Perceiving learning at a glance: A systematic literature review of learning dashboard research

This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining. Research on learning dashboards aims to identify what data is meaningful to different stakeholders and how data can be presented to support sense-making processes. Learning dashboards are becoming popular due to the increased use of educational technologies, such as Learning Management Systems (LMS) and Massive Open Online Courses (MOOCs). The initial search of five main academic databases and GScholar resulted in 346 papers out of which 55 papers were included in the final analysis. Our review distinguishes different kinds of research studies as well as various aspects of learning dashboards and their maturity regarding evaluation. As the research field is still relatively young, most studies are exploratory and proof-of-concept. The review concludes by offering a definition for learning dashboards and by outlining open issues and future lines of work in the area of learning dashboards. There is a need for longitudinal research in authentic settings and studies that systematically compare different dashboard designs.

Understanding learning at a glance: An overview of learning dashboard studies

Pierre Dillenbourg, Denis Gillet, Adrian Christian Holzer, Luis Pablo Prieto Santos, Maria Jesus Rodriguez Triana, Beat Adrian Schwendimann, Mina Shirvani Boroujeni, Andrii Vozniuk

Research on learning dashboards aims to identify what data is meaningful to different stakeholders in education, and how data can be presented to support sense-making processes. This paper summarizes the main outcomes of a systematic literature review on learning dashboards, in the fields of Learning Analytics and Educational Data Mining. The query was run in five main academic databases and enriched with papers coming from GScholar, resulting in 346 papers out of which 55 were included in the final analysis. Our review distinguishes different kinds of research studies as well as different aspects of learning dashboards and their maturity in terms of evaluation. As the research field is still relatively young, many of the studies are exploratory and proof-of-concept. Among the main open issues and future lines of work in the area of learning dashboards, we identify the need for longitudinal research in authentic settings, as well as studies that systematically compare different dashboard design options.

Assoc Computing Machinery2016

Special issue on: Learning Analytics (Editorial)

Maria Jesus Rodriguez Triana

With the general technological advances of the recent years, current learning environments amass an abundance of data. Albeit such data offer the chance of better understand the learning process, stakeholders – learners, teachers and institutions – often need additional support to make sense of it (Dyckhoff et al., 2013; Macfadyen and Dawson, 2012). The acknowledgement of these needs is at the heart of the recent emergence of Learning Analytics (LA), a research area that draws from multiple disciplines such as educational science, information and computer science, sociology, psychology, statistics and educational data mining (Buckingham Shum and Ferguson, 2012). This multidisciplinarity in LA has motivated the work done by Ferguson (2012), which provides a first review of the drivers, development and challenges of this novel and young research area. Our understanding of learning analytics is based on the definition from the Society for Learning Analytics (SoLAR – Society for Learning Analytics1) which specifies that “Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs”. Since 2011, the Horizon reports list Learning Analytics as a hot topic in higher education and indicate the importance of data for this field (Johnson et al., 2011). Learning analytics are able to provide a fresh view on understanding of teaching and learning by observing patterns of complex data (Johnson et al., 2012). Furthermore, it will influence the evolution of higher education in a great measure. Nowadays, learners have access to a huge amount of online information having themselves the possibility of being content creators and information sharers. Therefore the quantity of available information grows in an exponential way, once that each and every citizen can access and produce information. For these purposes, learners have at their disposal many online resources, including LMSs, VLEs, MOOCs and many other online tools that facilitate the learning process and the development of competences. Taking into account these online learning facilities and therefore the learners’ acquisition of knowledge, it is also easier to measure and analyse their experiences by using learning analytics tools. Different online courses and institutions provide dashboards with information about student experiences, flaws and successes. Although the investigation of behavioural specific data makes learning analytics complex, the time comes to utilise personalised learning environments adapted to students learning paths, skills, previous knowledge, competences and motivation.

2013

Special issue on: Learning Analytics (Editorial)

Maria Jesus Rodriguez Triana

2013