Research on the optimization of undergraduate teaching quality evaluation system and construction of a smart platform—an empirical analysis based on 51 universities
本科教学质量评价体系优化与智慧平台构建研究——基于51所高校的实证分析

摘要

教学质量评价是高等教育高质量发展的核心保障，也是一流人才培养的关键抓手。本研究以境内外51所不同层次、不同学科特色的高校为样本，通过文本分析、比较研究及问卷调查，系统梳理当前高校教学质量评价体系的现状与问题。研究发现，国内高校评价体系存在与培养目标适配性不足、评价主体单一、指标设计不科学、结果反馈与改进机制不健全等突出问题。基于此，本研究构建“督导评价、学生评价、同行评价、教师自评、学生自评”的“五维”教学质量评价体系，设计涵盖工科与文科理论课、实验实践课的综合评价指标体系，并提出基于人工智能技术的智慧评价平台方案，为高校教学质量评价改革提供理论参考与实践路径。

Abstract

Teaching quality evaluation serves as a cornerstone for the high-quality development of higher education and a key measure for cultivating first-rate talents. This study takes 51 domestic and international higher education institutions of varying levels and disciplinary characteristics as samples. Through text analysis, comparative research, and questionnaire surveys, it systematically examines the current state and problems of teaching quality evaluation systems in universities. The research finds that domestic evaluation systems face various challenges, including insufficient alignment with talent training objectives, a lack of diversity in evaluation participants, unscientific indicator design, and inadequate mechanisms for feedback and improvement. Based on these findings, this study constructs a "Five-Dimensional" teaching quality evaluation system encompassing "supervisory evaluation, student evaluation, peer evaluation, teacher self-evaluation, and student self-evaluation". It designs a comprehensive evaluation indicator system covering theoretical courses and experimental/practical courses in both engineering and liberal arts disciplines. Furthermore, it proposes a smart evaluation platform scheme based on artificial intelligence technology, providing theoretical reference and practical pathways for the reform of teaching quality evaluation in universities.