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ORCIDYun Huang 0002
Person information
- affiliation: Carnegie Mellon University, Human-Computer Interaction Institute, Pittsburgh, PA, USA
- affiliation (PhD 2018): University of Pittsburgh, School of Information Sciences, Intelligent Systems Program, PA, USA
Other persons with the same name
- Yun Huang — disambiguation page
- Yun Huang 0001
![[0000-0002-5287-1778]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-5287-1778")
— Northwestern University, Department of Industrial Engineering and Management Sciences, Evanston, IL, USA (and 1 more) - Yun Huang 0003 — University of Illinois at Urbana-Champaign, IL, USA (and 1 more)
- Yun Huang 0004 — Chongqing University of Posts and Telecommunications, Asset Management Department, China
- Yun Huang 0005 — City University of Hong Kong, Hong Kong, SAR, China
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2020 – today
- 2025
[i1]Vincent Aleven, Conrad Borchers, Yun Huang, Tomohiro Nagashima, Bruce M. McLaren, Paulo Carvalho, Octav Popescu, Jonathan Sewall, Kenneth R. Koedinger:
An Integrated Platform for Studying Learning with Intelligent Tutoring Systems: CTAT+TutorShop. CoRR abs/2502.10395 (2025)- 2024
- [j3]Yun Huang, Christian D. Schunn, Julio Guerra, Peter Brusilovsky:
Why Students Cannot Easily Integrate Component Skills: An Investigation of the Composition Effect in Programming. ACM Trans. Comput. Educ. 24(3): 1-37 (2024) - 2023
- [j2]Yun Huang, Peter Brusilovsky, Julio Guerra, Kenneth R. Koedinger, Christian Schunn:
Supporting skill integration in an intelligent tutoring system for code tracing. J. Comput. Assist. Learn. 39(2): 477-500 (2023) - [j1]Yun Huang, Steven Dang, J. Elizabeth Richey, Pallavi Chhabra, Danielle R. Thomas, Michael W. Asher, Nikki G. Lobczowski, Elizabeth A. McLaughlin, Judith M. Harackiewicz, Vincent Aleven, Kenneth R. Koedinger:
Using latent variable models to make gaming-the-system detection robust to context variations. User Model. User Adapt. Interact. 33(5): 1211-1257 (2023) - [c23]Meng Xia, Xinyi Zhao, Dong Sun, Yun Huang, Jonathan Sewall, Vincent Aleven:
Involving Teachers in the Data-Driven Improvement of Intelligent Tutors: A Prototyping Study. AIED 2023: 340-352 - 2022
- [c22]Yun Huang, Steven Dang, J. Elizabeth Richey, Michael W. Asher, Nikki G. Lobczowski, Danielle R. Chine, Elizabeth A. McLaughlin, Judith M. Harackiewicz, Vincent Aleven, Kenneth R. Koedinger:
Item Response Theory-Based Gaming Detection. EDM 2022 - 2021
- [c21]Yun Huang, Nikki G. Lobczowski, J. Elizabeth Richey, Elizabeth A. McLaughlin, Michael W. Asher, Judith M. Harackiewicz, Vincent Aleven, Kenneth R. Koedinger:
A General Multi-method Approach to Data-Driven Redesign of Tutoring Systems. LAK 2021: 161-172 - 2020
- [c20]Yun Huang, Vincent Aleven, Elizabeth A. McLaughlin, Kenneth R. Koedinger:
A General Multi-method Approach to Design-Loop Adaptivity in Intelligent Tutoring Systems. AIED (2) 2020: 124-129
2010 – 2019
- 2017
- [c19]Jordan Barria-Pineda, Julio Guerra, Yun Huang, Peter Brusilovsky:
Concept-Level Knowledge Visualization For Supporting Self-Regulated Learning. IUI Companion 2017: 141-144 - [c18]Igor Labutov, Yun Huang, Peter Brusilovsky, Daqing He:
Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites. KDD 2017: 907-915 - [c17]Yun Huang, Julio Daniel Guerra Hollstein, Jordan Barria-Pineda, Peter Brusilovsky:
Learner Modeling for Integration Skills. UMAP 2017: 85-93 - 2016
- [c16]Yun Huang, Julio Guerra, Peter Brusilovsky:
A Data-Driven Framework of Modeling Skill Combinations for Deeper Knowledge Tracing. EDM 2016: 593-594 - [c15]Yun Huang, Peter Brusilovsky:
Towards Modeling Chunks in a Knowledge Tracing Framework for Students' Deep Learning. EDM 2016: 666-668 - [c14]Yun Huang, Julio Daniel Guerra Hollstein, Peter Brusilovsky:
Modeling Skill Combination Patterns for Deeper Knowledge Tracing. UMAP (Extended Proceedings) 2016 - [c13]Yun Huang, Michael Yudelson, Shuguang Han, Daqing He, Peter Brusilovsky:
A Framework for Dynamic Knowledge Modeling in Textbook-Based Learning. UMAP 2016: 141-150 - [c12]Yun Huang:
Deeper Knowledge Tracing by Modeling Skill Application Context for Better Personalized Learning. UMAP 2016: 325-328 - [c11]Rui Meng, Shuguang Han, Yun Huang, Daqing He, Peter Brusilovsky:
Knowledge-Based Content Linking for Online Textbooks. WI 2016: 18-25 - 2015
- [c10]José P. González-Brenes, Yun Huang:
Using Data from Real and Simulated Learners to Evaluate Adaptive Tutoring Systems. AIED Workshops 2015 - [c9]Julio Guerra, Yun Huang, Roya Hosseini, Peter Brusilovsky:
Exploring the Effects of Open Social Student Model Beyond Social Comparison. AIED Workshops 2015 - [c8]Yun Huang, José P. González-Brenes, Peter Brusilovsky:
Challenges of Using Observational Data to Determine the Importance of Example Usage. AIED 2015: 633-637 - [c7]José P. González-Brenes, Yun Huang:
Your Model Is Predictive - but Is It Useful? Theoretical and Empirical Considerations of a New Paradigm for Adaptive Tutoring Evaluation. EDM 2015: 187-194 - [c6]Julio Guerra, Yun Huang, Roya Hosseini, Peter Brusilovsky:
Graph Analysis of Student Model Networks. EDM (Workshops) 2015 - [c5]Yun Huang, José P. González-Brenes, Rohit Kumar, Peter Brusilovsky:
A Framework for Multifaceted Evaluation of Student Models. EDM 2015: 203-210 - 2014
- [c4]Yun Huang, José P. González-Brenes, Peter Brusilovsky:
General Features in Knowledge Tracing to Model Multiple Subskills, Temporal Item Response Theory, and Expert Knowledge. EDM 2014: 84-91 - [c3]Shaghayegh Sahebi, Yun Huang, Peter Brusilovsky:
Predicting Student Performance in Solving Parameterized Exercises. Intelligent Tutoring Systems 2014: 496-503 - [c2]Yun Huang, Yanbo Xu, Peter Brusilovsky:
Doing More with Less: Student Modeling and Performance Prediction with Reduced Content Models. UMAP 2014: 338-349 - [c1]Mohammad Khajah, Yun Huang, José P. González-Brenes, Michael Mozer, Peter Brusilovsky:
Integrating Knowledge Tracing and Item Response Theory: A Tale of Two Frameworks. UMAP Workshops 2014
Coauthor Index
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