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2020 – today
- 2024
[c47]Harsh Kumar, Tong Li, Jiakai Shi, Ilya Musabirov, Rachel Kornfield, Jonah Meyerhoff, Ananya Bhattacharjee, Chris J. Karr, Theresa Nguyen, David C. Mohr, Anna N. Rafferty, Sofia S. Villar, Nina Deliu
, Joseph Jay Williams:
Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health. AAAI 2024: 22906-22912- [c46]S. Thomas Christie, Carson Cook, Anna N. Rafferty:
Uncertainty-preserving deep knowledge tracing with state-space models. EDM 2024 - [c45]Harsh Kumar, Ruiwei Xiao, Benjamin Lawson, Ilya Musabirov, Jiakai Shi, Xinyuan Wang, Huayin Luo, Joseph Jay Williams, Anna N. Rafferty, John C. Stamper, Michael Liut:
Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms. L@S 2024: 86-97 - [c44]Sara Nurollahian, Anna N. Rafferty, Noelle Brown, Eliane Wiese:
Growth in Knowledge of Programming Patterns: A Comparison Study of CS1 vs. CS2 Students. SIGCSE (1) 2024: 979-985 - [c43]Anna N. Rafferty, David Liben-Nowell, David R. Musicant, Emy Farley, Allie Lyman, Ann May:
Playing with Matches: Adopting Gale-Shapley for Managing Student Enrollments Beyond CS2. SIGCSE (1) 2024: 1084-1090 - [e2]Juan D. Pinto, Eamon Worden, Anthony Botelho, Lea Cohausz, Clayton Cohn, Mingyu Feng, Neil T. Heffernan, Arto Hellas, Lan Jiang, David Joyner, Tanja Käser, Juho Kim, Andrew Lan, Chenglu Li, Joshua Littenberg-Tobias, Qianhui Liu, Christopher MacLellan, Steven Moore, Maciej Pankiewicz, Luc Paquette, Zach A. Pardos, Anna N. Rafferty, Adish Singla, Shashank Sonkar, Vinitra Swamy, Rose E. Wang, Candace Walkington:
Joint Proceedings of the Human-Centric eXplainable AI in Education and the Leveraging Large Language Models for Next Generation Educational Technologies Workshops (HEXED-L3MNGET 2024) co-located with 17th International Conference on Educational Data Mining (EDM 2024), Atlanta, Georgia, USA, July 14, 2024. CEUR Workshop Proceedings 3840, CEUR-WS.org 2024 [contents] - [i14]Paul Denny, Sumit Gulwani, Neil T. Heffernan, Tanja Käser, Steven Moore, Anna N. Rafferty, Adish Singla:
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges. CoRR abs/2402.01580 (2024) - [i13]Harsh Kumar, Ruiwei Xiao, Benjamin Lawson, Ilya Musabirov, Jiakai Shi, Xinyuan Wang, Huayin Luo, Joseph Jay Williams, Anna N. Rafferty, John C. Stamper, Michael Liut:
Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classrooms. CoRR abs/2406.07571 (2024) - [i12]S. Thomas Christie, Carson Cook, Anna N. Rafferty:
Uncertainty-preserving deep knowledge tracing with state-space models. CoRR abs/2407.17427 (2024) - 2023
- [c42]Sara Nurollahian, Anna N. Rafferty, Eliane Wiese:
Improving Assessment of Programming Pattern Knowledge through Code Editing and Revision. SEET@ICSE 2023: 58-69 - [c41]S. Thomas Christie, Hayden Johnson, Carson Cook, Garron Gianopulos, Anna N. Rafferty:
LENS: Predictive Diagnostics for Flexible and Efficient Assessments. L@S 2023: 14-24 - [i11]Zhaobin Li, Luna Yee, Nathaniel Sauerberg, Irene Sakson, Joseph Jay Williams, Anna N. Rafferty:
Getting too personal(ized): The importance of feature choice in online adaptive algorithms. CoRR abs/2309.02856 (2023) - [i10]Harsh Kumar, Tong Li, Jiakai Shi, Ilya Musabirov, Rachel Kornfield, Jonah Meyerhoff, Ananya Bhattacharjee, Chris J. Karr, Theresa Nguyen, David C. Mohr, Anna N. Rafferty, Sofia S. Villar, Nina Deliu, Joseph Jay Williams:
Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health. CoRR abs/2310.18326 (2023) - 2022
- [c40]Collin F. Lynch, Mirko Marras, Mykola Pechenizkiy, Anna N. Rafferty, Steven Ritter, Vinitra Swamy, Renzhe Yu:
FATED 2022: Fairness, Accountability, and Transparency in Educational Data. EDM 2022 - [c39]Yang Zhi-Han, Shiyue Zhang, Anna N. Rafferty:
Adversarial bandits for drawing generalizable conclusions in non-adversarial experiments: an empirical study. EDM 2022 - [c38]Angela M. Zavaleta Bernuy, Ziwen Han, Hammad Shaikh, Qi Yin Zheng, Lisa-Angelique Lim, Anna N. Rafferty, Andrew Petersen, Joseph Jay Williams:
How can Email Interventions Increase Students' Completion of Online Homework? A Case Study Using A/B Comparisons. LAK 2022: 107-118 - [c37]David Liben-Nowell, Anna N. Rafferty:
Student Motivations and Goals for CS1: Themes and Variations. SIGCSE (1) 2022: 237-243 - [c36]Eliane Wiese, Anna N. Rafferty, Jordan Pyper:
Readable vs. Writable Code: A Survey of Intermediate Students' Structure Choices. SIGCSE (1) 2022: 321-327 - [i9]Angela M. Zavaleta Bernuy, Ziwen Han, Hammad Shaikh, Qi Yin Zheng, Lisa-Angelique Lim, Anna N. Rafferty, Andrew Petersen, Joseph Jay Williams:
How can Email Interventions Increase Students' Completion of Online Homework? A Case Study Using A/B Comparisons. CoRR abs/2208.05087 (2022) - [i8]Fernando J. Yanez, Angela M. Zavaleta Bernuy, Ziwen Han, Michael Liut, Anna N. Rafferty, Joseph Jay Williams:
Increasing Students' Engagement to Reminder Emails Through Multi-Armed Bandits. CoRR abs/2208.05090 (2022) - [i7]Angela M. Zavaleta Bernuy, Qi Yin Zheng, Hammad Shaikh, Jacob Nogas, Anna N. Rafferty, Andrew Petersen, Joseph Jay Williams:
Using Adaptive Experiments to Rapidly Help Students. CoRR abs/2208.05092 (2022) - 2021
- [c35]Angela M. Zavaleta Bernuy, Qi Yin Zheng, Hammad Shaikh, Jacob Nogas, Anna N. Rafferty, Andrew Petersen, Joseph Jay Williams:
Using Adaptive Experiments to Rapidly Help Students. AIED (2) 2021: 422-426 - [c34]Eliane Stampfer Wiese, Anna N. Rafferty, Garrett Moseke:
Students' Misunderstanding of the Order of Evaluation in Conjoined Conditions. ICPC 2021: 476-484 - [c33]Mohi Reza, Juho Kim, Ananya Bhattacharjee, Anna N. Rafferty, Joseph Jay Williams:
The MOOClet Framework: Unifying Experimentation, Dynamic Improvement, and Personalization in Online Courses. L@S 2021: 15-26 - [i6]Joseph Jay Williams, Jacob Nogas, Nina Deliu, Hammad Shaikh, Sofia S. Villar, Audrey Durand, Anna N. Rafferty:
Challenges in Statistical Analysis of Data Collected by a Bandit Algorithm: An Empirical Exploration in Applications to Adaptively Randomized Experiments. CoRR abs/2103.12198 (2021) - [i5]Adish Singla, Anna N. Rafferty, Goran Radanovic, Neil T. Heffernan:
Reinforcement Learning for Education: Opportunities and Challenges. CoRR abs/2107.08828 (2021) - [i4]Jacob Nogas, Tong Li, Fernando J. Yanez, Arghavan Modiri, Nina Deliu, Ben Prystawski, Sofia S. Villar, Anna N. Rafferty, Joseph Jay Williams:
Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization. CoRR abs/2112.08507 (2021) - 2020
- [j4]Anna N. Rafferty, Rachel Jansen, Thomas L. Griffiths:
Assessing Mathematics Misunderstandings via Bayesian Inverse Planning. Cogn. Sci. 44(10) (2020) - [c32]Rachel Jansen, Anna N. Rafferty, Tom Griffiths:
