The increasing use of technology for teaching and learning has led to a significant amount of data being collected on how learning occurs in today’s world. To capitalize on this rich data, Learning Analytics (LA) has emerged in recent years as an important field that enables the measurement, collection, analysis and reporting of educational data for the purpose of understanding and optimizing learning. The applications of LA in education can include leaner-facing dashboards showing individual’s course progress, staff-facing reports tracking student use of educational resources, and intelligent systems that predict students’ academic performances and risks of dropping out, and enable teachers to take corrective actions. In this short espresso course, we will explore what LA is and why it is widely adopted by institutions. We will then explain and showcase how LA is used to support learning and teaching. The course will conclude by examining key issues in the use of LA, including concerns over ethics and privacy relating to LA applications, and how LA insights should be interpreted. This course will be of interest to anyone interested in leveraging educational data for better learning outcomes and the challenges involved with it.
All are welcome
We welcome all staff, including tutors, demonstrators, professional staff, and academics at the Australian National University and beyond to join us for this course.
How to participate
There are 3 blog posts, one per day, that will take about 15-20 minutes to work through. You are welcome to work through the course at your own pace, any time. The entire course will be conducted online, at your own pace through this blog. We encourage you to make a cup of coffee or tea and work through the material. Each post includes an activity or discussion question for you to respond to in the comment section of the blog. Be sure to subscribe to the blog (scroll down to the bottom, enter your email address and click on the red Subscribe button). If you use an RSS reader you can subscribe to the blog feed as well. You’ll receive an email each time a new post is made, and you can unsubscribe at any time.
Day 1: The What and Why of Learning Analytics. We explain what LA means and characteristics of learning data. We also introduce basic concepts and techniques in data analytics, including data mining and visualization processes.
Day 2: Using Analytics to Support Learning and Teaching. We briefly look at popular LA tools, both generic and specific to Wattle (Moodle). We then present common use cases of LA from the literature and showcase some real-world LA applications.
Day 3: Key Issues in the Use of Learning Analytics: Ethics. Privacy and Engagement. We discuss the ethics and privacy issues relating to the collection and use of educational data. Finally, an important phenomenon often observed in LA reports, “pedagogic lurking”, is discussed.
Dr Patrick Tran
Educational Designer/Developer, UNSW Canberra (ADFA)