Conducting valid and reliable empirical research in the prevention sciences is an inherently difficult and challenging task. Chief among these is the need to obtain numerical scores of underlying theoretical constructs for use in subsequent analysis. This challenge is further exacerbated by the increasingly common need to consider multiple…

The Centre for Environmental Data Analysis (CEDA) is a provider of two major services to the environmental science community; JASMIN and the CEDA Archive. CEDA is frequently required to evidence the impact it has on researchers and wider society. However, this is challenging as there are currently no formal or standard processes for collecting…

Based on a statistical analysis, undergraduate business students are shown to prefer classification tree over six other standard data mining techniques. Data were collected over a 4-year period from students taking a data mining course offered at a business university in the US. The principal reason given by students for this preference is that…

Authentic participation involving jointly undertaken analysis of data and dissemination of findings is rarely evident in participatory research involving disabled people. This paper examines analysis and dissemination which offers greater participation, providing a theoretical underpinning for this approach. This conceptualization arises from…

In 2010, Nolan and Temple Lang proposed "integration of computing concepts into statistics curricula at all levels." The unprecedented growth in data and emphasis on data science has provided an impetus to finally realizing full implementations of this in new statistics and data science programs and courses. We discuss a proposal for the…

In this paper, we will describe an introduction to Data Science for secondary school students. We will report on the design and implementation of an introductory unit on "Data and data detectives with CODAP" in which secondary school students used the online tool CODAP to explore real and meaningful survey data on leisure time activities…

Teaching software engineering (SWE) as a core computer science course (ACM, 2013) is a challenging task. The challenge lies in the emphasis on what a large-scale software means, implementing teamwork, and teaching abstraction in software design while simultaneously engaging students into reasonable coding tasks. The abstraction of the system…

Much care has been paid to reflexivity, including considering emotional sensitivities?in relation to face-to-face interviews. However, less attention has been paid to the impact of sensitivities on the process of data?analysis and the presentation of research findings. This paper focuses on?what constitutes 'the data' to be analysed, who analyses…

Distance Learning has enabled educational practices based on digital platforms, generating massive amounts of data. Several initiatives use this data to identify dropout contexts, mainly providing teacher support about student behavior. Approaches such as Active Methodologies are known as having good potential to involve and motivate students.…

There is growing interest in how to better prepare K-12 students to work with data. In this article, we assert that these discussions of teaching and learning must attend to the human dimensions of data work. Specifically, we draw from several established lines of research to argue that practices involving the creation and manipulation of data are…

We present a case study to teach data visualization with Tableau in an introductory business analytics course. The case uses publicly available data sets from touringplans.com that record wait times for various attractions at Disney World in Orlando, Florida. In the case study, students use Tableau to clean, organize, and analyze wait time data,…

The use of multiple measures for the operationalization of subjective well-being (SWB) is highly recommended, as each approach brings exposure to different errors. To supplement the approaches proposed in the literature, the paper at hand outlines a complemental text mining technique -- sentiment detection -- which presents an efficient solution…

Cloud computing, internet of things (IoT), artificial intelligence, and big data are four very different technologies that are already discussed separately. The use of the four technologies is required to be more and more necessary in the present day in order to make them important components in today's world technology. In this paper, the authors…

Background: Within the context of the Special Interest Research Group (SIRG) on Persons with Profound Intellectual and Multiple Disabilities (PIMD), researchers often discuss the methodological problems and challenges they are confronted with. The aim of the current article was to give an overview of these challenges. Methods: The challenges are…

In this article we present and discuss the importance and relevance of the inclusion of spatial data analysis as part of the undergraduate statistics curriculum. Given its usefulness and applicability across a range of disciplines, spatial data are a topic that should receive more emphasis within undergraduate statistics curricula. There exist…