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Vocational Education 2025
面向智能化时代的C语言程序设计教学改革探析
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Abstract:
人工智能与大数据技术的快速发展对计算机基础教育模式产生深刻影响。传统C语言教学在编程思维训练和实践能力培养方面逐渐显现局限性,亟待探索适应智能时代需求的新型教学模式。针对上述问题,本研究构建了融合问题解决导向与项目驱动机制的教学体系,通过整合智能代码评测系统、虚拟仿真实验平台等数字化工具,重构理论教学与实践环节的衔接路径。同时建立课程思政与专业知识的协同机制,在案例设计中融入工程伦理与创新思维要素。通过跟踪发现,参与改革的学生在后续数据结构课程中的平均成绩持续高于基线组8~12分。实证研究表明,智能技术支持的教学模式重构能有效提升编程教育的实践效能。数字化工具的应用使知识转化效率提升40%以上,智能评测系统将教师批改作业时间缩减62%,虚拟平台使实验资源利用率达到传统模式的3.2倍。这种改革框架不仅强化了学生的工程实践能力,更通过教学过程的数字化改造形成了可复制的课程建设范式。未来教育模式应进一步深化智能技术与教学要素的融合,建立动态优化的教学资源生态系统,从而持续提升计算机人才培养质量。
The rapid advancement of artificial intelligence and big data technologies has profoundly reshaped computer science education. Traditional C programming instruction, constrained by limitations in cultivating programming logic and practical skills, urgently requires innovative pedagogical models tailored to intelligent-era demands. This study proposes a problem-solving-oriented and project-driven teaching framework integrating intelligent code evaluation systems, virtual simulation platforms, and digital tools to bridge theoretical instruction and practical application. A synergistic mechanism embedding engineering ethics and innovative thinking into curriculum design was established, aligning ideological education with technical competencies. Longitudinal tracking revealed that reformed cohorts outperformed control groups by 8~12 points in subsequent data structure courses. Empirical data demonstrate significant improvements: digital tools enhanced knowledge transfer efficiency by 40%, intelligent grading reduced instructors’ workload by 62%, and virtual platforms tripled resource utilization (3.2 × baseline). The restructured model not only strengthened engineering practice capabilities but also established replicable digital teaching paradigms through systematic process optimization. Future directions emphasize dynamic resource ecosystems and deeper integration of intelligent technologies to sustainably advance computing talent cultivation.
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