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2020 – today
- 2024
[j15]Mudit Mangal
, Zachary A. Pardos:
Implementing equitable and intersectionality-aware ML in education: A practical guide. Br. J. Educ. Technol. 55(5): 2003-2038 (2024)- [j14]Yerin Kwak, Zachary A. Pardos:
Bridging large language model disparities: Skill tagging of multilingual educational content. Br. J. Educ. Technol. 55(5): 2039-2057 (2024) - [j13]Zhi Li, Zachary A. Pardos, Cheng Ren:
Aligning open educational resources to new taxonomies: How AI technologies can help and in which scenarios. Comput. Educ. 216: 105027 (2024) - [c100]Aubrey Condor, Zachary A. Pardos:
Explainable Automatic Grading with Neural Additive Models. AIED (1) 2024: 18-31 - [c99]Zachary A. Pardos:
AI for Adaptive Tutoring and Transfer Student Success. CSEDU 2024: 7 - [c98]Conrad Borchers, Yinuo Xu, Zachary A. Pardos:
Are You an Early Dropper or Late Shopper? Mining Enrollment Transaction Data to Study Procrastination in Higher Education. EDM 2024 - [c97]Aubrey Condor, Zachary A. Pardos:
Auditing an Automatic Grading Model with deep Reinforcement Learning. EDM 2024 - [c96]Shreya K. Sheel, Ioannis Anastasopoulos, Zachary A. Pardos:
Comparing Authoring Experiences with Spreadsheet Interfaces vs GUIs. LAK 2024: 598-607 - [c95]Yinuo Xu, Zachary A. Pardos:
Extracting Course Similarity Signal using Subword Embeddings. LAK 2024: 857-863 - [c94]Frederik Baucks, Robin Schmucker, Conrad Borchers, Zachary A. Pardos, Laurenz Wiskott:
Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. L@S 2024: 165-176 - [i21]Cheng Ren, Zachary A. Pardos, Zhi Li:
Human-AI Collaboration Increases Skill Tagging Speed but Degrades Accuracy. CoRR abs/2403.02259 (2024) - [i20]Qi Liu, Yan Zhuang, Haoyang Bi, Zhenya Huang, Weizhe Huang, Jiatong Li, Junhao Yu, Zirui Liu, Zirui Hu, Yuting Hong, Zachary A. Pardos, Haiping Ma, Mengxiao Zhu, Shijin Wang, Enhong Chen:
Survey of Computerized Adaptive Testing: A Machine Learning Perspective. CoRR abs/2404.00712 (2024) - [i19]Aubrey Condor, Zachary A. Pardos:
Explainable Automatic Grading with Neural Additive Models. CoRR abs/2405.00489 (2024) - [i18]Aubrey Condor, Zachary A. Pardos:
Auditing an Automatic Grading Model with deep Reinforcement Learning. CoRR abs/2405.07087 (2024) - [i17]Ilia Sucholutsky, Katherine M. Collins, Maya Malaviya, Nori Jacoby, Weiyang Liu, Theodore R. Sumers, Michalis Korakakis, Umang Bhatt, Mark K. Ho, Joshua B. Tenenbaum, Bradley C. Love, Zachary A. Pardos, Adrian Weller, Thomas L. Griffiths:
Representational Alignment Supports Effective Machine Teaching. CoRR abs/2406.04302 (2024) - [i16]Frederik Baucks, Robin Schmucker, Conrad Borchers, Zachary A. Pardos, Laurenz Wiskott:
Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. CoRR abs/2406.04348 (2024) - [i15]Yunting Liu, Shreya Bhandari, Zachary A. Pardos:
Leveraging LLM-Respondents for Item Evaluation: a Psychometric Analysis. CoRR abs/2407.10899 (2024) - 2023
- [j12]Zachary A. Pardos, Conrad Borchers, Run Yu:
Credit hours is not enough: Explaining undergraduate perceptions of course workload using LMS records. Internet High. Educ. 56: 100882 (2023) - [c93]Zachary A. Pardos, Ioannis Anastasopoulos, Shreya K. Sheel:
