This presentation explores shortcomings of learning analytics for the wide adoption in educational organisations. It is NOT about ethics and privacy rather than focuses on shortcomings of learning analytics for teachers and students in the classroom (micro-level).
Tutorial, Learning Analytics Summer Institute, Ann Arbor, June 2017 As algorithms pervade societal life, they’re moving from an arcane topic reserved for computer scientists and mathematicians, to the object of far wider academic and mainstream media attention
Keynote presentation at LASI-Rocky Mountains online conference, 12 June 2017, based on a similar talk at LAK17, Learning Analytics and Knowledge Conference 2017, Vancouver. An analysis of the nature of evidence, the state of the evidence in the field of learning analytics, and some suggestions for ways to improve, based on work from the LACE project's Evidence Hub.
In the era of increasing technology mediation Learning experiences need to be designed considering the capacity to capture data, the possibility of making sense and derive knowledge from the data, and the need to act on that knowledge.
While interdisciplinary courses are regarded as a promising method for students to learn and apply knowledge from other disciplines, there is limited empirical evidence available whether interdisciplinary courses can effectively “create” interdisciplinary students.
The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process.