Understanding then optimising learning
Learning analytics includes: educational theory and practice, SNA, data mining, machine learning, semantic, data visualisations, sense-making, psychology (social, cognitive, organisational) and learning science. By collecting data from multiple points we can ask, what patterns exist and what do they indicate? Then, if changes are applied, what happens?
In our case we want to target at-risk students, prevent attrition and understand what affects learning and teaching. Yes it's complex; but we are working to distil the information we obtain into a dashboard, and so turn information in to knowledge.
The high growth in adoption of education technologies such as learning management systems (LMS) across the education sector has resulted in alternate and more accessible data on learning and teaching practice. As with most online systems, student interactions via the LMS are routinely captured and stored. These digital footprints can be 'mined' and analysed to reveal insights into the student learning process. As teachers and students engage more with digital resources and tools we are seeing a parallel rise in research associated with learning analytics, data mining, and learning sciences more broadly. Learning analytics in particular has had strong resonance across the education sector. This presentation will introduce the field of learning analytics and discuss a set of case studies to illustrate the diversity of research ranging from the provision of early alert systems towards more flexible and personalized learning opportunities.
When you logon to myUniSA Teaching you'll see the learnonline dashboard, designed to give you an immediate "picture" of how students are performing in your course. A lot of the data is self-evident; but, if you want to know how to really drill down in to the information we have an excellent help resource to guide you.
|Learning analytics overview: Building evidence based practice||Professor Shane Dawson, HERDSA Workshops 2013||View more on slideshare|
|Benchmarking Learning Analytics in Australia||Professor Shane Dawson, OLT Project 2015||View project website|
|Snodgrass Rangel, V., Bell, E., Monroy, C. and Whitaker, J. (2015). Toward a New Approach to the Evaluation of a Digital Curriculum Using Learning Analytics.Journal of Research on Technology in Education, 47(2), pp.89-104.|
|Daniel, B. (2014). Big Data and analytics in higher education: Opportunities and challenges.
Br J Educ Technol, p.n/a-n/a.
|Atkinson, S. (2015). Adaptive Learning and Learning Analytics: a new learning design paradigm.
(BPP University Working Papers)
|Beattie, S., Woodley, C., & Souter, K. (2014) Creepy Analytics and Learner Data Rights.
In B. Hegarty, J. McDonald, & S.-K. Loke (Eds.), Rhetoric and Reality: Critical perspectives on educational technology. Proceedings ascilite Dunedin 2014 (pp. 421-425).
|Pardo, A. (2015) Using data to support active learning experiences.
UniSA Learning Breakfast presentation August 2015
|Society for Learning Analytics Research
|Learning Analytics Summer Institutes
|Learning Analytics and Student Retention (Australian)
Let's talk LA
|Official website of the Higher Ed Online Analytics Revolution
|Learning Analytics Community Exchange (Europe)