Conducting Rapid Experimentation with an Open-Source Adaptive Tutoring System. AIED (Posters/Late Breaking Results/...) 2023: 38-43 - [c92]Zachary A. Pardos, Matthew Tang, Ioannis Anastasopoulos, Shreya K. Sheel, Ethan Zhang:
OATutor: An Open-source Adaptive Tutoring System and Curated Content Library for Learning Sciences Research. CHI 2023: 416:1-416:17 - [c91]Yinuo Xu, Zachary A. Pardos:
Mining Detailed Course Transaction Records for Semantic Information. EDM 2023 - [c90]Conrad Borchers, Zachary A. Pardos:
Insights into undergraduate pathways using course load analytics. LAK 2023: 219-229 - [c89]Lingrui Xu, Zachary A. Pardos, Anirudh Pai:
Convincing the Expert: Reducing Algorithm Aversion in Administrative Higher Education Decision-making. L@S 2023: 215-225 - [c88]Ioannis Anastasopoulos, Shreya K. Sheel, Zachary A. Pardos, Shreya Bhandari:
Introducing an Open-source Adaptive Tutoring System to Accelerate Learning Sciences Experimentation. L@S 2023: 251-253 - [c87]Yan Zhuang, Qi Liu, Guanhao Zhao, Zhenya Huang, Weizhe Huang, Zachary A. Pardos, Enhong Chen, Jinze Wu, Xin Li:
A Bounded Ability Estimation for Computerized Adaptive Testing. NeurIPS 2023 - [c86]Sara Khorasani, Sadia Nawaz, Brandon Victor Syiem, Jing Wei, Zachary A. Pardos, Jarrod Knibbe, Eduardo Velloso:
An Empirical Evaluation of Educational Data Mining Techniques in a Dynamic VR Application. OZCHI 2023: 604-623 - [i14]Zachary A. Pardos, Shreya Bhandari:
Learning gain differences between ChatGPT and human tutor generated algebra hints. CoRR abs/2302.06871 (2023) - 2022
- [j11]Zachary A. Pardos, Leah F. Rosenbaum, Dor Abrahamson:
Characterizing learner behavior from touchscreen data. Int. J. Child Comput. Interact. 31: 100357 (2022) - [j10]Dor Abrahamson, Marcelo Worsley, Zachary A. Pardos, Lu Ou:
Learning analytics of embodied design: Enhancing synergy. Int. J. Child Comput. Interact. 32: 100409 (2022) - [c85]Aubrey Condor, Zachary A. Pardos, Marcia C. Linn:
Representing Scoring Rubrics as Graphs for Automatic Short Answer Grading. AIED (1) 2022: 354-365 - [c84]Aubrey Condor, Zachary A. Pardos:
A deep reinforcement learning approach to automatic formative feedback. EDM 2022 - [c83]Yueqi Wang, Zachary A. Pardos:
Does chronology matter? Sequential vs contextual approaches to knowledge tracing. EDM 2022 - [i13]Conrad Borchers, Zachary A. Pardos:
Insights into undergraduate pathways using course load analytics. CoRR abs/2212.09974 (2022) - 2021
- [c82]Erzhuo Shao, Shiyuan Guo, Zachary A. Pardos:
Degree Planning with PLAN-BERT: Multi-Semester Recommendation Using Future Courses of Interest. AAAI 2021: 14920-14929 - [c81]Weijie Jiang, Zachary A. Pardos:
Towards Equity and Algorithmic Fairness in Student Grade Prediction. AIES 2021: 608-617 - [c80]Anirudhan Badrinath, Frédéric Wang, Zachary A. Pardos:
pyBKT: An Accessible Library of Bayesian Knowledge Tracing Models. EDM 2021 - [c79]Aubrey Condor, Max Litster, Zachary A. Pardos:
Automatic short answer grading with SBERT on out-of-sample questions. EDM 2021 - [c78]Shiwei Tong, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang, Zachary A. Pardos, Weijie Jiang:
Item Response Ranking for Cognitive Diagnosis. IJCAI 2021: 1750-1756 - [c77]Zhi Li, Cheng Ren, Xianyou Li, Zachary A. Pardos:
Learning Skill Equivalencies Across Platform Taxonomies. LAK 2021: 354-363 - [c76]Shruthi Chockkalingam, Run Yu, Zachary A. Pardos:
