基于AHP-FCE的深度学习能力评价模型的构建研究

Research on the Construction of Deep Learning Ability Evaluation Model Based on Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation

摘要: 深度学习能力的评价是典型的多指标复杂型综合性评价，主要表现在四个维度：认知维度、思维维度、技能维度、情感维度。层次分析法(AHP)可以人为控制某些指标的权重，对定性指标进行量化处理，使主观判断变为客观描述；模糊综合评价法(FCE)可以将定性评价转化为定量评价，对受到多种因素制约的深度学习能力进行总体评价，能够较好地解决模糊、难以量化的问题。本研究将采用层次分析法确定深度学习能力的评价因素权重，利用模糊综合评价法建立评价模型，量化出深度学习能力评价的等级，最终进行指标体系构建和评价研究。

Abstract: The evaluation of deep learning ability is a typical multi-index and complex comprehensive evaluation. It is mainly manifested in the following four dimensions: cognitive dimension, dimension of thinking, skill dimension, emotional dimension. Analytic hierarchy process can artificially control the weight of some indicators, quantify qualitative indicators, and make subjective judgment into objective description. The fuzzy comprehensive evaluation method can transform the qualitative evaluation into the quantitative evaluation, and make the overall evaluation of the deep learning ability restricted by many factors, which can better solve the problems of fuzzy and difficult to quantify. In this study, Analytic hierarchy process will be used to determine the evaluation factor weight of deep learning ability, and fuzzy comprehensive evaluation method will be used to establish the evaluation model, quantify the level of deep learning ability evaluation, and finally conduct the index system construction and evaluation research.