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ORCIDNeil T. Heffernan
Neil Thomas Heffernan III
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- affiliation: Worcester Polytechnic Institute, Worcester, MA, USA
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2020 – today
- 2023
[j16]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): 823-840 (2023)- [c201]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: 28-40 - [c200]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: 74-78 - [c199]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: 290-295 - [c198]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: 341-346 - [c197]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: 156-164 - [c196]Kirk Vanacore, Ashish Gurung, Andrew A. McReynolds, Allison S. 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: 165-174 - [c195]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: 399-410 - [c194]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: 4-13 - [c193]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: 70-80 - [c192]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: 174-182 - [c191]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: 248-250 - [c190]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: 254-256 - [c189]Ethan Prihar, Adam Sales, Neil T. Heffernan:
A Bandit You Can Trust. UMAP 2023: 106-115 - [i10]Mengxue Zhang, Neil T. Heffernan, Andrew Lan:
Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions. CoRR abs/2306.00791 (2023) - 2022
- [j15]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): 81-94 (2022) - [c188]Aaron Haim, Ethan Prihar, Neil T. Heffernan:
Toward Improving Effectiveness of Crowdsourced, On-Demand Assistance from Educators in Online Learning Platforms. AIED (2) 2022: 29-34 - [c187]Ashish Gurung, Neil T. Heffernan:
Exploring Fairness in Automated Grading and Feedback Generation of Open-Response Math Problems. AIED (2) 2022: 71-76 - [c186]Anthony F. Botelho, Ethan Prihar, Neil T. Heffernan:
Deep Learning or Deep Ignorance? Comparing Untrained Recurrent Models in Educational Contexts. AIED (1) 2022: 281-293 - [c185]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: 524-527 - [c184]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: 685-690 - [c183]Jim Goodell, Neil T. Heffernan:
Human-Centered Learning Engineering for the Emerging Intelligence Augmentation Economy. HCI (49) 2022: 619-623 - [c182]Ethan Prihar, Aaron Haim, Adam Sales, Neil T. Heffernan:
Automatic Interpretable Personalized Learning. L@S 2022: 1-11 - [c181]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: 252-254 - [i9]Mengxue Zhang, Sami Baral, Neil T. Heffernan, Andrew S. Lan:
Automatic Short Math Answer Grading via In-context Meta-learning. CoRR abs/2205.15219 (2022) - 2021
- [c180]Ethan Prihar, Alexander Moore, Neil T. Heffernan:
Identifying Struggling Students by Comparing Online Tutor Clickstreams. AIED (2) 2021: 290-295 - [c179]Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee:
Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT. AIED (1) 2021: 408-419 - [c178]Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan:
Fairness-aware Bandit-based Recommendation. IEEE BigData 2021: 1273-1278 - [c177]Sami Baral, Anthony F. Botelho, John A. Erickson, Priyanka Benachamardi, Neil T. Heffernan:
Improving Automated Scoring of Student Open Responses in Mathematics. EDM 2021 - [c176]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 - [c175]Ethan Prihar, Neil T. Heffernan:
A Novel Algorithm for Aggregating Crowdsourced Opinions. EDM 2021 - [c174]Adam Sales, Ethan Prihar, Neil T. Heffernan, John Pane:
Estimating the Intelligent Tutor Effects on Specific Posttest Problems. EDM 2021 - [c173]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: 151-160 - [c172]Ashish Gurung, Anthony F. Botelho, Neil T. Heffernan:
