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O Papel da Inteligência Artificial na Aprendizagem Personalizada de Alunos do Ensino Secundário com Necessidades Especiais: a perspetiva dos Professores
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Abstract(s)
Este estudo qualitativo explorou as perceções e práticas de professores portugueses do ensino secundário relativamente à Inteligência Artificial (IA) na personalização da aprendizagem e na inclusão de alunos com Necessidades Educativas Especiais (NEE). Oito entrevistas semiestruturadas foram realizadas e analisadas, de acordo com a estrutura de análise de conteúdo de Bardin (2009), produzindo uma matriz detalhada que capturou usos funcionais, benefícios percebidos, barreiras e recomendações. Os professores referiram que as plataformas adaptativas adequam o conteúdo, o ritmo e o desafio aos perfis individuais, automatizam a avaliação com feedback formativo imediato e fornecem painéis de análise da aprendizagem que destacam os padrões de risco. Consideraram que as tecnologias assistivas baseadas em IA – leitores de ecrã, sintetizadores de voz, legendagem e tradução em tempo real - são essenciais para o Desenho Universal para a Aprendizagem, reforçando a autonomia, a motivação e a participação social dos alunos com NEE. No entanto, os inquiridos identificaram obstáculos significativos: desenvolvimento profissional inadequado, infraestruturas fracas, acesso desigual aos dispositivos e à banda larga e preocupações não resolvidas sobre a privacidade dos dados e os preconceitos algorítmicos. As diferenças disciplinares foram evidentes; as disciplinas STEM adotaram a IA mais rapidamente do que os domínios cinestésicos. Os professores defenderam sistematicamente que a utilização da IA deve crescer, sem substituir a relação humana que é fundamental para a pedagogia. As limitações metodológicas incluem a amostra pequena e geograficamente delimitada, a dependência do autorrelato e a natureza rápida da inovação da IA. Os trabalhos futuros devem utilizar métodos mistos e conceções longitudinais, integrar as perspetivas dos estudantes e investigar modelos de governação sistémica. De um modo geral, os resultados sugerem que o potencial transformador da IA dependerá de uma estratégia política coerente, de recursos equitativos e de um reforço sustentado das capacidades dos professores, permitindo que a tecnologia funcione quer como um andaime cognitivo, quer como um motor de uma educação inclusiva e de alta qualidade.
This qualitative study explored Portuguese secondary-school teachers’ perceptions and practices regarding Artificial Intelligence (AI) in personalizing learning and inclusion of pupils with Special Educational Needs (SEN). Eight semi-structured interviews were carried out and analysed following Bardin’s content-analysis framework, yielding a detailed matrix that captured functional uses, perceived benefits, barriers, and recommendations. Teachers reported that adaptive platforms tailor content, pace, and challenge to individual profiles, automate assessment with immediate formative feedback, and provide learning analytics dashboards highlighting risk patterns. They viewed AI-driven assistive technologies - speech-to-text, text-to-speech, captioning, and real-time translation- as pivotal for Universal Design for Learning, enhancing autonomy, motivation, and social participation among SEN learners. Nevertheless, respondents identified significant obstacles: inadequate professional development, fragile infrastructure, unequal access to devices and broadband, and unresolved concerns over data privacy and algorithmic bias. Disciplinary differences were evident; STEM subjects adopted AI more readily than kinaesthetic domains. Teachers consistently argued that AI should augment rather than replace the human relationship fundamental to pedagogy. Methodological limitations include the small, geographically bounded sample, reliance on self-report, and the fast-moving nature of AI innovation. Future work should employ mixed-methods and longitudinal designs, integrate student perspectives, and investigate systemic governance models. Overall, the findings suggest that AI’s transformative potential will depend on coherent policy strategy, equitable resourcing, and sustained teacher capacity-building, enabling technology to function as both a cognitive scaffold and a driver of inclusive, high-quality education.
This qualitative study explored Portuguese secondary-school teachers’ perceptions and practices regarding Artificial Intelligence (AI) in personalizing learning and inclusion of pupils with Special Educational Needs (SEN). Eight semi-structured interviews were carried out and analysed following Bardin’s content-analysis framework, yielding a detailed matrix that captured functional uses, perceived benefits, barriers, and recommendations. Teachers reported that adaptive platforms tailor content, pace, and challenge to individual profiles, automate assessment with immediate formative feedback, and provide learning analytics dashboards highlighting risk patterns. They viewed AI-driven assistive technologies - speech-to-text, text-to-speech, captioning, and real-time translation- as pivotal for Universal Design for Learning, enhancing autonomy, motivation, and social participation among SEN learners. Nevertheless, respondents identified significant obstacles: inadequate professional development, fragile infrastructure, unequal access to devices and broadband, and unresolved concerns over data privacy and algorithmic bias. Disciplinary differences were evident; STEM subjects adopted AI more readily than kinaesthetic domains. Teachers consistently argued that AI should augment rather than replace the human relationship fundamental to pedagogy. Methodological limitations include the small, geographically bounded sample, reliance on self-report, and the fast-moving nature of AI innovation. Future work should employ mixed-methods and longitudinal designs, integrate student perspectives, and investigate systemic governance models. Overall, the findings suggest that AI’s transformative potential will depend on coherent policy strategy, equitable resourcing, and sustained teacher capacity-building, enabling technology to function as both a cognitive scaffold and a driver of inclusive, high-quality education.
Description
Keywords
Inteligência artificial Aprendizagem personalizada Educação inclusiva Perceções dos professores