2 citations · 3 across the 8 of their papers we have counts for
3 papers · 1 filter
Supervised Fine-Tuning LLMs to Behave as Pedagogical Agents in Programming Education
Emily Ross, Yuval Kansal, Jake Renzella +2
Large language models (LLMs) are increasingly being explored in higher education, yet their effectiveness as teaching agents remains underexamined. In this paper, we present the de…
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…
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…