Andrew S. Lan - RankMe

192 papers A* 14A 10B 35Misc 7Journal 86Unranked 33

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	KASER: Knowledge-Aligned Student Error Simulator for Open-Ended Coding Tasks. CoRR Zhangqi Duan, Nigel Fernandez, Andrew S. Lan
2026	J	`jnl`	Simulated Students in Tutoring Dialogues: Substance or Illusion? CoRR Alexander Scarlatos, Jaewook Lee, Simon Woodhead, Andrew S. Lan
2025	B	`conf`	9th Educational Data Mining in Computer Science Education (CSEDM) Workshop. EDM Bita Akram, Yang Shi, Peter Brusilovsky, Thomas W. Price, Ken Koedinger, Paulo Carvalho, Shan Zhang, Andrew S. Lan, Juho Leinonen
2025	J	`jnl`	Automated Knowledge Component Generation and Knowledge Tracing for Coding Problems. CoRR Zhangqi Duan, Nigel Fernandez, Sri Kanakadandi, Bita Akram, Andrew S. Lan
2025	A	`conf`	Exploring Knowledge Tracing in Tutor-Student Dialogues using LLMs. LAK Alexander Scarlatos, Ryan Shaun Baker, Andrew S. Lan
2025	J	`jnl`	Exploring LLMs for Predicting Tutor Strategy and Student Outcomes in Dialogues. CoRR Fareya Ikram, Alexander Scarlatos, Andrew S. Lan
2025	J	`jnl`	From Text to Visuals: Using LLMs to Generate Math Diagrams with Vector Graphics. CoRR Jaewook Lee, Jeongah Lee, Wanyong Feng, Andrew S. Lan
2025	J	`jnl`	Intelligent Textbooks. Int. J. Artif. Intell. Educ. Sergey A. Sosnovsky, Peter Brusilovsky, Andrew S. Lan
2025	J	`jnl`	Interpretable Mnemonic Generation for Kanji Learning via Expectation-Maximization. CoRR Jaewook Lee, Alexander Scarlatos, Andrew S. Lan
2025	J	`jnl`	Learning Code-Edit Embedding to Model Student Debugging Behavior. CoRR Hasnain Heickal, Andrew S. Lan
2025	—	`conf`	Learning Code-Edit Embeddings to Model Student Debugging Behavior. AIED (6) Hasnain Heickal, Andrew S. Lan
2025	J	`jnl`	LookAlike: Consistent Distractor Generation in Math MCQs. CoRR Nisarg Parikh, Nigel Fernandez, Alexander Scarlatos, Simon Woodhead, Andrew S. Lan
2025	J	`jnl`	Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics. IEEE Trans. Emerg. Top. Comput. Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura Melissa Cruz Castro, Kerrie A. Douglas, Andrew S. Lan, Christopher G. Brinton
2025	J	`jnl`	Pattern-based Knowledge Component Extraction from Student Code Using Representation Learning. CoRR Muntasir Hoq, Griffin Pitts, Andrew S. Lan, Peter Brusilovsky, Bita Akram
2025	J	`jnl`	RADAR: Reasoning-Ability and Difficulty-Aware Routing for Reasoning LLMs. CoRR Nigel Fernandez, Branislav Kveton, Ryan A. Rossi, Andrew S. Lan, Jack Zichao Wang
2025	—	`conf`	Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs. AIED (4) Wanyong Feng, Peter Tran, Stephen Sireci, Andrew S. Lan
2025	J	`jnl`	Reasoning and Sampling-Augmented MCQ Difficulty Prediction via LLMs. CoRR Wanyong Feng, Peter Tran, Stephen Sireci, Andrew S. Lan
2025	A*	`conf`	SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction. EMNLP Alexander Scarlatos, Nigel Fernandez, Christopher Ormerod, Susan Lottridge, Andrew S. Lan
2025	J	`jnl`	SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction. CoRR Alexander Scarlatos, Nigel Fernandez, Christopher Ormerod, Susan Lottridge, Andrew S. Lan
2025	A	`conf`	Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks. LAK Zhangqi Duan, Nigel Fernandez, Alexander Hicks, Andrew S. Lan
2025	—	`conf`	The Efficiency of Teacher-Driven Context Personalization in Mathematics with Large Language Models. AIED (4) Candace A. Walkington, Theodora Beauchamp, Andrew S. Lan, Tiffini Pruitt-Britton
2025	J	`jnl`	The StudyChat Dataset: Student Dialogues With ChatGPT in an Artificial Intelligence Course. CoRR Hunter McNichols, Andrew S. Lan
2025	J	`jnl`	The Use of Large Language Models in Education. Int. J. Artif. Intell. Educ. Wanli Xing, Nia Nixon, Scott A. Crossley, Paul Denny, Andrew S. Lan, John C. Stamper, Zhou Yu
