Neil T. Heffernan

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 103

Top Venues

Publications

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 (2024)
Michael Smalenberger, Elham Sohrabi, Mengxue Zhang, Sami Baral, Kelly Smalenberger, Andrew S. Lan, Neil T. Heffernan
Automatic Short Answer Grading in College Mathematics Using In-Context Meta-learning: An Evaluation of the Transferability of Findings. AIED Companion (1) (2024)
Allison Wang, Ethan Prihar, Aaron Haim, Neil T. Heffernan
Can Large Language Models Generate Middle School Mathematics Explanations Better Than Human Teachers? AIED Companion (2) (2024)
Aaron Haim, Eamon Worden, Neil T. Heffernan
The Effectiveness of AI Generated, On-Demand Assistance Within Online Learning Platforms. AIED Companion (2) (2024)
Hai Li, Chenglu Li, Wanli Xing, Sami Baral, Neil T. Heffernan
Automated Feedback for Student Math Responses Based on Multi-Modality and Fine-Tuning. LAK (2024)
Morgan P. Lee, Abubakir Siedahmed, Neil T. Heffernan
Expert Features for a Student Support Recommendation Contextual Bandit Algorithm. LAK (2024)
Hai Li, Wanli Xing, Chenglu Li, Wangda Zhu, Neil T. Heffernan
Positive Affective Feedback Mechanisms in an Online Mathematics Learning Platform. L@S (2024)
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)
Ashish Gurung, Kirk Vanacore, Andrew A. McReynolds, Korinn S. Ostrow, Eamon Worden, Adam C. Sales, Neil T. Heffernan
Multiple Choice vs. Fill-In Problems: The Trade-off Between Scalability and Learning. LAK (2024)
Kirk Vanacore, Ashish Gurung, Adam Sales, Neil T. Heffernan
The Effect of Assistance on Gamers: Assessing The Impact of On-Demand Hints & Feedback Availability on Learning for Students Who Game the System. LAK (2024)
Aaron Haim, Stephen Hutt, Stacy T. Shaw, Neil T. Heffernan
Promoting Open Science in Artificial Intelligence: An Interactive Tutorial on Licensing, Data, and Containers. AIED Companion (2) (2024)
Anthony Botelho, Sami Baral, John A. Erickson, Priyanka Benachamardi, Neil T. Heffernan
Leveraging natural language processing to support automated assessment and feedback for student open responses in mathematics. J. Comput. Assist. Learn. 39 (3) (2023)
Aaron Haim, Stacy T. Shaw, Neil T. Heffernan
How to Open Science: Promoting Principles and Reproducibility Practices within the Educational Data Mining Community. EDM (2023)
Aaron Haim, Chris Baxter, Robert Gyurcsan, Stacy T. Shaw, Neil T. Heffernan
How to Open Science: Analyzing the Open Science Statement Compliance of the Learning @ Scale Conference. L@S (2023)
Ethan Prihar, Adam Sales, Neil T. Heffernan
A Bandit You Can Trust. UMAP (2023)
Aaron Haim, Stacy T. Shaw, Neil T. Heffernan
How to Open Science: Promoting Principles and Reproducibility Practices within the Learning @ Scale Community. L@S (2023)
Ashish Gurung, Sami Baral, Morgan P. Lee, Adam C. Sales, Aaron Haim, Kirk P. Vanacore, Andrew A. McReynolds, Hilary Kreisberg, Cristina Heffernan, Neil T. Heffernan
How Common are Common Wrong Answers? Crowdsourcing Remediation at Scale. L@S (2023)
Kirk Vanacore, Ashish Gurung, Andrew Mcreynolds, Allison Liu, Stacy Shaw, Neil T. Heffernan
Impact of Non-Cognitive Interventions on Student Learning Behaviors and Outcomes: An analysis of seven large-scale experimental inventions. LAK (2023)
Sami Baral, Anthony F. Botelho, Abhishek Santhanam, Ashish Gurung, John A. Erickson, Neil T. Heffernan
