With a background in learning analytics, I am always keen on finding out when and on what factors we teachers can rely upon to detect disengagement in the online or hybrid learning context. In this blog, we continue the conversation by describing an approach we call Activity-Based Conditional (ABC) messaging. A simple form of ABC messaging can be handled using the Canvas ‘Message Students Who‘ function. FEIT’s Amara Atif has used this in her subjects, to communicate regular and personalised feedback to students who are less engaged. Amara shares her process below. Learning Analytics enable academics to leverage automated feedback systems to address these challenges. LX.lab and the Connected Intelligence Centre (CIC) just wrapped up a series of workshops on Automated Feedback tools, showing the range of systems available at UTS, and showcasing how these are being used by academics. This post is a collaboration between Simon Buckingham Shum (CIC), Lisa-Angelique Lim (CIC), David Yeats (IML LX.Lab), Martin van de Weyer (IML LX.Lab), and Amara Atif (FEIT).įeedback is a key issue in learning and teaching at university, with many students expressing dissatisfaction with the timeliness and extent to which it is personalised for actionability. With large cohorts and an increasing use of virtual learning spaces, academics also face the challenge of being able to provide timely and personalised feedback.
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