Digital Technology in Brazilian Schools after COVID-19: Distraction, School Climate, and Equity in PISA 2022

• Fábio Sant’Anna Linhares UFAL
• Fabiane da Silva Queiroz UFAL
• Jean Cristian Ferreira Machado Instituto Infnet

Resumo

This short paper critically synthesizes PISA 2022 and recent literature on device-related distraction, school climate, and educational equity in Brazil. In mathematics lessons, 45% of Brazilian students reported distraction by their own devices and 40% by classmates' use, compared with OECD averages of 30% and 25%. Because the study does not re-estimate PISA microdata, its claims are associative rather than causal. The synthesis distinguishes digital distraction from school climate and proposes four governance domains: pedagogical purpose, conditions of use, equity safeguards, and evidence-based monitoring. It also discusses Brazil's device regulation and generative AI.

Palavras-chave: digital technology, digital distraction, school climate, educational equity, PISA 2022, educational governance

Referências

Brazil (2025a) “Decree No. 12,385, of 18 February 2025”, Regulates Law No. 15,100/2025 on personal portable electronic devices in basic education.

Brazil (2025b) “Law No. 15,100, of 13 January 2025”, Regulates students' use of personal portable electronic devices in public and private basic-education institutions.

Cito, L. and Marôco, J. (2025) “Beyond the Average: Mapping Educational Inequality in Brazil with PISA 2022”, Research Square, preprint. DOI: 10.21203/rs.3.rs-7273143/v1.

Huang, F. L. (2024) “Using Plausible Values When Fitting Multilevel Models with Large-Scale Assessment Data Using R”, Large-scale Assessments in Education, v. 12, 7. DOI: 10.1186/s40536-024-00192-1.

Karakolidis, A., Pitsia, V. and Cosgrove, J. (2022) “Multilevel Modelling of International Large-Scale Assessment Data”, In: Khine, M. S. (ed.) Methodology for Multilevel Modeling in Educational Research, Springer, Singapore, p. 141-159. DOI: 10.1007/978-981-16-9142-3_8.

Lichand, G. et al. (2022) “The Impacts of Remote Learning in Secondary Education During the Pandemic in Brazil”, Nature Human Behaviour, v. 6, n. 8, p. 1079-1086. DOI: 10.1038/s41562-022-01350-3.

Mang, J., Küchenhoff, H., Meinck, S. and Prenzel, M. (2021) “Sampling Weights in Multilevel Modelling: An Investigation Using PISA Sampling Structures”, Large-scale Assessments in Education, v. 9, 6. DOI: 10.1186/s40536-021-00099-0.

Moro, A., Vinha, T. P. and Morais, A. (2019) “Avaliação do Clima Escolar: Construção e Validação de Instrumentos de Medida”, Cadernos de Pesquisa, v. 49, n. 172, p. 312-335. DOI: 10.1590/198053145305.

OECD (2023a) PISA 2022 Results (Volume I): The State of Learning and Equity in Education, OECD Publishing, Paris. DOI: 10.1787/53f23881-en.

OECD (2023b) PISA 2022 Results (Volume II): Learning During - and From - Disruption, OECD Publishing, Paris. DOI: 10.1787/a97db61c-en.

OECD (2024) PISA 2022 Technical Report, OECD Publishing, Paris. DOI: 10.1787/01820d6d-en.

OECD (2026) OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education, OECD Publishing, Paris. DOI: 10.1787/062a7394-en.

Queiroga, E. M. et al. (2024) “Data-Driven Strategies for Achieving School Equity: Insights From Brazil and Policy Recommendations”, IEEE Access, v. 12. DOI: 10.1109/ACCESS.2024.3422822.

Robinson, L. et al. (2015) “Digital Inequalities and Why They Matter”, Information, Communication & Society, v. 18, n. 5, p. 569-582. DOI: 10.1080/1369118X.2015.1012532.

Schady, N. et al. (2023) Collapse and Recovery: How the COVID-19 Pandemic Eroded Human Capital and What to Do About It, World Bank, Washington, DC. DOI: 10.1596/978-1-4648-1901-8.

Xavier, F. P. (coord.) (2024) Gestão das Redes de Ensino e Clima Escolar: Mapeamento das Ações e Uma Proposta de Matriz Avaliativa Sensível à Equidade, Centro Lemann; Nupede/UFMG, Belo Horizonte.