文章摘要
工学门类学术硕士学位论文质量的学科差异——以2014年全国硕士论文抽检数据为例
Quality Differences of Master Theses among Different Engineering Disciplines——Based on Data from National Sampling on Master Theses, 2014
投稿时间:2016-12-18  
DOI:
中文关键词: 工学门类;硕士学位论文质量;学科差异;论文抽检
英文关键词: engineering category;master thesis quality;quality differences among disciplines;paper sampling
基金项目:国务院教育督导委员会办公室委托课题"全国硕士学位论文质量发展报告(2014年)";中国博士后科学基金第59批面上资助项目(2016M590005);中国学位与研究生教育学会2015年度重点课题"三位一体"研究生学位论文质量监测与评价体系研究(2015Y0407)
作者单位
高耀 北京大学 教育学院, 北京 100871 
陈洪捷 北京大学 教育学院, 北京 100871 
沈文钦 北京大学 教育学院, 北京 100871 
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中文摘要:
      基于2014年全国5415篇工学门类学术硕士学位论文抽检结果对工学门类学位论文质量的学科差异进行量化研究,结果显示:总体质量方面,工学门类抽检论文的整体合格率为99.02%,比同年度全部学术硕士学位论文抽检的平均合格率高出0.78个百分点,工学门类下各一级学科的总体得分均值为82.50分,高出同年度全部抽检总体样本得分均值1.48分。分项质量方面,工学门类分项得分由高到低分别为选题与综述、科研能力与基础知识、论文规范性、创新性及论文价值,且不同一级学科在各个二级指标维度上的表现存在差异性。本研究中所识别出的工学门类一级学科质量差异状况,可为学位授予单位、学科点和导师开展诊断性评估、质量提升计划及预警和监测工作提供参考依据。
英文摘要:
      Based on the outcomes of a sampling on 5,415 engineering master theses nationwide 2014, the author has carried out a quantitative study on the quality of the theses divided into different disciplines. The results show that the overall qualified rate of all the engineering theses sampled is 99.02 percent, 0.78 percentage point higher than that of all the master theses sampled the same year in China, and that the overall mean score of the theses from the first-class disciplines under engineering category is 82.50 points, 1.48 points higher than that of all the theses sampled the same year in China. The score of engineering theses being broken down in items is ranked, from high to low, in the sequence of topic selection, general description, research ability, mastery of basic knowledge, standardability and innovation in paper writing and the paper value. In different first-class disciplines, the score of the theses, disclosed by the secondary indicator dimensions, shows differences. The identified disciplines quality differences under the engineering category of this study may provide a reference for degree-granting institutions, disciplines institutions and supervisors to carry out diagnostic assessments, quality improvement programs and early warning and monitoring jobs.
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