Detecção de Afetos sem Sensores em Ambientes de Aprendizagem: Uma Revisão Sistemática da Literatura
DOI:
https://doi.org/10.5753/rbie.2024.4362Keywords:
Detecção de Afetos sem Sensores, Revisão Sistemática da Literatura, Ambientes de Aprendizagem Emocional, Detecção de Emoções, Ambientes de Aprendizagem Baseados em ComputadorAbstract
Emoções e estados afetivos influenciam a cognição e os processos de aprendizagem. Ambientes de aprendizagem baseados em computador (CBLEs, do inglês Computer-Based Learning Environments) capazes de detectar e adaptar-se a esses estados aprimoram significativamente os resultados de aprendizagem. No entanto, restrições práticas muitas vezes dificultam o uso de sensores para a detecção afetiva em CBLEs, especialmente em contextos de larga escala ou de longo prazo. Consequentemente, a detecção de afetos sem sensores, baseada exclusivamente nos registros de interação, surge como uma alternativa promissora. Este artigo apresenta uma revisão sistemática da literatura sobre detecção de afetos sem sensores, abordando estados afetivos comumente identificados, metodologias para desenvolvimento de sensores, características dos CBLEs e tendências de pesquisa. Apesar da maturidade do campo, ainda há amplo espaço para exploração. Pesquisas futuras devem focar na melhoria dos modelos de detecção sem sensores, na coleta de mais amostras de emoções sub-representadas e no refinamento das práticas de desenvolvimento de modelos. Além disso, esforços devem ser direcionados para integrar esses modelos aos CBLEs para detecção em tempo real, proporcionar intervenções significativas baseadas nas emoções detectadas e aprofundar a compreensão do impacto das emoções na aprendizagem. Sugestões-chave incluem a comparação de técnicas de coleta de dados, a otimização da granularidade temporal, o estabelecimento de bases de dados compartilhadas e a garantia de acessibilidade ao código-fonte dos modelos.
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