Investigating Patterns of Tone and Sentiment in Teacher Written Feedback Messages. AIED (Posters/Late Breaking Results/...) (2023)
Mengxue Zhang, Neil T. Heffernan, Andrew Lan
Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions. CoRR (2023)
Sami Baral, Anthony Botelho, Abhishek Santhanam, Ashish Gurung, Li Cheng, Neil T. Heffernan
Auto-scoring Student Responses with Images in Mathematics. EDM (2023)
Ethan Prihar, Kirk Vanacore, Adam Sales, Neil T. Heffernan
Effective Evaluation of Online Learning Interventions with Surrogate Measures. EDM (2023)
Aaron Haim, Stacy Shaw, Neil T. Heffernan
How to Open Science: A Principle and Reproducibility Review of the Learning Analytics and Knowledge Conference. LAK (2023)
Mingyu Feng, Neil T. Heffernan, Kelly Collins, Cristina Heffernan, Robert F. Murphy
Implementing and Evaluating ASSISTments Online Math Homework Support At large Scale over Two Years: Findings and Lessons Learned. AIED (2023)
Ethan Prihar, Aaron Haim, Tracy Jia Shen, Adam Sales, Dongwon Lee, Xintao Wu, Neil T. Heffernan
Investigating the Impact of Skill-Related Videos on Online Learning. L@S (2023)
Morgan P. Lee, Ethan A. Croteau, Ashish Gurung, Anthony F. Botelho, Neil T. Heffernan
Knowledge Tracing Over Time: A Longitudinal Analysis. EDM (2023)
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)
Ashish Gurung, Sami Baral, Kirk P. Vanacore, Andrew A. Mcreynolds, Hilary Kreisberg, Anthony F. Botelho, Stacy T. Shaw, Neil T. Heffernan
Identification, Exploration, and Remediation: Can Teachers Predict Common Wrong Answers? LAK (2023)
Aaron Haim, Robert Gyurcsan, Chris Baxter, Stacy T. Shaw, Neil T. Heffernan
How to Open Science: Debugging Reproducibility within the Educational Data Mining Conference. EDM (2023)
Ethan Prihar, Morgan P. Lee, Mia Hopman, Adam Tauman Kalai, Sofia Vempala, Allison Wang, Gabriel Wickline, Aly Murray, Neil T. Heffernan
Comparing Different Approaches to Generating Mathematics Explanations Using Large Language Models. AIED (Posters/Late Breaking Results/...) (2023)
Aaron Haim, Stacy T. Shaw, Neil T. Heffernan
How to Open Science: Promoting Principles and Reproducibility Practices Within the Artificial Intelligence in Education Community. AIED (Posters/Late Breaking Results/...) (2023)
Mengxue Zhang, Neil T. Heffernan, Andrew S. Lan
Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions. EDM (2023)
Adam Sales, Ethan Prihar, Johann Gagnon-Bartsch, Ashish Gurung, Neil T. Heffernan
More Powerful A/B Testing Using Auxiliary Data and Deep Learning. AIED (2) (2022)
Anthony F. Botelho, Ethan Prihar, Neil T. Heffernan
Deep Learning or Deep Ignorance? Comparing Untrained Recurrent Models in Educational Contexts. AIED (1) (2022)
Raysa Rivera-Bergollo, Sami Baral, Anthony Botelho, Neil T. Heffernan
Leveraging Auxiliary Data from Similar Problems to Improve Automatic Open Response Scoring. EDM (2022)
Adam Sales, Neil T. Heffernan
Causal Inference in Educational Data Mining. EDM (2022)
Jim Goodell, Neil T. Heffernan
Human-Centered Learning Engineering for the Emerging Intelligence Augmentation Economy. HCI (49) (2022)
Sami Baral, Karthik Seetharaman, Anthony F. Botelho, Anzhuo Wang, George T. Heineman, Neil T. Heffernan
Enhancing Auto-scoring of Student Open Responses in the Presence of Mathematical Terms and Expressions. AIED (1) (2022)
Aaron Haim, Ethan Prihar, Neil T. Heffernan
