Students often struggle with the relationship between mathematical graphs and the data they represent. To truly understand types of evolutionary selection, students need to be proficient with several different skills in math, science, and literacy contexts. With math, students must be able to identify variables, design appropriate graphs based on…

Collapsing categories is a commonly used data reduction technique; however, to date there do not exist principled methods to determine whether collapsing categories is appropriate in practice. With ordinal responses under the partial credit model, when collapsing categories, the true model for the collapsed data is no longer a partial credit…

Background: Data representing people's behaviour, attitudes, feelings and relationships are increasingly being harvested from social media platforms and re-used for research purposes. This can be ethically problematic, even where such data exist in the public domain. We set out to explore how the academic community is addressing these challenges…

Like other parts of the social system, education is becoming an information-driven venture: data technologies pervade all levels of the system. This datafication of education seems to take place alongside a general turn to learning that Gert Biesta has called learnification: a progressively singular focus on the manipulable features of individual…

The definition of visualization in engineering graphics has evolved over the years due in part to extensive research in visualization by the engineering design graphics profession. The literature indicates research in the areas of engineering graphics and the use of visualization has grown from improvement of visualization skills and the…

During the 2014-2015 school year, a mixed-methods study was conducted in a Midwestern urban school district with twenty-five school social workers to assess professional practice utilizing an electronic data system. Given the emphasis in the literature on mandates for school social workers to be actively engaged in positive behavior support and…

An important aspect of qualitative research is reaching saturation--loosely, a point at which observing more data will not lead to discovery of more information related to the research questions. However, there has been no validated means of objectively establishing saturation. This article proposes a novel quantitative approach to measuring…

Physical literacy is developing as a contested concept with definitional blurring across international contexts, confusing both practitioners and researchers. This paper serves the dual purpose of reporting on an interrogation of concepts associated with physical literacy in academic writing and exploring the use of a text mining data analysis…

The National Study of Protest Events (NSPE) employed hypernetwork sampling to generate the first-ever nationally representative sample of protest events. Nearly complete information about various event characteristics was collected from participants in 1,037 unique protests across the United States in 2010 to 2011. The first part of this article…

This study presents a model for the early identification of students who are likely to fail in an academic course. To enhance predictive accuracy, sentiment analysis is used to identify affective information from text-based self-evaluated comments written by students. Experimental results demonstrated that adding extracted sentiment information…

Challenging and confronting educational systems and structures, the vast majority of which come from a place of privilege, is uncomfortable but necessary. Education, from early childhood to post-secondary, should challenge and address the racial inequities that inevitably characterize such systems and structures. Yet, we do not always do this…

Cognitive diagnosis models (CDMs) allow for the extraction of fine-grained, multidimensional diagnostic information from appropriately designed tests. In recent years, interest in such models has grown as formative assessment grows in popularity. Many dichotomous as well as several polytomous CDMs have been proposed in the last two decades, but…

Big data analytics are prevalent in fields like business, engineering, public health, and the physical sciences, but social scientists are slower than their peers in other fields in adopting this new methodology. One major reason for this is that traditional statistical procedures are typically not suitable for the analysis of large and complex…

A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless "all" potential confounding factors are included in an analysis (which is unlikely to be…

There are numerous literature including professional guides that describes how to collect qualitative data, specifically in information systems (IS) studies. In practice, the reality is different from the theoretical academic materials. This is the part where many early career researchers and postgraduate students continue to be challenged,…