Which one's more work? Predicting effective credit hours between courses. LAK 2021: 599-605 - [c75]Run Yu, Zachary A. Pardos, Hung Chau, Peter Brusilovsky:
Orienting Students to Course Recommendations Using Three Types of Explanation. UMAP (Adjunct Publication) 2021: 238-245 - [i12]Zhi Li, Cheng Ren, Xianyou Li, Zachary A. Pardos:
Learning Skill Equivalencies Across Platform Taxonomies. CoRR abs/2102.09377 (2021) - [i11]Renzhe Yu, John Scott, Zachary A. Pardos:
Unsupervised Representations Predict Popularity of Peer-Shared Artifacts in an Online Learning Environment. CoRR abs/2103.00163 (2021) - [i10]Anirudhan Badrinath, Frédéric Wang, Zachary A. Pardos:
pyBKT: An Accessible Python Library of Bayesian Knowledge Tracing Models. CoRR abs/2105.00385 (2021) - [i9]Weijie Jiang, Zachary A. Pardos:
Towards Equity and Algorithmic Fairness in Student Grade Prediction. CoRR abs/2105.06604 (2021) - 2020
- [c74]Aishwarya Jadhav, Yifat Amir, Zachary A. Pardos:
Lexical Relation Mining in Neural Word Embeddings. COLING 2020: 1299-1311 - [c73]Hsiao-Yu Chiang, José Camacho-Collados, Zachary A. Pardos:
Understanding the Source of Semantic Regularities in Word Embeddings. CoNLL 2020: 119-131 - [c72]Clarence Chen, Zachary A. Pardos:
Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling. EDM 2020 - [c71]Weijie Jiang, Zachary A. Pardos:
Evaluating sources of course information and models of representation on a variety of institutional prediction tasks. EDM 2020 - [c70]Zachary A. Pardos, Weijie Jiang:
Designing for serendipity in a university course recommendation system. LAK 2020: 350-359 - [i8]Clarence Chen, Zachary A. Pardos:
Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modeling. CoRR abs/2001.08333 (2020)
2010 – 2019
- 2019
- [j9]Zachary A. Pardos, Lev Horodyskyj:
Analysis of Student Behaviour in Habitable Worlds Using Continuous Representation Visualization. J. Learn. Anal. 6(1) (2019) - [j8]Zachary A. Pardos, Zihao Fan, Weijie Jiang:
Connectionist recommendation in the wild: on the utility and scrutability of neural networks for personalized course guidance. User Model. User Adapt. Interact. 29(2): 487-525 (2019) - [c69]Mohamed Alkaoud, Zachary A. Pardos:
Degree Curriculum Contraction: A Vector Space Approach. AIED (2) 2019: 14-18 - [c68]Matthew Dong, Run Yu, Zachary A. Pardos:
Design and Deployment of a Better Course Search Tool: Inferring Latent Keywords from Enrollment Networks. EC-TEL 2019: 480-494 - [c67]Matthew Dong, Run Yu, Zachary A. Pardos:
Design and Deployment of a Better University Course Search: Inferring Latent Keywords from Enrollments. EDM 2019 - [c66]Nan Jiang, Zachary A. Pardos:
Binary Q-matrix Learning with dAFM. EDM 2019 - [c65]John Kolb, Scott Farrar, Zachary A. Pardos:
Generalizing Expert Misconception Diagnoses Through Common Wrong Answer Embedding. EDM 2019 - [c64]Korah J. Wiley, Allison Bradford, Zachary A. Pardos, Marcia C. Linn:
Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction. EDM 2019 - [c63]Korah J. Wiley, Allison Bradford, Zachary A. Pardos, Marcia C. Linn:
Beyond Autoscoring: Extracting Conceptual Connections from Essays for Classroom Instruction. EDM 2019 - [c62]Renzhe Yu, Zachary A. Pardos, John Scott:
