The use of open data as a material for learning

Open data has potential value as a material for use in learning activities. However, approaches to harnessing this are not well understood or in mainstream use in education. In this research, early adopters from a diverse range of educational projects and teaching settings were interviewed to explore their rationale for using open data in teaching, how suitable activity designs could be achieved, and the practical challenges of using open data. A thematic analysis was conducted to identify patterns and relationships in these open data-based practices that have already emerged. A document analysis of teaching materials and other related artefacts was used to augment and validate the findings. Drawing on this, common approaches and issues are identified, and a conceptual framework to support greater use of open data by educators is described. This paper also highlights where existing concepts in education and educational technology research, including inquiry-based learning, authenticity, motivation, dialogue, and personalisation can help us to understand the value and challenges of using open data in education

Augmenting Assessment with Learning Analytics

Learning analytics as currently deployed has tended to consist of large-scale analyses of available learning process data to provide descriptive or predictive insight into behaviours. What is sometimes missing in this analysis is a connection to human-interpretable, actionable, diagnostic information. To gain traction, learning analytics researchers should work within existing good practice particularly in assessment, where high quality assessments are designed to provide both student and educator with diagnostic or formative feedback. Such a model keeps the human in the analytics design and implementation loop, by supporting student, peer, tutor, and instructor sense-making of assessment data, while adding value from computational analyses