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2020 – today
- 2026
[c16]Muntasir Hoq
, Griffin Pitts, Bradford W. Mott, Seung Y. Lee, Jessica Vandenberg, Shuyin Jiao, Narges Norouzi, James C. Lester, Bita Akram:
An Explainable AI Assistant for Introductory Programming Education: Improving Feedback Reliability with Instructor-AI Collaboration. AIED (1) 2026: 187-201- [c15]Griffin Pitts, Muntasir Hoq, Peter Brusilovsky, Narges Norouzi, Arto Hellas, Juho Leinonen, Bita Akram:
Personalized Worked Example Generation from Student Code Submissions Using Pattern-based Knowledge Components. L@S 2026: 501-505 - [c14]Muntasir Hoq, Jessica Vandenberg, Seung Y. Lee, Bradford W. Mott, James C. Lester, Narges Norouzi, Shuyin Jiao, Bita Akram:
INSIGHT: An Explainable, Instructor-Guided AI Assistant for Active Learning in CS1. SIGCSE (2) 2026: 1363-1364 - [c13]Griffin Pitts, Aum Pandya, Darsh Rank, Muntasir Hoq, Tirth Bhatt, Bita Akram:
Automated Program Repair of Uncompilable Student Code. SIGCSE (2) 2026: 1483-1484 - [i7]Griffin Pitts, Muntasir Hoq, Peter Brusilovsky, Narges Norouzi, Arto Hellas, Juho Leinonen, Bita Akram:
Personalized Worked Example Generation from Student Code Submissions using Pattern-based Knowledge Components. CoRR abs/2604.24758 (2026) - [i6]Muntasir Hoq, Griffin Pitts, Bradford W. Mott, Seung Y. Lee, Jessica Vandenberg, Shuyin Jiao, Narges Norouzi, James C. Lester, Bita Akram:
An Explainable AI Assistant for Introductory Programming Education: Improving Feedback Reliability with Instructor-AI Collaboration. CoRR abs/2606.12425 (2026) - 2025
- [c12]Muntasir Hoq, Bradford W. Mott, Seung Y. Lee, Jessica Vandenberg, Narges Norouzi, James C. Lester, Bita Akram:
Explainable AI in the Loop: An Instructor-Transformer Collaboration for Improving Explainability and Reliability of Feedback in Introductory Programming Classrooms. CSEDM@EDM 2025 - [c11]Muntasir Hoq, Ananya Rao, Reisha Jaishankar, Krish Piryani, Nithya Janapati, Jessica Vandenberg, Bradford W. Mott, Narges Norouzi, James C. Lester, Bita Akram:
Automated Identification of Logical Errors in Programs: Advancing Scalable Analysis of Student Misconceptions. EDM 2025 - [c10]Anurata Prabha Hridi, Muntasir Hoq, Zhikai Gao, Collin Lynch, Rajeev Sahay, Seyyedali Hosseinalipour, Bita Akram:
Privacy-Preserving Distributed Link Predictions Among Peers in Online Classrooms Using Federated Learning. EDM 2025 - [c9]Muntasir Hoq, Atharva Patil, Kamil Akhuseyinoglu, Peter Brusilovsky, Bita Akram:
An Automated Approach to Recommending Relevant Worked Examples for Programming Problems. SIGCSE (1) 2025: 527-533 - [i5]Muntasir Hoq, Jessica Vandenberg, Shuyin Jiao, Seung Y. Lee, Bradford W. Mott, Narges Norouzi, James C. Lester, Bita Akram:
Facilitating Instructors-LLM Collaboration for Problem Design in Introductory Programming Classrooms. CoRR abs/2504.01259 (2025) - [i4]Anurata Prabha Hridi, Muntasir Hoq, Zhikai Gao, Collin Lynch, Rajeev Sahay, Seyyedali Hosseinalipour, Bita Akram:
Privacy-Preserving Distributed Link Predictions Among Peers in Online Classrooms Using Federated Learning. CoRR abs/2504.10456 (2025) - [i3]Muntasir Hoq, Ananya Rao, Reisha Jaishankar, Krish Piryani, Nithya Janapati, Jessica Vandenberg, Bradford W. Mott, Narges Norouzi, James C. Lester, Bita Akram:
Automated Identification of Logical Errors in Programs: Advancing Scalable Analysis of Student Misconceptions. CoRR abs/2505.10913 (2025) - [i2]Muntasir Hoq, Griffin Pitts, Andrew S. Lan, Peter Brusilovsky, Bita Akram:
Pattern-based Knowledge Component Extraction from Student Code Using Representation Learning. CoRR abs/2508.09281 (2025) - [i1]Griffin Pitts, Aum Pandya, Darsh Rank, Tirth Bhatt, Muntasir Hoq, Bita Akram:
Automated Program Repair of Uncompilable Student Code. CoRR abs/2510.06187 (2025) - 2024
- [c8]Muntasir Hoq, Atharva Patil, Kamil Akhuseyinoglu, Bita Akram, Peter Brusilovsky:
Automated Identification of Relevant Worked Examples for Programming Problems. CSEDM@EDM 2024 - [c7]Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin F. Lynch, Thomas W. Price, Bita Akram:
Detecting ChatGPT-Generated Code Submissions in a CS1 Course Using Machine Learning Models. SIGCSE (1) 2024: 526-532 - [c6]Muntasir Hoq, Jessica Vandenberg, Bradford W. Mott, James C. Lester, Narges Norouzi, Bita Akram:
Towards Attention-Based Automatic Misconception Identification in Introductory Programming Courses. SIGCSE (2) 2024: 1680-1681 - [c5]Rose Niousha, Muntasir Hoq, Bita Akram, Narges Norouzi:
Use of Large Language Models for Extracting Knowledge Components in CS1 Programming Exercises. SIGCSE (2) 2024: 1762-1763 - 2023
- [c4]Muntasir Hoq, Yang Shi, Juho Leinonen, Damilola Babalola, Collin F. Lynch, Bita Akram:
Detecting ChatGPT-Generated Code in a CS1 Course. LLM@AIED 2023: 53-63 - [c3]Muntasir Hoq, Sushanth Reddy Chilla, Melika Ahmadi Ranjbar, Peter Brusilovsky, Bita Akram:
SANN: Programming Code Representation Using Attention Neural Network with Optimized Subtree Extraction. CIKM 2023: 783-792 - [c2]Muntasir Hoq, Peter Brusilovsky, Bita Akram:
Analysis of an Explainable Student Performance Prediction Model in an Introductory Programming Course. EDM 2023 - 2021
- [c1]Muntasir Hoq, Promila Haque, Mohammed Nazim Uddin:
Sentiment Analysis of Bangla Language Using Deep Learning Approaches. COMS2 2021: 140-151
Coauthor Index
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