Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…

Leading by doing takes an unwavering and visible commitment to an intentional, continuous improvement process. Teams at every system level distribute leadership to support effective practice so outcomes improve. Using a practice-based approach to improving mathematics outcomes, the Kentucky Department of Education (KDE) facilitated a continuous…

"Disrupting Disruption" shows how three racially and ethnically diverse school districts--Union NJ, Union City OK, and Roanoke City VA--have defied the demographic odds, boosting overall graduation rates while shrinking or eliminating the opportunity gap. These districts resemble many others in their student population. What makes them…

Despite the often-negative discussion about testing in schools, assessments are a necessary and useful tool in the teaching and learning process. This is especially true when it comes to diagnostic and formative assessments, which give teachers real-time direction for what students need to learn to master course content. It is this space where the…

This article summarizes some emerging concerns as learning analytics become implemented throughout education. The article takes a sociotechnical perspective -- positioning learning analytics as shaped by a range of social, cultural, political, and economic factors. In this manner, various concerns are outlined regarding the propensity of learning…

Thanks to an increase in the amount of information on the Internet and the spread of ICT-supported educational environments, much attention has been paid to learning support based on "smart" recommendation technologies. In this study, we propose an education improvement model based on the recommender system using the human-in-the-loop…

This chapter considers some of the limit points of contemporary relations between International Large-Scale Assessments, learning analytic platforms, and theories of mind circulating in contemporary comparative and transnational educational policy discourses. First, aspects of the rise of Big Data and predictive analytics are historicized, with…

Machine learning technology is currently a new frontier for higher education globally, and the African higher education system needs to change in tandem with this technological trend in order to combat challenges faced by the system. These challenges include lack of institutional research to discover new knowledge, unfavorable methods of…

Assessment and learning analytics both collect, analyse and use student data, albeit different types of data and to some extent, for various purposes. Based on the data collected and analysed, learning analytics allow for decisions to be made not only with regard to evaluating progress in achieving learning outcomes but also evaluative judgments…

The DoD's [Department of Defense's] Advanced Distributed Learning (ADL) Initiative is designing a framework of commercial standards, technical specifications, and business rules to enable plug and play interoperability of learning technologies. The Total Learning Architecture (TLA) framework will allow education and training products to…

Access to early learning before kindergarten has wide-ranging positive effects for children--effects that are evident from a child's early years into adulthood. Despite these facts being well-known within many education spaces, children from low-income families and children of color lack consistent access to public early learning programs. This…

Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…

Data collection and analysis is nothing new in computer-assisted language learning, but with the phenomenon of massive sets of human language collected into corpora, and especially integrated into systems driven by artificial intelligence, new opportunities have arisen for language teaching and learning. We are now seeing powerful artificial…

MegaSoTL projects are scholarship of teaching and learning (SoTL) projects that generate evidence of learning from multiple institutions. While being increasingly practiced, MegaSoTL projects and their potential contribution to improve higher education pedagogy remain understudied in higher education literature. In this article, we introduce…

The Education-to-Workforce Indicator Framework (E-W Framework), commissioned by the Bill & Melinda Gates Foundation and developed in partnership with leading experts representing more than 15 national and community organizations, is designed to encourage greater cross-sector collaboration and alignment across local, state, and national data…