RESUMEN
This review explored the investigations on the role of teacher immediacy in English as a Foreign Language (EFL) learners' foreign language enjoyment. Earlier investigations have proved that teacher immediacy, such as posture, body language, vocal variety, gestures, and smile, can significantly affect learners' positive emotions like foreign language enjoyment. It means that teachers should try both to control the feelings of their learners and manage their feelings to enhance enjoyment among learners. Moreover, studies have shown that teacher immediacy is significantly related to learner motivation which is a basis for increasing foreign language enjoyment among learners. However, specific strategies can be employed to increase learner motivation, which in return increases learner foreign language enjoyment. Furthermore, the study presented the implications and future directions of this line of research for different people, such as EFL teachers, teacher educators, and foreign language scholars. The ideas can improve their awareness of teacher-student relationships, in particular, teacher immediacy and its role in learners' foreign language enjoyment.
RESUMEN
Metaverse is to build a virtual world that is both mapped and independent of the real world in cyberspace by using the improvement in the maturity of various digital technologies, such as virtual reality (VR), augmented reality (AR), big data, and 5G, which is important for the future development of a wide variety of professions, including education. The metaverse represents the latest stage of the development of visual immersion technology. Its essence is an online digital space parallel to the real world, which is becoming a practical field for the innovation and development of human society. The most prominent advantage of the English-teaching metaverse is that it can provide an immersive and interactive teaching field for teachers and students, simultaneously meeting the teaching and learning needs of teachers and students in both the physical world and virtual world. This study constructs experiential situational English-teaching scenario and convolutional neural networks (CNNs)-recurrent neural networks (RNNs) fusion models are proposed to recognize students' emotion electroencephalogram (EEG) in experiential English teaching during the feature space of time domain, frequency domain, and spatial domain. Analyzing EEG data collected by OpenBCI EEG Electrode Cap Kit from students, experiential English-teaching scenario is designed into three types: sequential guidance, comprehensive exploration, and crowd-creation construction. Experimental data analysis of the three kinds of learning activities shows that metaverse-powered experiential situational English teaching can promote the improvement of students' sense of interactivity, immersion, and cognition, and the accuracy and analysis time of CNN-RNN fusion model is much higher than that of baselines. This study can provide a nice reference for the emotion recognition of students under COVID-19.
