DER seminar double feature: data-driven feedback AND data justice!

DER seminar double feature: data-driven feedback AND data justice!


Please join us for a double seminar (two short presentations and some discussion) on 11/11/2021 at 2pm.

This is an online seminar. Contact for the link.

Yi-Shan Tsai will be talking about data-driven feedback. This will be followed by a brief session about “data justice” in education with Carlo Perrotta. Details in the flyer.

Yi-Shan joined Monash’s Faculty of IT last year to research Learning Analytics. We recently welcomed her to DER: Yi-Shan Tsai | Digital Education Research @ Monash


Yi-Shan Tsai: Learning analytics (LA) provides data-driven feedback that aims to improve learning and inform action. For learners, LA-based feedback may scaffold self-regulated learning skills, which are crucial to learning success. For teachers, LA-based feedback can help the evaluation of teaching effects and the need for interventions. However, the current development of LA has presented problems related to the cognitive, social-affective, and structural dimensions of feedback. In this talk, I will outline these issues and argue that attention needs to shift from the design of LA as a feedback product to one that facilitates a process in which both teachers and students play active roles in meaning-making. In particular, I will discuss the implications for feedback literacy in the context of LA.

Carlo Perrotta: In 2020 OFQUAL, the UK regulator of qualifications and exams, developed a ‘grades standardisation algorithm’ for exams sat by all students at ages 16 and 18 – the General Certificate of Secondary Education (GCSE) and the A Level exam. As widely reported in the media, the algorithm displayed ‘bias’ by downgrading the performance of state-funded schools and upgrading that of private or independent institutions. In this quick ‘burst’ talk Carlo will provide a generalist overview of algorithmic bias in education from a perspective of data justice.