数据驱动与产教融合：高职教学质量智能评价体系的构建研究

Data-Driven and Industry-Education Integration: Research on Establishing an Intelligent Evaluation System for Vocational College Teaching Quality

摘要: 随着大数据、人工智能等新一代信息技术的迅猛发展，职业教育质量评价体系正面临深刻变革。当前高职院校教学质量评价普遍存在评价主体单一、数据采集片面、结果反馈滞后、与产业发展脱节等问题，难以适应技术技能人才培养的新要求。本文在分析高职教学质量评价现实困境的基础上，结合大数据技术特征，提出构建“数据驱动、多元参与、过程覆盖、产教融合”的新型教学质量评价体系，并从评价理念、指标体系、技术平台、保障机制四个方面提出具体实施路径，以期为高职教育质量提升提供理论参考与实践指导。

Abstract: With the rapid advancement of new-generation information technologies such as big data and artificial intelligence, the quality evaluation system for vocational education is undergoing profound transformation. Current teaching quality assessments in higher vocational colleges generally suffer from issues including single-source evaluation, fragmented data collection, delayed feedback, and disconnect from industrial development, making it difficult to meet the new demands for cultivating technical and skilled talent. Based on an analysis of the current challenges in higher vocational teaching quality evaluation, this paper proposes a new evaluation system characterized by “data-driven, multi-stakeholder participation, process coverage, and industry-education integration”, leveraging the features of big data technology. Specific implementation pathways are outlined across four dimensions—evaluation philosophy, indicator system, technical platform, and safeguarding mechanisms—to provide theoretical reference and practical guidance for enhancing the quality of higher vocational education.