Response-to-intervention (RtI) is a multi-tiered framework designed to prevent academic difficulties by facilitating robust, research-based instruction and providing targeted or individualized short-term interventions for students at-risk per periodic screening and progress monitoring data. The cornerstone of RtI is data-based decision-making to…

Transforming spoken words into written text in qualitative research is a vital step in familiarizing and immersing oneself in the data. We share a three-step approach of how data transcription facilitated an interpretative act of analysis in a study using qualitative data collection methods on the barriers and facilitators of HIV testing and…

Background: Britain is rich in longitudinal population cohort studies that posit valuable data resources for social science. However, education researchers currently underutilize these resources. Aims: The current paper (1) outlines the power and benefits of secondary data analyses for educational science and (2) provides a practical guide for…

Preregistration and registered reports are two promising open science practices for increasing transparency in the scientific process. In particular, they create transparency around one of the most consequential distinctions in research design: the data analytics decisions made before data collection and post-hoc decisions made afterwards.…

Writing and communication researchers are in the early stages of developing procedures for reusing and maximizing the analytical potentials of qualitative data. Contributing to this effort, we critically reflect on our methodological decision-making process in developing innovative procedures for cross-analyzing two distinct studies. Our…

The past 20 years have seen the steady 'datafication' of school systems -- i.e. the rendering of key aspects of school practice into data that is digitally collected, processed and circulated. In contrast to assumptions of 'data-driven' schools as sites of more efficient and automated forms of data work, this paper examines the extensive human…

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…

The COVID-19 pandemic has been one of the greatest challenges faced for a very long time. However, it has also presented educators with novel opportunities for teaching, none more so than in science. There are the obvious links between COVID-19 and the body of scientific knowledge that curriculum designers think educators should help students to…

With various digital technologies increasingly integrated into higher education, understanding how students engage with such technologies has become vital. There are different ways to measure student engagement; however, self-reported measures such as questionnaires are predominantly used to understand student engagement. In contrast, this study…

Historically, there has been concern about students losing reading ability over extended breaks from school, commonly in the summer, but studies of this phenomenon have produced inconsistent results. We applied exploratory visual analysis of multiple datasets to examine whether students in Grades K-5 appear to lose or improve in various reading…

We are interested in how codified knowledge is produced around the globe (which inputs are used to produce scientific articles and patented inventions) and the efficiency of the process (how do the best performers produce more with the same inputs or produce the same with less inputs). Using a Data Envelopment Analysis (DEA) efficiency frontier…

Research on the use of modeling and mapping tools in curriculum management is thriving, often focusing on the perspectives of the faculty alone. However, scholarly works that also incorporate the students' curriculum concerns are rare. A recurring theme in students' curriculum concerns is the perceived overlap among courses, usually expressed at…

Qualitative data analysis has been criticised for a lack of credibility over recent years when vagueness has been afforded to the reporting of how findings are attained. In response, there has been a growing body of literature emphasising a need to detail methods of qualitative data analysis. This paper adds to this body of knowledge by presenting…

The contemporary Human activity utilizes huge volumes of digital data to solve efficiently multiple socio-economic, scientific and technical problems. Now the big data analysis is mainly oriented to the socioeconomic sphere with a goal to lift the profit. The science and technology to penetrate deeper in the nature of objects and systems under…

We provide a computational exercise suitable for early introduction in an undergraduate statistics or data science course that allows students to "play the whole game" of data science: performing both data collection and data analysis. While many teaching resources exist for data analysis, such resources are not as abundant for data…