2025	—	`conf`	Training LLM-Based Tutors to Improve Student Learning Outcomes in Dialogues. AIED (1) Alexander Scarlatos, Naiming Liu, Jaewook Lee, Richard G. Baraniuk, Andrew S. Lan
2025	J	`jnl`	Training LLM-based Tutors to Improve Student Learning Outcomes in Dialogues. CoRR Alexander Scarlatos, Naiming Liu, Jaewook Lee, Richard G. Baraniuk, Andrew S. Lan
2025	J	`jnl`	Whose story is it? Personalizing story generation by inferring author styles. CoRR Nischal Ashok Kumar, Chau Minh Pham, Mohit Iyyer, Andrew S. Lan
2024	B	`conf`	8th Educational Data Mining in Computer Science Education (CSEDM) Workshop. EDM Yang Shi, Peter Brusilovsky, Bita Akram, Thomas W. Price, Juho Leinonen, Kenneth R. Koedinger, Andrew S. Lan
2024	J	`jnl`	A Benchmark for Math Misconceptions: Bridging Gaps in Middle School Algebra with AI-Supported Instruction. CoRR Nancy Otero, Stefania Druga, Andrew S. Lan
2024	—	`conf`	Automatic Short Answer Grading in College Mathematics Using In-Context Meta-learning: An Evaluation of the Transferability of Findings. AIED Companion (1) Michael Smalenberger, Elham Sohrabi, Mengxue Zhang, Sami Baral, Kelly Smalenberger, Andrew S. Lan, Neil T. Heffernan
2024	B	`conf`	Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions? EDM Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steven Ritter, Andrew S. Lan
2024	J	`jnl`	Can Large Language Models Replicate ITS Feedback on Open-Ended Math Questions? CoRR Hunter McNichols, Jaewook Lee, Stephen Fancsali, Steven Ritter, Andrew S. Lan
2024	A*	`conf`	DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions. EMNLP Nigel Fernandez, Alexander Scarlatos, Wanyong Feng, Simon Woodhead, Andrew S. Lan
2024	J	`jnl`	DiVERT: Distractor Generation with Variational Errors Represented as Text for Math Multiple-choice Questions. CoRR Nigel Fernandez, Alexander Scarlatos, Simon Woodhead, Andrew S. Lan
2024	J	`jnl`	Evaluating GPT-4 at Grading Handwritten Solutions in Math Exams. CoRR Adriana Caraeni, Alexander Scarlatos, Andrew S. Lan
2024	—	`conf`	Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models. NAACL-HLT (Findings) Wanyong Feng, Jaewook Lee, Hunter McNichols, Alexander Scarlatos, Digory Smith, Simon Woodhead, Nancy Otero Ornelas, Andrew S. Lan
2024	J	`jnl`	Exploring Automated Distractor Generation for Math Multiple-choice Questions via Large Language Models. CoRR Wanyong Feng, Jaewook Lee, Hunter McNichols, Alexander Scarlatos, Digory Smith, Simon Woodhead, Nancy Otero Ornelas, Andrew S. Lan
2024	—	`conf`	Exploring Automated Keyword Mnemonics Generation with Large Language Models via Overgenerate-and-Rank. EMNLP (Findings) Jaewook Lee, Hunter McNichols, Andrew S. Lan
2024	J	`jnl`	Exploring Automated Keyword Mnemonics Generation with Large Language Models via Overgenerate-and-Rank. CoRR Jaewook Lee, Hunter McNichols, Andrew S. Lan
2024	J	`jnl`	Exploring Knowledge Tracing in Tutor-Student Dialogues. CoRR Alexander Scarlatos, Andrew S. Lan
2024	B	`conf`	From Reaction to Anticipation: Predicting Future Affect. EDM Andres Felipe Zambrano, Ryan S. Baker, Sami Baral, Neil T. Heffernan, Andrew S. Lan
2024	B	`conf`	Generating Feedback-Ladders for Logical Errors in Programming using Large Language Models. EDM Hasnain Heickal, Andrew S. Lan
2024	J	`jnl`	Generating Feedback-Ladders for Logical Errors in Programming using Large Language Models. CoRR Hasnain Heickal, Andrew S. Lan
2024	—	`conf`	Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank. BEA Alexander Scarlatos, Wanyong Feng, Andrew S. Lan, Simon Woodhead, Digory Smith
2024	J	`jnl`	Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank. CoRR Alexander Scarlatos, Wanyong Feng, Digory Smith, Simon Woodhead, Andrew S. Lan
2024	—	`conf`	Improving Socratic Question Generation using Data Augmentation and Preference Optimization. BEA Nischal Ashok Kumar, Andrew S. Lan
