研究生数据素养评价量表构建及应用研究

发布时间：2018-01-20 01:12

本文关键词： 研究生数据素养评价标准评价量表胜任特征高校图书馆　出处：《江苏大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着数据密集型科研范式的兴起,数据作为一种重要的学术资源,对研究工作产生极大的价值,数据素养成为研究生学术发展的必备能力之一,已经引起国内外学者的高度重视。对研究生数据素养评价是开展针对性、有效性数据素养教育的前提基础,加强研究生数据素养教育关系到数字时代高层次人才数据利用和创新能力的培养,对于提升大数据时代高校研究生信息素养水平、优化科研方式以及深化图书馆服务具有重要意义。本研究借鉴国内外数据素养研究成果,在理清数据素养及其相关概念的基础上,以信息素养、数据生命周期、胜任特征模型理论为指导,综合使用文献调研、问卷调查、专家访谈、教育测量等方法,探析研究生数据素养评价量表的构建和应用。通过分析研究生数据素养能力需求及高校图书馆数据素养供给现状,归纳图书馆数据素养教育实践不足;围绕科研活动流程构建研究生数据素养胜任特征标准:包括数据意识、数据收集与评估、数据组织与管理、数据处理与分析、数据利用与归档及数据伦理等六个大类19项标准,依此标准编制了研究生数据素养评价量表,选取合适样本研究生进行试测和重测,结合专家意见对量表内容进行修改,最终量表包含48个题项,经检验量表具有较高的信度、效度、相关性和拟合度;应用评价量表在全国13所高校开展大规模测评,构建了研究生数据素养全国常模、地区常模、学科常模、年级常模等,以便考察研究生数据素养总体水平,揭示不同类别研究生的数据素养能力差异;同时,将样本数据分为绩优组和一般绩效组,提取出研究生数据素养基准性能力和鉴别性能力;结合上述研究结果,从高校院系、图书馆、个人层面提出相应的研究生数据素养教育优化策略,有利于高校拓展信息素养教育,提升研究生数据素养水平,提高人才培养质量。
[Abstract]:With the rise of data-intensive research paradigm, data, as an important academic resource, has great value to the research work. Data literacy has become one of the necessary abilities of graduate academic development. The evaluation of graduate students' data literacy is the prerequisite for the development of targeted and effective data literacy education. Strengthening the data literacy education of graduate students is related to the use of high-level talent data and the cultivation of innovative ability in the digital age, which will improve the level of information literacy of graduate students in big data era. It is of great significance to optimize scientific research methods and deepen library services. This study draws lessons from domestic and foreign data literacy research results, on the basis of sorting out data literacy and its related concepts, information literacy, data life cycle. Under the guidance of competency model theory, comprehensive use of literature research, questionnaires, expert interviews, educational measurement and other methods. Through analyzing the demand of graduate students' data literacy ability and the current situation of data literacy supply in university library, the author concludes that the practice of library data literacy education is insufficient; Construction of graduate data literacy competency standards around the process of scientific research activities: including data awareness, data collection and evaluation, data organization and management, data processing and analysis. Data utilization and archiving and data ethics and other six categories of 19 standards, according to this standard developed graduate data literacy evaluation scale, selected appropriate samples of graduate students to test and retest. The content of the scale was revised according to the expert opinion. The final scale contained 48 items, and the scale had higher reliability, validity, relevance and fit. In order to investigate the general level of postgraduates' data literacy, the national norm, regional norm, subject norm, grade norm and so on were constructed by using the evaluation scale in 13 colleges and universities in China. To reveal the difference of data literacy ability of different types of graduate students; At the same time, the sample data are divided into excellent performance group and general performance group, and extract the data literacy benchmark ability and discriminative ability of graduate students. Combined with the above research results, from the university departments, libraries, personal level to put forward the corresponding graduate data literacy education optimization strategy, which is conducive to the expansion of information literacy education in colleges and universities, improve the level of graduate data literacy. Improve the quality of personnel training.
【学位授予单位】：江苏大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G252.7

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