As you get ready for the coming semester, have you thought about how learning analytics could be used to improve your teaching?
The University of Alberta uses eClass (aka Moodle), a Learning Management System (LMS) which can, among its many uses, keep a track of which activities and resources users have viewed. This data can be used for a number of purposes, the most common of which is to analyze learning (hence the name learning analytics) and also to analyze aspects of teaching. A new feature in eClass is Analytics (Beta) which presents the data in a more user-friendly way.
Learning analytics is valuable as a reviewing tool. This usually takes places at the end of a unit or course, focusing on what the students did . What trends can be identified as the students worked through the course? Did the engagement with the online materials wane over time? Were there certain links which were over- or under-used? What changes to the course content could be made based on the trends? The focus is to determine the effectiveness of a course and to make changes accordingly for the next time the course is running (Arroway et al 2016).
The other way learning analytics is valuable is as an intervention tool. This usually takes places during the unit or course, focussing on what the students are doing. Which students are not engaging with the online documentation or online discussion forum? Which students failed the online quiz? Which students are accessing the seminar material for the first time only 15 minutes before the seminar? The focus is to determine the engagement students have with a course, allowing for interventions and support to be put in place for these students at risk (Sclater and Peasgood 2017). It demonstrates to students that you are taking an active interest in their learning and are actively supporting their success. Of course, students can also access their own analytics (when permissions are set for them to do so) which allows them to take more responsibility for their own learning and development.
The Centre for Teaching and Learning (CTL) can help support faculties, courses and individuals in the use of learning analytics, providing assistance in instructional design by creating student interventions and offering both theoretical and practical suggestions based on current research.
Graeme Pate - Education Developer, Centre for Teaching and Learning
Graeme came to the U of A following a 16-year career at the University of Glasgow, Scotland, where he developed innovative instructional materials and designed Technology-Enhanced Active Learning approaches. As a member of the CTL team, he supports staff who wish to use technology to enhance their teaching and learning, and who want to become more confident and competent using aspects of technology in their teaching.
References
Arroway, P., Morgan, G., O'Keefe, M., Yanosky, R. (2016). Learning Analytics in Higher Education. Educause Center for Analysis and Research.
Sclater, N., Peasgood, A.. (2017). Jisc briefing: Learning analytics and student success - assessing the evidence. JISC. Bristol, UK. http://repository.jisc.ac.uk/6560/1/learning-analytics_and_student_success.pdf
Further Reading
Collins, B. Learning Analytics in Higher Ed: The Potential of Learning Analytics. Wiley Education Services. https://edservices.wiley.com/potential-for-higher-education-learning-analytics/
Sclater, N., Peasgood, A., Mullan, J. (2016). Learning analytics in higher education: A review of UK and international practice. JISC https://www.jisc.ac.uk/reports/learning-analytics-in-higher-education (Last Referenced: 2017.08.15).
Macfadyen, L.P. & Dawson, S. (2012). Numbers are not enough. Why e-learning analytics failed to inform an institutional strategic plan. Educational Technology & Society, 15 (3), 149-163.
Yu, L., Shimaoka, M., Koga, Y, Tanaka, A, Kobayashi, N. and Higginson, J. (2016). Novel applications of data analytics to higher education. JAIST Conference Paper. JAIST Repository.