Where do you come from,where do you go? Assessing skills gaps and labour market outcomes for young adults with different immigration backgrounds

Using PISA and PIAAC data from twelve OECD countries, we examine the gap in cognitive skills among immigrants and natives and evaluate how those differences have evolved over time. We also consider how demographics, family background and school quality explain the development of cognitive skills of young people with immigrant backgrounds. The results show, first, that some convergence in skills occurs between second-generation immigrants and natives over time. Second, demographics, family background and school quality variables all contribute to the achievement gaps across different groups.     

图书馆情报学主要研究方法:了解、选择及使用

[目的/意义]研究方法在学术研究中发挥着至关重要的作用。确认图书馆情报学领域主要的研究方法，并对它们进行了解熟悉，以在开展研究时能合理选择、灵活使用，确保研究质量。[方法/过程]对近2 000篇图书馆情报学领域的研究文献以及相关研究方法论文进行内容分析，在此基础上对研究方法的类分命名、图书馆情报学界主要的研究方法的确定、特点和使用注意事项进行介绍和讨论。[结果/结论]研究方法应以数据收集法而不是数据分析法命名。图书馆情报学领域常用的研究方法包括实验法、问卷法、理论研讨法、内容分析法、访谈法和书目计量法，每种方法都有各自的特点。因而在选择使用时，既应根据具体研究课题及研究方法之特性，也要考虑使用注意事项，并尽量在同一研究中采用两种或更多的方法，以扬长避短，更有效地展开研究。     

科学数据共享研究现状与展望

[目的/意义] 分析科学数据共享的研究现状及其发展趋势，为促进国内相关理论研究与实践进展提供参考。[方法/过程] 通过对国内外文献进行梳理和归纳，提炼出与科学数据共享研究相关的三大类主题：科学数据共享发展需求、科学数据管理共享模式与机制和科学数据服务共享度与服务效果，并构建科学数据共享管理分析框架，该框架体现上述三类主题之间的因果关联，强调科学数据共享管理与服务的合理面、重要度、关键性。[结果/结论] 国内外现有研究尚存不足，未来研究在加强实证研究、着眼管理机制完善的同时，还需注重共享服务模式的创新。     

Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws

In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published.     

Data Visualization as Participatory Research: A Model for Digital Collections to Inspire User-Driven Research

The emerging creative practices of digital collections are increasing in prominence thanks to the access to, and appeal of, data visualizations. Interactive data visualizations, such as a map, timeline, chart, graph, or artist’s rendering of data, enable users to pursue their own research interests within a collection and participate in new areas of research. Use of these data visualizations enhances the scope of the collection and enables a modern and diverse thematic collection to emerge. This article considers the question: Does the addition of data visualizations affect how users participate with a research collection? Impacts on collection development, application of user-centered design, and analysis of users’ exploratory strategies are discussed. Examples of data visualizations used in digital humanities projects and digital collections are presented as case studies.     

Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

大数据时代个人信息保护研究综述

[目的/意义]通过梳理大数据时代个人信息保护的研究文献，为未来研究个人信息保护提供借鉴。[方法/过程]利用CNKI数据库，系统收集关于大数据时代个人信息保护的国内核心期刊论文，对文献的内容进行分析，归纳研究主题，并进行论述。[结果/结论]将现有的研究成果按主题分为5类：国内外实践经验研究、基本理论问题研究、个人信息保护机制探索、个人信息安全风险与应对、相关法律法规研究，评述现有研究的不足之处并对未来的研究方向提出展望。     

高校扩招后体育教学质量下降的原因分析及对策

运用综合研究方法，对扩大招生后广西10所高校体育教学情况进行了问卷调查，并对调查结果进行相关分析。发现影响体育教学质量的主要因素为运动场地、设施；师资力量；生源质量；教学管理水平。提出：加大体育经费投入，改善运动场地、设施；加强体育师资的建设与管理；因材施教，实施学分制；提高体育教学的管理水平。制定科学的教学质量评估体系，是稳定和提高体育教学质量的重要举措。     

阿克洛夫模型与图书馆馆员素质建设

为适应信息社会的需要，馆员素质建设不容忽视。章以图书馆馆员素质之间的差异为前提，通过应用阿克洛夫模型对图书馆人员素质低下及人才流失的现象进行分析，提出加强馆员素质建设的方法。     

普通高校体育课编班教学改革实验研究

体育课教学是高等学校体育工作的核心。教学质量的好坏直接影响学生的体质。但是 ,现行的班级体育授课制仍然是沿袭以智力、高考分数为核心 ,方便文化课教学的编班制进行体育课教学 ,这无疑影响学生体质的发展和终身体育思想的形成 ,而且给体育课教学带来许多困难。因此 ,从发展学生体质和培养终身锻炼习惯的实际需要出发 ,打破单纯按智力、分数的分班制是当前高校体育教学工作中亟待解决的问题。