This study employs a bibliometric approach to analyse common research themes, high-impact publications and research venues, identify the most recent transformative research, and map the developmental stages of data-driven learning (DDL) since its genesis. A dataset of 126 articles and 3,297 cited references (1994-2021) retrieved from the Web of…

The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…

A recent issue of the Australian Journal of Language and Literacy included an article reporting on a systematic narrative review of the research literature that indicated that there was insufficient evidence to conclude whether genre theory and systemic functional linguistics either 'worked' or 'did not work'. The criteria used to evaluate these…

Purpose: This article argues that the potential of the vast amount of research, published each year in the history of education, remains untapped. Given the rapidly growing number of academic publications in the field, there is a need for research that is based on articles, chapters and monographs already published. While analyses of existing…

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…

Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…

As Twitter's (or X's) influence permeates aspects of education, researchers must consider how to ethically and effectively leverage the unique types of data that this social media platform offers. This paper provides recommended methodological practice considerations for working with qualitative Twitter data toward the advancement of education…

Meta-analyses can be used to comprehensively summarize the state of a given literature base, understand development and relations between constructs, and synthesize intervention effects to identify "what works for whom," all of which can directly inform research, practice, and policy. In this tutorial, we first argue that data reporting…

Predictive analytics methods in education are seeing widespread use and are producing increasingly accurate predictions of students' outcomes. With the increased use of predictive analytics comes increasing concern about fairness for specific subgroups of the population. One approach that has been proposed to increase fairness is using demographic…

Background: For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require each document first be manually coded for constructs of interest by trained human raters. These hand-coded scores are then used as a measured outcome for an impact analysis, with the average scores of the treatment group…

Collected Biannually since 1968, the Civil Rights Data Collection (CRDC) represents the U.S. Department of Education's most substantial effort to understand data related to students' educational opportunities throughout K-12 schooling, particularly for historically marginalized student populations. Due to the COVID-19 pandemic, the Department…

Education research for practice is in need of textbook studies, especially those having well-defined theoretical framework. This paper is an attempt to apply phenomenography in textbook research. It begins with a review of four existing types of textbook studies found in the literature. Next, the main features of phenomenography (qualitative…

Learning analytics are increasingly used in medical education to analyze data and make decisions about learners' abilities. While there are many potential benefits of using learning analytics to drive improvement in medical education, there are also ethical concerns surrounding how this may affect learners and their patients. We conducted a…

In order to produce the most reliable syntheses of the effectiveness of educational interventions, systematic reviews need to adhere to rigorous methodological standards. This meta-review investigated risk of bias occurring while conducting a systematic review and the presence of open science practices like data sharing and reproducibility of the…

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data--both genetic and behavioral--that are collected as part of scientific studies or a part of treatment can provide a deeper,…