基于课程体系改革的本科院校大数据实验班建设方案探究
Exploration of the Construction Plan for Big Data Experimental Classes in Undergraduate Colleges Based on Curriculum System Reform

本文探讨基于课程体系改革的本科院校大数据实验班建设的重要举措。教学模式方面，采用知识图谱及跨学科融合教学，提升学生实践与综合运用知识能力；师资队伍建设方面，组建跨学科团队、引入企业导师并加强教师培训进修；实践平台方面，构建校内实验平台、与企业共建实习基地及开展虚拟实验室项目，为学生提供丰富实践环境；课程体系优化包含设置个性化选修及分层实践课程；考核评价方式采用多元化指标、以过程性评价为主并引入企业评价机制，旨在全方位提升大数据实验班的教学质量与学生专业素养，培养适应行业需求的高素质大数据专业人才，增强本科院校在大数据领域的人才输出能力与竞争力，推动大数据专业教育的创新发展，为高校相关专业建设提供有益借鉴。
This paper explores important measures for the construction of big data experimental classes in undergraduate institutions. In terms of the teaching mode, knowledge graph based and interdisciplinary integrated teaching methods are adopted to enhance students’ practical ability and their capacity to comprehensively apply knowledge. Regarding the construction of the teaching staff, interdisciplinary teams are formed, enterprise mentors are introduced, and teachers’ training and further education are strengthened. For the practical platform, on campus experimental platforms are built, internship bases are jointly established with enterprises, and virtual laboratory projects are carried out to provide students with a rich practical environment. The optimization of the curriculum system includes setting up personalized elective courses and hierarchical practical courses. The assessment and evaluation methods adopt diversified indicators, focus on process-based evaluation, and introduce an enterprise evaluation mechanism. The aim is to comprehensively improve the teaching quality of big data experimental classes and students’ professional proficiency, cultivate high-quality big data professionals who meet industry demands, enhance the talent-output capacity and competitiveness of undergraduate institutions in the big data field, promote the innovative development of big data professional education, and provide valuable reference for the construction of related majors in universities.