Flow Prediction Model in English Intercultural Learning Based on BP Algorithm
Abstract
In recent years, the emotions in English learning have been studied. To investigate the flow experience in the intercultural learning in English as a Foreign Language (EFL) class, a questionnaire survey was conducted with 460 students in one vocational college and 450 valid questionnaires were collected. The SmartPSL was utilized for data analysis to determine the moderating effects of flow experience and core input vectors were selected for the Backpropagation Neural Network (BPNN) model. After constructing a flow prediction model for English intercultural learning and validating the predictive results, the study showed that learners were able to enter a flow state and the predictive outcomes were relatively accurate. Based on the results, the study has been highlighted the significance of flow experience in intercultural English learning. It also offers a flow prediction model, which assists teacher to assess students’ active emotion in English learning and to enhance the teaching quality in intercultural teaching.
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