基于数智技术驱动的高职专业调整科学化与精准化研究

Research on the Scientific and Precise Adjustment of Higher Vocational Education Specialties Driven by Digital Intelligence Technology

摘要: 产业数字化转型催生大量新职业及产业新业态，传统高职专业调整机制存在响应滞后、供需错位等问题。通过数智技术打破传统调整中的路径依赖和制度壁垒，从驱动数据采集到决策输出实现全流程智能化。依托数据来源的多面性、分析模型的精准化、数据驱动的专业质量评估与动态监测机制等达到决策支撑的有效性以实现高职专业调整的科学性。通过数据评估和趋势预测专业发展、综合权重模型的构建、技术预测未来技能的前瞻性等进行专业方向调整，来精准实现调整时机的恰当性、调整幅度的适度性和调整方向的正确性。推动高职专业调整从经验判断转向科学决策与精准调整，提升人才培养与产业需求匹配度。

Abstract: The digital transformation of industries has led to the emergence of numerous new occupations and industrial forms. However, the traditional mechanism for adjusting higher vocational education specialties faces significant challenges, including delayed responsiveness and a mismatch between supply and demand. By leveraging digital and intelligent technologies to overcome path dependence and institutional barriers, the entire process, from data collection to decision-making, can be fully automated and optimized. Drawing on diverse data sources, high-precision analytical models, and a data-driven quality evaluation framework coupled with dynamic monitoring mechanisms, this approach enhances decision support and ensures the scientific rigor of specialty adjustments in higher vocational education. Through data-based assessment and trend forecasting of occupational development, the construction of comprehensive weighting models, and forward-looking predictions of future skill requirements enabled by advanced technologies, adjustments to specialties can be made precisely. This ensures appropriate timing, reasonable scale, and accurate directionality in program modifications. Ultimately, it facilitates a shift from experience-based judgment to evidence-driven, precise decision-making in specialty adjustment, thereby strengthening the alignment between talent development and evolving industry needs.