← all papers · overview

Can Large Language Models Make The Grade? An Empirical Study Evaluating Llms Ability To Mark Short Answer Questions In K-12 Education

Abstract

This paper presents reports on a series of experiments with a novel dataset evaluating how well Large Language Models (LLMs) can mark (i.e. grade) open text responses to short answer questions, Specifically, we explore how well different combinations of GPT version and prompt engineering strategies performed at marking real student answers to short answer across different domain areas (Science and

Related papers

Ranked by semantic similarity — how closely each paper's abstract matches this one (100% = near-identical topic).