2024	J	`jnl`	Improving Socratic Question Generation using Data Augmentation and Preference Optimization. CoRR Nischal Ashok Kumar, Andrew S. Lan
2024	—	`conf`	Improving the Validity of Automatically Generated Feedback via Reinforcement Learning. AIED (1) Alexander Scarlatos, Digory Smith, Simon Woodhead, Andrew S. Lan
2024	J	`jnl`	Improving the Validity of Automatically Generated Feedback via Reinforcement Learning. CoRR Alexander Scarlatos, Digory Smith, Simon Woodhead, Andrew S. Lan
2024	B	`conf`	Interpreting Latent Student Knowledge Representations in Programming Assignments. EDM Nigel Fernandez, Andrew S. Lan
2024	J	`jnl`	Interpreting Latent Student Knowledge Representations in Programming Assignments. CoRR Nigel Fernandez, Andrew S. Lan
2024	—	`ed.`	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. HEXED/L3MNGET@EDM 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 S. 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 A. Walkington
2024	B	`conf`	Leveraging Large Language Models for Next-Generation Educational Technologies. EDM Neil T. Heffernan, Rose E. Wang, Christopher MacLellan, Arto Hellas, Chenglu Li, Candace A. Walkington, Joshua Littenberg-Tobias, David Joyner, Steven Moore, Adish Singla, Zach A. Pardos, Maciej Pankiewicz, Juho Kim, Shashank Sonkar, Clayton Cohn, Anthony Botelho, Andrew S. Lan, Lan Jiang, Mingyu Feng, Tanja Käser, Eamon Worden
2024	B	`conf`	Math Multiple Choice Question Generation via Human-Large Language Model Collaboration. EDM Jaewook Lee, Digory Smith, Simon Woodhead, Andrew S. Lan
2024	J	`jnl`	Math Multiple Choice Question Generation via Human-Large Language Model Collaboration. CoRR Jaewook Lee, Digory Smith, Simon Woodhead, Andrew S. Lan
2024	—	`ed.`	Proceedings of 8th Educational Data Mining in Computer Science Education Workshop (CSEDM 2024) co-located with the 17th Educational Data Mining Conference (EDM 2024), Atlanta, GA, USA, July 14, 2024. CSEDM@EDM Yang Shi, Peter Brusilovsky, Bita Akram, Thomas W. Price, Juho Leinonen, Ken Koedinger, Andrew S. Lan
2024	—	`conf`	SyllabusQA: A Course Logistics Question Answering Dataset. ACL (1) Nigel Fernandez, Alexander Scarlatos, Andrew S. Lan
2024	J	`jnl`	SyllabusQA: A Course Logistics Question Answering Dataset. CoRR Nigel Fernandez, Alexander Scarlatos, Andrew S. Lan
2024	J	`jnl`	Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks. CoRR Zhangqi Duan, Nigel Fernandez, Alexander Hicks, Andrew S. Lan
2024	J	`jnl`	Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science Education. CoRR Nischal Ashok Kumar, Andrew S. Lan
2023	B	`conf`	A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing. EDM Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee, Hunter McNichols, Aritra Ghosh, Andrew S. Lan
2023	J	`jnl`	A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing. CoRR Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee, Hunter McNichols, Aritra Ghosh, Andrew S. Lan
2023	—	`conf`	Active Learning for a Classroom Observer who Can't Time Travel. ACIIW Andres Felipe Zambrano, Ryan S. Baker, Andrew S. Lan
2023	A	`conf`	Algebra Error Classification with Large Language Models. AIED Hunter McNichols, Mengxue Zhang, Andrew S. Lan
2023	J	`jnl`	Algebra Error Classification with Large Language Models. CoRR Hunter McNichols, Mengxue Zhang, Andrew S. Lan
2023	A	`conf`	Balancing Test Accuracy and Security in Computerized Adaptive Testing. AIED Wanyong Feng, Aritra Ghosh, Stephen Sireci, Andrew S. Lan
2023	J	`jnl`	Balancing Test Accuracy and Security in Computerized Adaptive Testing. CoRR Wanyong Feng, Aritra Ghosh, Stephen Sireci, Andrew S. Lan
2023	A*	`conf`	DiFA: Differentiable Feature Acquisition. AAAI Aritra Ghosh, Andrew S. Lan
2023	J	`jnl`	Exploring Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context Learning. CoRR Hunter McNichols, Wanyong Feng, Jaewook Lee, Alexander Scarlatos, Digory Smith, Simon Woodhead, Andrew S. Lan
