Research on a Data-Intelligence-Driven "Training-Evaluation-Competition" Cultivation System for Teacher Education Students

Abstract

The rapid development of artificial intelligence technology is driving the digital transformation of teacher education, imposing new requirements on the cultivation of teaching skills among teacher candidates in the new era. To address issues such as fragmented processes, inconsistent standards, delayed feedback, and low educational efficiency in traditional teacher training, this study takes the Teacher Training Center at Hubei University of Science and Technology as a case to establish an integrated, full-chain "training-evaluation-competition" cultivation system empowered by data and intelligence. Relying on a three-tier architecture, a four-dimensional collaborative mechanism, and a data-intelligence-based training platform, the system achieves precise skill training, intelligent competency assessment, systematic competition development, and closed-loop educational processes. Four years of practical validation have demonstrated that the system effectively enhances both the teaching competencies and competitive excellence of teacher candidates, promoting the transformation of teacher education towards digitization, precision, and systematization. Future efforts will focus on continuously optimizing platform algorithms, training resources, and talent development mechanisms to strengthen the comprehensive qualities of teacher candidates and cultivate high-quality, innovative teachers for basic education.