基于综合加权融合算法的学习评价方法及其证实  

A Comprehensive Weighting and Integration Algorithm Based Learning Evaluation and Its Verification

作　　者：唐立 李亚平[2,3] 吴新胜 王媛媛 TANG Li;LI Ya-ping;WU Xin-sheng;WANG Yuan-yuan(Department of Information Engineering,Anhui Institute of Economics and Management,Hefei 230031,China;Academic Affairs Office,Anhui Institute of Economics and Management,Hefei 230031,China;School of Management,Hefei University of Technology,Hefei 230009,China)

机构地区：[1]安徽经济管理学院信息工程系,合肥230031 [2]安徽经济管理学院教务处,合肥230031 [3]合肥工业大学管理学院,合肥230009

出　　处：《辽东学院学报（自然科学版）》2020年第4期290-295,共6页Journal of Eastern Liaoning University:Natural Science Edition

基　　金：安徽省高校自然科学研究重点项目(KJ2019A0965);安徽高校继续教育教学改革项目(2018jxjygg008);安徽省教育厅教学研究项目(2019jyxm0910);安徽省高水平教学团队项目(2018jxtd044)。

摘　　要：为解决单一学数据的学习评价信息缺失问题,提出多源教学数据融合的学习评价,用以探析数据融合技术在教学中的应用价值。先用Spearman计算不同数据源之间的相关性,算出不同数据源的关系权重和寻优权重,然后综合加权进行融合计算。通过综合加权融合对学生的综合学习评价进行融合计算,不仅可以平衡学生在不同教学方式下的学习评价的差异,融合不同学习方式之间的优缺点。通过实验验证综合加权的数据融合算法是效的,可以为更全面的学习评价提供帮助,为适应自身学习提供依据。In order to solve the problem of lack of learning evaluation information of single learning data,a learning evaluation with multi-source teaching data fusion was proposed.The correlation among different data sources was analyzed with Spearman and the relationship weight and optimization weight of each data source was calculated,by which the fusion calculation was done with comprehensive weighting.By such a way,the differences of students’learning evaluation with different teaching methods can be balanced and the advantages and disadvantages of various learning styles can be fused.The results show that this method is effective,which is helpful for comprehensive learning evaluation and provides a basis for adaptive learning.

关 键 词：数据融合 综合加权 Spearman 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] G434[自动化与计算机技术—计算机科学与技术]