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2020 – today
- 2024
[c55]Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steve Ritter, Andrew S. Lan:
Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions? EDM 2024- [c54]Mary Ann Simpson, Kole A. Norberg, Stephen E. Fancsali:
Replicating an "Astonishing Regularity in Student Learning Rate". EDM 2024 - [c53]Clara Belitz
, Haejin Lee, Nidhi Nasiar, Stephen E. Fancsali, Steven Ritter, Husni Almoubayyed, Ryan S. Baker, Jaclyn Ocumpaugh, Nigel Bosch:
Hierarchical Dependencies in Classroom Settings Influence Algorithmic Bias Metrics. LAK 2024: 210-218 - [c52]Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger:
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. LAK 2024: 404-415 - [c51]Emma Brunskill, Kole A. Norberg, Stephen Fancsali, Steven Ritter:
Examining the Use of an AI-Powered Teacher Orchestration Tool at Scale. L@S 2024: 356-360 - [c50]Abisha Thapa Magar, Stephen E. Fancsali, Vasile Rus, April Murphy, Steven Ritter, Deepak Venugopal:
Learning Representations for Math Strategies using BERT. L@S 2024: 514-518 - [c49]Steven Ritter, Stephen E. Fancsali, April Murphy, Neil T. Heffernan, Ben Motz, Debshila Basu Mallick, Jeremy Roschelle, Danielle S. McNamara, Joseph Jay Williams:
Fifth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S 2024: 565-566 - [i2]Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steven Ritter, Andrew S. Lan:
Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions? CoRR abs/2405.06414 (2024) - 2023
- [j2]Clara Belitz, Jaclyn Ocumpaugh, Steven Ritter, Ryan S. Baker, Stephen E. Fancsali, Nigel Bosch:
Constructing categories: Moving beyond protected classes in algorithmic fairness. J. Assoc. Inf. Sci. Technol. 74(6): 663-668 (2023) - [c48]Stephen E. Fancsali, Michael Sandbothe, Steven Ritter:
Orchestrating Classrooms and Tutoring with Carnegie Learning's MATHia and LiveLab. Human-AI Math Tutoring@AIED 2023: 1-11 - [c47]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 - [c46]Kole Norberg, Husni Almoubayyed, Stephen E. Fancsali, Logan De Ley, Kyle Weldon, April Murphy, Steven Ritter:
Rewriting Math Word Problems with Large Language Models. LLM@AIED 2023: 163-172 - [c45]Husni Almoubayyed, Rae Bastoni, Susan R. Berman, Sarah Galasso, Megan Jensen, Leila Lester, April Murphy, Mark Swartz, Kyle Weldon, Stephen E. Fancsali, Jess Gropen, Steven Ritter:
Rewriting Math Word Problems to Improve Learning Outcomes for Emerging Readers: A Randomized Field Trial in Carnegie Learning's MATHia. AIED (Posters/Late Breaking Results/...) 2023: 200-205 - [c44]Husni Almoubayyed, Stephen Fancsali, Steven Ritter:
Generalizing Predictive Models of Reading Ability in Adaptive Mathematics Software. EDM 2023 - [c43]Husni Almoubayyed, Stephen E. Fancsali, Steven Ritter:
Instruction-Embedded Assessment for Reading Ability in Adaptive Mathematics Software. LAK 2023: 366-377 - [c42]Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Klinton Bicknell, Jeremy Roschelle, Ben Motz, Danielle S. McNamara, Richard G. Baraniuk, Debshila Basu Mallick, René F. Kizilcec, Ryan Baker, Stephen Fancsali, April Murphy:
Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S 2023: 254-256 - [i1]Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger:
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. CoRR abs/2312.11274 (2023) - 2022
- [c41]Stephen Fancsali, April Murphy, Steven Ritter:
"Closing the Loop" in Educational Data Science with an Open Source Architecture for Large-Scale Field Trials. EDM 2022 - [c40]Nathan Levin, Ryan Baker, Nidhi Nasiar, Stephen Fancsali, Stephen Hutt:
Evaluating Gaming Detector Model Robustness Over Time. EDM 2022 - [c39]Vasile Rus, Stephen Fancsali:
