Can LLMs Grade Short-Answer Reading Comprehension Questions : An Empirical Study with a Novel Dataset

Understand

Open-ended questions, which require students to produce multi-word, nontrivial responses, are a popular tool for formative assessment as they provide more specific insights into what students do and don't know.

• However, grading open-ended questions can be time-consuming leading teachers to resort to simpler question formats or conduct fewer formative assessments.
• While there has been a longstanding interest in automating of short-answer grading (ASAG), but previous approaches have been technically complex, limiting their use in formative assessment contexts.
• The newest generation of Large Language Models (LLMs) potentially makes grading short answer questions more feasible.