Simulation-based learning provides students with unique opportunities to develop key procedural and teamwork skills in close-to-authentic physical learning and training environments. Yet, assessing students' performance in such situations can be challenging and mentally exhausting for teachers. Multimodal learning analytics can support the…

Multimodal data have the potential to explore emerging learning practices that extend human cognitive capacities. A critical issue stretching in many multimodal learning analytics (MLA) systems and studies is the current focus aimed at supporting researchers to model learner behaviours, rather than directly supporting learners. Moreover, many MLA…

Learning Analytics (LA) systems can offer new insights into learners' behaviours through analysis of multiple data streams. There remains however a dearth of research about how LA interfaces can enable effective communication of educationally meaningful insights to teachers and learners. This highlights the need for a participatory, horizontal…

The term "Classroom Proxemics" refers to how teachers and students use classroom space, and the impact of this and the spatial design on learning and teaching. This study addresses the divide between, on the one hand, substantial work on proxemics based on classroom observations and, on the other hand, emerging work to design automated…

Teachers' spatial behaviours in the classroom can strongly influence students' engagement, motivation and other behaviours that shape their learning. However, classroom teaching behaviour is ephemeral, and has largely remained opaque to computational analysis. Inspired by the notion of Spatial Pedagogy, this paper presents a system called 'Moodoo'…

Multimodal learning analytics (MMLA) has increasingly been a topic of discussion within the learning analytics community. The Society of Learning Analytics Research is home to the CrossMMLA Special Interest Group and regularly hosts workshops on MMLA during the Learning Analytics Summer Institute (LASI). In this paper, we articulate a set of 12…

Using data to generate a deeper understanding of collaborative learning is not new, but automatically analyzing log data has enabled new means of identifying key indicators of effective collaboration and teamwork that can be used to predict outcomes and personalize feedback. Collaboration analytics is emerging as a new term to refer to…

This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…

There is growing interest in creating learning analytics feedback interfaces that support students directly. While dashboards and other visualizations are proliferating, the evidence is that many fail to provide meaningful insights that help students reflect productively. The contribution of this article is qualitative and quantitative evidence…

Current writing support tools tend to focus on assessing final or intermediate products, rather than the writing process. However, sensing technologies, such as keystroke logging, can enable provision of automated feedback during, and on aspects of, the writing process. Despite this potential, little is known about the critical indicators that can…

In Computer-Supported Collaborative Learning (CSCL) classrooms it may be challenging for teachers to keep awareness of certain aspects of the learning process of each small group or assess whether the enactment of the class script deviates from the original plan. Orchestration tools, aimed at supporting the management of the increasing uncertainty…