In today's era of large-scale data, academic institutions, businesses, and government agencies are increasingly faced with heterogeneous datasets. Consequently, there is a growing need to develop effective methods for extracting meaningful insights from this type of data. Quantile, expectile, and expected shortfall regression methods offer useful…

This systematic review presents the first synthesis of the scientific literature on estimating school and teacher/class effects on student academic performance using random-effects (RE) models with three or more levels. The review delves into the theoretical framework underpinning the estimation of educational effects, the associated statistical…

The purpose of this study is to review journal papers on educational big data research published from 2010 to 2018. A total of 143 papers were selected. The papers were characterized based on three dimensions: (a) educational goals; (b) educational problems addressed; and (c) big data analytical techniques used. A qualitative content analysis…

Big data is a unique field of study which requires specialized analytics. The field of education has a lot of data: individual student test scores, attendance, behavior, and demographic data are just some of the regularly collected information year after year. Individual student data across an entire state over several years quickly becomes big…

The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term "actionable insight" means. This selective literature review provides a look into…

How data are collected and how they are analyzed is typically described in the literature, but how the data are encoded is often not described in detail. In this paper, we discuss how data typically gathered in PER are encoded and how the choice of encoding plays a role in data analysis. We describe the kinds of data that are found when using…

The Education Insights Center produced a series of reports culminating in recommendations for the structure and governance of a preschool through higher education and into the workforce (known as a P20W data system). This brief follows up on that series, with a focus on data quality; the brief was informed by the author's experience using…

Big qualitative data (Big Qual), or research involving large qualitative data sets, has introduced many newly evolving conventions that have begun to change the fundamental nature of some qualitative research. In this methodological essay, we first distinguish big data from big qual. We define big qual as data sets containing either primary or…

This paper argues that learning analytics (LA) can make contributions to learning research, in addition to aiming for improvements in learning and teaching practices in a solely applied sense. Indeed, there is potential for transforming learning research if certain approaches developed in LA were used more extensively to study learning. The…

Thanks to extraordinary and exponential improvements in data storage and computing capacities, it is now possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago. As the world has developed this remarkable capacity to store and analyze data, so have the world's governments…

There is an urgent need to develop an evidence-based framework for learning analytics whereby stakeholders can manage, evaluate, and make decisions about which types of interventions work well and under which conditions. In this article, we will work towards developing a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is…

It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…

Learning technologies are now commonplace in education, and generate large volumes of educational data. Scholars have argued that analytics can and should be employed to optimize learning and learning environments. This article explores what is really meant by "analytics", describes the current best-known examples of institutional…

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…

This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field and identify some of the trends in recent research. As the field continues to expand, there seem to be at least three directions of vigorous growth: (1) the inclusion of multimodal data (gesture,…