A rational model of sequential self-assessment. CogSci 2020 - [c31]Zhaobin Li, Luna Yee, Nathaniel Sauerberg, Irene Sakson, Joseph Jay Williams, Anna N. Rafferty:
Getting too personal(ized): The importance of feature choice in online adaptive algorithms. EDM 2020 - [c30]Tyler A. Chang, Anna N. Rafferty:
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages. RepL4NLP@ACL 2020: 7-16 - [e1]Anna N. Rafferty, Jacob Whitehill, Cristóbal Romero, Violetta Cavalli-Sforza:
Proceedings of the 13th International Conference on Educational Data Mining, EDM 2020, Fully virtual conference, July 10-13, 2020. International Educational Data Mining Society 2020, ISBN 978-1-7336736-1-7 [contents] - [i3]Tyler A. Chang, Anna N. Rafferty:
Encodings of Source Syntax: Similarities in NMT Representations Across Target Languages. CoRR abs/2005.08177 (2020)
2010 – 2019
- 2019
- [c29]Anna N. Rafferty, Rachel Jansen, Tom Griffiths:
Modeling students' fraction arithmetic strategies using inverse planning. CogSci 2019: 3554 - [c28]Hammad Shaikh, Arghavan Modiri, Joseph Jay Williams, Anna N. Rafferty:
Balancing Student Success and Inferring Personalized Effects in Dynamic Experiments. EDM 2019 - [c27]Eliane Stampfer Wiese, Anna N. Rafferty, Armando Fox:
Linking code readability, structure, and comprehension among novices: it's complicated. ICSE (SEET) 2019: 84-94 - [c26]Eliane Stampfer Wiese, Anna N. Rafferty, Daniel M. Kopta, Jacqulyn M. Anderson:
Replicating novices' struggles with coding style. ICPC 2019: 13-18 - 2018
- [c25]Anna N. Rafferty, Huiji Ying, Joseph Jay Williams:
Bandit Assignment for Educational Experiments: Benefits to Students Versus Statistical Power. AIED (2) 2018: 286-290 - [c24]Joseph Jay Williams, Anna N. Rafferty, Dustin Tingley, Andrew M. Ang, Walter S. Lasecki, Juho Kim:
Enhancing Online Problems Through Instructor-Centered Tools for Randomized Experiments. CHI 2018: 207 - [c23]Rachel Jansen, Anna N. Rafferty, Tom Griffiths:
Modeling the Dunning-Kruger Effect: A Rational Account of Inaccurate Self-Assessment. CogSci 2018 - [i2]Xiaojin Zhu, Adish Singla, Sandra Zilles, Anna N. Rafferty:
An Overview of Machine Teaching. CoRR abs/1801.05927 (2018) - 2017
- [c22]Joseph Jay Williams, Anna N. Rafferty, Andrew M. Ang, Dustin Tingley, Walter S. Lasecki, Juho Kim:
Connecting Instructors and Learning Scientists via Collaborative Dynamic Experimentation. CHI Extended Abstracts 2017: 3012-3018 - [c21]Rachel Jansen, Anna N. Rafferty, Tom Griffiths:
Algebra is not like trivia: Evaluating self-assessment in an online math tutor. CogSci 2017 - [c20]Eliane Wiese, Anna N. Rafferty, Marcia C. Linn:
Eliciting Middle School Students' Ideas About Graphs Supports Their Learning from a Computer Model. CogSci 2017 - [c19]Joseph Jay Williams, Anna N. Rafferty, Samuel G. Maldonado, Andrew M. Ang, Dustin Tingley, Juho Kim:
MOOClets: A Framework for Dynamic Experimentation and Personalization. L@S 2017: 287-290 - 2016
- [j3]Anna N. Rafferty, Emma Brunskill, Thomas L. Griffiths, Patrick Shafto:
Faster Teaching via POMDP Planning. Cogn. Sci. 40(6): 1290-1332 (2016) - [c18]Anna N. Rafferty, Rachel Jansen, Thomas L. Griffiths:
Using Inverse Planning for Personalized Feedback. EDM 2016: 472-477 - [c17]Joseph Jay Williams, Juho Kim, Anna N. Rafferty, Samuel G. Maldonado, Krzysztof Z. Gajos, Walter S. Lasecki, Neil T. Heffernan:
