The daunting challenge of Artificial Intelligence in Education: a systematic literature review
This paper presents a Systematic Literature Review on the challenges that Artificial Intelligence (AI) poses in the field of education, specifically, on teaching and learning processes. Based on an exhaustive search in the Web of Science and Scopus databases, 1657 articles published between 2010 an...
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| Language: | English |
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Italian e-Learning Association
2025-03-01
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| Series: | Je-LKS: Journal of E-Learning and Knowledge Society |
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| Online Access: | http://je-lks.org/ojs/index.php/Je-LKS_EN/article/view/1135992 |
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| author | Rubén Arriazu |
| author_facet | Rubén Arriazu |
| author_sort | Rubén Arriazu |
| collection | DOAJ |
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This paper presents a Systematic Literature Review on the challenges that Artificial Intelligence (AI) poses in the field of education, specifically, on teaching and learning processes. Based on an exhaustive search in the Web of Science and Scopus databases, 1657 articles published between 2010 and 2024 were initially selected to be examined. The final sample consisted of 52 studies. To achieve this goal, the PRISMA 2020 protocol was employed. Identified challenges are grouped into several key categories. In pedagogical terms, the need to adapt teaching methods and curricula to leverage AI capabilities is highlighted, as well as the importance of maintaining a balance between AI-assisted teaching and human interaction. Additionally, training teachers to use these tools effectively is also considered as a significant obstacle to integrate the new ecology of learning. Finally, there are also ethical and social challenges that address concerns about the privacy of student data, equity in access to advanced technologies, and the potential of AI to perpetuate existing biases. Transparency in the operation of AI systems and the involvement of educational stakeholders are crucial to mitigating these risks. In conclusion, although AI has the potential to transform new ways of teaching and learning. These challenges encourage new paradigms where learning will be more flexible and closer to people's interests. Therefore, AI is not inherently good or bad; rather, it is the way we use it that will be the true key to promoting or not promoting changes in educational paradigms.
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| format | Article |
| id | doaj-art-2e73dc8e1eed462cb91dfbfccd6b9888 |
| institution | OA Journals |
| issn | 1826-6223 1971-8829 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Italian e-Learning Association |
| record_format | Article |
| series | Je-LKS: Journal of E-Learning and Knowledge Society |
| spelling | doaj-art-2e73dc8e1eed462cb91dfbfccd6b98882025-08-20T02:19:47ZengItalian e-Learning AssociationJe-LKS: Journal of E-Learning and Knowledge Society1826-62231971-88292025-03-0121110.20368/1971-8829/1135992The daunting challenge of Artificial Intelligence in Education: a systematic literature reviewRubén Arriazu0{'en_US': 'Profesor Titular de Universidad'} This paper presents a Systematic Literature Review on the challenges that Artificial Intelligence (AI) poses in the field of education, specifically, on teaching and learning processes. Based on an exhaustive search in the Web of Science and Scopus databases, 1657 articles published between 2010 and 2024 were initially selected to be examined. The final sample consisted of 52 studies. To achieve this goal, the PRISMA 2020 protocol was employed. Identified challenges are grouped into several key categories. In pedagogical terms, the need to adapt teaching methods and curricula to leverage AI capabilities is highlighted, as well as the importance of maintaining a balance between AI-assisted teaching and human interaction. Additionally, training teachers to use these tools effectively is also considered as a significant obstacle to integrate the new ecology of learning. Finally, there are also ethical and social challenges that address concerns about the privacy of student data, equity in access to advanced technologies, and the potential of AI to perpetuate existing biases. Transparency in the operation of AI systems and the involvement of educational stakeholders are crucial to mitigating these risks. In conclusion, although AI has the potential to transform new ways of teaching and learning. These challenges encourage new paradigms where learning will be more flexible and closer to people's interests. Therefore, AI is not inherently good or bad; rather, it is the way we use it that will be the true key to promoting or not promoting changes in educational paradigms. http://je-lks.org/ojs/index.php/Je-LKS_EN/article/view/1135992Artificial IntelligenceTeaching and LearningLearning EcologyEngagementSystematic Literature Review |
| spellingShingle | Rubén Arriazu The daunting challenge of Artificial Intelligence in Education: a systematic literature review Je-LKS: Journal of E-Learning and Knowledge Society Artificial Intelligence Teaching and Learning Learning Ecology Engagement Systematic Literature Review |
| title | The daunting challenge of Artificial Intelligence in Education: a systematic literature review |
| title_full | The daunting challenge of Artificial Intelligence in Education: a systematic literature review |
| title_fullStr | The daunting challenge of Artificial Intelligence in Education: a systematic literature review |
| title_full_unstemmed | The daunting challenge of Artificial Intelligence in Education: a systematic literature review |
| title_short | The daunting challenge of Artificial Intelligence in Education: a systematic literature review |
| title_sort | daunting challenge of artificial intelligence in education a systematic literature review |
| topic | Artificial Intelligence Teaching and Learning Learning Ecology Engagement Systematic Literature Review |
| url | http://je-lks.org/ojs/index.php/Je-LKS_EN/article/view/1135992 |
| work_keys_str_mv | AT rubenarriazu thedauntingchallengeofartificialintelligenceineducationasystematicliteraturereview AT rubenarriazu dauntingchallengeofartificialintelligenceineducationasystematicliteraturereview |