Navigating the Evolving Role of College Teachers in China's Intelligent Era

Abstract

This research examines the incorporation of intelligent technologies, including Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), and the Internet of Things (IoT), into pedagogical methods among college teachers in China. The main goals were to evaluate the degree of technology integration, analyze teacher profiles concerning gender, age, years of teaching experience, and area of expertise, and determine any significant disparities in technology integration based on these demographic parameters—the research aimed to identify the perceived advantages and obstacles related to using these technologies in higher education. Data was gathered via surveys and interviews with 320 college instructors across several fields at five institutions in China. Descriptive and inferential statistical methods were used to assess the degree of intelligent technology integration and to discern significant variations based on demographic characteristics. Qualitative data from interviews provide profound insights into intelligent technology adoption's perceived advantages and obstacles. The findings indicated that innovative technologies are extensively used across all categories, with AI, machine learning, IoT, and predictive analytics most often incorporated into educational procedures. No substantial disparities in technology adoption were seen concerning gender, age, years of experience, or area of expertise, except for predictive analytics, where men indicated somewhat greater utilization. The primary advantages of using intelligent technology include tailored learning, enhanced efficiency, and availability of real-time data. Nonetheless, educators also identified obstacles like insufficient training, poor infrastructure, excessive dependence on technology, and apprehensions around data privacy.