Student Behavioral Embeddings and Their Relationship to Outcomes in a Collaborative Online Course. EDM (Workshops) 2019: 23-29 - [c61]Weijie Jiang, Zachary A. Pardos, Qiang Wei:
Goal-based Course Recommendation. LAK 2019: 36-45 - [c60]Zachary A. Pardos, Hung Chau, Haocheng Zhao:
Data-Assistive Course-to-Course Articulation Using Machine Translation. L@S 2019: 22:1-22:10 - [c59]Zachary A. Pardos, Weijie Jiang:
Designing for Serendipity in a University Course Recommendation System. IntRS@RecSys 2019: 19-27 - [c58]Weijie Jiang, Zachary A. Pardos:
Time slice imputation for personalized goal-based recommendation in higher education. RecSys 2019: 506-510 - [i7]Zachary A. Pardos, Weijie Jiang:
Combating the Filter Bubble: Designing for Serendipity in a University Course Recommendation System. CoRR abs/1907.01591 (2019) - 2018
- [c57]Yuetian Luo, Zachary A. Pardos:
Diagnosing University Student Subject Proficiency and Predicting Degree Completion in Vector Space. AAAI 2018: 7920-7927 - [c56]Christopher Vu Le, Zachary A. Pardos, Samuel D. Meyer, Rachel Thorp:
Communication at Scale in a MOOC Using Predictive Engagement Analytics. AIED (1) 2018: 239-252 - [c55]Vinitra Swamy, Allen Guo, Samuel Lau, Wilton Wu, Madeline Wu, Zachary A. Pardos, David E. Culler:
Deep Knowledge Tracing for Free-Form Student Code Progression. AIED (2) 2018: 348-352 - [c54]Zachary A. Pardos, Scott Farrar, John Kolb, Gao Xian Peh, Jong Ha Lee:
Distributed Representation of Misconceptions. ICLS 2018 - [c53]Zhiping Xiao, Siqi Li, Zachary A. Pardos:
AutoQuiz: A Personalized, Adaptive, Test Practice System (Abstract Only). SIGCSE 2018: 1089 - [c52]Zachary A. Pardos, Changran Hu, Pengqiu Meng, Michael Neff, Dor Abrahamson:
Classifying Learner Behavior from High Frequency Touchscreen Data Using Recurrent Neural Networks. UMAP (Adjunct Publication) 2018: 317-322 - [i6]Zachary A. Pardos, Zihao Fan, Weijie Jiang:
Connectionist Recommendation in the Wild. CoRR abs/1803.09535 (2018) - [i5]Zachary A. Pardos, Andrew Joo Hun Nam:
A Map of Knowledge. CoRR abs/1811.07974 (2018) - [i4]Weijie Jiang, Zachary A. Pardos, Qiang Wei:
Goal-based Course Recommendation. CoRR abs/1812.10078 (2018) - 2017
- [c51]Kshitij Sharma, Patrick Jermann, Pierre Dillenbourg, Luis Pablo Prieto, Sarah D'Angelo, Darren Gergle, Bertrand Schneider, Martina A. Rau, Zachary A. Pardos, Nikol Rummel:
CSCL and Eye-Tracking: Experiences, Opportunities and Challenges. CSCL 2017 - [c50]Zachary A. Pardos, Steven Tang, Daniel Davis, Christopher Vu Le:
Enabling Real-Time Adaptivity in MOOCs with a Personalized Next-Step Recommendation Framework. L@S 2017: 23-32 - [c49]Zachary A. Pardos, Anant Dadu:
Imputing KCs with Representations of Problem Content and Context. UMAP 2017: 148-155 - [c48]Steven Tang, Zachary A. Pardos:
Personalized Behavior Recommendation: A Case Study of Applicability to 13 Courses on edX. UMAP (Adjunct Publication) 2017: 165-170 - [i3]Zachary A. Pardos, Lev Horodyskyj:
Analysis of Student Behaviour in Habitable Worlds Using Continuous Representation Visualization. CoRR abs/1710.06654 (2017) - 2016
- [j7]John C. Stamper, Zachary A. Pardos:
The 2010 KDD Cup Competition Dataset: Engaging the machine learning community in predictive learning analytics. J. Learn. Anal. 3(2): 312-316 (2016) - [j6]Zachary A. Pardos, Anthony Whyte, Kevin Kao:
moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization. Technol. Knowl. Learn. 21(1): 75-98 (2016) - [c47]Martina A. Rau, Zachary A. Pardos:
Adding eye-tracking AOI data to models of representation skills does not improve prediction accuracy. EDM 2016: 622-623 - [c46]Zachary A. Pardos, Yanbo Xu:
Improving efficacy attribution in a self-directed learning environment using prior knowledge individualization. LAK 2016: 435-439 - [c45]Elizabeth A. McBride, Jonathan M. Vitale, Hannah Gogel, Mario M. Martinez, Zachary A. Pardos, Marcia C. Linn:
Predicting Student Learning using Log Data from Interactive Simulations on Climate Change. L@S 2016: 185-188 - [c44]Steven Tang, Joshua C. Peterson, Zachary A. Pardos:
Deep Neural Networks and How They Apply to Sequential Education Data. L@S 2016: 321-324 - [i2]Steven Tang, Joshua C. Peterson, Zachary A. Pardos:
Modelling Student Behavior using Granular Large Scale Action Data from a MOOC. CoRR abs/1608.04789 (2016) - 2015
- [j5]Zachary A. Pardos:
Commentary On "Beyond Time-on-Task: The Relationship Between Spaced Study and Certification in MOOCs". J. Learn. Anal. 2(2): 70-74 (2015) - [c43]Joshua C. Peterson, Zachary A. Pardos, Martina A. Rau, Anna Swigart, Colin Gerber, Jonathan McKinsey:
Understanding Student Success in Chemistry Using Gaze Tracking and Pupillometry. AIED 2015: 358-366 - [c42]Rinat B. Rosenberg-Kima, Zachary A. Pardos:
Is this Model for Real? Simulating Data to Reveal the Proximity of a Model to Reality. AIED Workshops 2015 - [c41]Dragan Gasevic, Taylor Martin, Zachary A. Pardos, Mykola Pechenizkiy, John C. Stamper, Osmar R. Zaïane:
Ethics and Privacy in EDM. EDM 2015: 13 - [c40]Steven Tang, Hannah Gogel, Elizabeth A. McBride, Zachary A. Pardos:
Desirable Difficulty and Other Predictors of Effective Item Orderings. EDM 2015: 416-419 - [c39]Zachary MacHardy, Zachary A. Pardos:
Evaluating Educational Videos using Bayesian Knowledge Tracing and Big Data. EDM 2015: 424-427 - [c38]Zachary A. Pardos, Kevin Kao:
moocRP: An Open-source Analytics Platform. L@S 2015: 103-110 - [c37]Steven Tang, Elizabeth A. McBride, Hannah Gogel, Zachary A. Pardos:
Item Ordering Effects with Qualitative Explanations using Online Adaptive Tutoring Data. L@S 2015: 313-316 - [c36]Zachary MacHardy, Zachary A. Pardos:
Toward the Evaluation of Educational Videos using Bayesian Knowledge Tracing and Big Data. L@S 2015: 347-350 - [c35]Seth Corrigan, Tiffany Barkley, Zachary A. Pardos:
Dynamic Approaches to Modeling Student Affect and its Changing Role in Learning and Performance. UMAP 2015: 92-103 - [i1]Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan:
The Utility of Clustering in Prediction Tasks. CoRR abs/1509.06163 (2015) - 2014
- [j4]Martina A. Rau, Vincent Aleven, Nikol Rummel, Zachary A. Pardos:
How Should Intelligent Tutoring Systems Sequence Multiple Graphical Representations of Fractions? A Multi-Methods Study. Int. J. Artif. Intell. Educ. 24(2): 125-161 (2014) - [j3]Zachary A. Pardos, Ryan S. Baker, Maria Ofelia San Pedro, Sujith M. Gowda, Supreeth M. Gowda:
Affective States and State Tests: Investigating How Affect and Engagement during the School Year Predict End-of-Year Learning Outcomes. J. Learn. Anal. 1(1): 107-128 (2014) - [c34]Seth Adjei, Douglas Selent, Neil T. Heffernan, Zachary A. Pardos, Angela Broaddus, Neal Kingston:
