13 Nov seminar with Shibani Antonette: Augmenting pedagogical writing support with contextualizable learning analytics
Learning analytics (LA) has potential to improve student learning. However, LA applications can achieve the most impact when educators can contextualize them to particular learning contexts. Through contextualizable learning analytics, the learning analytics applications can be aligned with the learning design for pragmatic, real-world deployment, rather than acting as rigid computational black boxes. Thus, contextualizable learning analytics supports the integration of learning analytics techniques in authentic practice by augmenting (rather than revolutionizing) existing educational practice.
This talk will use the example of applying learning analytics to the creation of scalable, instant feedback on writing, to exemplify this perspective of ‘augmentation’ for contextualizable analytics. I take a design approach, to illustrate how existing good practice in writing instruction might be augmented by learning analytics to further strengthen that practice. I will discuss the implementation of contextualizable LA using a writing analytics example, where the features, feedback and learning activities around the automated writing feedback tool are tuned for the pedagogical context and the assessment regime in hand, by co-designing them with educators. The approach can be employed for learning analytics to move from generalized support to meaningful contextualized support for enhancing learning, and increased adoption by practitioners.
- When: Tues Nov 13th, 2.00-3.30 (join us for refreshments from 1.45pm)
- Where: Room 612, Education Building A35, University of Sydney
- No registration is needed, just come on the day
- This seminar will be recorded
Shibani Antonette is a researcher and doctoral student in Learning Analytics at the Connected Intelligence Centre, University of Technology (UTS) Sydney. A computer science engineer by training, she uses analytic techniques to study and improve educational practice, with primary focus on text analytics. In her doctoral research, she works on Writing Analytics technology providing automated feedback on student writing, and its integration into the classroom for pedagogic use. She has chaired Writing Analytics workshops in international conferences and is an active member of the Society for Learning Analytics Research.