Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…

Group composition affects learning by individuals. Dialogic pedagogy approaches demonstrate that this is particularly true when each grouped student knows something others do not (i.e., "mutuality" grouping). Learning analytics can help grouping by providing teachers with data on students' content-specific learning. What are mathematics…

Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this…

Schools now face considerable pressure to be using educational data to inform decision-making and become more efficient. Key to this rise of the 'data-driven' school is the increased use of digital technologies -- with computer-based data processing fuelling hopes for the technology-driven 'smart schooling' and a general 'datafication' of…

The increased reliance on Big Data Analytics (BDA) in society, politics, policy, and industry has catalyzed conversations related to the need for promoting ethical reasoning and decision-making in the mathematical sciences. While the majority of professional data scientists today come from privileged positions in society, those processed by the…

The National Assessment of Educational Progress (NAEP), often referred to as The Nation's Report Card, offers a window into the state of U.S. K-12 education system. Since 2017, NAEP has transitioned to digital assessments, opening new research opportunities that were previously impossible. Process data tracks students' interactions with the…

Research indicates that data-informed practice helps teachers change their teaching and promotes teacher professional development (TPD). Although educational data are often collected from digital spaces, in-action evidence from physical spaces is seldom gathered, providing an incomplete view of the classroom reality. Also, most learning analytics…

Games can be rich environments for learning and can elicit evidence of students' conceptual understanding and inquiry processes. Illuminating students' content-specific gameplay decisions, or methods of completing game tasks related to a certain domain, requires a context that is open-ended enough for students to make choices that demonstrate…

Increasing school dropout rates are a problem in many educational systems, with student disengagement being one significant factor. Learning analytics is a new field with a key role in educational institutions in the coming years. It may help make strategic decisions to reduce student disengagement. The use of technology in educational…

This paper explores how learning analytics data provided by a math problem-solving educational technology platform informed 5th and 6th grade teachers' instructional decisions around socioemotional learning (SEL). MathSpring is an educational technology tool that provides teachers with data on students' effort, progress, and emotions while…

Background: Data-driven educational technology solutions have the potential to support teachers in different tasks, such as the designing and orchestration of collaborative learning activities. When designing, such solutions can improve teacher understanding of how learning designs impact student learning and behaviour; and guide them to refine…

Automatic machine learning (AutoML) methods automate the time-consuming, feature-engineering process so that researchers produce accurate student models more quickly and easily. In this paper, we compare two AutoML feature engineering methods in the context of the National Assessment of Educational Progress (NAEP) data mining competition. The…

The present work describes the challenges faced during the development of a countrywide Learning Analytics study and tool focused on tracking and understanding the trajectories of Uruguayan students during their first three years of secondary education. Due to the large scale of the project, which covers an entire national educational system,…

Intelligent tutoring systems (ITSs) are commonly designed to enhance student learning. However, they are not typically designed to meet the needs of teachers who use them in their classrooms. ITSs generate a wealth of analytics about student learning and behavior, opening a rich design space for real-time teacher support tools such as dashboards.…