2023	—	`conf`	Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank. BEA@ACL Nischal Ashok Kumar, Nigel Fernandez, Zichao Wang, Andrew S. Lan
2023	J	`jnl`	Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank. CoRR Nischal Ashok Kumar, Nigel Fernandez, Zichao Wang, Andrew S. Lan
2023	—	`conf`	Intelligent Textbooks: The Fifth International Workshop. AIED (Posters/Late Breaking Results/...) Sergey A. Sosnovsky, Peter Brusilovsky, Andrew S. Lan
2023	J	`jnl`	Interpretable Math Word Problem Solution Generation Via Step-by-step Planning. CoRR Mengxue Zhang, Zichao Wang, Zhichao Yang, Weiqi Feng, Andrew S. Lan
2023	—	`conf`	Interpretable Math Word Problem Solution Generation via Step-by-step Planning. ACL (1) Mengxue Zhang, Zichao Wang, Zhichao Yang, Weiqi Feng, Andrew S. Lan
2023	B	`conf`	Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions. EDM Mengxue Zhang, Neil T. Heffernan, Andrew S. Lan
2023	J	`jnl`	Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions. CoRR Mengxue Zhang, Neil T. Heffernan, Andrew S. Lan
2023	—	`ed.`	Proceedings of the Fifth International Workshop on Intelligent Textbooks 2023 co-located with the 24th International Conference on Artificial Intelligence in Education (AIED 2023), Tokyo, Japan, July 3, 2023. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Andrew S. Lan
2023	J	`jnl`	RetICL: Sequential Retrieval of In-Context Examples with Reinforcement Learning. CoRR Alexander Scarlatos, Andrew S. Lan
2023	A	`conf`	SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual Cues. AIED Jaewook Lee, Andrew S. Lan
2023	J	`jnl`	SmartPhone: Exploring Keyword Mnemonic with Auto-generated Verbal and Visual Cues. CoRR Jaewook Lee, Andrew S. Lan
2023	—	`conf`	Tree-Based Representation and Generation of Natural and Mathematical Language. ACL (1) Alexander Scarlatos, Andrew S. Lan
2023	J	`jnl`	Tree-Based Representation and Generation of Natural and Mathematical Language. CoRR Alexander Scarlatos, Andrew S. Lan
2022	—	`conf`	Automated Scoring for Reading Comprehension via In-context BERT Tuning. AIED (1) Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
2022	J	`jnl`	Automated Scoring for Reading Comprehension via In-context BERT Tuning. CoRR Nigel Fernandez, Aritra Ghosh, Naiming Liu, Zichao Wang, Benoît Choffin, Richard G. Baraniuk, Andrew S. Lan
2022	B	`conf`	Automatic Short Math Answer Grading via In-context Meta-learning. EDM Mengxue Zhang, Sami Baral, Neil T. Heffernan, Andrew S. Lan
2022	J	`jnl`	Automatic Short Math Answer Grading via In-context Meta-learning. CoRR Mengxue Zhang, Sami Baral, Neil T. Heffernan, Andrew S. Lan
2022	A*	`conf`	DiPS: Differentiable Policy for Sketching in Recommender Systems. AAAI Aritra Ghosh, Saayan Mitra, Andrew S. Lan
2022	—	`conf`	Intelligent Textbooks: Themes and Topics. AIED (2) Sergey A. Sosnovsky, Peter Brusilovsky, Andrew S. Lan
2022	A	`conf`	Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning. CIKM Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura M. Cruz Castro, Kerrie A. Douglas, Andrew S. Lan, Christopher G. Brinton
2022	J	`jnl`	Mitigating Biases in Student Performance Prediction via Attention-Based Personalized Federated Learning. CoRR Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura M. Cruz Castro, Kerrie A. Douglas, Andrew S. Lan, Christopher G. Brinton
2022	J	`jnl`	Multi-Layer Personalized Federated Learning for Mitigating Biases in Student Predictive Analytics. CoRR Yun-Wei Chu, Seyyedali Hosseinalipour, Elizabeth Tenorio, Laura M. Cruz Castro, Kerrie A. Douglas, Andrew S. Lan, Christopher G. Brinton
2022	J	`jnl`	Open-Ended Knowledge Tracing. CoRR Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2022	A*	`conf`	Open-ended Knowledge Tracing for Computer Science Education. EMNLP Naiming Liu, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2022	—	`ed.`	Proceedings of the Fourth International Workshop on Intelligent Textbooks 2022 co-located with 23d International Conference on Artificial Intelligence in Education (AIED 2022), Durham, UK, July 27, 2022. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Andrew S. Lan
