Twelfth International Conference on e-Learning & Innovative Pedagogies

Abstract

In the last decade there has been a significant increase of technologies that claim to personalize learning in K-12 classrooms. Dependent on the algorithmic analysis of big data, there are myriads of apps or platforms offering predictions of learner behaviour, insights on student activity and offering teacher recommendations. This brings new forms of learning, such as apps utilising gamification techniques to predict when engagement will be lost. Apps that use predictive technologies are also arguably shaping the pedagogy for both the better and the worse. In the context of K-12 education, new technologies can predict the risk of a student dropping out of school, however such predictive analytics has also been shown to perpetuate discrimination and bias, even in the absence of conscious prejudice. Therefore, understanding how teachers are negotiating apps underscored by algorithmic logics as part of their educational practice is both timely and significant. This presentation aims to engage teachers to evaluate the use of predictive technologies in their learning environments by illuminating some of the ‘black boxed’ risks, such as algorithmic bias, a shift in teacher agency and the notion of platform capitalism. The theoretical presentation will be supported by empirical evidence gathered from an Australian mini-survey and interviews with Victorian teachers completed by the researcher from October 2018 – March 2019 as part of her PhD studies with the University of Newcastle.