Toward Improving Effectiveness of Crowdsourced, On-Demand Assistance from Educators in Online Learning Platforms. AIED (2) (2022)
Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Ben Motz, Debshila Basu Mallick, Klinton Bicknell, Danielle S. McNamara, René F. Kizilcec, Jeremy Roschelle, Richard G. Baraniuk, Ryan Baker
Third Annual Workshop on A/B Testing and Platform-Enabled Learning Research. L@S (2022)
Aaron Haim, Neil T. Heffernan
Student Perception on the Effectiveness of On-Demand Assistance in Online Learning Platforms. EDM (2022)
Mengxue Zhang, Sami Baral, Neil T. Heffernan, Andrew S. Lan
Automatic Short Math Answer Grading via In-context Meta-learning. EDM (2022)
Ethan Prihar, Aaron Haim, Adam Sales, Neil T. Heffernan
Automatic Interpretable Personalized Learning. L@S (2022)
Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan
Achieving User-Side Fairness in Contextual Bandits. Hum. Centric Intell. Syst. 2 (3-4) (2022)
Ethan Prihar, Alexander Moore, Neil T. Heffernan
Identifying Explanations Within Student-Tutor Chat Logs. EDM (2022)
Ashish Gurung, Neil T. Heffernan
Exploring Fairness in Automated Grading and Feedback Generation of Open-Response Math Problems. AIED (2) (2022)
Mengxue Zhang, Sami Baral, Neil T. Heffernan, Andrew S. Lan
Automatic Short Math Answer Grading via In-context Meta-learning. CoRR (2022)
Adish Singla, Anna N. Rafferty, Goran Radanovic, Neil T. Heffernan
Reinforcement Learning for Education: Opportunities and Challenges. CoRR (2021)
Adam Sales, Ethan Prihar, Neil T. Heffernan, John Pane
Estimating the Intelligent Tutor Effects on Specific Posttest Problems. EDM (2021)
John A. Erickson, Anthony F. Botelho, Zonglin Peng, Rui Huang, Meghana V. Kasal, Neil T. Heffernan
Is It Fair? Automated Open Response Grading. EDM (2021)
Sami Baral, Anthony F. Botelho, John A. Erickson, Priyanka Benachamardi, Neil T. Heffernan
Improving Automated Scoring of Student Open Responses in Mathematics. EDM (2021)
Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Klinton Bicknell
Second Workshop on Educational A/B Testing at Scale. L@S (2021)
Ashish Gurung, Anthony F. Botelho, Neil T. Heffernan
Examining Student Effort on Help through Response Time Decomposition. LAK (2021)
Ethan Prihar, Neil T. Heffernan
A Novel Algorithm for Aggregating Crowdsourced Opinions. EDM (2021)
Shamya Karumbaiah, Andrew S. Lan, Sachit Nagpal, Ryan S. Baker, Anthony Botelho, Neil T. Heffernan
Using Past Data to Warm Start Active Machine Learning: Does Context Matter? LAK (2021)
Renah Razzaq, Korinn S. Ostrow, Neil T. Heffernan
Effect of Immediate Feedback on Math Achievement at the High School Level. AIED (2) (2020)
Thanaporn Patikorn, Neil T. Heffernan
Effectiveness of Crowd-Sourcing On-Demand Assistance from Teachers in Online Learning Platforms. L@S (2020)
Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Burr Settles, Phillip Grimaldi, Derek Lomas
Workshop Proposal: Educational A/B Testing at Scale. L@S (2020)
Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan
Context-Aware Attentive Knowledge Tracing. KDD (2020)
Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan
Context-Aware Attentive Knowledge Tracing. CoRR (2020)
Ashvini Varatharaj, Anthony F. Botelho, Xiwen Lu, Neil T. Heffernan
Supporting Teacher Assessment in Chinese Language Learning Using Textual and Tonal Features. AIED (1) (2020)
