The Impact of Generative Artificial Intelligence on Education: A Comparative Study

Generative Artificial Intelligence (GAI), also known as creative AI, is a technology capable of independently producing original and creative content, such as text, images, videos, music, or code. It uses machine learning algorithms to analyze and learn from a vast amount of data to generate similar or even innovative content. This type of AI is used in several fields, such as health for the production of new drugs, design to generate adaptive designs, video games to create immersive environments, and artificial intelligence to generate training data for new networks. Seizing the opportunities offered by AI innovations in education is crucial. We cannot afford to let time pass without doing anything and without benefiting from this technique. It is time to enhance traditional learning methods and adopt more innovative approaches that take advantage of the potential of AI, like content and exam generation, and also improve students' learning experience by exploiting their closeness to the technology. This paper aims to answer the question of when and how to use artificial intelligence responsibly, considering it as a technology and limiting its excessive use. Additionally, we present the impact of GAI through a comparative study of student performance in three exam types: a classical MCQ exam written by the teacher, an adaptive MCQ exam generated by GAI from a topic, and a third MCQ exam generated by GAI based on the content of the provided documents. This study is conducted on students undergoing a software testing training program. By evaluating their performance in the AI-generated adaptive MCQ exams and the traditional MCQ exam, we can gain insights into the potential of this technology to enhance educational practices and provide personalized learning experiences. This research will contribute to the ongoing discussion on responsible and effective utilization of GAI in education, paving the way for future advancements in the field.

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Publication Details

Journal
European Conference on e-Learning
Published
2024-10-23
DOI
https://doi.org/10.34190/ecel.23.1.2975
Citations
3
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
1.24
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article

The Impact of Generative Artificial Intelligence on Education: A Comparative Study

Asmaâ Retbi, Nour-eddine El Faddouli, Zohair Elmourabit
3 citations
European Conference on e-Learning
Online Learning and Analytics
1.24
article

The Impact of Generative Artificial Intelligence on Education: A Comparative Study

Asmaâ Retbi, Nour-eddine El Faddouli, Zohair Elmourabit
article en
3 citations

Abstract

Generative Artificial Intelligence (GAI), also known as creative AI, is a technology capable of independently producing original and creative content, such as text, images, videos, music, or code. It uses machine learning algorithms to analyze and learn from a vast amount of data to generate similar or even innovative content. This type of AI is used in several fields, such as health for the production of new drugs, design to generate adaptive designs, video games to create immersive environments, and artificial intelligence to generate training data for new networks. Seizing the opportunities offered by AI innovations in education is crucial. We cannot afford to let time pass without doing anything and without benefiting from this technique. It is time to enhance traditional learning methods and adopt more innovative approaches that take advantage of the potential of AI, like content and exam generation, and also improve students' learning experience by exploiting their closeness to the technology. This paper aims to answer the question of when and how to use artificial intelligence responsibly, considering it as a technology and limiting its excessive use. Additionally, we present the impact of GAI through a comparative study of student performance in three exam types: a classical MCQ exam written by the teacher, an adaptive MCQ exam generated by GAI from a topic, and a third MCQ exam generated by GAI based on the content of the provided documents. This study is conducted on students undergoing a software testing training program. By evaluating their performance in the AI-generated adaptive MCQ exams and the traditional MCQ exam, we can gain insights into the potential of this technology to enhance educational practices and provide personalized learning experiences. This research will contribute to the ongoing discussion on responsible and effective utilization of GAI in education, paving the way for future advancements in the field.

European Conference on e-LearningVol. 23(1)
Mohammed V University (MA), Ecole Mohammadia d'Ingénieurs (MA)
Quality Education
Openalex Percentile: Top 14%
Online Learning and Analytics
1.24
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