The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper presents an exploratory systematic scoping review to investigate findings regarding LA usage in digital materials, teaching, and learning in K–12 mathematics education. In all, 3,654 records were identified, of which 19 studies met all the inclusion criteria. Results show that LA research in mathematics education is an emerging field where applications of LA are used in many contexts across many curricula content and standards of K–12 mathematics education, supporting a wide variety of teacher data use. Teaching with DBDM is mainly focused on supervision and guidance and LA usage had a generally positive effect on student learning with high-performing students benefiting most. We highlight a need for further research to develop knowledge of LA usage in classroom practice that considers both teacher and student perspectives in relation to design and affordances of digital learning systems. Finally, we propose a new class of LA, which we define as guiding analytics for learners, which harnesses the potential of LA for promoting achievement and independent learning.

The promise of Learning Analytics Dashboards in education is to collect, analyze, and visualize data with the ultimate ambition of improving students’ learning. Our overview of the latest systematic reviews on the topic shows a number of research trends: learning analytics research is growing rapidly; it brings to the front inequality and inclusiveness measures; it reveals an unclear path to data ownership and privacy; it provides predictions which are not clearly translated into pedagogical actions; and the possibility of self-regulated learning and game-based learning are not capitalized upon. However, as learning analytics research progresses, greater opportunities lie ahead, and a better integration between information science and learning sciences can bring added value of learning analytics dashboards in education.

Data-driven school improvement has been proposed to improve and support educational practices, and more studies are emerging describing data-driven practices in schools and the effects of data-driven interventions. This paper reports on a study that has taken place within a national program where 15 schools from 6 different municipalities and organizations are working at classroom, school and municipality levels to improve educational practices using data-driven methods. The study aimed at understanding what educational problems teachers, principals and administrative staff in the project aimed to address through the utilization of data-driven methods and the challenges they face in doing so. Using a mixed-methods design, we identified four thematic areas that reflect the focused problem areas of the participants in the project, namely didactics, democracy, assessment and planning, and mental health. All development groups identified problems that can be solved with data-driven methods. Along with this, we also identified five challenges faced by the participants: time and resources, competence, ethics, digital systems and common language. We conclude that the main chal-lenge faced by the participants is data literacy, and that professional development is needed to support effective and successful data-driven practices in schools.