John A. Erickson, Anthony F. Botelho, Steven McAteer, Ashvini Varatharaj, Neil T. Heffernan
The automated grading of student open responses in mathematics. LAK (2020)
Ashvini Varatharaj, Anthony F. Botelho, Xiwen Lu, Neil T. Heffernan
Hao Fa Yin: Developing Automated Audio Assessment Tools for a Chinese Language Course. EDM (2019)
Thanaporn Patikorn, David Deisadze, Leo Grande, Ziyang Yu, Neil T. Heffernan
Generalizability of Methods for Imputing Mathematical Skills Needed to Solve Problems from Texts. AIED (1) (2019)
Anthony F. Botelho, Ryan S. Baker, Neil T. Heffernan
Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Student Behavior and Affect. EDM (2019)
Anthony F. Botelho, Ashvini Varatharaj, Eric G. Van Inwegen, Neil T. Heffernan
Refusing to Try: Characterizing Early Stopout on Student Assignments. LAK (2019)
Xiwen Lu, Korinn S. Ostrow, Neil T. Heffernan
Understanding the Complexities of Chinese Word Acquisition within an Online Learning Platform. CSEDU (1) (2019)
Tsung-Yen Yang, Ryan S. Baker, Christoph Studer, Neil T. Heffernan, Andrew S. Lan
Active Learning for Student Affect Detection. EDM (2019)
Korinn S. Ostrow, Neil T. Heffernan
Testing the Validity and Reliability of Intrinsic Motivation Inventory Subscales Within ASSISTments. AIED (1) (2018)
Anthony F. Botelho, Ryan S. Baker, Jaclyn Ocumpaugh, Neil T. Heffernan
Studying Affect Dynamics and Chronometry Using Sensor-Free Detectors. EDM (2018)
Adam Sales, Anthony Botelho, Thanaporn Patikorn, Neil T. Heffernan
Using Big Data to Sharpen Design-Based Inference in A/B Tests. EDM (2018)
Paul Salvador Inventado, Sharris Gayle Francisco Inventado, Noboru Matsuda, Yeping Li, Peter Scupelli, Korinn Ostrow, Neil T. Heffernan, Shihfen Tu, Craig Mason, Mary Logue, Pat McGuire
Using Design Patterns for Math Preservice Teacher Education. EuroPLoP (2018)
Shayan Doroudi, Joseph Jay Williams, Juho Kim, Thanaporn Patikorn, Korinn Ostrow, Douglas Selent, Neil T. Heffernan, Thomas T. Hills, Carolyn Penstein Rosé
Crowdsourcing and Education: Towards a Theory and Praxis of Learnersourcing. ICLS (2018)
Thanaporn Patikorn, Neil T. Heffernan, Jian Zou
An Offline Evaluation Method for Individual Treatment Rules and How to Find Heterogeneous Treatment Effect. EDM (2017)
Stefan Slater, Jaclyn Ocumpaugh, Ryan S. Baker, Ma. Victoria Almeda, Laura Allen, Neil T. Heffernan
Using natural language processing tools to develop complex models of student engagement. ACII (2017)
Jaclyn Ocumpaugh, Ryan S. Baker, Maria Ofelia Clarissa Z. San Pedro, M. Aaron Hawn, Cristina Heffernan, Neil T. Heffernan, Stefan A. Slater
Guidance counselor reports of the ASSISTments college prediction model (ACPM). LAK (2017)
Biao Yin, Thanaporn Patikorn, Anthony F. Botelho, Neil T. Heffernan
Observing Personalizations in Learning: Identifying Heterogeneous Treatment Effects Using Causal Trees. L@S (2017)
Biao Yin, Anthony F. Botelho, Thanaporn Patikorn, Neil T. Heffernan, Jian Zou
Causal Forest vs. Naive Causal Forest in Detecting Personalization: An Empirical Study in ASSISTments. EDM (2017)
Siyuan Zhao, Yaqiong Zhang, Xiaolu Xiong, Anthony Botelho, Neil T. Heffernan
A Memory-Augmented Neural Model for Automated Grading. L@S (2017)
Shimin Kai, Ma. Victoria Almeda, Ryan S. Baker, Nicole Shechtman, Cristina Heffernan, Neil T. Heffernan
Modeling Wheel-spinning and Productive Persistence in Skill Builders. EDM (2017)
