Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

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In the realm of education, crafting appropriate questions for examinations is a meticulous and time-consuming task that is crucial for assessing students' understanding of the subject matter. This paper explores the potential of leveraging large language models (LLMs) to automate question generation in the educational domain. Specifically, we focus on generating educational questions from contexts extracted from school-level textbooks. Our study aims to prompt LLMs such as GPT-4 Turbo, GPT-3.5 Turbo, Llama-2-70B, Llama-3.1-405B, and Gemini Pro to generate a complete set of questions for each context, potentially streamlining the question generation process for educators. We performed a...

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