Examining Student Effort on Help through Response Time Decomposition. LAK 2021: 292-301 - [c171]Steven Ritter, Neil T. Heffernan, Joseph Jay Williams, Derek Lomas, Klinton Bicknell:
Second Workshop on Educational A/B Testing at Scale. L@S 2021: 1-3 - [c170]Ethan Prihar, Thanaporn Patikorn, Anthony Botelho, Adam Sales, Neil T. Heffernan:
Toward Personalizing Students' Education with Crowdsourced Tutoring. L@S 2021: 37-45 - [i8]Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee:
Classifying Math KCs via Task-Adaptive Pre-Trained BERT. CoRR abs/2105.11343 (2021) - [i7]Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Dongwon Lee:
MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education. CoRR abs/2106.07340 (2021) - [i6]Adish Singla, Anna N. Rafferty, Goran Radanovic, Neil T. Heffernan:
Reinforcement Learning for Education: Opportunities and Challenges. CoRR abs/2107.08828 (2021) - 2020
- [c169]Renah Razzaq, Korinn S. Ostrow, Neil T. Heffernan:
Effect of Immediate Feedback on Math Achievement at the High School Level. AIED (2) 2020: 263-267 - [c168]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: 562-573 - [c167]Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan:
Context-Aware Attentive Knowledge Tracing. KDD 2020: 2330-2339 - [c166]Zitao Liu, Songfan Yang, Jiliang Tang, Neil T. Heffernan, Rose Luckin:
Recent Advances in Multimodal Educational Data Mining in K-12 Education. KDD 2020: 3549-3550 - [c165]John A. Erickson, Anthony F. Botelho, Steven McAteer, Ashvini Varatharaj, Neil T. Heffernan:
The automated grading of student open responses in mathematics. LAK 2020: 615-624 - [c164]Thanaporn Patikorn, Neil T. Heffernan:
Effectiveness of Crowd-Sourcing On-Demand Assistance from Teachers in Online Learning Platforms. L@S 2020: 115-124 - [c163]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: 219-220 - [i5]Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan:
Context-Aware Attentive Knowledge Tracing. CoRR abs/2007.12324 (2020) - [i4]Wen Huang, Kevin Labille, Xintao Wu, Dongwon Lee, Neil T. Heffernan:
Achieving User-Side Fairness in Contextual Bandits. CoRR abs/2010.12102 (2020)
2010 – 2019
- 2019
- [c162]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: 396-405 - [c161]Xiwen Lu, Korinn S. Ostrow, Neil T. Heffernan:
Understanding the Complexities of Chinese Word Acquisition within an Online Learning Platform. CSEDU (1) 2019: 321-329 - [c160]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 - [c159]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 - [c158]Tsung-Yen Yang, Ryan S. Baker, Christoph Studer, Neil T. Heffernan, Andrew S. Lan:
Active Learning for Student Affect Detection. EDM 2019 - [c157]Anthony F. Botelho, Ashvini Varatharaj, Eric G. Van Inwegen, Neil T. Heffernan:
Refusing to Try: Characterizing Early Stopout on Student Assignments. LAK 2019: 391-400 - 2018
- [c156]Korinn S. Ostrow, Neil T. Heffernan:
Testing the Validity and Reliability of Intrinsic Motivation Inventory Subscales Within ASSISTments. AIED (1) 2018: 381-394 - [c155]Anthony F. Botelho, Ryan S. Baker, Jaclyn Ocumpaugh, Neil T. Heffernan:
Studying Affect Dynamics and Chronometry Using Sensor-Free Detectors. EDM 2018 - [c154]Adam Sales, Anthony Botelho, Thanaporn Patikorn, Neil T. Heffernan:
Using Big Data to Sharpen Design-Based Inference in A/B Tests. EDM 2018 - [c153]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: 31:1-31:8 - [c152]Shayan Doroudi, Joseph Jay Williams, Juho Kim, Thanaporn Patikorn, Korinn Ostrow, Douglas Selent, Neil T. Heffernan, Thomas T. Hills, Carolyn P. Rosé:
Crowdsourcing and Education: Towards a Theory and Praxis of Learnersourcing. ICLS 2018 - 2017
- [j14]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) - [j13]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): 243-270 (2017) - [c151]Stefan Slater, Jaclyn Ocumpaugh, Ryan S. Baker, Ma. Victoria Almeda, Laura K. Allen, Neil T. Heffernan:
