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High-Order Question Generation in a Multilingual Educational Context

arXiv 2607.13901 ↗First posted 15 Jul 2026cs.CLcited by 0

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Abstract (arXiv)

Critical thinking is a fundamental skill that helps learners move beyond simple memorization. One way to develop this skill is through high-order questioning. However, crafting such questions remains a challenge for educators, and classroom practices tend to rely on low-order questions. Large Language Models have demonstrated strong capabilities in generating high-order questions, especially when guided by prompts based on Bloom's Taxonomy. Yet, existing research has largely centered on this framework and focused only on English. This study addresses these gaps by introducing prompts grounded in two alternative frameworks: Claim-Evidence-Reasoning and Divergent Questioning within a multilingual context using Basque, Spanish, and English. Results indicate that while both an open-source and a proprietary model rather effectively generate questions in all three languages, only about half of the answerable questions are recognized by teachers as high-order. A positive finding is that the alternative frameworks produce structurally and conceptually varied questions, suggesting they could complement each other and provide viable alternatives to Bloom's Taxonomy.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 17 references that are in the map. First posted on arXiv 15 Jul 2026.

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References · 2

  1. 2024Automated Educational Question Generation at Different Bloom's Skill Levels using Large Language Models: Strategies and Evaluationcited by 29
  2. 2024How Teachers Can Use Large Language Models and Bloom's Taxonomy to Create Educational Quizzescited by 17

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