of hints from a corpus of student work

Tiffany Barnes, John C. Stamper, 2009, AIED.

The Effects of Adaptive Sequencing Algorithms on Player Engagement within an Online Game

Kenneth R. Koedinger, John C. Stamper, Kishan Patel, 2012, ITS.

Towards improving programming habits to create better computer science course outcomes

Davide Fossati, John C. Stamper, Jaime Spacco, 2013, ITiCSE '13.

Towards an Intelligent Tutoring System for Propositional Proof Construction

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2008 .

CloudCoder: building a community for creating, assigning, evaluating and sharing programming exercises (abstract only)

David Hovemeyer, John C. Stamper, Jaime Spacco, 2013, SIGCSE '13.

Data-driven Learner Modeling to Understand and Improve Online Learning: MOOCs and technology to advance learning and learning research (Ubiquity symposium)

Kenneth R. Koedinger, John C. Stamper, Elizabeth A. McLaughlin, 2014, UBIQ.

Human-Machine Student Model Discovery and Improvement Using DataShop

Kenneth R. Koedinger, John C. Stamper, 2011, AIED.

Automatic generation of intelligent tutoring capabilities via educational data mining

Tiffany Barnes, John C. Stamper, 2010 .

Predicting Bias in the Evaluation of Unlabeled Political Arguments

Ken Koedinger, John C. Stamper, Nicholas Diana, 2019, CogSci.

Using Markov Decision Processes for Automatic Hint

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2010 .

Automatic Peer Tutor Matching: Data-Driven Methods to Enable New Opportunities for Help

Shuchi Grover, Michael Eagle, John C. Stamper, 2017, EDM.

EDM 2011: 4th international conference on educational data mining : Eindhoven, July 6-8, 2011 : proceedings

Cristina Conati, Tgk Toon Calders, Mykola Pechenizkiy, 2011, EDM 2011.

Experimental Evaluation of Automatic Hint Generation for a Logic Tutor

Michael Eagle, Tiffany Barnes, John C. Stamper, 2011, AIED.

A Data Repository for the EDM Community: The PSLC DataShop

Kenneth R. Koedinger, John C. Stamper, Brett Leber, 2010 .

Decision Support for an Adversarial Game Environment Using Automatic Hint Generation

John C. Stamper, Steven Moore, Steven Moore, 2019, ITS.

Community based educational data repositories and analysis tools

Ran Liu, Ken Koedinger, Candace Thille, 2017, LAK.

Automating the Generation of Student Models for Intelligent Tutoring Systems

John C. Stamper, 2007, AIED.

Experimental Evaluation of Automatic Hint Generation for a Logic Tutor

Michael Eagle, Tiffany Barnes, John C. Stamper, 2011, Int. J. Artif. Intell. Educ..

Toward Automatic Hint Generation for Logic Proof Tutoring Using Historical Student Data

Tiffany Barnes, John C. Stamper, T. Barnes, 2008, Intelligent Tutoring Systems.

Predictive Student Modeling for Interventions in Online Classes

Michael Eagle, John C. Stamper, Mary Jean Blink, 2018, EDM.

Predicting Individualized Learner Models Across Tutor Lessons

Michael Eagle, Albert T. Corbett, John C. Stamper, 2018, EDM.

The 2010 KDD Cup Competition Dataset: Engaging the machine learning community in predictive learning analytics

Zachary A. Pardos, John C. Stamper, Z. Pardos, 2016, J. Learn. Anal..

A Comparison of Model Selection Metrics in DataShop

Kenneth R. Koedinger, John C. Stamper, Elizabeth A. McLaughlin, 2013, EDM.

Toward "Hyper-Personalized" Cognitive Tutors: Non-Cognitive Personalization in the Generalized Intelligent Framework for Tutoring

John C. Stamper, Steven Ritter, Stephen Fancsali, 2013, AIED Workshops.

Using Time Pressure to Promote Mathematical Fluency

John C. Stamper, Steven Ritter, Tristan Nixon, 2012, ITS.

Using Knowledge Component Modeling to Increase Domain Understanding in a Digital Learning Game

Huy Nguyen, John C. Stamper, Bruce M. McLaren, 2019, EDM.

Proceedings of the 7th International Conference on Educational Data Mining.

Manolis Mavrikis, John C. Stamper, Pardos Zach, 2014, EDM 2014.

How Does Order of Gameplay Impact Learning and Enjoyment in a Digital Learning Game?

Huy Nguyen, John C. Stamper, Bruce M. McLaren, 2019, AIED.

Automated Student Model Improvement

Kenneth R. Koedinger, John C. Stamper, Elizabeth A. McLaughlin, 2012, EDM.

Predictive protocol management with contingency planning for wireless sensor networks

Anita Raja, John C. Stamper, Ivan Howitt, 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

Building the learning analytics curriculum: workshop

Stephanie D. Teasley, John C. Stamper, Charles Lang, 2017, LAK.

Program Representation for Automatic Hint Generation for a Data-Driven Novice Programming Tutor

Michael Eagle, Tiffany Barnes, John C. Stamper, 2012, ITS.

Enhancing the Automatic Generation of Hints with Expert Seeding

Tiffany Barnes, John C. Stamper, Marvin J. Croy, 2010, Intelligent Tutoring Systems.

DataShop: A Data Repository and Analysis Service for the Learning Science Community (Interactive Event)

Ryan Shaun Joazeiro de Baker, Kenneth R. Koedinger, John C. Stamper, 2011, AIED.

