Loading...
Publication
Integrating artificial intelligence in the flipped classroom approach
| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 4.33 MB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
Esta dissertação investiga uma questão central: Como é que a Inteligência Artificial (IA) pode melhorar a aprendizagem da língua inglesa de alunos adultos falantes da língua portuguesa numa sala de aula invertida (Flipped Classroom em inglês)?
Este estudo tem como objetivo compreender o impacto das ferramentas de IA na motivação, no desempenho e na aprendizagem de alunos adultos quando integradas no ensino de línguas.
Ao utilizar uma abordagem que envolve métodos de pesquisa mistos para a obtenção de dados quantitativos e qualitativos antes e após a experiência, esta investigação pretende avaliar o impacto do uso da IA em adultos nas atividades de compreensão do oral, leitura, expressão escrita e produção oral, em comparação com os métodos tradicionais.
Com base nas teorias construtivistas de Dewey (1929), Bruner (1961), Vygotsky (1962) e Piaget (1971), que enfatizam a importância do papel ativo dos alunos na aprendizagem, a dissertação examina a forma como as ferramentas de IA, como o ChatGPT e o Gemini, fornecem feedback personalizado e em tempo real e apoiam a autonomia dos alunos (Von Glasersfeld, 1995; Jonassen, 1994).
O modelo de sala de aula invertida, destacado por Bergmann e Sams (2012) como uma abordagem pedagógica eficaz, serve de enquadramento para a implementação de ferramentas de IA que permitam a preparação dos alunos para as aulas seguintes e a aprendizagem ativa durante a aula.
Os resultados indicam que a integração da IA numa sala de aula invertida pode aumentar o envolvimento dos alunos, aumentar o ritmo de aprendizagem e reforçar a motivação, fornecendo-lhes feedback adaptado, conferindo-lhes, assim, uma componente prática personalizada. No entanto, há limitações, incluindo a possível dependência excessiva da IA, preocupações relativamente à redução da interação interpessoal e as dificuldades que alguns alunos enfrentam ao usar tecnologia (Lin et al., 2017; Pokrivcakova, 2019). Apesar desses desafios, a natureza adaptativa da IA alinha-se bem com as necessidades dos alunos adultos que procuram uma aprendizagem flexível e autodirigida, sugerindo que a IA pode complementar os métodos tradicionais para assim criarem aulas mais dinâmicas e interativas.
A dissertação termina recomendando mais investigação no aspeto ético da IA na educação, particularmente em torno da privacidade dos dados e do impacto na relação professor-aluno. Estudos futuros devem também explorar a aplicabilidade da IA em diferentes níveis linguísticos e os seus efeitos a longo prazo na retenção da língua e na confiança dos alunos. Esta investigação contribui para a crescente literatura sobre a IA no ensino das línguas, oferecendo perspetivas práticas sobre a forma como os professores de línguas podem integrar a IA de forma responsável nas suas aulas de modo a enriquecerem o ambiente de aprendizagem dos alunos adultos.
Quando devidamente utilizada, a IA consegue oferecer apoio personalizado e feedback em tempo real, tornando a aprendizagem mais cativante e eficaz tanto para os alunos como para os professores. Ao explorar esta combinação, o estudo procura desenvolver experiências de aprendizagem de línguas mais eficientes e bem-sucedidas para estudantes adultos que procuram aulas mais dinâmicas e menos centradas no professor. É essencial optar por novos métodos e ferramentas de ensino que tornem os alunos mais ativos e participativos na sala de aula e em casa. Graças à IA, é possível criar mais ambientes de interação entre os alunos e o conteúdo abordado, bem como dar-lhes mais autonomia.
