I gave this talk on OnTask at the LALA symposium—Learning Analytics for Feedback at Scale on 1 July, 2019, KU Leuven, Belgium. OnTask was developed as part of a research project led by Professor Abelardo Pardo. The tool uses ‘if this… then that…’ rule to enable feedback to be personalised at scale. It is a powerful tool to save teaching staff time without taking away their teaching agency. At the end of the day, it is the instructor, not the machine, who has to construct feedback content that contains effective elements to support a learning process.
Abstract
Feedback is a crucial part of communication between students and teachers in terms of clarifying expectations, monitoring the current progress of learners, and moving towards desired learning goals. However, there is substantial evidence showing that higher education struggles to deliver consistent, timely, and constructive feedback to meet the needs and expectations of students. The inadequacy in delivering effective feedback to students is partly due to conflicts between an increasing focus on ‘massiveness’, ‘inclusiveness’, and ‘personalisation’ in higher education and yet unmatched capacity of staff to produce feedback that speaks to the needs of individual students. OnTask is a semi-automated feedback tool, which uses ‘if…then’ rules to help teachers compose personalised feedback for a large cohort of students based on parameters relevant to the course design. In this talk, I talked about key elements of effective feedback and how we can leverage feedback practice using OnTask.
