Daniel Weitekamp III

25 papers A* 2B 2Journal 11Unranked 10
YearRankTypeTitle / 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