Review of automatic question generation in Education: assessment techniques, datasets and metrics
DOI:
https://doi.org/10.51359/2317-0115.2025.265432Keywords:
automatic question generation, natural language processing, machine learningAbstract
AQG is an interdisciplinary area that combines natural language processing, machine learning and educational techniques to create systems that generate questions automatically. This article presents a systematic review on automatic question generation (AQG) applied to education. We analyzed the main approaches, identifying that the rule-based approach is the most used, followed by machine learning techniques. The most common datasets include SQuAD, while evaluation metrics range from BLEU, accuracy, and precision. The review also highlights the limitations of current methodologies and highlights research opportunities, such as the need for open datasets and improvements in automatic assessment techniques. We hope that this study will assist researchers in exploring new opportunities and advances in AQG.
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Copyright (c) 2025 Alana Viana Borges da Silva Neo , Giseldo da Silva Neo, Mario Diego Ferreira dos Santos , Kleber Jose Araujo Galvao Filho , Olival de Gusmão Freitas Junior

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