Using natural language processing tools to develop complex models of student engagement. ACII 2017: 542-547 - [c150]Anthony F. Botelho, Ryan S. Baker, Neil T. Heffernan:
Improving Sensor-Free Affect Detection Using Deep Learning. AIED 2017: 40-51 - [c149]Seth Adjei, Korinn Ostrow, Erik Erickson, Neil T. Heffernan:
Clustering Students in ASSISTments: Exploring System- and School-Level Traits to Advance Personalization. EDM 2017 - [c148]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 - [c147]Thanaporn Patikorn, Neil T. Heffernan, Jian Zou:
An Offline Evaluation Method for Individual Treatment Rules and How to Find Heterogeneous Treatment Effect. EDM 2017 - [c146]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 - [c145]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 - [c144]Siyuan Zhao, Neil T. Heffernan:
Estimating Individual Treatment Effect from Educational Studies with Residual Counterfactual Networks. EDM 2017 - [c143]Paul Salvador Inventado, Peter Scupelli, Cristina Heffernan, Neil T. Heffernan:
Feedback Design Patterns for Math Online Learning Systems. EuroPLoP 2017: 31:1-31:15 - [c142]Seth Akonor Adjei, Anthony F. Botelho, Neil T. Heffernan:
Sequencing content in an adaptive testing system: the role of choice. LAK 2017: 178-182 - [c141]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: 393-397 - [c140]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: 479-488 - [c139]Liang Zhang, Xiaolu Xiong, Siyuan Zhao, Anthony Botelho, Neil T. Heffernan:
Incorporating Rich Features into Deep Knowledge Tracing. L@S 2017: 169-172 - [c138]Siyuan Zhao, Yaqiong Zhang, Xiaolu Xiong, Anthony Botelho, Neil T. Heffernan:
A Memory-Augmented Neural Model for Automated Grading. L@S 2017: 189-192 - [c137]Biao Yin, Thanaporn Patikorn, Anthony F. Botelho, Neil T. Heffernan:
Observing Personalizations in Learning: Identifying Heterogeneous Treatment Effects Using Causal Trees. L@S 2017: 299-302 - [c136]Xiwen Lu, Xiaolu Xiong, Neil T. Heffernan:
Experimenting Choices of Video and Text Feedback in Authentic Foreign Language Assignments at Scale. L@S 2017: 335-338 - 2016
- [j12]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): 615-644 (2016) - [c135]Stefan Slater, Jaclyn Ocumpaugh, Ryan S. Baker, Peter Scupelli, Paul Salvador Inventado, Neil T. Heffernan:
Semantic Features of Math Problems: Relationships to Student Learning and Engagement. EDM 2016: 223-230 - [c134]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: 292-297 - [c133]Paul Salvador Inventado, Peter Scupelli, Eric Van Inwegen, Korinn Ostrow, Neil Thomas Heffernan III, Jaclyn Ocumpaugh, Ryan S. Baker, Stefan Slater, Mia Almeda:
Hint Availability Slows Completion Times in Summer Work. EDM 2016: 388-393 - [c132]Joseph Jay Williams, Anthony Botelho, Adam Sales, Neil T. Heffernan, Charles Lang:
Discovering 'Tough Love' Interventions Despite Dropout. EDM 2016: 650-651 - [c131]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: 279-288 - [c130]Yan Wang, Korinn Ostrow, Joseph Beck, Neil T. Heffernan:
Enhancing the efficiency and reliability of group differentiation through partial credit. LAK 2016: 454-458 - [c129]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: 469-473 - [c128]Yan Wang, Korinn Ostrow, Seth Adjei, Neil T. Heffernan:
The Opportunity Count Model: A Flexible Approach to Modeling Student Performance. L@S 2016: 113-116 - [c127]Kim M. Kelly, Neil T. Heffernan:
Optimizing the Amount of Practice in an On-Line Platform. L@S 2016: 145-148 - [c126]Douglas Selent, Thanaporn Patikorn, Neil T. Heffernan:
ASSISTments Dataset from Multiple Randomized Controlled Experiments. L@S 2016: 181-184 - [c125]Korinn S. Ostrow, Neil T. Heffernan:
Studying Learning at Scale with the ASSISTments TestBed. L@S 2016: 333-334 - [c124]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
- [c123]Korinn Ostrow, Neil T. Heffernan, Cristina Heffernan, Zoe Peterson:
