Research on the Construction of an Educational Service Quality Evaluation System Driven by Artificial Intelligence Technology

Abstract

In the context of high-quality educational development, the scientific and objective evaluation of educational service quality has become a key concern in educational governance and management. Traditional evaluation approaches face limitations in indicator design, data sources, and result application, which restrict their ability to reflect the dynamic and multidimensional nature of educational service processes. With the deepening application of artificial intelligence in education, its strengths in multi-source data processing, pattern recognition, and intelligent analysis offer new possibilities for improving evaluation systems. Based on a systematic review of existing studies and the foundations of AI applications, this research constructs an educational service quality evaluation system centered on data integration and intelligent analysis. The study focuses on evaluation framework design, indicator system construction, and evaluation model development, and examines how artificial intelligence supports comprehensive assessment and result feedback. A case study is conducted to validate the feasibility and effectiveness of the proposed system. The findings demonstrate that artificial intelligence can enhance the scientific rigor, dynamic adaptability, and practical value of educational service quality evaluation, contributing to the modernization of educational governance.