Refining Learning Maps with Data Fitting Techniques: Searching for Better Fitting Learning Maps. EDM 2014: 413-414 - [c33]Asif Dhanani, Seung Yeon Lee, Phitchaya Mangpo Phothilimthana, Zachary A. Pardos:
A Comparison of Error Metrics for Learning Model Parameters in Bayesian Knowledge Tracing. EDM (Workshops) 2014 - [c32]Rinat B. Rosenberg-Kima, Zachary A. Pardos:
Is this Data for Real? EDM (Workshops) 2014 - [c31]Steven Lonn, Christopher Brooks, Zachary A. Pardos, Barry W. Peddycord III, Emily Schneider, Ido Roll, Ashley Shaw:
MOOCShop 2014. ICLS 2014 - [e1]John C. Stamper, Zachary A. Pardos, Manolis Mavrikis, Bruce M. McLaren:
Proceedings of the 7th International Conference on Educational Data Mining, EDM 2014, London, UK, July 4-7, 2014. International Educational Data Mining Society (IEDMS) 2014, ISBN 978-0-9839-5254-1 [contents] - 2013
- [c30]Zachary A. Pardos, Emily Schneider:
First Annual Workshop on Massive Open Online Courses. AIED 2013: 950 - [c29]Zachary A. Pardos, Michael Yudelson:
Towards Moment of Learning Accuracy. AIED Workshops 2013 - [c28]Kalyan Veeramachaneni, Franck Dernoncourt, Colin Taylor, Zachary A. Pardos, Una-May O'Reilly:
Developing Data Standards and Systems for MOOC Data Science. AIED Workshops 2013 - [c27]Mohammad Hassan Falakmasir, Zachary A. Pardos, Geoffrey J. Gordon, Peter Brusilovsky:
A Spectral Learning Approach to Knowledge Tracing. EDM 2013: 28-34 - [c26]Zachary A. Pardos, Yoav Bergner, Daniel T. Seaton, David E. Pritchard:
Adapting Bayesian Knowledge Tracing to a Massive Open Online Course in edX. EDM 2013: 137-144 - [c25]Zachary A. Pardos, Ryan Shaun Joazeiro de Baker, Maria Ofelia Clarissa Z. San Pedro, Sujith M. Gowda, Supreeth M. Gowda:
Affective states and state tests: investigating how affect throughout the school year predicts end of year learning outcomes. LAK 2013: 117-124 - 2012
- [c24]Shubhendu Trivedi, Zachary A. Pardos, Gábor N. Sárközy, Neil T. Heffernan:
Co-Clustering by Bipartite Spectral Graph Partitioning for Out-of-Tutor Prediction. EDM 2012: 33-40 - [c23]Martina A. Rau, Zachary A. Pardos:
Investigating Practice Schedules of Multiple Fraction Representations Using Knowledge Tracing Based Learning Analysis Techniques. EDM 2012: 168-171 - [c22]Zachary A. Pardos, Qing Yang Wang, Shubhendu Trivedi:
The real world significance of performance prediction. EDM 2012: 192-195 - [c21]Zachary A. Pardos, Neil T. Heffernan:
Tutor Modeling Versus Student Modeling. FLAIRS 2012 - [c20]Yumeng Qiu, Zachary A. Pardos, Neil T. Heffernan:
Towards Data Driven Model Improvement. FLAIRS 2012 - [c19]Mario Karlovcec, Mariheida Cordova-Sanchez, Zachary A. Pardos:
Knowledge Component Suggestion for Untagged Content in an Intelligent Tutoring System. ITS 2012: 195-200 - [c18]Zachary A. Pardos, Shubhendu Trivedi, Neil T. Heffernan, Gábor N. Sárközy:
Clustered Knowledge Tracing. ITS 2012: 405-410 - [c17]Sujith M. Gowda, Zachary A. Pardos, Ryan Shaun Joazeiro de Baker:
Content Learning Analysis Using the Moment-by-Moment Learning Detector. ITS 2012: 434-443 - 2011
- [j2]Zachary A. Pardos, Matthew D. Dailey, Neil T. Heffernan:
Learning What Works in its from Non-Traditional Randomized Controlled Trial Data. Int. J. Artif. Intell. Educ. 21(1-2): 47-63 (2011) - [j1]Zachary A. Pardos, Sujith M. Gowda, Ryan Shaun Joazeiro de Baker, Neil T. Heffernan:
