As part of LAK 2018, the Eighth International Learning Analytics and Knowledge Conference, we are thrilled to announce the second Multimodal Learning Analytics Across (Physical and Digital) Spaces (CrossMMLA) workshop. Student’s learning happens where the learner is rather than being constrained to a single physical or digital environment. Educational research has revealed the pedagogical benefits of letting students experience different types of content, ”real world” challenges, and physical and social interactions with educators or other learners. In this way students commonly work outside the boundaries of the institutional learning system(s). This inherently blended nature of learning settings makes it essential to move beyond learning analytics that rely solely on a single data source (e.g. log files).

CrossMMLA is the successor to the Learning Analytics Across Spaces (CrossLAK) and MultiModal Learning Analytics (MMLA) series of workshops that were merged in 2017, after synergetic efforts between the two communities. Multimodal learning analytics (MMLA) can provide insights into such learning processes that happen across multiple contexts between people, devices and resources (both physical and digital), which often are hard to model and orchestrate. MMLA leverages the increasingly widespread availability of sensors and high-frequency data collection technologies to enrich the existing data available. Using such technologies in combination with machine learning and artificial intelligence techniques, LA researchers offers a number of solutions to ubiquitous learning.

By contrast, CrossLAK embraces the complexity of learning as an activity which is distributed across spaces, people, tools (both digital and physical) and time. Once a “learning problem” has been identified, a CrossLAK initiative would analyse the feasibility of offering learning analytics solutions by means of very simple (unimodal) or quite sophisticated (multimodal) analyses.

One of the key aims of the workshop is to attract researchers (from diverse communities) to consider how multimodal learning analytics can be used across diverse learning environments. This workshop intention is to gather interested parties in ubiquitous, mobile and/or face-to-face learning analytics with a focus on multimodal interaction. An overarching concern is how to integrate and coordinate learning analytics to provide continued support to learning across digital and physical spaces.