How Useful Are Educational Questions Generated by Large Language Models?

Document Type

Conference Proceeding

Publication Title

Communications in Computer and Information Science

Abstract

Controllable text generation (CTG) by large language models has a huge potential to transform education for teachers and students alike. Specifically, high quality and diverse question generation can dramatically reduce the load on teachers and improve the quality of their educational content. Recent work in this domain has made progress with generation, but fails to show that real teachers judge the generated questions as sufficiently useful for the classroom setting; or if instead the questions have errors and/or pedagogically unhelpful content. We conduct a human evaluation with teachers to assess the quality and usefulness of outputs from combining CTG and question taxonomies (Bloom’s and a difficulty taxonomy). The results demonstrate that the questions generated are high quality and sufficiently useful, showing their promise for widespread use in the classroom setting.

First Page

536

Last Page

542

DOI

10.1007/978-3-031-36336-8_83

Publication Date

6-30-2023

Keywords

Controllable Text Generation, Personalized Learning, Prompting, Question Generation

Comments

IR conditions: non-described

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