Academic resilience captures academic success despite adversity and thus is an important concept for promoting equity within education. However, our understanding of how and why rates of academic resilience differ between contexts is currently limited by variation in the ways that the construct has been operationalised in quantitative research.…

Schools are frequently seen as the hubs of the community, providing resources and a gathering place for members of the community. The process of surveying the community in order to identify unique needs within the community, and then intentionally forging partnerships capable of ameliorating the specific needs, are strategies used by community…

Intelligent tutoring systems (ITSs) teach skills using learning-by-doing principles and provide learners with individualized feedback and materials adapted to their level of understanding. Given a learner's history of past interactions with an ITS, a learner performance model estimates the current state of a learner's knowledge and predicts her…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…

Learning Dashboards display analytics pertaining to student performance and attainment, often alongside scores for the class cohort average. Little research has considered the effects of this social comparison information on students' well-being, motivation, and engagement. The current study presented participants with hypothetical data that…

Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…

The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…

Federal law requires states and school districts to institute accountability systems that report disaggregated student data to ensure that all children make academic progress. However, one of the mandated categories for disaggregation -- English Learner (EL) -- is reported as a single group despite representing students who are beginning,…

The 2017 NAPLAN results were followed by political and media attention focusing on a decline in achievement in writing. This article analyses NAPLAN data to identify the locus of the decline. Contrary to media reports in which it was suggested Year 3 was problematic, the article systematically compares NAPLAN results between 2011 and 2017 to…

This qualitative study focuses on capturing students' understanding two visualizations often utilized by learning analytics-based educational technologies: bar graphs, and line graphs. It is framed by Achievement Goal Theory--a prominent theory of students' academic motivation--and utilizes interviews (n = 60) to investigate how students at risk…

The Education Equality Index (EEI), created through a unique collaboration of GreatSchools and Education Cities, is a nationally comparative measure that looks at how well students from low-income families are achieving in schools, cities, and states across the country and The EEI taps GreatSchools' national school information database and…

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…

In 1989, New Zealand started to follow an international trend of reforming education policy according to the neoliberal principles of competition, choice and self-managing schools. Since then, the increasing availability of digital data in schools has corresponded with the development of student achievement measurement tools and benchmarking of…

The use of data for adaptive, tailor-made education can be beneficial for students with learning difficulties. While evaluating the effects of a data-based decision-making (DBDM) intervention on student outcomes, considerable variation between intervention effects, ranging from high-intervention effects to small or even negative intervention…