2022	B	`conf`	Process-BERT: A Framework for Representation Learning on Educational Process Data. EDM Alexander Scarlatos, Christopher Brinton, Andrew S. Lan
2022	J	`jnl`	Process-BERT: A Framework for Representation Learning on Educational Process Data. CoRR Alexander Scarlatos, Christopher G. Brinton, Andrew S. Lan
2021	A*	`conf`	BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing. IJCAI Aritra Ghosh, Andrew S. Lan
2021	J	`jnl`	BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing. CoRR Aritra Ghosh, Andrew S. Lan
2021	—	`conf`	Click-Based Student Performance Prediction: A Clustering Guided Meta-Learning Approach. IEEE BigData Yun-Wei Chu, Elizabeth Tenorio, Laura M. Cruz Castro, Kerrie A. Douglas, Andrew S. Lan, Christopher G. Brinton
2021	J	`jnl`	Click-Based Student Performance Prediction: A Clustering Guided Meta-Learning Approach. CoRR Yun-Wei Chu, Elizabeth Tenorio, Laura Melissa Cruz Castro, Kerrie A. Douglas, Andrew S. Lan, Christopher G. Brinton
2021	—	`conf`	Contrastive Learning Improves Model Robustness Under Label Noise. CVPR Workshops Aritra Ghosh, Andrew S. Lan
2021	J	`jnl`	Contrastive Learning Improves Model Robustness Under Label Noise. CoRR Aritra Ghosh, Andrew S. Lan
2021	J	`jnl`	DiPS: Differentiable Policy for Sketching in Recommender Systems. CoRR Aritra Ghosh, Saayan Mitra, Andrew S. Lan
2021	J	`jnl`	Do We Really Need Gold Samples for Sample Weighting Under Label Noise? CoRR Aritra Ghosh, Andrew S. Lan
2021	A	`conf`	Do We Really Need Gold Samples for Sample Weighting under Label Noise? WACV Aritra Ghosh, Andrew S. Lan
2021	J	`jnl`	Learning Student Interest Trajectory for MOOCThread Recommendation. CoRR Shalini Pandey, Andrew S. Lan, George Karypis, Jaideep Srivastava
2021	A	`conf`	Linguistic Skill Modeling for Second Language Acquisition. LAK Brian Zylich, Andrew S. Lan
2021	B	`conf`	Math Operation Embeddings for Open-ended Solution Analysis and Feedback. EDM Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2021	J	`jnl`	Math Operation Embeddings for Open-ended Solution Analysis and Feedback. CoRR Mengxue Zhang, Zichao Wang, Richard G. Baraniuk, Andrew S. Lan
2021	—	`conf`	Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. EMNLP (1) Zichao Wang, Andrew S. Lan, Richard G. Baraniuk
2021	J	`jnl`	Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints. CoRR Zichao Wang, Andrew S. Lan, Richard G. Baraniuk
2021	—	`conf`	Mathematical Formula Representation via Tree Embeddings. iTextbooks@AIED Zichao Wang, Andrew S. Lan, Richard G. Baraniuk
2021	J	`jnl`	MetaSense: Boosting RF Sensing Accuracy Using Dynamic Metasurface Antenna. IEEE Internet Things J. Guohao Lan, Mohammadreza F. Imani, Zida Liu, José Manjarrés, Wenjun Hu, Andrew S. Lan, David R. Smith, Maria Gorlatova
2021	—	`conf`	Option Tracing: Beyond Correctness Analysis in Knowledge Tracing. AIED (1) Aritra Ghosh, Jay Raspat, Andrew S. Lan
2021	J	`jnl`	Option Tracing: Beyond Correctness Analysis in Knowledge Tracing. CoRR Aritra Ghosh, Jay Raspat, Andrew S. Lan
2021	J	`jnl`	Personalized Education in the AI Era: What to Expect Next? CoRR Setareh Maghsudi, Andrew S. Lan, Jie Xu, Mihaela van der Schaar
2021	J	`jnl`	Personalized Education in the Artificial Intelligence Era: What to Expect Next. IEEE Signal Process. Mag. Setareh Maghsudi, Andrew S. Lan, Jie Xu, Mihaela van der Schaar
2021	—	`ed.`	Proceedings of the Third International Workshop on Inteligent Textbooks 2021 Co-located with 22nd International Conference on Artificial Intelligence in Education (AIED 2021), Online, June 15, 2021. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Andrew S. Lan
