Data mining in education predictions are made about other groups based on the big data of education. However, the extent to which training data can be accessed is relative. A group that can be described as missing data is children living or working on the street. For this reason this study aimed to deal with children working or living on the…

This paper dwells on the metaphor of "shadow organising" for exploring what happens in the space of the 'not-yet data'. It wonders what we do to 'data' and what 'data' do to us, to our subjectivities as professionals. It deals with elusive knowledges and how professionals construct what counts as 'data' and what is discarded as…

The use of data in schools may contribute to reducing educational and social inequalities. This article seeks to examine the use of data in school intervention programs implemented within vulnerable schools in Chile and the transfer and use of this data by schools. Utilizing an exploratory descriptive multiple case study design. Results indicate…

Meta-analyzing count data can be challenging when follow-up time varies across studies. Simply pooling aggregate data over time-periods would result in biased estimates, which may erroneously inform clinical decision-making. In this study, we exploit the convolution property of the Poisson distribution to develop a likelihood for observed…

Hanns Scharff, an interrogator during the Second World War, was known for his remarkable effectiveness at collecting intelligence from prisoners of war using a friendly, conversational approach in which he led the prisoners to unknowingly reveal the information he wanted. In the last decade, psychologists have produced a body of experimental…

There is a current discussion in universities regarding the need for dedicated research data stewards. This article presents a set of fictional personas for research data support based on experience and requests by experts in different areas of data management. Using a modified Delphi study, 24 participants from different stakeholder groups have…

In this paper, we propose that informal aspects of data science could be introduced in primary school. The International Data Science in Schools Project (IDSSP) framework for data science curriculum provides a guide for a data science curriculum aimed at upper secondary level. We analyzed synergies between the IDSSP framework and the current…

Data-driven decision-making (DDDM) has been playing an increasing role in contemporary teaching, since it includes systematic collection, analysis, and application of data to improve students' educational performance. However, little is known about the affective factors that influence this data-based practice. Thus, the purpose of this study was…

Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many scholars still fail to address this vital issue. In this article, we present a simple-to-use method for generating multiple imputations (MIs) using a Gaussian copula. The…

A gap exists between the ability to gauge the success of institutions by deploying a relatively simple set of measures typically based upon the federal cohort, versus the ability to monitor the successful (or unsuccessful) progression of the varied students who move through them. Daniel Regan questions which matters more. To gauge the health of an…

We have updated a version of the coordination geometry table of the d-block elements and their ions that Moore and co-workers presented in 1997. This table is constructed by searching and analyzing the data in the Cambridge Structural Database. In this updated version, we have also analyzed impact of ligands on the coordination geometry and…

There is increasing pressure from funders, publishers, the public and other research organizations on researchers to improve their research data management. The main objective of the study was to examine the practices of research data management at higher education institutions in Ethiopia. The study was employed multi-stage sampling technique to…

The use of text mining tools can help librarians improve the precision of searches, increase search sensitivity, and translate search strategies across multiple research databases. When combined with the intuitive approaches that librarians commonly use, text mining tools help reduce biases by improving the objectivity, transparency, and…

Over the past few years, art educators (Cooper et al., 2018; Grodoski, 2018; Taylor, 2017) have begun to embrace data visualization for curricular purposes. In this article, the authors make a case for the inclusion of data visualizations in K-12 art curricula and illustrate a curriculum that focused on introductory data visualization concepts and…

Respondent-driven sampling (RDS) is a methodology for sampling and analysing survey data from rare and elusive populations that has gained increasing attention in migration research in recent years. Since its introduction in 1997, it has been applied in numerous surveys in the field of epidemiology (mainly for the estimation of HIV/AIDS prevalence…