The sum is greater than the parts: ensembling models of student knowledge in educational software. SIGKDD Explor. 13(2): 37-44 (2011) - [c16]Shubhendu Trivedi, Zachary A. Pardos, Neil T. Heffernan:
Clustering Students to Generate an Ensemble to Improve Standard Test Score Predictions. AIED 2011: 377-384 - [c15]Bahador B. Nooraei, Zachary A. Pardos, Neil T. Heffernan, Ryan Shaun Joazeiro de Baker:
Less is More: Improving the Speed and Prediction Power of Knowledge Tracing by Using Less Data. EDM 2011: 101-110 - [c14]Shubhendu Trivedi, Zachary A. Pardos, Gábor N. Sárközy, Neil T. Heffernan:
Spectral Clustering in Educational Data Mining. EDM 2011: 129-138 - [c13]Yumeng Qiu, Yingmei Qi, Hanyuan Lu, Zachary A. Pardos, Neil T. Heffernan:
Does Time Matter? Modeling the Effect of Time with Bayesian Knowledge Tracing. EDM 2011: 139-148 - [c12]Zachary A. Pardos, Sujith M. Gowda, Ryan Shaun Joazeiro de Baker, Neil T. Heffernan:
Ensembling Predictions of Student Post-Test Scores for an Intelligent Tutoring System. EDM 2011: 189-198 - [c11]Mingyu Feng, Neil T. Heffernan, Zachary A. Pardos, Cristina Heffernan:
Comparing of Traditional Assessment with Dynamic Testing in a Tutoring System. EDM 2011: 295-300 - [c10]Ryan Shaun Joazeiro de Baker, Zachary A. Pardos, Sujith M. Gowda, Bahador B. Nooraei, Neil T. Heffernan:
Ensembling Predictions of Student Knowledge within Intelligent Tutoring Systems. UMAP 2011: 13-24 - [c9]Zachary A. Pardos, Neil T. Heffernan:
KT-IDEM: Introducing Item Difficulty to the Knowledge Tracing Model. UMAP 2011: 243-254 - 2010
- [c8]Zachary A. Pardos, Neil T. Heffernan:
Navigating the parameter space of Bayesian Knowledge Tracing models: Visualizations of the convergence of the Expectation Maximization algorithm. EDM 2010: 161-170 - [c7]Zachary A. Pardos, Matthew D. Dailey, Neil T. Heffernan:
Learning What Works in ITS from Non-traditional Randomized Controlled Trial Data. Intelligent Tutoring Systems (2) 2010: 41-50 - [c6]Zachary A. Pardos, Neil T. Heffernan:
Modeling Individualization in a Bayesian Networks Implementation of Knowledge Tracing. UMAP 2010: 255-266
2000 – 2009
- 2009
- [c5]Zachary A. Pardos, Neil T. Heffernan:
Detecting the Learning Value of Items In a Randomized Problem Set. AIED 2009: 499-506 - [c4]Zachary A. Pardos, Neil T. Heffernan:
Determining the Significance of Item Order In Randomized Problem Sets. EDM 2009: 111-120 - 2008
- [c3]Zachary A. Pardos, Neil T. Heffernan, Carolina Ruiz, Joseph E. Beck:
The Composition Effect: Conjuntive or Compensatory? An Analysis of Multi-Skill Math Questions in ITS. EDM 2008: 147-156 - 2007
- [c2]Zachary A. Pardos, Mingyu Feng, Neil T. Heffernan, Cristina Linquist-Heffernan:
Analyzing Fine-Grained Skill Models Using Bayesian and Mixed Effects Methods. AIED 2007: 626-628 - [c1]Zachary A. Pardos, Neil T. Heffernan, Brigham S. Anderson, Cristina Linquist-Heffernan:
The Effect of Model Granularity on Student Performance Prediction Using Bayesian Networks. User Modeling 2007: 435-439
Coauthor Index
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last updated on 2024-10-31 21:08 CET by the dblp team
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