2021	—	`conf`	Scientific Formula Retrieval via Tree Embeddings. IEEE BigData Zichao Wang, Mengxue Zhang, Richard G. Baraniuk, Andrew S. Lan
2021	A	`conf`	Using Past Data to Warm Start Active Machine Learning: Does Context Matter? LAK Shamya Karumbaiah, Andrew S. Lan, Sachit Nagpal, Ryan S. Baker, Anthony Botelho, Neil T. Heffernan
2020	A*	`conf`	Context-Aware Attentive Knowledge Tracing. KDD Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan
2020	J	`jnl`	Context-Aware Attentive Knowledge Tracing. CoRR Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan
2020	—	`conf`	Exploring Automated Question Answering Methods for Teaching Assistance. AIED (1) Brian Zylich, Adam Viola, Brokk Toggerson, Lara Al-Hariri, Andrew S. Lan
2020	J	`jnl`	Highlights as an Early Predictor of Student Comprehension and Interests. Cogn. Sci. Adam Winchell, Andrew S. Lan, Michael Mozer
2020	—	`conf`	Learning Student Interest Trajectory for MOOC Thread Recommendation. ICDM (Workshops) Shalini Pandey, Andrew S. Lan, George Karypis, Jaideep Srivastava
2020	Misc	`conf`	MSE-Optimal Neural Network Initialization via Layer Fusion. CISS Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer
2020	J	`jnl`	MSE-Optimal Neural Network Initialization via Layer Fusion. CoRR Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer
2020	J	`jnl`	Meta-knowledge dictionary learning on 1-bit response data for student knowledge diagnosis. Knowl. Based Syst. Yupei Zhang, Huan Dai, Yue Yun, Shuhui Liu, Andrew S. Lan, Xuequn Shang
2020	—	`ed.`	Proceedings of the Second International Workshop on Intelligent Textbooks 2020 co-located with 21st International Conference on Artificial Intelligence in Education (AIED 2020), Online, July 06, 2020. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Andrew S. Lan
2020	—	`conf`	Robust and Interpretable Grounding of Spatial References with Relation Networks. EMNLP (Findings) Tsung-Yen Yang, Andrew S. Lan, Karthik Narasimhan
2020	—	`conf`	Skill-based Career Path Modeling and Recommendation. IEEE BigData Aritra Ghosh, Beverly P. Woolf, Shlomo Zilberstein, Andrew S. Lan
2020	B	`conf`	VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. EDM Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk
2020	J	`jnl`	VarFA: A Variational Factor Analysis Framework For Efficient Bayesian Learning Analytics. CoRR Jack Zichao Wang, Yi Gu, Andrew S. Lan, Richard G. Baraniuk
2020	B	`conf`	qDKT: Question-centric Deep Knowledge Tracing. EDM Shashank Sonkar, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk
2020	J	`jnl`	qDKT: Question-centric Deep Knowledge Tracing. CoRR Shashank Sonkar, Andrew E. Waters, Andrew S. Lan, Phillip J. Grimaldi, Richard G. Baraniuk
2019	B	`conf`	A Meta-Learning Augmented Bidirectional Transformer Model for Automatic Short Answer Grading. EDM Zichao Wang, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk
2019	B	`conf`	Active Learning for Student Affect Detection. EDM Tsung-Yen Yang, Ryan S. Baker, Christoph Studer, Neil T. Heffernan, Andrew S. Lan
2019	—	`conf`	Adaptive Remediation with Multi-modal Content. HCI (32) Yuwei Tu, Christopher G. Brinton, Andrew S. Lan, Mung Chiang
2019	B	`conf`	Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. EDM Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala
2019	B	`conf`	Grade Prediction with Neural Collaborative Filtering. DSAA Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala
2019	A*	`conf`	Hurts to Be Too Early: Benefits and Drawbacks of Communication in Multi-Agent Learning. INFOCOM Parinaz Naghizadeh, Maria Gorlatova, Andrew S. Lan, Mung Chiang
2019	J	`jnl`	IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election. CoRR Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk
2019	B	`conf`	IdeoTrace: a framework for ideology tracing with a case study on the 2016 U.S. presidential election. ASONAM Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk
2019	A	`conf`	Predicting the Timing and Quality of Responses in Online Discussion Forums. ICDCS Patrick Hansen, Richard Junior Bustamante, Tsung-Yen Yang, Elizabeth Tenorio, Christopher G. Brinton, Mung Chiang, Andrew S. Lan
2019	—	`ed.`	Proceedings of the First Workshop on Intelligent Textbooks co-located with 20th International Conference on Artificial Intelligence in Education (AIED 2019), Chicago, IL, USA, June 25, 2019. iTextbooks@AIED Sergey A. Sosnovsky, Peter Brusilovsky, Richard G. Baraniuk, Rakesh Agrawal, Andrew S. Lan
2018	A*	`conf`	An Estimation and Analysis Framework for the Rasch Model. ICML Andrew S. Lan, Mung Chiang, Christoph Studer
2018	J	`jnl`	An Estimation and Analysis Framework for the Rasch Model. CoRR Andrew S. Lan, Mung Chiang, Christoph Studer
2018	B	`conf`	Behavioral Analysis at Scale: Learning Course Prerequisite Structures from Learner Clickstreams. EDM Weiyu Chen, Andrew S. Lan, Da Cao, Christopher G. Brinton, Mung Chiang
2018	Misc	`conf`	Insense: Incoherent Sensor Selection for Sparse Signals. ICASSP Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk
2018	J	`jnl`	Insense: Incoherent sensor selection for sparse signals. Signal Process. Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk
2018	—	`conf`	Learner Behavioral Feature Refinement and Augmentation Using GANs. AIED (2) Da Cao, Andrew S. Lan, Weiyu Chen, Christopher G. Brinton, Mung Chiang
2018	A*	`conf`	Learning Cloud Dynamics to Optimize Spot Instance Bidding Strategies. INFOCOM Mikhail Khodak, Liang Zheng, Andrew S. Lan, Carlee Joe-Wong, Mung Chiang
2018	—	`conf`	Learning Informative and Private Representations via Generative Adversarial Networks. IEEE BigData Tsung-Yen Yang, Christopher G. Brinton, Prateek Mittal, Mung Chiang, Andrew S. Lan
2018	A*	`conf`	Linear Spectral Estimators and an Application to Phase Retrieval. ICML Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer
2018	J	`jnl`	Linear Spectral Estimators and an Application to Phase Retrieval. CoRR Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer
2018	Misc	`conf`	Linearized binary regression. CISS Andrew S. Lan, Mung Chiang, Christoph Studer
2018	J	`jnl`	On the Efficiency of Online Social Learning Networks. IEEE/ACM Trans. Netw. Christopher G. Brinton, Swapna Buccapatnam, Liang Zheng, Da Cao, Andrew S. Lan, Felix Ming Fai Wong, Sangtae Ha, Mung Chiang, H. Vincent Poor
2018	—	`conf`	Personalized Thread Recommendation for MOOC Discussion Forums. ECML/PKDD (2) Andrew S. Lan, Jonathan C. Spencer, Ziqi Chen, Christopher G. Brinton, Mung Chiang
2018	J	`jnl`	Personalized Thread Recommendation for MOOC Discussion Forums. CoRR Andrew S. Lan, Jonathan C. Spencer, Ziqi Chen, Christopher G. Brinton, Mung Chiang
2018	J	`jnl`	PhaseLin: Linear Phase Retrieval. CoRR Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer
2018	Misc	`conf`	PhaseLin: Linear phase retrieval. CISS Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer
2018	B	`conf`	QG-net: a data-driven question generation model for educational content. L@S Zichao Wang, Andrew S. Lan, Weili Nie, Andrew E. Waters, Phillip J. Grimaldi, Richard G. Baraniuk
2018	B	`conf`	Textbook annotations as an early predictor of student learning. EDM Adam Winchell, Michael Mozer, Andrew S. Lan, Phillip Grimaldi, Harold Pashler
2017	B	`conf`	A Latent Factor Model For Instructor Content Preference Analysis. EDM Jack Z. Wang, Andrew S. Lan, Phillip Grimaldi, Richard G. Baraniuk
2017	J	`jnl`	BLAh: Boolean Logic Analysis for Graded Student Response Data. IEEE J. Sel. Top. Signal Process. Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2017	B	`conf`	Behavior-Based Latent Variable Model for Learner Engagement. EDM Andrew S. Lan, Christopher G. Brinton, Tsung-Yen Yang, Mung Chiang
