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2020 – today
- 2024
[j1]Ji-Eun Lee
, Amisha Jindal, Sanika Nitin Patki, Ashish Gurung, Reilly Norum, Erin Ottmar:
A comparison of machine learning algorithms for predicting student performance in an online mathematics game. Interact. Learn. Environ. 32(9): 5302-5316 (2024)- [c17]Sami Baral, Eamon Worden, Wen-Chiang Lim, Zhuang Luo, Christopher Santorelli, Ashish Gurung:
Automated Assessment in Math Education: A Comparative Analysis of LLMs for Open-Ended Responses. EDM 2024 - [c16]Jionghao Lin, Eason Chen, Zifei FeiFei Han, Ashish Gurung, Danielle R. Thomas, Wei Tan, Ngoc Dang Nguyen, Kenneth R. Koedinger:
How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses. EDM 2024 - [c15]Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger:
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. LAK 2024: 404-415 - [c14]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: 462-472 - [c13]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: 507-517 - [c12]Siddhartha Pradhan, Ashish Gurung, Erin Ottmar:
Gamification and Deadending: Unpacking Performance Impacts in Algebraic Learning. LAK 2024: 899-906 - [c11]Jionghao Lin, Eason Chen, Ashish Gurung, Kenneth R. Koedinger:
MuFIN: A Framework for Automating Multimodal Feedback Generation using Generative Artificial Intelligence. L@S 2024: 550-552 - [i5]Zifei FeiFei Han, Jionghao Lin, Ashish Gurung, Danielle R. Thomas, Eason Chen, Conrad Borchers, Shivang Gupta, Kenneth R. Koedinger:
Improving Assessment of Tutoring Practices using Retrieval-Augmented Generation. CoRR abs/2402.14594 (2024) - [i4]Jionghao Lin, Eason Chen, Zeifei Han, Ashish Gurung, Danielle R. Thomas, Wei Tan, Ngoc Dang Nguyen, Kenneth R. Koedinger:
How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses. CoRR abs/2405.00291 (2024) - [i3]Jionghao Lin, Zifei FeiFei Han, Danielle R. Thomas, Ashish Gurung, Shivang Gupta, Vincent Aleven, Kenneth R. Koedinger:
How Can I Get It Right? Using GPT to Rephrase Incorrect Trainee Responses. CoRR abs/2405.00970 (2024) - [i2]Sami Baral, Eamon Worden, Wen-Chiang Lim, Zhuang Luo, Christopher Santorelli, Ashish Gurung, Neil T. Heffernan:
Automated Feedback in Math Education: A Comparative Analysis of LLMs for Open-Ended Responses. CoRR abs/2411.08910 (2024) - 2023
- [c10]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 - [c9]Sami Baral, Anthony Botelho, Abhishek Santhanam, Ashish Gurung, Li Cheng, Neil T. Heffernan:
Auto-scoring Student Responses with Images in Mathematics. EDM 2023 - [c8]Morgan P. Lee, Ethan A. Croteau, Ashish Gurung, Anthony F. Botelho, Neil T. Heffernan:
Knowledge Tracing Over Time: A Longitudinal Analysis. EDM 2023 - [c7]Kirk Vanacore, Ashish Gurung, Andrew A. McReynolds, Allison S. Liu, Stacy T. 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 - [c6]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 - [c5]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 - [i1]Danielle R. Thomas, Jionghao Lin, Erin Gatz, Ashish Gurung, Shivang Gupta, Kole Norberg, Stephen E. Fancsali, Vincent Aleven, Lee G. Branstetter, Emma Brunskill, Kenneth R. Koedinger:
Improving Student Learning with Hybrid Human-AI Tutoring: A Three-Study Quasi-Experimental Investigation. CoRR abs/2312.11274 (2023) - 2022
- [c4]Ashish Gurung, Neil T. Heffernan:
Exploring Fairness in Automated Grading and Feedback Generation of Open-Response Math Problems. AIED (2) 2022: 71-76 - [c3]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 - [c2]Ashish Gurung, Anthony Botelho, Russell Thompson, Adam Sales, Sami Baral, Neil T. Heffernan:
Considerate, Unfair, or Just Fatigued? Examining Factors that Impact Teacher. ICCE 2022 - 2021
- [c1]Ashish Gurung, Anthony F. Botelho, Neil T. Heffernan:
Examining Student Effort on Help through Response Time Decomposition. LAK 2021: 292-301
Coauthor Index
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