Daniel Weitekamp III

25 papers A* 2B 2Journal 11Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	When Should Users Check? Modeling Confirmation Frequency in Multi-Step Agentic AI Tasks. CHI Jieyu Zhou, Aryan Roy, Sneh Gupta, Daniel Weitekamp III, Christopher J. MacLellan
2025	—	`conf`	Beyond Final Answers: Evaluating Large Language Models for Math Tutoring. AIED (1) Adit Gupta, Jennifer M. Reddig, Tommaso Calò, Daniel Weitekamp III, Christopher J. MacLellan
2025	J	`jnl`	Beyond Final Answers: Evaluating Large Language Models for Math Tutoring. CoRR Adit Gupta, Jennifer M. Reddig, Tommaso Calò, Daniel Weitekamp III, Christopher J. MacLellan
2025	J	`jnl`	Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI. IEEE Trans. Learn. Technol. Liang Zhang, Jionghao Lin, John Sabatini, Conrad Borchers, Daniel Weitekamp III, Meng Cao, John Hollander, Xiangen Hu, Arthur C. Graesser
2025	B	`conf`	Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency. CogSci Daniel Weitekamp III, Christopher MacLellan, Erik Harpstead, Napol Rachatasumrit, Kenneth R. Koedinger
2025	J	`jnl`	Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency. CoRR Daniel Weitekamp III, Christopher MacLellan, Erik Harpstead, Kenneth R. Koedinger
2025	—	`conf`	TutorGym: A Testbed for Evaluating AI Agents as Tutors and Students. AIED (3) Daniel Weitekamp III, Momin Naushad Siddiqui, Christopher J. MacLellan
2025	J	`jnl`	TutorGym: A Testbed for Evaluating AI Agents as Tutors and Students. CoRR Daniel Weitekamp III, Momin Naushad Siddiqui, Christopher J. MacLellan
2025	J	`jnl`	When Should Users Check? A Decision-Theoretic Model of Confirmation Frequency in Multi-Step AI Agent Tasks. CoRR Jieyu Zhou, Aryan Roy, Sneh Gupta, Daniel Weitekamp III, Christopher J. MacLellan
2024	J	`jnl`	AI2T: Building Trustable AI Tutors by Interactively Teaching a Self-Aware Learning Agent. CoRR Daniel Weitekamp III, Erik Harpstead, Kenneth R. Koedinger
2024	J	`jnl`	Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI. CoRR Liang Zhang, Jionghao Lin, John Sabatini, Conrad Borchers, Daniel Weitekamp III, Meng Cao, John Hollander, Xiangen Hu, Arthur C. Graesser
2024	—	`conf`	Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency. AAAI Spring Symposia Daniel Weitekamp III
2024	—	`conf`	Good Fit Bad Policy: Why Fit Statistics Are a Biased Measure of Knowledge Tracer Quality. AIED Companion (2) Napol Rachatasumrit, Daniel Weitekamp III, Kenneth R. Koedinger
2024	J	`jnl`	STAND: Data-Efficient and Self-Aware Precondition Induction for Interactive Task Learning. CoRR Daniel Weitekamp III, Kenneth R. Koedinger
2023	—	`conf`	Building Educational Technology Quickly and Robustly with an Interactively Teachable AI. AIED (Posters/Late Breaking Results/...) Daniel Weitekamp III
2023	—	`conf`	Computational Models of Learning: Deepening Care and Carefulness in AI in Education. AIED (Posters/Late Breaking Results/...) Daniel Weitekamp III, Kenneth R. Koedinger
2023	—	`conf`	Simulating Learning from Language and Examples. AIED (Posters/Late Breaking Results/...) Daniel Weitekamp III, Napol Rachatasumrit, Rachael Wei, Erik Harpstead, Kenneth R. Koedinger
2022	—	`conf`	A Mobile Invented Spelling Tutoring System. AIED (2) Daniel Weitekamp III, Patience Stevens
2021	J	`jnl`	Decomposed Inductive Procedure Learning. CoRR Daniel Weitekamp III, Christopher MacLellan, Erik Harpstead, Kenneth R. Koedinger
2021	—	`conf`	Toward Stable Asymptotic Learning with Simulated Learners. AIED (2) Daniel Weitekamp III, Erik Harpstead, Kenneth R. Koedinger
2020	A*	`conf`	An Interaction Design for Machine Teaching to Develop AI Tutors. CHI Daniel Weitekamp III, Erik Harpstead, Kenneth R. Koedinger
2020	—	`conf`	Investigating Differential Error Types Between Human and Simulated Learners. AIED (1) Daniel Weitekamp III, Zihuiwen Ye, Napol Rachatasumrit, Erik Harpstead, Kenneth R. Koedinger
2019	J	`jnl`	Topology Classification with Deep Learning to Improve Real-Time Event Selection at the LHC. Comput. Softw. Big Sci. Thong Q. Nguyen, Daniel Weitekamp III, Dustin Anderson, Roberto Castello, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant
2019	B	`conf`	Toward Near Zero-Parameter Prediction Using a Computational Model of Student Learning. EDM Daniel Weitekamp III, Erik Harpstead, Christopher J. MacLellan, Napol Rachatasumrit, Kenneth R. Koedinger
2018	J	`jnl`	Topology classification with deep learning to improve real-time event selection at the LHC. CoRR Thong Q. Nguyen, Daniel Weitekamp III, Dustin Anderson, Roberto Castello, Olmo Cerri, Maurizio Pierini, Maria Spiropulu, Jean-Roch Vlimant