TRANSFORMATIONS IN TEACHING-LEARNING WITH THE USE OF ARTIFICIAL INTELLIGENCE - SYSTEMATIC REVIEW OF THE LITERATURE

Authors

DOI:

https://doi.org/10.47820/recima21.v4i5.3103

Keywords:

Artificial Intelligence, Education, Machine Learning, Teaching-Learning

Abstract

The use of artificial intelligence (AI) in teaching-learning is an increasingly present theme in the academic literature and one of the main challenges for the implementation of AI in education is the need to deal with ethical issues. Given this scenario, what are the transformations in teaching-learning with the use of artificial intelligence for the automatic generation of texts? Therefore, the general objective of this work was to perform a systematic review of the literature on the transformations in teaching-learning with the use of AI for the automatic generation of texts. The response occurred through the development of a systematic literature review, with publications between the years 2021 and 2023, which resulted in the examination of 15 articles. It can be verified that the personalization and adaptation of student learning, provided by AI, can result in better engagement and performance outcomes, in addition to the fact that the analysis of educational data through advanced algorithms allows a deeper understanding of pedagogical practices and identification of patterns for improvements in the educational process. It is concluded that it is essential that AI is used with caution and in conjunction with the pedagogical knowledge of education professionals, without teachers being fully or partially replaced – it is preponderant that they are in the classroom for the conduct of teaching-learning.

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Author Biography

Carlos Roberto de Almeida Correa Barbosa

Advogado e professor, graduado em Direito pela PUC-Campinas, graduando em Análises de Sistemas pela Faculdade de Tecnologia de Mogi Mirim e Pós-graduando em Docência do Ensino Superior pelo Instituto Líbano. 

References

AHADI, Alireza et al. Text mining in education—A bibliometrics-based systematic review. Education Sciences, v. 12, n. 3, p. 210, 2022. Disponível em https://www.mdpi.com/2227-7102/12/3/210/pdf. Acesso em 07 abr. 2023.

AKGUN, Selin; GREENHOW, Christine. Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, p. 1-10, 2021. Disponível em https://link.springer.com/article/10.1007/s43681-021-00096-7. Acesso em 07 abr. 2023.

ALAM, Ashraf. A digital game-based learning approach for effective curriculum transaction for teaching-learning of artificial intelligence and machine learning. In: 2022 International Conference on Sustainable Computing and Data Communication Systems (ICSCDS). IEEE, 2022. p. 69-74. Disponível em https://ieeexplore.ieee.org/abstract/document/9760932/. Acesso em 07 abr. 2023.

ALAM, Ashraf. Possibilities and apprehensions in the landscape of artificial intelligence in education. In: 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA). IEEE, 2021. p. 1-8. Disponível em https://ieeexplore.ieee.org/abstract/document/9697272/. Acesso em 07 abr. 2023.

BARBOSA, C. R. A. Guia prático para a categorização da Metodologia do Trabalho de Conclusão de Curso de graduação: explicações simples com exemplos de aplicação. São Paulo: Uiclap, 2023.

COPE, Bill; KALANTZIS, Mary; SEARSMITH, Duane. Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, v. 53, n. 12, p. 1229-1245, 2021. Disponível em https://www.tandfonline.com/doi/abs/10.1080/00131857.2020.1728732. Acesso em 07 abr. 2023.

EYSENBACH, Gunther et al. The role of chatgpt, generative language models, and artificial intelligence in medical education: A conversation with chatgpt and a call for papers. JMIR Medical Education, v. 9, n. 1, p. e46885, 2023.Disponível em https://mededu.jmir.org/2023/1/e46885/. Acesso em 07 abr. 2023.

KIM, Seonghun et al. Why and what to teach: AI curriculum for elementary school. In: proceedings of the AAAI Conference on Artificial Intelligence. 2021. p. 15569-15576. Disponível em https://ojs.aaai.org/index.php/AAAI/article/download/17833/17638. Acesso em 07 abr. 2023.

OKOYE, Kingsley et al. Towards teaching analytics: a contextual model for analysis of students’ evaluation of teaching through text mining and machine learning classification. Education and Information Technologies, p. 1-43, 2022. Disponível em https://link.springer.com/article/10.1007/s10639-021-10751-5. Acesso em 07 abr. 2023.

OUYANG, Fan; ZHENG, Luyi; JIAO, Pengcheng. Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, v. 27, n. 6, p. 7893-7925, 2022. Disponível em https://www.sciencedirect.com/science/article/pii/S2352827321001117. Acesso em 07 abr. 2023.

RAKHIMOV, Mehriddin; YULDASHEV, Axrorjon; SOLIDJONOV, Dilyorjon. The role of artificial intelligence in the management of e-learning platforms and monitoring knowledge of students. Oriental renaissance: Innovative, educational, natural and social sciences, v. 1, n. 9, p. 308-314, 2021. Disponível em https://cyberleninka.ru/article/n/the-role-of-artificial-intelligence-in-the-management-of-e-learning-platforms-and-monitoring-knowledge-of-students. Acesso em 07 abr. 2023.

RAZZAQ, Saad et al. DeepClassRooms: a deep learning based digital twin framework for on-campus class rooms. Neural Computing and Applications, p. 1-10, 2022. Disponível em https://www.mdpi.com/2076-3417/12/5/2534/pdf. Acesso em 07 abr. 2023.

SHAH, Dhruvil et al. Exploiting the capabilities of blockchain and machine learning in education. Augmented Human Research, v. 6, p. 1-14, 2021. Disponível em https://link.springer.com/article/10.1007/s41133-020-00039-7. Acesso em 07 abr. 2023.

SHIN, Jinnie; BULUT, Okan. Building an intelligent recommendation system for personalized test scheduling in computerized assessments: A reinforcement learning approach. Behavior Research Methods, v. 54, n. 1, p. 216-232, 2022.Disponível em https://link.springer.com/article/10.3758/s13428-021-01602-9. Acesso em 07 abr. 2023.

SORTE, Paulo Boa et al. Inteligência artificial e escrita acadêmica: o que nos reserva o algoritmo GPT-3? Revista EntreLinguas, p. e021035-e021035, 2021. Disponível em https://periodicos.fclar.unesp.br/entrelinguas/article/download/15352/11411. Acesso em 07 abr. 2023.

ZHAI, Xuesong et al. A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, v. 2021, p. 1-18, 2021. Disponível em https://www.hindawi.com/journals/complexity/2021/8812542/. Acesso em 07 abr. 2023.

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Published

29/04/2023

How to Cite

Almeida Correa Barbosa, C. R. de. (2023). TRANSFORMATIONS IN TEACHING-LEARNING WITH THE USE OF ARTIFICIAL INTELLIGENCE - SYSTEMATIC REVIEW OF THE LITERATURE. RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218, 4(5), e453103. https://doi.org/10.47820/recima21.v4i5.3103

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Vol. 4 No. 5 (2023): EDITORIAL - CLICK HERE TO ACCESS THE ARTICLES

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ARTIGOS

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