AXIS: Generating Explanations at Scale with Learnersourcing and Machine Learning. L@S 2016: 379-388 - 2015
- [j2]Anna N. Rafferty, Michelle M. LaMar, Thomas L. Griffiths:
Inferring Learners' Knowledge From Their Actions. Cogn. Sci. 39(3): 584-618 (2015) - [c16]Anna N. Rafferty, Thomas L. Griffiths:
Interpreting Freeform Equation Solving. AIED 2015: 387-397 - 2014
- [b1]Anna N. Rafferty:
Applying Probabilistic Models for Knowledge Diagnosis and Educational Game Design. University of California, Berkeley, USA, 2014 - [j1]Anna N. Rafferty, Thomas L. Griffiths, Dan Klein:
Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor. Cogn. Sci. 38(7): 1406-1431 (2014) - [c15]Stephan C. Meylan, Brett Goldstein, Anna N. Rafferty, Thomas L. Griffiths:
The Telephone Game: Exploring Inductive Biases In Naturalistic Language Use. CogSci 2014 - [c14]Rebecca Neumann, Anna N. Rafferty, Thomas L. Griffiths:
A Bounded Rationality Account of Wishful Thinking. CogSci 2014 - [c13]Anna N. Rafferty, Jodi L. Davenport, David Yaron:
Tracking Student Understanding of Chemical Reactions in ChemVLab+. CogSci 2014 - [c12]Anna N. Rafferty, Thomas L. Griffiths:
Diagnosing Algebra Understanding via Bayesian Inverse Planning. EDM 2014: 351-352 - [c11]Anna N. Rafferty, Libby F. Gerard, Kevin W. McElhaney, Marcia C. Linn:
Promoting Student Learning through Automated Formative Guidance on Chemistry Drawings. ICLS 2014 - 2013
- [c10]Anna N. Rafferty, Elizabeth Gerard, Kevin W. McElhaney, Marcia C. Linn:
Automating Guidance for Students' Chemistry Drawings. AIED Workshops 2013 - [c9]Anna N. Rafferty, Jodi L. Davenport, Emma Brunskill:
Estimating Student Knowledge from Paired Interaction Data. EDM 2013: 260-263 - 2012
- [c8]Anna N. Rafferty, Matei Zaharia, Thomas L. Griffiths:
Optimally Designing Games for Cognitive Science Research. CogSci 2012 - [c7]Anna N. Rafferty, Michelle M. LaMar, Thomas L. Griffiths:
Inferring learners' knowledge from observed actions. EDM 2012: 226-227 - [c6]Jodi L. Davenport, Anna N. Rafferty, Michael J. Timms, David Yaron, Michael Karabinos:
ChemVLab+: Evaluating a Virtual Lab Tutor for High School Chemistry. ICLS 2012 - 2011
- [c5]Anna N. Rafferty, Thomas L. Griffiths, Marc Ettlinger:
Exploring the Relationship Between Learnability and Linguistic Universals. CMCL@ACL 2011: 49-57 - [c4]Anna N. Rafferty, Emma Brunskill, Thomas L. Griffiths, Patrick Shafto:
Faster Teaching by POMDP Planning. AIED 2011: 280-287
2000 – 2009
- 2009
- [c3]Daniel Ramage, Anna N. Rafferty, Christopher D. Manning:
Random Walks for Text Semantic Similarity. Graph-based Methods for Natural Language Processing 2009: 23-31 - 2008
- [c2]Marie-Catherine de Marneffe, Anna N. Rafferty, Christopher D. Manning:
Finding Contradictions in Text. ACL 2008: 1039-1047 - [i1]Sebastian Padó, Marie-Catherine de Marneffe, Bill MacCartney, Anna N. Rafferty, Eric Yeh, Christopher D. Manning:
Deciding Entailment and Contradiction with Stochastic and Edit Distance-based Alignment. TAC 2008 - 2007
- [c1]Anna N. Rafferty, Michael Yudelson:
Applying Learning Factors Analysis to Build Stereotypic Student Models. AIED 2007: 697-698
Coauthor Index
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last updated on 2024-12-18 19:21 CET by the dblp team
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