Artificial Intelligence, Programming, and Computational Thinking in Physics and Science Education

A Systematic Review

Authors

DOI:

https://doi.org/10.25749/sis.45263

Keywords:

artificial intelligence, physics teaching, science teaching, computational thinking, systematic review

Abstract

This study presents a systematic literature review on the integration of Artificial Intelligence, Programming Language, and Computational Thinking in Physics and Science Education. The review was conducted in accordance with the PRISMA 2020 protocol, including searches in the Web of Science, Scopus, and Google Scholar databases, with a time frame between 2015 and 2025. After rigorous application of eligibility and duplication criteria, 17 fully traceable studies were included in the qualitative synthesis. The results indicate recent growth in research, with a predominance of reviews and empirical studies focused on personalised learning, problem solving, computational modelling, and teacher training. Despite the identified pedagogical potential, the studies highlight challenges related to teacher training, technological infrastructure, and ethical issues. It is concluded that the integration of these technologies requires critical pedagogical approaches, aligned with educational objectives and teaching practices.

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Author Biographies

Dadson Luis Ferreira Leite, Programa de Pós-Graduação em Ensino – RENOEN, Universidade Estadual do Maranhão - UEMA, Brazil

Graduado em Física pela Universidade Estadual do Maranhão (2015), Mestrado em Física pela Universidade Federal do Maranhão (2021) e é Doutorando em Ensino pela Universidade Estadual do Maranhão (UEMA), em colaboração com o Programa de Pós-Graduação em Ensino da Rede Nordeste de Ensino (RENOEN). Membro do Grupo de Modelagem Computacional (GMC), contribuindo para a articulação da pesquisa em ensino de Ciências/Física/Matemática e prática dos professores de Ciências/Física/Matemática. Professor da Rede Estadual e professor do Departamento de Física da UEMA (substituto). Bolsista FAPEMA.

Wellington Cantanhede dos Santos, Programa de Pós-Graduação em Ensino – RENOEN, Universidade Estadual do Maranhão - UEMA, Brazil

Graduado em Física pelo Instituto Federal de Educação, Ciência e Tecnologia do Maranhão (IFMA), Mestrado em Física da Matéria Condensada (Experimental) pela Universidade Federal do Rio Grande do Norte (UFRN). Doutorando em Ensino pela Universidade Estadual do Maranhão (UEMA), em colaboração com o Programa de Pós-Graduação em Ensino da Rede Nordeste de Ensino (RENOEN). Professor do IEMA Pleno São José de Ribamar. Grupo de Pesquisa em Ensino de Física do Instituto Federal de Educação, Ciência e Tecnologia do Maranhão (GPEF/IFMA), linha de pesquisa em Ensino de Física. Membro do Grupo de Modelagem Computacional (GMC).

Edvan Moreira, Departamento de Física, Centro de Educação, Ciências Exatas e Naturais, Universidade Estadual do Maranhão, Brazil

Graduado em Física pela Universidade Federal do Maranhão, Mestre em Física pela Universidade Federal do Maranhão, e Doutor em Física pela Universidade Federal do Rio Grande do Norte. Fez estágio de Pós-Doutorado no Centro de Biociências da Universidade Federal do Rio Grande do Norte. Atualmente é Professor do Departamento de Física da Universidade Estadual do Maranhão (UEMA). Docente permanente do Doutorado em Ensino (RENOEN), atuando nas Linhas de Pesquisa: Práticas Pedagógicas no Ensino de Física e Ensino Tecnológico. Tem experiência na área de Física, com ênfase em Física Atômica e Molecular, Física da Matéria Condensada e Ensino de Física.

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Published

2026-06-30

Issue

Vol. 14 No. 2 (2026): Educators’ Digital Competence in the Age of Artificial Intelligence: Reconfigurations of Pedagogical Practice

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Articles

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