Tipo: artículo

Metodología: estudio empírico

Temas: inteligencia artificial

Resumen:

Emotional disengagement has attracted considerable attention in educational research, particularly research on online learning environments. Negative emotions can narrow learners’ attentional focus and suppress spoken output, making it difficult for teachers to gauge students’ actual oral abilities. This study investigates whether real-time recognition of learners’ facial emotions, combined with targeted questioning strategies, can foster more positive affect during synchronous online second language (L2) classes. Using a multitask convolutional neural network (MTCNN) for face detection and the VGGFace model for expression classification, we captured seven emotions from 61 Chinese undergraduates during one-on-one online interactions. Each teacher question was coded for type, mood, and subject pronoun. The results extend research on...

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