A Novel Approach to Identify the Comprehensive Quality of PhD Dissertations
Peng Xiaoju,Qu Jiansheng
( Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China)
(Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041, China)
(Library of University of Chinese Academy of Sciences, Beijing 100049, China)
(Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)
[Objective]We proposed a novel approach to identify the comprehensive quality grade of PhD Dissertations. [Methods]Based on evaluation scores, we applied data envelopment analysis (DEA) which calculates the quality distance from the best practices according to both the performances of the individual sample and the group. The grading results by DEA is compared with the conventional grading method using the value of total-score. [Results] The advantages and effectiveness of the two methods were discussed and proved by using the dissertations at the margin or awarded ones as test indicators. Compare to total marks, DEA could identify the diversity of dissertations of high quality other than making judgments only according to the weighted total score. [Limitations]The DEA grading method could only base on reliable, valid and rigorous examining system to rank dissertations according to their comprehensive quality. The qualification line must be determined by academic experts who are assigned to evaluate the dissertation quality. [Conclusions] DEA is a rapid method on identifying PhD dissertation quality more precisely and more sensitively than the conventional method. Referencing DEA results could improve the efficiency and the effectiveness during the inspection; thus, it has great potential application in monitoring and directing PhD education in real scenario.
彭笑菊, 曲建升.
博士学位论文综合质量等级识别方法及有效性验证
[J]. 数据分析与知识发现, 10.11925/infotech.2096-3467.2022.1154.
Peng Xiaoju, Qu Jiansheng.
A Novel Approach to Identify the Comprehensive Quality of PhD Dissertations
. Data Analysis and Knowledge Discovery, 0, (): 1-.