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…

This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…

The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…

With student and staff wellbeing a growing concern, several authors have asked whether existing data might help institutions provide better support. By analogy with the established field of Learning Analytics, this might involve identifying causes of stress, improving access to information for those who need it, suggesting options, providing rapid…

In June 2022, the Norwegian Expert Commission on Learning Analytics delivered an interim report to the Norwegian Minister of Education and Research. Motivated by the need to establish a solid foundation upon which to regulate and promote the use of learning analytics in the Norwegian educational sector, the Ministry asked the Expert Commission to…

In this short thought-piece, I attempt to capture the type of freewheeling discussions I had with our late colleague, Mika Seppälä, a research mathematician from Helsinki. Mika, not being a psychometrician or learning scientist, was blissfully free from the design constraints that experts sometimes ingest, unwittingly. I also draw on delightful…

Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…

Open Learning Analytics (OLA) is an emerging concept in the field of Learning Analytics (LA). It deals with learning data collected from multiple environments and contexts, analyzed with a wide range of analytics methods to address the requirements of different stakeholders. Due to this diversity in different dimensions of OLA, the LA developers…

It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…

This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field and identify some of the trends in recent research. As the field continues to expand, there seem to be at least three directions of vigorous growth: (1) the inclusion of multimodal data (gesture,…

The importance of temporality in learning has been long established, but it is only recently that serious attention has begun to be paid to the precise identification, measurement, and analysis of the temporal features of learning. From 2009 to 2016, a series of temporality workshops explored temporal concepts and data types, analysis methods for…

This commentary elaborates on the role of "grounding" as a focal theoretical concept and aims to contextualize the claims formulated by Schneider and Pea (2015, this issue) in previous CSCL discussions. It provides fingerposts for enriching and refining the concept of grounding from a pedagogical point of view. It also suggests using the…

Topological data analysis (TDA) is a collection of powerful tools that can quantify shape and structure in data in order to answer questions from the data's domain. This is done by representing some aspect of the structure of the data in a simplified topological signature. In this article, we introduce two of the most commonly used topological…

Data used in learning analytics rarely provide strong and clear signals about how learners process content. As a result, learning as a process is not clearly described for learners or for learning scientists. Gaševic, Dawson, and Siemens (2015) urged data be sought that more straightforwardly describe processes in terms of events within learning…

This paper identifies some of the main challenges of data governance modelling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data…