互联网驱使下计算机基础课程教改质量评估

Quality evaluation of computer basic course teaching reform driven by internet

传统评估方法忽略了对计算机基础课程的教改质量特征进行量化决策,导致评估效果不理想,难以达到提高计算机基础课程教改质量的目标,由此提出一种基于分段统计平均分析和模糊预测的互联网驱使下计算机基础课程教改质量评估方法.构建互联网驱使下计算机基础课程教改质量指数大数据模型,采用教改质量量化特征分析方法进行量化决策,构建计算机基础课程教改质量评估的模糊决策函数,结合教改质量评估数据的关联规则性进行分段融合和自相关匹配检测,对检测的计算机基础课程教改质量评估数据进行模糊聚类处理,实现对教改质量评估数据的特征提取,根据特征提取结果进行最大熵分析,实现计算机基础课程教改质量评估优化.仿真结果表明,采用该方法进行互联网驱使下计算机基础课程教改质量评估的决策准确性较好,课程教改质量评估的可靠性较强,置信度较高.

Traditional evaluation methods neglect the quantitative decision-making on the quality characteristics of computer basic courses,resulting in unsatisfactory evaluation effect and difficulty in achieving the goal of improving the quality of computer basic courses.Therefore,a method of computer basic courses teaching reform quality evaluation based on piecewise statistical average analysis and fuzzy prediction driven by the internet is proposed.The quality index big data model of computer basic course teaching reform is constructed,and the quantitative decision of teaching reform quality is made by using the quantitative characteristic analysis method of teaching reform quality.The fuzzy decision function of the quality evaluation of computer basic course teaching reform is constructed.Combining with the association rule of the quality evaluation data of computer basic course teaching reform,the segmentation fusion and auto-correlation matching detection are carried out.The quality evaluation data of computer basic course teaching reform are processed by fuzzy clustering,and the feature extraction of the quality evaluation data is realized,and the maximum entropy analysis is carried out according to the feature extraction result,to optimize the quality evaluation of computer basic course teaching reform.The simulation results show that this method is more accurate,reliable and degree of confidence in the evaluation of the quality of computer basic course teaching reform driven by the internet.