《机器学习与数据挖掘》课程的模糊综合评价法改革

Curriculum Reform of “Machine Learning and Data Mining” with Fuzzy Comprehensive Evaluation

摘要: 课程是学校教育的核心，在高等教育中，它是根本支柱，与教育理念和人才培养战略紧密相连，旨在促进学生全面发展，且需契合社会需求、影响社会发展。2020年疫情爆发，传统线下教学受冲击，线上学习模式兴起，钉钉等平台使远程学习成为可能，许多学校因此重新审视和改革课程，以适应新模式和未来社会需求。本文以重庆理工大学“机器学习与数据挖掘”课程为例，通过研读文献、咨询专家，采用专家调查法和问卷调查法建立指标体系，运用层次分析法(AHP)和熵值法融合主客观权重，使权重确定更科学，得出教育领域主观注重自身效果、客观注重实现教育目标、综合倾向解决疑难问题提升学习效果的结论。

Abstract: Curriculum is the core of school education. In higher education, it is the fundamental pillar, closely linked to educational concepts and talent cultivation strategies. It aims to promote the all-round development of students and needs to be in line with social needs and influence social development. In 2020, with the outbreak of the COVID-19 pandemic, the traditional offline teaching model was impacted, and the online learning model emerged. Online learning platforms such as DingTalk made remote learning possible. As a result, many schools began to re-examine and reform their curricula to adapt to the new model and the needs of future society. This article takes the “Machine Learning and Data Mining” course offered by Chongqing University of Technology as an example. Through studying a large number of literatures and consulting industry experts, it uses the expert investigation method and the questionnaire survey method to establish an index system, and uses the Analytic Hierarchy Process (AHP) and the entropy method to fuse subjective and objective weights, making the determination of weights more scientific. It draws the conclusion that in the field of education, subjectively, more attention is paid to the enhancement of one’s own effectiveness; objectively, more attention is paid to the better realization of educational goals, and comprehensively, there is a tendency to solve difficult problems to improve one’s own learning effect.