Purpose: The aim of this study was to map the use of implementation science frameworks, models, and theories in intervention research targeting learning needs in the classroom. Method: A scoping review was conducted. Electronic database and manual searches were conducted. Two reviewers independently completed screening, data extraction, and…

This study examines the current research on educational data mining, educational learning support services, personalized learning services, and personalized learning paths in education. The authors aim to integrate personalized learning concepts into traditional support services by drawing on the latest theoretical and practical research. Using…

The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…

Group design research studies can provide evidence to draw conclusions about "what works," "for whom," and "under what conditions" in special education. The quality indicators introduced by Gersten and colleagues (2005) have contributed to increased rigor in group design research, which has provided substantial…

The implementation of analytics in support of student success requires effective use of feedback and interventions, as well as a system by which the use of feedback and institutional supports can be tracked and evaluated.

More aggregate data on school performance is available than ever before, opening up new possibilities for applied researchers interested in assessing the effectiveness of school-level interventions quickly and at a relatively low cost by implementing comparative interrupted times series (CITS) designs. We examine the extent to which effect…

This paper examines the origins and influences of the introduction of longitudinal student data-sets as a way of gaining insight into the operation of American schools and as a tool for policy-makers. The paper argues that the creation of this new form of data in the 1960s and 1970s represented a relatively new way of thinking about American…

Learning design has traditionally been thought of as an activity occurring prior to the presentation of a learning experience or a description of that activity. With the advent of near real-time data and new opportunities of representing the decisions and actions of learners in digital learning environments, learning designers can now apply…

To identify the ways teachers and educational systems can improve learning, researchers need to make causal inferences. Analyses of existing datasets play an important role in detecting causal patterns, but conducting experiments also plays an indispensable role in this research. In this article, we advocate for experiments to be embedded in real…

The article deals with the interplay between learning analytics and massive open online courses (MOOCs) and provides a conceptual framework to situate ongoing research in the MOOC and learning analytics innovation cycle (MOLAC framework). The MOLAC framework is organized on three levels: On the micro-level, the data collection and analytics…

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…

While learning analytics (LA) practices have been shown to be practical and effective, most of them require a huge amount of data and effort. This paper reports a case study which demonstrates the feasibility of practising LA at a low cost for instructors to identify at-risk students in an undergraduate business quantitative methods course.…

Estimating the efficacy of different instructional modalities, techniques, and interventions is challenging because teaching style covaries with instructor, and the typical student only takes a course once. We introduce the individualized treatment effect (ITE) from analyses of personalized medicine as a means to quantify individual student…

Suppose an education researcher wants to test the impact of a high school drop-out prevention intervention in which at-risk students attend classes to receive intensive summer school instruction. The district will allow the researcher to randomly assign students to the treatment classes or to the control group. Half of the students (the treatment…