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Automated Bloom’s Taxonomy-Based Question Generation for Course Outcome Attainment in Obe Frameworks

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This system automates question generation aligned with Bloom's taxonomy in OBE, indicating reduced manual effort and improved educational alignment.

The system generates targeted questions that meet educational objectives effectively.
It utilizes a vector database to store private data, enhancing context relevance during question generation.
The use of Retrieval-Augmented Generation allows for alignment with Bloom's taxonomy and course outcomes.
This automation significantly reduces the time and effort required for manual question preparation.

P et al. (2024) studied this question.

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This system automates question generation aligned with Bloom's taxonomy in OBE, indicating reduced manual effort and improved educational alignment.