Blocking Vs. Interleaving: Examining Single-Session Effects Within Middle School Math Homework. AIED 2015: 338-347 - [c122]Seth Akonor Adjei, Neil T. Heffernan:
Improving Learning Maps Using an Adaptive Testing System: PLACEments. AIED 2015: 517-520 - [c121]Yang Jiang, Ryan Shaun Joazeiro de Baker, Luc Paquette, Maria Ofelia Clarissa Z. San Pedro, Neil T. Heffernan:
Learning, Moment-by-Moment and Over the Long Term. AIED 2015: 654-657 - [c120]Korinn S. Ostrow, Neil T. Heffernan:
The Role of Student Choice Within Adaptive Tutoring. AIED 2015: 752-755 - [c119]Douglas Selent, Neil T. Heffernan:
When More Intelligent Tutoring in the Form of Buggy Messages Does not Help. AIED 2015: 768-771 - [c118]Kim M. Kelly, Neil T. Heffernan:
Developing Self-regulated Learners Through an Intelligent Tutoring System. AIED 2015: 840-843 - [c117]Joseph Jay Williams, Markus Krause, Praveen K. Paritosh, Jacob Whitehill, Justin Reich, Juho Kim, Piotr Mitros, Neil T. Heffernan, Brian C. Keegan:
Connecting Collaborative & Crowd Work with Online Education. CSCW Companion 2015: 313-318 - [c116]Ryan S. Baker, Peter Brusilovsky, Dragan Gasevic, Neil T. Heffernan, Mykola Pechenizkiy, Alyssa Friend Wise:
Grand Challenges for EDM and Related Research Areas. EDM 2015: 15 - [c115]Maria Ofelia San Pedro, Erica L. Snow, Ryan S. Baker, Danielle S. McNamara, Neil T. Heffernan:
Exploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test Achievement. EDM 2015: 85-92 - [c114]Charles Lang, Neil T. Heffernan, Korinn Ostrow, Yutao Wang:
The Impact of Incorporating Student Confidence Items into an Intelligent Tutor: A Randomized Controlled Trial. EDM 2015: 144-149 - [c113]Eric Van Inwegen, Seth Adjei, Yan Wang, Neil T. Heffernan:
Using Partial Credit and Response History to Model User Knowledge. EDM 2015: 313-319 - [c112]Korinn Ostrow, Christopher Donnelly, Neil T. Heffernan:
Optimizing Partial Credit Algorithms to Predict Student Performance. EDM 2015: 404-407 - [c111]Francisco Enrique Vicente Castro, Seth Adjei, Tyler Colombo, Neil T. Heffernan:
Building Models to Predict Hint-or-Attempt Actions of Students. EDM 2015: 476-479 - [c110]Eric Van Inwegen, Yan Wang, Seth Adjei, Neil T. Heffernan:
The Effect of the Distribution of Predictions of User Models. EDM 2015: 620-621 - [c109]Anthony F. Botelho, Seth Akonor Adjei, Hao Wan, Neil T. Heffernan:
Predicting Student Aptitude Using Performance History. EDM 2015: 622-623 - [c108]Kim M. Kelly, Yan Wang, Tamisha Thompson, Neil T. Heffernan:
Defining Mastery: Knowledge Tracing Versus N- Consecutive Correct Responses. EDM 2015: 630-631 - [c107]Yutao Wang, Neil T. Heffernan, Cristina Heffernan:
Towards better affect detectors: effect of missing skills, class features and common wrong answers. LAK 2015: 31-35 - [c106]Maria Ofelia Clarissa Z. San Pedro, Ryan Shaun Baker, Neil T. Heffernan, Jaclyn Ocumpaugh:
Exploring college major choice and middle school student behavior, affect and learning: what happens to students who game the system? LAK 2015: 36-40 - [c105]Eric Van Inwegen, Seth Adjei, Yan Wang, Neil T. Heffernan:
An analysis of the impact of action order on future performance: the fine-grain action model. LAK 2015: 320-324 - [c104]Korinn Ostrow, Christopher Donnelly, Seth Adjei, Neil T. Heffernan:
Improving Student Modeling Through Partial Credit and Problem Difficulty. L@S 2015: 11-20 - [c103]Anthony Botelho, Hao Wan, Neil T. Heffernan:
The Prediction of Student First Response Using Prerequisite Skills. L@S 2015: 39-45 - [c102]Joseph Jay Williams, Korinn Ostrow, Xiaolu Xiong, Elena L. Glassman, Juho Kim, Samuel G. Maldonado, Na Li, Justin Reich, Neil T. Heffernan:
Using and Designing Platforms for In Vivo Educational Experiments. L@S 2015: 409-412 - [c101]Joseph Jay Williams, Neil T. Heffernan:
A Methodology for Discovering how to Adaptively Personalize to Users using Experimental Comparisons. UMAP Workshops 2015 - [e1]Cristina Conati, Neil T. Heffernan, Antonija Mitrovic,