This dissertation investigates one central question: How can Artificial Intelligence (AI) enhance adult English language learning in a flipped classroom setting for Portuguese-speaking learners? This study aims to understand how AI tools impact learner motivation, performance, and acquisition outcomes when integrated into language education. By employing a mixed-methods approach that includes both quantitative and qualitative data from pre- and post-intervention assessments, this research evaluates adult students’ learning with AI-driven tasks in listening, reading, writing, and speaking activities compared to traditional methods. Building on the constructivist theories of Dewey (1929), Bruner (1961), Vygotsky (1962), and Piaget (1971), which emphasise active learner engagement, the dissertation examines how AI tools such as ChatGPT and Gemini provide personalised, real-time feedback and support learners’ autonomy (Von Glasersfeld, 1995; Jonassen, 1994). The flipped classroom model, highlighted by Bergmann and Sams (2012) as an effective pedagogical approach, serves as the framework for implementing AI tools to allow pre-class preparation and in-class active learning. The findings indicate that AI integration in a flipped classroom setting can boost engagement, increase the learning pace, and enhance motivation by providing tailored feedback and enabling personalised practice. However, limitations include the potential for over-reliance on AI, concerns about reduced interpersonal interaction, and the challenges some learners face with technology (Lin et al., 2017; Pokrivcakova, 2019). Despite these challenges, AI’s adaptive learning capabilities align well with adult learners’ needs for flexible, self-directed learning, suggesting that AI can complement traditional methods to create a more dynamic, interactive classroom experience. The dissertation concludes by recommending further research to address the ethical considerations of AI in education, particularly around data privacy and the impact on teacher-student relationships. Future studies should also explore AI’s applicability across different language levels and its long-term effects on language retention and learner confidence. This research contributes to the growing body of literature on AI in language education, offering practical insights into how educators can responsibly integrate AI to enrich the learning environment for adult language learners. When used correctly, AI can offer personalised support and real-time feedback, making learning more engaging and effective for both students and teachers. By exploiting this combination, the study seeks to develop more efficient and successful language learning experiences for adult students looking for more dynamic lessons that are less teacher-centred. Opting for new teaching methods and tools that make students more active and participative in the classroom and at home is essential. Thanks to AI, it is possible to create more environments for interaction between students and the content covered and give them more autonomy.
This dissertation investigates one central question: How can Artificial Intelligence (AI) enhance adult English language learning in a flipped classroom setting for Portuguese-speaking learners? This study aims to understand how AI tools impact learner motivation, performance, and acquisition outcomes when integrated into language education. By employing a mixed-methods approach that includes both quantitative and qualitative data from pre- and post-intervention assessments, this research evaluates adult students’ learning with AI-driven tasks in listening, reading, writing, and speaking activities compared to traditional methods. Building on the constructivist theories of Dewey (1929), Bruner (1961), Vygotsky (1962), and Piaget (1971), which emphasise active learner engagement, the dissertation examines how AI tools such as ChatGPT and Gemini provide personalised, real-time feedback and support learners’ autonomy (Von Glasersfeld, 1995; Jonassen, 1994). The flipped classroom model, highlighted by Bergmann and Sams (2012) as an effective pedagogical approach, serves as the framework for implementing AI tools to allow pre-class preparation and in-class active learning. The findings indicate that AI integration in a flipped classroom setting can boost engagement, increase the learning pace, and enhance motivation by providing tailored feedback and enabling personalised practice. However, limitations include the potential for over-reliance on AI, concerns about reduced interpersonal interaction, and the challenges some learners face with technology (Lin et al., 2017; Pokrivcakova, 2019). Despite these challenges, AI’s adaptive learning capabilities align well with adult learners’ needs for flexible, self-directed learning, suggesting that AI can complement traditional methods to create a more dynamic, interactive classroom experience. The dissertation concludes by recommending further research to address the ethical considerations of AI in education, particularly around data privacy and the impact on teacher-student relationships. Future studies should also explore AI’s applicability across different language levels and its long-term effects on language retention and learner confidence. This research contributes to the growing body of literature on AI in language education, offering practical insights into how educators can responsibly integrate AI to enrich the learning environment for adult language learners. When used correctly, AI can offer personalised support and real-time feedback, making learning more engaging and effective for both students and teachers. By exploiting this combination, the study seeks to develop more efficient and successful language learning experiences for adult students looking for more dynamic lessons that are less teacher-centred. Opting for new teaching methods and tools that make students more active and participative in the classroom and at home is essential. Thanks to AI, it is possible to create more environments for interaction between students and the content covered and give them more autonomy.
Description
Tese de Mestrado em Didática do Inglês, em associação com a Faculdade de Ciências Sociais e Humanas da UNL, apresentada à Universidade Aberta
Keywords
Inteligência artificial Sala de aula invertida Aprendizagem de línguas Teoria construtivista Educação de adultos Feedback personalizado Autonomia do aluno Artificial intelligence Flipped classroom Language learning Constructivist theory Adult education Personalized feedback Learner autonomy