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How Effective is GPT-4 Turbo in Generating School-Level Questions from Textbooks Based on Bloom's Revised Taxonomy?

Computation and Language 2024-06-24 v1 Artificial Intelligence

Abstract

We evaluate the effectiveness of GPT-4 Turbo in generating educational questions from NCERT textbooks in zero-shot mode. Our study highlights GPT-4 Turbo's ability to generate questions that require higher-order thinking skills, especially at the "understanding" level according to Bloom's Revised Taxonomy. While we find a notable consistency between questions generated by GPT-4 Turbo and those assessed by humans in terms of complexity, there are occasional differences. Our evaluation also uncovers variations in how humans and machines evaluate question quality, with a trend inversely related to Bloom's Revised Taxonomy levels. These findings suggest that while GPT-4 Turbo is a promising tool for educational question generation, its efficacy varies across different cognitive levels, indicating a need for further refinement to fully meet educational standards.

Keywords

Cite

@article{arxiv.2406.15211,
  title  = {How Effective is GPT-4 Turbo in Generating School-Level Questions from Textbooks Based on Bloom's Revised Taxonomy?},
  author = {Subhankar Maity and Aniket Deroy and Sudeshna Sarkar},
  journal= {arXiv preprint arXiv:2406.15211},
  year   = {2024}
}

Comments

Accepted at Learnersourcing: Student-Generated Content @ Scale 2024