Secret Squirrel Stuff in the Australian Curriculum English: The genesis of the ‘new’ grammar

In much the same way that a squirrel stores a range of food in a range of places, the Australian Curriculum, Assessment and Reporting Authority’s (ACARA) Australian Curriculum: English (ACARA, 2015) stores references to grammar in a range of places. This paper explores some seemingly ‘hidden’ grammars within the AC:E to (re)discover their genesis and how they unfold across Foundation to Year 6. The first ‘Secret Squirrel’ moment centres on the introduction of a new grammar which weaves traditional Latin-based and Systemic Functional Linguistics (SFL) theory. The second ‘Secret Squirrel’ moment centres on the use of one sub-system of SFL Theory, the System of Appraisal, and its potential to provide an analytical lens for ‘reading’ the interpersonal meaning within narratives. The remainder of the paper draws on Goodson’s (1990) notion of curriculum as a social construction, paying attention to the levels of processes and (potential) practice. This part of the paper focuses on the System of Appraisal as it is introduced in the AC:E and then translates the Content Descriptions to an example analysis. One stimulus text, Melanie Watt’s (2012) children’s picture book ‘Scaredy Squirrel at the Beach’, is introduced then analysed using the System of Appraisal as an analytical lens for identifying how language choices ‘go to work’ (Macken-Horarik, 2003, p. 285) on readers, that is how Watt’s language choices are crafted so a ‘compliant’ child reader (Martin & White, 2005, p. 62) has the opportunity to ‘feel with’ and thus ‘adjudicate’ the behaviour of characters in particular ways (Macken-Horarik, 2003, p. 285).

Electronic states of trans-polyacetylene, poly(p-phenylene vinylene) and sp-hybridised carbon species in amorphous hydrogenated carbon probed by resonant Raman scattering

Inclusions of sp-hybridised, trans-polyacetylene [trans-(CH)x] and poly(p-phenylene vinylene) (PPV) chains are revealed using resonant Raman scattering (RRS) investigation of amorphous hydrogenated carbon (a-C:H) films in the near IR – UV range. The RRS spectra of trans-(CH)x core Ag modes and the PPV CC-H phenylene mode are found to transform and disperse as the laser excitation energy ћωL is increased from near IR through visible to UV, whereas sp-bonded inclusions only become evident in UV. This is attributed to ћωL probing of trans-(CH)x chain inhomogeneity and the distribution of chains with varying conjugation length; for PPV to the resonant probing of phelynene ring disorder; and for sp segments, to ћωL probing of a local band gap of end-terminated polyynes. The IR spectra analysis confirmed the presence of sp, trans-(CH)x and PPV inclusions. The obtained RRS results for a-C:H denote differentiation between the core Ag trans-(CH)x modes and the PPV phenylene mode. Furthermore, it was found that at various laser excitation energies the changes in Raman spectra features for trans-(CH)x segments included in an amorphous carbon matrix are the same as in bulk trans-polyacetylene. The latter finding can be used to facilitate identification of trans-(CH)x in the spectra of complex carbonaceous materials.

The genesis of science education research in Australasia

Although the sciences were being taught in Australian schools well before the Second World War, the only evidence of research studies of this teaching is to be found in the report, published by ACER in 1932 of Roy Stanhope’s survey of the teaching of chemistry in New South Wales and a standardized test he had developed. Roy Stanhope was a science teacher with a research masters degree in chemistry. He had won a scholarship to go to Stanford University for doctoral studies, but returned after one year when his scholarship was not extended. He went on to be a founder in 1943 of the Australian Science Teachers Association (ASTA), which honours this remarkable pioneer through its annual Stanhope Oration. In his retirement Stanhope undertook a comparative study of science

The Student Success Project : Helping students at-risk of failing or leaving a unit - a work in progress

In Semester 1 2007, a Monitoring Student Engagement study, conducted as part of the Enhancing Transition at Queensland University of Technology (ET@QUT) Project and extending earlier work in the Project by Arora (2006), aimed at mapping the processes and resources used at that time to identify, monitor and manage students in their first year who were at risk of leaving QUT (Shaw, 2007). This identified a lack of documentation of the processes and resources used and revealed an ad-hoc rather than holistic and systematic approach to monitoring student engagement. One of Shaw’s recommendations was to: “To introduce a centralised case management approach to student engagement” (p. 14). That provided the genesis for the Student Success Project that is being reported on here. The aim of the Student Success Project is to trial, evaluate and ultimately establish holistic and systematic ways of helping students who appear to be at-risk of failing or withdrawing from a unit to persist and succeed. Students are profiled as being at-risk if they are absent from more than 2 tutorials in a row without contacting their tutor or if they fail to submit their first assignment. A Project Officer makes personal contact with these students to suggest ways they can get further assistance depending on their situation.

Marx as critical discourse analyst : the genesis of a critical method and its relevance to the critique of global capital.

In this paper we identify elements in Marx´s economic and political writings that are relevant to contemporary critical discourse analysis (CDA). We argue that Marx can be seen to be engaging in a form of discourse analysis. We identify the elements in Marx´s historical materialist method that support such a perspective, and exemplify these in a longitudinal comparison of Marx´s texts.

Are combination forecasts of S&P 500 volatility statistically superior?

Forecasting volatility has received a great deal of research attention, with the relative performances of econometric model based and option implied volatility forecasts often being considered. While many studies find that implied volatility is the pre-ferred approach, a number of issues remain unresolved, including the relative merit of combining forecasts and whether the relative performances of various forecasts are statistically different. By utilising recent econometric advances, this paper considers whether combination forecasts of S&P 500 volatility are statistically superior to a wide range of model based forecasts and implied volatility. It is found that a combination of model based forecasts is the dominant approach, indicating that the implied volatility cannot simply be viewed as a combination of various model based forecasts. Therefore, while often viewed as a superior volatility forecast, the implied volatility is in fact an inferior forecast of S&P 500 volatility relative to model-based forecasts.

The jump component of S&P 500 volatility and the VIX index

Much research has investigated the differences between option implied volatilities and econometric model-based forecasts. Implied volatility is a market determined forecast, in contrast to model-based forecasts that employ some degree of smoothing of past volatility to generate forecasts. Implied volatility has the potential to reflect information that a model-based forecast could not. This paper considers two issues relating to the informational content of the S&P 500 VIX implied volatility index. First, whether it subsumes information on how historical jump activity contributed to the price volatility, followed by whether the VIX reflects any incremental information pertaining to future jump activity relative to model-based forecasts. It is found that the VIX index both subsumes information relating to past jump contributions to total volatility and reflects incremental information pertaining to future jump activity. This issue has not been examined previously and expands our understanding of how option markets form their volatility forecasts.