Thanaporn Patikorn, Douglas Selent, Neil T. Heffernan, Joseph Beck, Jian Zou
Using a Single Model Trained across Multiple Experiments to Improve the Detection of Treatment Effects. EDM (2017)
Stefan Slater, Ryan S. Baker, Ma. Victoria Almeda, Alex J. Bowers, Neil T. Heffernan
Using correlational topic modeling for automated topic identification in intelligent tutoring systems. LAK (2017)
Liang Zhang, Xiaolu Xiong, Siyuan Zhao, Anthony Botelho, Neil T. Heffernan
Incorporating Rich Features into Deep Knowledge Tracing. L@S (2017)
Xiwen Lu, Xiaolu Xiong, Neil T. Heffernan
Experimenting Choices of Video and Text Feedback in Authentic Foreign Language Assignments at Scale. L@S (2017)
Siyuan Zhao, Neil T. Heffernan
Estimating Individual Treatment Effect from Educational Studies with Residual Counterfactual Networks. EDM (2017)
Seth Akonor Adjei, Anthony F. Botelho, Neil T. Heffernan
Sequencing content in an adaptive testing system: the role of choice. LAK (2017)
Anthony F. Botelho, Ryan S. Baker, Neil T. Heffernan
Improving Sensor-Free Affect Detection Using Deep Learning. AIED (2017)
Paul Salvador Inventado, Peter Scupelli, Cristina Heffernan, Neil T. Heffernan
Feedback Design Patterns for Math Online Learning Systems. EuroPLoP (2017)
Korinn S. Ostrow, Yan Wang, Neil T. Heffernan
How Flexible Is Your Data? A Comparative Analysis of Scoring Methodologies across Learning Platforms in the Context of Group Differentiation. J. Learn. Anal. 4 (2) (2017)
Seth Adjei, Korinn Ostrow, Erik Erickson, Neil T. Heffernan
Clustering Students in ASSISTments: Exploring System- and School-Level Traits to Advance Personalization. EDM (2017)
Maria Ofelia Clarissa Z. San Pedro, Ryan S. Baker, Neil T. Heffernan
An Integrated Look at Middle School Engagement and Learning in Digital Environments as Precursors to College Attendance. Technol. Knowl. Learn. 22 (3) (2017)
Seth Akonor Adjei, Anthony F. Botelho, Neil T. Heffernan
Predicting student performance on post-requisite skills using prerequisite skill data: an alternative method for refining prerequisite skill structures. LAK (2016)
Korinn S. Ostrow, Douglas Selent, Yan Wang, Eric Van Inwegen, Neil T. Heffernan, Joseph Jay Williams
The assessment of learning infrastructure (ALI): the theory, practice, and scalability of automated assessment. LAK (2016)
Anthony F. Botelho, Seth Adjei, Neil T. Heffernan
Modeling Interactions Across Skills: A Method to Construct and Compare Models Predicting the Existence of Skill Relationships. EDM (2016)
Yan Wang, Korinn Ostrow, Seth Adjei, Neil T. Heffernan
The Opportunity Count Model: A Flexible Approach to Modeling Student Performance. L@S (2016)
Kim M. Kelly, Neil T. Heffernan
Optimizing the Amount of Practice in an On-Line Platform. L@S (2016)
Korinn S. Ostrow, Neil T. Heffernan
Studying Learning at Scale with the ASSISTments TestBed. L@S (2016)
Neil T. Heffernan, Korinn S. Ostrow, Kim M. Kelly, Douglas Selent, Eric Van Inwegen, Xiaolu Xiong, Joseph Jay Williams
The Future of Adaptive Learning: Does the Crowd Hold the Key? Int. J. Artif. Intell. Educ. 26 (2) (2016)
Joseph Jay Williams, Anthony Botelho, Adam Sales, Neil T. Heffernan, Charles Lang
Discovering 'Tough Love' Interventions Despite Dropout. EDM (2016)
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)

Neil T. Heffernan.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Neil T. Heffernan