Multivariate Analysis of an LA-ICP-MS Trace Element Dataset for Pyrite

Application of multivariate statistics to trace element datasets is reviewed using 164 multi-element LA-ICP-MS spot analyses of pyrite from the Moonlight epithermal gold prospect, Queensland, Australia. Multivariate analysis of variance (MANOVA) is used to demonstrate that classification of pyrite on morphological and other non-numeric factors is geochemically valid. Parallel coordinate plots and correlation cluster analysis using Spearman’s coefficients are used to discover unexpected elemental relationships without making assumptions a priori. Finally, principal component analysis and factor analysis are used to demonstrate the presence of sub-classes of pyrite. Corroborated with geological data, statistical analysis provides evidence for successive generations of hydrothermal fluids, each introducing specific metals, and for partial or complete replacement of different minerals. The data permit reinterpretation of Moonlight as a telescoped system where epithermal-Au (± base metals) is superposed onto early porphyry-Mo mineralization.Lyron Winderbaum, Cristiana L. Ciobanu, Nigel J. Cook, Matthew Paul, Andrew Metcalfe, Sarah Gilber

Motivation and engagement in mathematics: a qualitative framework for teacher-student interactions

We started with a classic research question (How do teachers motivate and engage middle year students in mathematics?) that is solidly underpinned and guided by an integration of two theoretical and multidimensional models. In particular, the current study illustrates how theory is important for guiding qualitative analytical approaches to motivation and engagement in mathematics. With little research on how teachers of mathematics are able to maintain high levels of student motivation and engagement, we focused on developing a qualitative framework that highlights the influence of teacher-student interactions. Participants were six teachers (upper primary and secondary) that taught students with higher-than-average levels of motivation and engagement in mathematics. Data sources included one video-recorded lesson and associated transcripts from pre- and post-lesson interviews with each teacher. Overall, effective classroom organisation stood out as a priority when promoting motivation and engagement in mathematics. Results on classroom organisation revealed four key indicators within teacher-student interactions deemed important for motivation and engagement in mathematics—confidence, climate, contact, and connection. Since much of the effect of teachers on student learning relies on interactions, and given the universal trend of declining mathematical performance during the middle years of schooling, future research and intervention studies might be assisted by our qualitative framework