2017	Misc	`conf`	Contextual multi-armed bandit algorithms for personalized learning action selection. ICASSP Indu Manickam, Andrew S. Lan, Richard G. Baraniuk
2017	B	`conf`	D.TRUMP: Data-mining Textual Responses to Uncover Misconception Patterns. L@S Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk
2017	B	`conf`	Data-Mining Textual Responses to Uncover Misconception Patterns. EDM Joshua J. Michalenko, Andrew S. Lan, Andrew E. Waters, Phillip Grimaldi, Richard G. Baraniuk
2017	J	`jnl`	Data-Mining Textual Responses to Uncover Misconception Patterns. CoRR Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk
2017	J	`jnl`	Insense: Incoherent Sensor Selection for Sparse Signals. CoRR Amirali Aghazadeh, Mohammad Golbabaee, Andrew S. Lan, Richard G. Baraniuk
2017	B	`conf`	Personalized Feedback for Open-Response Mathematical Questions using Long Short-Term Memory Networks. EDM Joshua J. Michalenko, Andrew S. Lan, Richard G. Baraniuk
2017	A*	`conf`	RHash: Robust Hashing via L_infinity-norm Distortion. IJCAI Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk
2017	B	`conf`	Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning. EDM Andrew E. Waters, Phillip Grimaldi, Andrew S. Lan, Richard G. Baraniuk
2016	B	`conf`	A Contextual Bandits Framework for Personalized Learning Action Selection. EDM Andrew S. Lan, Richard G. Baraniuk
2016	A*	`conf`	Dealbreaker: A Nonlinear Latent Variable Model for Educational Data. ICML Andrew S. Lan, Tom Goldstein, Richard G. Baraniuk, Christoph Studer
2016	J	`jnl`	Near-Isometric Binary Hashing for Large-scale Datasets. CoRR Amirali Aghazadeh, Andrew S. Lan, Anshumali Shrivastava, Richard G. Baraniuk
2016	—	`conf`	Optimal ranking of test items using the Rasch model. Allerton Divyanshu Vats, Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2015	B	`conf`	Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. L@S Andrew S. Lan, Divyanshu Vats, Andrew E. Waters, Richard G. Baraniuk
2015	J	`jnl`	Mathematical Language Processing: Automatic Grading and Feedback for Open Response Mathematical Questions. CoRR Andrew S. Lan, Divyanshu Vats, Andrew E. Waters, Richard G. Baraniuk
2014	Misc	`conf`	Matrix recovery from quantized and corrupted measurements. ICASSP Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	B	`conf`	Quantized Matrix Completion for Personalized Learning. EDM Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Quantized Matrix Completion for Personalized Learning. CoRR Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Sparse factor analysis for learning and content analytics. J. Mach. Learn. Res. Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2014	J	`jnl`	Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. CoRR Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2014	A*	`conf`	Time-varying learning and content analytics via sparse factor analysis. KDD Andrew S. Lan, Christoph Studer, Richard G. Baraniuk
2013	J	`jnl`	Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data CoRR Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2013	B	`conf`	Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data. EDM Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2013	J	`jnl`	Sparse Factor Analysis for Learning and Content Analytics CoRR Andrew S. Lan, Andrew E. Waters, Christoph Studer, Richard G. Baraniuk
2013	Misc	`conf`	Sparse probit factor analysis for learning analytics. ICASSP Andrew E. Waters, Andrew S. Lan, Christoph Studer
2013	B	`conf`	Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics. EDM Andrew S. Lan, Christoph Studer, Andrew E. Waters, Richard G. Baraniuk
2013	B	`conf`	Test-size Reduction for Concept Estimation. EDM Divyanshu Vats, Christoph Studer, Andrew S. Lan, Lawrence Carin, Richard G. Baraniuk
2013	J	`jnl`	Time-varying Learning and Content Analytics via Sparse Factor Analysis. CoRR Andrew S. Lan, Christoph Studer, Richard G. Baraniuk