Creación de distractores para preguntas de opción múltiple mediante técnicas de incrustación (Word Embedding)

The automatic generation of distractors for multiple-choice questions in academic documents relies on advanced word embedding techniques, such as Word2Vec. These techniques represent words as vectors in a semantic space, facilitating the discovery of relationships and similarities between them. Through these methods, plausible but incorrect distractors can be created that reflect common misconceptions or are semantically related to the question. This approach has enhanced the quality of assessments by providing more challenging and realistic answer options. Additionally, it has automated the process of creating quizzes, saving time for educators and ensuring greater consistency. However, it is necessary to monitor and adjust this process to avoid implausible incorrect answers or implicit biases. This innovative methodology is transforming the way assessments are designed and administered in educational settings and in academic documents such as guides, quizzes, and written evaluations. In this paper, we present an introduction to the topic, followed by an exhaustive literature review. Subsequently, we describe in detail the methods and algorithms employed. The results obtained from experimentation are analysed and discussed, culminating in robust conclusions and practical recommendations.

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Publication Details

Journal
Revista Tecnológica - ESPOL
Published
2024-12-30
DOI
https://doi.org/10.37815/rte.v36n2.1161
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
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article

Creación de distractores para preguntas de opción múltiple mediante técnicas de incrustación (Word Embedding)

Rommel Torres, Eliana I. Pinza, Verónica Segarra-Faggioni, Jammil Israel Ramos Alvarez
Revista Tecnológica - ESPOL
Software Engineering Research
article

Creación de distractores para preguntas de opción múltiple mediante técnicas de incrustación (Word Embedding)

Rommel Torres, Eliana I. Pinza, Verónica Segarra-Faggioni, Jammil Israel Ramos Alvarez
article en

Abstract

The automatic generation of distractors for multiple-choice questions in academic documents relies on advanced word embedding techniques, such as Word2Vec. These techniques represent words as vectors in a semantic space, facilitating the discovery of relationships and similarities between them. Through these methods, plausible but incorrect distractors can be created that reflect common misconceptions or are semantically related to the question. This approach has enhanced the quality of assessments by providing more challenging and realistic answer options. Additionally, it has automated the process of creating quizzes, saving time for educators and ensuring greater consistency. However, it is necessary to monitor and adjust this process to avoid implausible incorrect answers or implicit biases. This innovative methodology is transforming the way assessments are designed and administered in educational settings and in academic documents such as guides, quizzes, and written evaluations. In this paper, we present an introduction to the topic, followed by an exhaustive literature review. Subsequently, we describe in detail the methods and algorithms employed. The results obtained from experimentation are analysed and discussed, culminating in robust conclusions and practical recommendations.

Revista Tecnológica - ESPOLVol. 36(2)
Universidad Técnica Particular de Loja (EC)
Quality Education
Openalex Percentile: Top 61%
Software Engineering Research
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