2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CL2025
Tell Me Who Your Students Are: GPT Can Generate Valid Multiple-Choice Questions When Students' (Mis)Understanding Is Hinted
Machi Shimmei, Masaki Uto, Yuichiroh Matsubayashi +3
The primary goal of this study is to develop and evaluate an innovative prompting technique, AnaQuest, for generating multiple-choice questions (MCQs) using a pre-trained large lan…
cs.CY2024★ 2 cited
Leveraging Prompts in LLMs to Overcome Imbalances in Complex Educational Text Data
Jeanne McClure, Machi Shimmei, Noboru Matsuda +1
In this paper, we explore the potential of Large Language Models (LLMs) with assertions to mitigate imbalances in educational datasets. Traditional models often fall short in such…