2 citations · 3 across the 9 of their papers we have counts for
3 papers · 1 filter
Towards Pedagogical LLMs with Supervised Fine Tuning for Computing Education
Alexandra Vassar, Jake Renzella, Emily Ross +1
This paper investigates supervised fine-tuning of large language models (LLMs) to improve their pedagogical alignment in computing education, addressing concerns that LLMs may hind…
Scaling CS1 Support with Compiler-Integrated Conversational AI
Jake Renzella, Alexandra Vassar, Lorenzo Lee Solano +1
This paper introduces DCC Sidekick, a web-based conversational AI tool that enhances an existing LLM-powered C/C++ compiler by generating educational programming error explanations…
Striking a Balance between Classical and Deep Learning Approaches in Natural Language Processing Pedagogy
Aditya Joshi, Jake Renzella, Pushpak Bhattacharyya +2
While deep learning approaches represent the state-of-the-art of natural language processing (NLP) today, classical algorithms and approaches still find a place in NLP textbooks an…