基于数据生命周期的高校研究生数据素养评价研究

Data Literacy Evaluation of University Graduate Students Based on Data Life CycleLife Cycle

【目的/意义】大数据背景下,数据密集型科研时代已经来临,对高校研究生数据素养的评价能够帮助了解现状,推动数据素养教育的完善和优化。【方法/过程】本研究在相关研究的基础上,构建基于数据生命周期的高校研究生数据素养评价指标体系,包括4个一级指标和18个二级指标。通过问卷调查收集数据,利用BP神经网络对评价指标体系进行验证。【结果/结论】数据分析结果表明,所构建的评价指标体系具有一定的实用性,并能够对大数据背景下的高校研究生数据素养教育提供借鉴和参考。【创新/局限】本研究的局限性主要有两个方面,一是样本的选择以硕士研究生为主,导致评价结果的代表性有限;二是评价方法较为单一,没有对不同评价方法进行对比。

【Purpose/significance】In the context of big data,the era of data-intensive research has arrived.The evaluation of data literacy of university graduate students can help understand the current situation and promote the improvement and optimization of data literacy education.【Method/process】Based on related researches,this study constructs a data literacy evaluation index system for university graduate students based on data life cycle,including 4 primary indicators and 18 secondary indicators.The data are collected through questionnaires and the evaluation index system is validated by using BP neural network.【Result/conclusion】The results of data analysis show that the constructed evaluation index system has certain practicality and can provide reference to the data literacy education of university graduate students in the context of big data.【Innovation/limitation】The limitations of this study are mainly in two aspects.First,the sample was selected mainly from masters,which led to the limited representativeness of the evaluation results.Second,the evaluation method is single,and there is no comparison of different evaluation methods.