The Third Workshop of the Learner Data Institute: Big Data, Research Challenges, \& Science Convergence in Educational Data Science. EDM 2022 - 2021
- [c38]Stephen E. Fancsali, Martina Pavelko, Josh Fisher, Leslie Wheeler, Steven Ritter:
Scaffolds and Nudges: A Case Study in Learning Engineering Design Improvements. AIED (2) 2021: 441-445 - [c37]LuEttaMae Lawrence, Kenneth Holstein, Susan R. Berman, Stephen Fancsali, Bruce M. McLaren, Steven Ritter, Vincent Aleven:
Teachers' Orchestration Needs During the Shift to Remote Learning. EC-TEL 2021: 347-351 - [c36]Stephen E. Fancsali, Hao Li, Steven Ritter:
Toward Scalable Improvement of Large Content Portfolios for Adaptive Instruction. EDM (Workshops) 2021 - [c35]Stephen Fancsali, Hao Li, Michael Sandbothe, Steven Ritter:
Targeting Design-Loop Adaptivity. EDM 2021 - [c34]Leigh M. Harrell-Williams, Christian Mueller, Stephen Fancsali, Steven Ritter, Xiaofei Zhang, Deepak Venugopal:
The Nature of Achievement Goal Motivation Profiles: Exploring Situational Motivation in An Algebra-Focused Intelligent Tutoring System. EDM (Workshops) 2021 - [c33]Vasile Rus, Stephen E. Fancsali, Philip I. Pavlik Jr., Deepak Venugopal, Arthur C. Graesser, Steven Ritter, Dale Bowman, The L. D. I. Team:
The Learner Data Institute - Conceptualization: A Progress Report. EDM (Workshops) 2021 - 2020
- [c32]Josh Fisher, Stephen Fancsali, Amy Lewis, Victoria Fisher, Robert G. M. Hausmann, Martina Pavelko, Sandy Bartle Finocchi, Steven Ritter:
LiveHint: Intelligent Digital Support for Analog Learning Experiences. iTextbooks@AIED 2020: 80-89 - [c31]Stephen E. Fancsali, Kenneth Holstein, Michael Sandbothe, Steven Ritter, Bruce M. McLaren, Vincent Aleven:
Towards Practical Detection of Unproductive Struggle. AIED (2) 2020: 92-97
2010 – 2019
- 2019
- [j1]Guoguo Zheng, Stephen E. Fancsali, Steven Ritter, Susan R. Berman:
Using Instruction-Embedded Formative Assessment to Predict State Summative Test Scores and Achievement Levels in Mathematics. J. Learn. Anal. 6(2) (2019) - [c30]Steven Ritter, Josh Fisher, Amy Lewis, Sandy Bartle Finocchi, Bob Hausmann, Stephen Fancsali:
What's a Textbook? Envisioning the 21st Century K-12 Text. iTextbooks@AIED 2019: 87-94 - [c29]Chuankai Zhang, Yanzun Huang, Jingyu Wang, Dongyang Lu, Weiqi Fang, John C. Stamper, Stephen Fancsali, Kenneth Holstein, Vincent Aleven:
Early Detection of Wheel Spinning: Comparison across Tutors, Models, Features, and Operationalizations. EDM 2019 - 2018
- [c28]Stephen Fancsali, Michael Yudelson, Susan R. Berman, Steven Ritter:
Intelligent Instructional Hand Offs. EDM 2018 - [c27]Benjamin Nye, Stephen Fancsali:
Special Track on Intelligent Learning Technologies. FLAIRS 2018: 420 - [c26]Stephen E. Fancsali, Steven Ritter:
Assessments That Care About Student Learning. ITS Workshops 2018: 135-140 - [c25]Stephen E. Fancsali, Guoguo Zheng, Yanyan Tan, Steven Ritter, Susan R. Berman, April Galyardt:
Using embedded formative assessment to predict state summative test scores. LAK 2018: 161-170 - 2017
- [c24]Vasile Rus, Nabin Maharjan, Lasang Jimba Tamang, Michael Yudelson, Susan R. Berman, Stephen E. Fancsali, Steven Ritter:
An Analysis of Human Tutors' Actions in Tutorial Dialogues. FLAIRS 2017: 122-127 - 2016
- [c23]Stephen E. Fancsali, Steven Ritter, Susan R. Berman, Michael Yudelson, Vasile Rus, Donald M. Morrison:
Toward Integrating Cognitive Tutor Interaction Data with Human Tutoring Text Dialogue Data in LearnSphere. EDM (Workshops) 2016 - [c22]Steven Ritter, Stephen Fancsali:
MATHia X: The Next Generation Cognitive Tutor. EDM 2016: 624-625 - [c21]Steven Ritter, Michael Yudelson, Stephen Fancsali, Susan R. Berman:
