Some in our discipline have recently voiced the opinion that political science is a data science. What follows from this argument is that we as instructors are training the next generation of data scientists, especially professionals and researchers who will work with big data. This paper explores the implications for political science education,…

Biomedical data science education faces the challenge of preparing students for conducting rigorous research with increasingly complex and large datasets. At the same time, philosophers of science face the challenge of making their expertise accessible for scientists in such a way that it can improve everyday research practice. Here, we…

Purpose: This paper aims to consider ways to visually model data generated by qualitative case studies, pointing out a need for visualizations that depict both synchronic relations across representations and how those relations change diachronically. To develop an appropriate modeling approach, the paper critically examines Max Boisot's I-Space…

Umbrella reviews (reviews of systematic reviews) are increasingly used to synthesize findings from systematic reviews. One important challenge when pooling data from several systematic reviews is publication overlap, that is, the same primary publications being included in multiple reviews. Pieper et al. have proposed using the corrected covered…

The purpose of this paper is to analyze the use of the exemplar methodology (ExM) as a method for selecting exemplars in education research. ExM is a systematic approach to selecting outliers that can be used to education researchers who investigate outliers to better understand phenomena among students, teachers, schools, and communities. While…

School attendance/absenteeism (SA/A) is a crucial indicator of health and development in youth but educational policies and health-based practices in this area rely heavily on a simple metric of physical presence or absence in a school setting. SA/A data suffer from problems of quality (reliability, construct validity, data integrity) and utility…

The purpose of this paper is to analyze various dimensions for measurement of human behavior. Human behaviour is complex. Behaviors, emotions, cognitions, and attitudes can rarely be described in terms of one or two variables. It is multimodal in nature. Furthermore, the traits, modalities and dimensions cannot be measured directly, but must be…

Mission-driven nonprofit organizations sometimes struggle within a cycle of disempowerment resulting from oversaturation of data collection that is reactive to funder demands. In this article, we problematize Community Music School (CMS) data-collection and analysis efforts and discuss alternate approaches to learning about family and community…

This article draws on a new materialist paradigm to explore bricolaging data from an early childhood research project through an immanent ethical lens. This lens enables the researcher to stretch towards non-hierarchical relationships in between subjects and objects, thinking and doing. A bricoleur explores and builds different…

The global scale of COVID-19 has constrained academics from conducting much person-facing research. Reactively, trend is increasing for digital-based methodologies capturing already existing online data. Scholars often 'scrape' user-postings from internet forums using coding algorithms and text capture tools, before analysing data, drawing…

The article focuses on infrastructures as heterogeneous assemblages. Our claim is that to examine something as elusive as data infrastructure calls for an epistemological and methodological approach consistent with the fluid ontology of the object of study. Moreover, we assert that there is no position of exteriority from which to critique data…

Purpose: Reflexivity involves critical reflection by the qualitative researcher as to the influence of the researcher's culture, history and belief on the conduct and outcome of the research. It is often seen as a practice exercised in the analysis of results in order to attempt to objectify the research. The purpose of this paper is to argue that…

Qualitative comparative analysis (QCA) is an empirical research method that has gained some popularity in the social sciences. At the same time, the literature has long been convinced that QCA is prone to committing causal fallacies when confronted with non-causal data. More specifically, beyond a certain case-to-factor ratio, the method is…

This paper argues for three aspects of tolerance with respect to QCA research: tolerance with respect to different approaches to QCA; producing QCA research with tolerance (work that is resistant to criticism); and for QCA researchers to be clear about the tolerance of the solutions they present -- especially in terms of calibration and truth…

This brief explores data science methods that workforce programs can use to predict participant success. With access to vast amounts of data on their programs, workforce training providers can leverage their management information systems (MIS) to understand and improve their programs' outcomes. By predicting which participants are at greater risk…