An Instructional Factors Analysis of an Online Logical Fallacy Tutoring System

Ken Koedinger, John C. Stamper, Nicholas Diana, 2018, AIED.

Building the Learning Analytics Curriculum

Stephanie D. Teasley, John C. Stamper, Charles Lang, 2017, MLA/BLAC@LAK.

LearnLab's DataShop: A Data Repository and Analytics Tool Set for Cognitive Science

Kenneth R. Koedinger, John C. Stamper, Brett Leber, 2013, Top. Cogn. Sci..

Estimating Individual Differences for Student Modeling in Intelligent Tutors from Reading and Pretest Data

Michael Eagle, Albert T. Corbett, John C. Stamper, 2016, ITS.

PSLC DataShop: A Data Analysis Service for the Learning Science Community

Ryan Shaun Joazeiro de Baker, Kenneth R. Koedinger, John C. Stamper, 2010, Intelligent Tutoring Systems.

Proceedings of the International Conference on Educational Data Mining (EDM) (4th, Eindhoven, the Netherlands, July 6-8, 2011).

Cristina Conati, Toon Calders, Mykola Pechenizkiy, 2011, EDM 2011.

Managing the Educational Dataset Lifecycle with DataShop

Ryan Shaun Joazeiro de Baker, Kenneth R. Koedinger, John C. Stamper, 2011, AIED.

Exploring Teachable Humans and Teachable Agents: Human Strategies Versus Agent Policies and the Basis of Expertise

John C. Stamper, Steven Moore, Steven Moore, 2019, AIED.

Exploring Learner Model Differences Between Students

Michael Eagle, Ryan Shaun Joazeiro de Baker, Albert T. Corbett, 2017, AIED.

A Framework for Using Hypothesis-Driven Approaches to Support Data-Driven Learning Analytics in Measuring Computational Thinking in Block-Based Programming Environments

Shuchi Grover, Michael Eagle, John C. Stamper, 2017, ACM Trans. Comput. Educ..

The Rise of the Super Experiment

Kenneth R. Koedinger, John C. Stamper, Steven Ritter, 2012, EDM.

EDM and the 4th Paradigm of Scientific Discovery - Reflections on KDD Cup 2010

John C. Stamper, 2011, EDM.

Avoiding Problem Selection Thrashing with Conjunctive Knowledge Tracing

Kenneth R. Koedinger, John C. Stamper, Philip I. Pavlik, 2011, EDM.

Examining the Effects of Student Participation and Performance on the Quality of Learnersourcing Multiple-Choice Questions

John C. Stamper, Huy A. Nguyen, Steven Moore, 2021, L@S.

Exploring Metrics for the Analysis of Code Submissions in an Introductory Data Science Course

Eric Nyberg, John C. Stamper, Huy A. Nguyen, 2021, LAK.

Toward the extraction of production rules for solving logic proofs

John C. Stamper, T. Barnes, 2008 .

Internet Scale Experimental Design and Deployment for Educational Games using BrainPOP®

John C. Stamper, D. Lomas, 2012 .

The Hint Factory: Automatic Generation of Contextualized Help for Existing Computer Aided Instruction

John C. Stamper, T. Barnes, L. Lehmann, 2008 .

A Novel Method for the In-Depth Multimodal Analysis of Student Learning Trajectories in Intelligent Tutoring Systems

John C. Stamper, Jodi L. Davenport, Ran Liu, 2018, J. Learn. Anal..

Learnersourcing: Student-generated Content @ Scale

John C. Stamper, Christopher A. Brooks, Hassan Khosravi, 2022, L@S.

Assessing the Quality of Student-Generated Short Answer Questions Using GPT-3

John C. Stamper, Huy A. Nguyen, Norman L. Bier, 2022, EC-TEL.

Learnersourcing in the Age of AI: Student, Educator and Machine Partnerships for Content Creation

John C. Stamper, Hassan Khosravi, Paul Denny, 2023, Comput. Educ. Artif. Intell..

Evaluating Crowdsourcing and Topic Modeling in Generating Knowledge Components from Explanations

John C. Stamper, Steven Moore, Huy A. Nguyen, 2020, AIED.

Moving beyond Test Scores: Analyzing the Effectiveness of a Digital Learning Game through Learning Analytics

John C. Stamper, Bruce M. McLaren, Huy A. Nguyen, 2020, EDM.

Improving Students’ Problem-Solving Flexibility in Non-routine Mathematics

John C. Stamper, Bruce M. McLaren, Yuqing Guo, 2020, AIED.

An unsupervised, frequency-based metric for selecting hints in an MDP-based tutor

John C. Stamper, T. Barnes, 2009, EDM.

Assessing the Quality of Multiple-Choice Questions Using GPT-4 and Rule-Based Methods

John C. Stamper, Steven Moore, H. A. Nguyen, 2023, EC-TEL.

Empowering Education with LLMs - The Next-Gen Interface and Content Generation

John C. Stamper, Xiangen Hu, Zitao Liu, 2023, AIED.

Persuasion Invasion: Reducing Bias with Value-Adaptive Instruction

Jessica Hammer, John C. Stamper, Nicholas Diana, 2020, CHI PLAY.

Towards Value-Adaptive Instruction: A Data-Driven Method for Addressing Bias in Argument Evaluation Tasks

Ken Koedinger, John C. Stamper, Nicholas Diana, 2020, CHI.