Construction of undergraduate education teacher team under the background of big data and artificial intelligence

Abstract

In the context of the increasing impact of big data and artificial intelligence (AI) technologies on the field of education, this study aims to explore the impact of these technologies on the construction of undergraduate education faculty. Through questionnaires and data analysis, the study assesses teachers’ attitudes toward big data and AI technologies, their applications, and the challenges they face. The results show that teachers generally have a positive attitude towards these technologies, but there are differences in the frequency and familiarity with their application. Model analysis further revealed the positive effects of technology use frequency, technology familiarity, and training support on improving teaching quality and student learning outcomes. Research shows that providing teachers with targeted technology training, updating teaching methods, and ensuring data privacy and security are key to improving the quality of education. These findings are of great significance for guiding the application of big data and AI technology in undergraduate education, and also provide a valuable reference for future education policy making and teacher professional development.