Publications

Exploring The Effectiveness of Reading vs. Tutoring For Enhancing Code Comprehension For Novices

Priti Oli, Rabin Banjade, Arun Balajiee Lekshmi Narayanan, Peter Brusilovsky, and Vasile Rus. 2024. Exploring The Effectiveness of Reading vs. Tutoring For, Enhancing Code Comprehension For Novices. In Proceedings of ACM SAC Conference (SAC’24). ACM, Avila, Spain, Article 4, 10 pages

Automated Extraction of Domain Models from Textbook Indexes for Developing Intelligent Tutoring Systems

Banjade, Rabin, Priti Oli, and Vasile Rus. 'Automated Extraction of Domain Models from Textbook Indexes for Developing Intelligent Tutoring Systems.' In International Conference on Intelligent Tutoring Systems, pp. 124-136. Cham: Springer Nature Switzerland, 2023.

SelfCode: An Annotated Corpus and a Model for Automated Assessment of Self-Explanation During Source Code Comprehension

Chapagain, Jeevan, Zak Risha, Rabin Banjade, Priti Oli, Lasang Tamang, Peter Brusilovsky, and Vasile Rus. 'SelfCode: An Annotated Corpus and a Model for Automated Assessment of Self-Explanation During Source Code Comprehension.' In The International FLAIRS Conference Proceedings, vol. 36. 2023.

Automated Assessment of Student Self-explanation During Source Code Comprehension

Chapagain, Jeevan, Lasang Tamang, Rabin Banjade, Priti Oli, and Vasile Rus. 'Automated Assessment of Student Self-explanation During Source Code Comprehension.' In The International FLAIRS Conference Proceedings, vol. 35. 2022.6

Preliminary Experiments with Transformer based Approaches To Automatically Inferring Domain Models from Textbooks

Banjade, Rabin, Priti Oli, Lasang Jimba Tamang, and Vasile Rus. 'Preliminary Experiments with Transformer based Approaches To Automatically Inferring Domain Models from Textbooks.' In Proceedings of the 15th International Conference on Educational Data Mining, p. 667. 2022.

The Behavior of Large Language Models When Prompted to Generate Code Explanations

P Oli, R Banjade, J Chapagain, V Rus - arXiv preprint arXiv:2311.01490, 2023

Improving Code Comprehension Through Scaffolded Self-explanations

Oli, P., Banjade, R., Lekshmi Narayanan, A. B., Chapagain, J., Tamang, L. J., Brusilovsky, P., & Rus, V. (2023, June). Improving Code Comprehension Through Scaffolded Self-explanations. In International Conference on Artificial Intelligence in Education (pp. 478-483). Cham: Springer Nature Switzerland.

Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Srivastava, Aarohi, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown et al. 'Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.' arXiv preprint arXiv:2206.04615 (2022).

Nl-augmenter: A framework for task-sensitive natural language augmentation

Dhole, Kaustubh D., Varun Gangal, Sebastian Gehrmann, Aadesh Gupta, Zhenhao Li, Saad Mahamood, Abinaya Mahendiran et al. 'Nl-augmenter: A framework for task-sensitive natural language augmentation.' arXiv preprint arXiv:2112.02721 (2021).

A Comparative Study of Free Self-Explanations and Socratic Tutoring Explanations for Source Code Comprehension

Tamang, Lasang Jimba, Zeyad Alshaikh, Nisrine Ait Khayi, Priti Oli, and Vasile Rus. 'A comparative study of free self-explanations and socratic tutoring explanations for source code comprehension.' In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, pp. 219-225. 2021.

Domain Model Discovery from Textbooks for Computer Programming Intelligent Tutors

Banjade, Rabin, Priti Oli, Lasang Jimba Tamang, Jeevan Chapagain, and Vasile Rus. 'Domain Model Discovery from Textbooks for Computer Programming Intelligent Tutors.'

Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code

Oli, Priti, Rabin Banjade, Lasang Jimba Tamang, and Vasile Rus. 'Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code.' In The International FLAIRS Conference Proceedings, vol. 34. 2021.