Cognicraft: Smart Exam Question Generation with AI and Bloom's Taxonomy

Authors

  • Christian SAGADRACA Mariano Marcos State University Author
  • Zainal SANTOS Mariano Marcos State University Author
  • Danilo SIMON Jr. Mariano Marcos State University Author
  • Marianne Jessica TOLENTINO Mariano Marcos State University Author
  • Reymar VENTURA Mariano Marcos State University Author

DOI:

https://doi.org/10.58459/icce.2024.4918

Abstract

Conventional approaches of exam question creation are often characterized by time-consuming manual methods and challenges in aligning questions with specific educational objectives. This study addresses these challenges by developing an innovative AI-powered exam question generation tool designed to streamline and improve the exam composition process. Cognicraft uses the Feature Driven Development-Agile Methodology and Bloom's Taxonomy to automatically generate exam questions that are academically acceptable. Iterative design cycles were used in the development process to identify, implement, and revise important features in response to continuous user feedback. The methodology included gathering requirements from educators, designing and implementing system features, and conducting User Acceptability Testing (UAT) to evaluate performance across four key dimensions: functionality, reliability, efficiency, and acceptability. The results from the UAT , involving 50 participants, demonstrated high ratings across all criteria. Cognicraft also achieved strong scores in generating relevant and varied exam questions, maintaining consistency and accuracy, and providing a user-friendly experience. The findings indicate that Cognicraft successfully addresses the limitations of traditional exam creation methods by significantly reducing the time and effort required for question generation while ensuring alignment with educational objectives. The system's ability to generate questions that adhere to Taxonomy enhances the quality and diversity of assessments, offering a valuable for educators seeking to improve their exam creation processes. represents a significant advancement in educational technology, providing a practical and efficient solution to longstanding challenges in exam question development.

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Published

2024-11-25

How to Cite

Cognicraft: Smart Exam Question Generation with AI and Bloom’s Taxonomy. (2024). International Conference on Computers in Education. https://doi.org/10.58459/icce.2024.4918