Towards Integrating Human and Automated Tutoring Systems. EDM 2016: 626-627 - [c20]Stephen E. Fancsali, Steven Ritter, Michael Yudelson, Michael Sandbothe, Susan R. Berman:
Implementation Factors and Outcomes for Intelligent Tutoring Systems: A Case Study of Time and Efficiency with Cognitive Tutor Algebra. FLAIRS 2016: 473-478 - [c19]Steven Ritter, Michael Yudelson, Stephen E. Fancsali, Susan R. Berman:
How Mastery Learning Works at Scale. L@S 2016: 71-79 - 2015
- [c18]Stephen Fancsali:
Confounding Carelessness? Exploring Causal Relationships Between Carelessness, Affect, Behavior, and Learning in Cognitive Tutor Algebra Using Graphical Causal Models. EDM 2015: 508-511 - [c17]Steven Ritter, Stephen Fancsali:
Carnegie Learning's Cognitive Tutor. EDM 2015: 633-634 - 2014
- [c16]Stephen Fancsali, Matthew L. Bernacki, Timothy J. Nokes-Malach, Michael Yudelson, Steven Ritter:
Goal Orientation, Self-Efficacy, and "Online Measures" in Intelligent Tutoring Systems. CogSci 2014 - [c15]Stephen Fancsali:
Causal Discovery with Models: Behavior, Affect, and Learning in Cognitive Tutor Algebra. EDM 2014: 28-35 - [c14]Candace A. Walkington, Virginia Clinton, Steven Ritter, Mitchell J. Nathan, Stephen E. Fancsali:
The Impact of Cognitive and Non-Cognitive Text-Based Factors on Solving Mathematics Story Problems. EDM (Workshops) 2014 - [c13]Michael Yudelson, Stephen Fancsali, Steven Ritter, Susan R. Berman, Tristan Nixon, Ambarish Joshi:
Better Data Beats Big Data. EDM 2014: 205-208 - [c12]Ambarish Joshi, Stephen Fancsali, Steven Ritter, Tristan Nixon, Susan R. Berman:
Generalizing and Extending a Predictive Model for Standardized Test Scores Based On Cognitive Tutor Interactions. EDM 2014: 369-370 - [c11]Stephen E. Fancsali, Steven Ritter:
Context personalization, preferences, and performance in an intelligent tutoring system for middle school mathematics. LAK 2014: 73-77 - 2013
- [c10]Stephen E. Fancsali, Tristan Nixon, Annalies Vuong, Steven Ritter:
Simulated Students, Mastery Learning, and Improved Learning Curves for Real-World Cognitive Tutors. AIED Workshops 2013 - [c9]Stephen Fancsali, Steven Ritter, John C. Stamper, Tristan Nixon:
Toward "Hyper-Personalized" Cognitive Tutors: Non-Cognitive Personalization in the Generalized Intelligent Framework for Tutoring. AIED Workshops 2013 - [c8]R. Charles Murray, Steven Ritter, Tristan Nixon, Ryan Schwiebert, Robert G. M. Hausmann, Brendon Towle, Stephen E. Fancsali, Annalies Vuong:
Revealing the Learning in Learning Curves. AIED 2013: 473-482 - [c7]Stephen Fancsali, Tristan Nixon, Steven Ritter:
Optimal and Worst-Case Performance of Mastery Learning Assessment with Bayesian Knowledge Tracing. EDM 2013: 35-42 - [c6]Steven Ritter, Ambarish Joshi, Stephen Fancsali, Tristan Nixon:
Predicting Standardized Test Scores from Cognitive Tutor Interactions. EDM 2013: 169-176 - [c5]Tristan Nixon, Stephen Fancsali, Steven Ritter:
The Complex Dynamics of Aggregate Learning Curves. EDM 2013: 338-339 - 2012
- [c4]Stephen Fancsali:
Variable Construction and Causal Discovery for Cognitive Tutor Log Data: Initial Results. EDM 2012: 238-239 - 2011
- [c3]Stephen Fancsali:
Variable Construction and Causal Modeling of Online Education Messaging Data: Initial Results. EDM 2011: 331-332 - [c2]Stephen Fancsali:
Variable construction for predictive and causal modeling of online education data. LAK 2011: 54-63
2000 – 2009
- 2005
- [c1]Stephen Fancsali, Laura McGinnis:
Untapped resources: can intellectual diversity promote cultural diversity in technology? Richard Tapia Celebration of Diversity in Computing Conference 2005: 51-52
Coauthor Index
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last updated on 2024-10-31 21:09 CET by the dblp team
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