Mathematics: Launching Futures Proceedings of the 24th Biennial Conference of The Australian Association of Mathematics Teachers Inc.

‘Mathematics: Launching Futures’ was the theme for the 24th Biennial Conference of The Australian Association of Mathematics Teachers Inc.It was the first national conference on mathematics education since the introduction of the Australian Curriculum and so addresses the support educators will need to implement this curriculum. It also addressed concerns regarding  the low numbers of students studying higher level mathematics at school and university. A major aim of the conference was the sharing of knowledge to encourage  and support teachers at all
stages of their careers. This conference featured a joint day with the 36th Annual Conference of the Mathematics Education Research Group of Australasia (MERGA), aiming to enhance collaboations between researchers and teachers.

Bayesian nonparametric multilevel clustering with group-level contexts

We present a Bayesian nonparametric framework for multilevel clustering which utilizes group- level context information to simultaneously discover low-dimensional structures of the group contents and partitions groups into clusters. Using the Dirichlet process as the building block, our model constructs a product base-measure with a nested structure to accommodate content and context observations at multiple levels. The proposed model possesses properties that link the nested Dinchiet processes (nDP) and the Dirichlet process mixture models (DPM) in an interesting way: integrating out all contents results in the DPM over contexts, whereas integrating out group-specific contexts results in the nDP mixture over content variables. We provide a Polyaurn view of the model and an efficient collapsed Gibbs inference procedure. Extensive experiments on real-world datasets demonstrate the advantage of utilizing context information via our model in both text and image domains.