Smart classrooms have attracted much attention as a new type of educational environment, and it is of great significance to study the diversified facilities in smart classrooms to improve the comfort and learning effect during the use of the classroom. In this paper, the TGAM module is used to collect and pre-process the EEG signals of English learners when they are studying in the smart classroom, and wavelet analysis and support vector machine are used to extract and identify the EEG signals, and the EEG signals are used to reflect the effect of English learning, so as to realize the intelligent analysis of the learning effect. Finally, based on the important elements in the space design of the smart classroom, the lighting facilities and thermal environment regulation facilities are selected to analyze their impact on the learning effect. It is found that the EEG signal α and β levels of English learners in the smart classroom are relatively highest when the illumination value is 700lx, and the English learning effect is more ideal at this time. When the PMV value of the thermal environment is -0.29, the R-value of the EEG signals δ + θ of the English learners decreases to 0.063, which indicates that the lighting and the thermal environment facilities in the smart classroom have a greater impact on the English learning effect. This study provides ideas for the development of future programs for the scientific and effective implementation of diverse facilities in smart classrooms.
