Academic career development workshop for research students and early career academics

For research students and early career academics, universities offer resources that help develop their research skills – for example, critical theory development, literature reviews, research methods, data analysis, writing skills, etc. However, building a successful career in academia poses a wide range of new challenges in addition to the pure academic craft of research. The resources and resilience one needs in order to shape an academic career path often appear ambiguous, particularly in the innately transformative field of Internet research. In response to feedback from AoIR members, this full-day workshop seeks to address this concern by offering a supportive and constructive environment to discuss career development related issues that are of specific interest to research students and early career academics.

The contribution of physical activity and sedentary behaviours to the growth and development of children and adolescents : implications for overweight and obesity

The obesity epidemic is a global trend and is of particular concern in children. Recent reports have highlighted the severity of obesity in children by suggesting: “today's generation of children will be the first for over a century for whom life expectancy falls.” This review assesses the evidence that identifies the important role of physical activity in the growth, development and physical health of young people, owing to its numerous physical and psychological health benefits. Key issues, such as “does a sedentary lifestyle automatically lead to obesity” and “are levels of physical activity in today's children less than physical activity levels in children from previous generations?”, are also discussed. Today's environment enforces an inactive lifestyle that is likely to contribute to a positive energy balance and childhood obesity. Whether a child or adolescent, the evidence is conclusive that physical activity is conducive to a healthy lifestyle and prevention of disease. Habitual physical activity established during the early years may provide the greatest likelihood of impact on mortality and longevity. It is evident that environmental factors need to change if physical activity strategies are to have a significant impact on increasing habitual physical activity levels in children and adolescents. There is also a need for more evidence-based physical activity guidelines for children of all ages. Efforts should be concentrated on facilitating an active lifestyle for children in an attempt to put a stop to the increasing prevalence of obese children

A prospective study of personality features predictive of early adolescent alcohol misuse

Personality factors implicated in alcohol misuse have been extensively investigated in adult populations. Fewer studies have clarified the robustness of personality dimensions in predicting early onset alcohol misuse in adolescence. The aim of this study was to examine the predictive utility of two prominent models of personality (Cloninger, 1987; Eysenck & Eysenck, 1975) in emergent alcohol misuse in adolescence. One hundred and 92 secondary school students (mean age = 13.8 years, SD = 0.5) were administered measures of personality (Revised Junior Eysenck Personality Questionnaire – abbreviated; Temperament scale of Junior Temperament and Character Inventory) and drinking behavior (quantity and frequency of consumption, Alcohol Use Disorders Identification Test) at Time 1. At 12-month follow-up, 170 students (88.5%) were retained. Hierarchical multiple regressions revealed the dimensions of psychoticism, extraversion, and Novelty-Seeking to be the most powerful predictors of future alcohol misuse in adolescents. Results provide support for the etiological relevance of these dimensions in the development of early onset alcohol misuse. Findings can be used to develop early intervention programs that target personality risk factors for alcohol misuse in high-risk youth.

On PAR : Using Participatory Action Research to Improve Early Intervention

This manual is designed to assist human service practitioners and agencies, and the communities they work with, to enhance their skills in undertaking Participatory Action Research, and, in so doing improve the situations of people who are vulnerable. It utilises insights derived from a number of Australian Government funded programs, most notably Reconnect, NAYSS and Household Organisational Management Expenses (HOME) Advice.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

A world elsewhere : virtual reality, motion capture and early modern theatre

This paper investigates virtual reality representations of the 1599 Boar’s Head Theatre and the Rose Theatre, two renaissance places and spaces. These models become a “world elsewhere” in that they represent virtual recreations of these venues in as much detail as possible. The models are based on accurate archeological and theatre historical records and are easy to navigate particularly for current use. This paper demonstrates the ways in which these models can be instructive for reading theatre today. More importantly we introduce human figures onto the stage via motion capture which allows us to explore the potential between space, actor and environment. This facilitates a new way of thinking about early modern playwrights’ “attitudes to locality and localities large and small”. These venues are thus activated to intersect productively with early modern studies so that the paper can test the historical and contemporary limits of such research.

Art in early childhood : the discourse of 'proper' teaching

This thesis is a problematisation of the teaching of art to young children. To problematise a domain of social endeavour, is, in Michel Foucault's terms, to ask how we come to believe that "something ... can and must be thought" (Foucault, 1985:7). The aim is to document what counts (i.e., what is sayable, thinkable, feelable) as proper art teaching in Queensland at this point ofhistorical time. In this sense, the thesis is a departure from more recognisable research on 'more effective' teaching, including critical studies of art teaching and early childhood teaching. It treats 'good teaching' as an effect of moral training made possible through disciplinary discourses organised around certain epistemic rules at a particular place and time. There are four key tasks accomplished within the thesis. The first is to describe an event which is not easily resolved by means of orthodox theories or explanations, either liberal-humanist or critical ones. The second is to indicate how poststructuralist understandings of the self and social practice enable fresh engagements with uneasy pedagogical moments. What follows this discussion is the documentation of an empirical investigation that was made into texts generated by early childhood teachers, artists and parents about what constitutes 'good practice' in art teaching. Twenty-two participants produced text to tell and re-tell the meaning of 'proper' art education, from different subject positions. Rather than attempting to capture 'typical' representations of art education in the early years, a pool of 'exemplary' teachers, artists and parents were chosen, using "purposeful sampling", and from this pool, three videos were filmed and later discussed by the audience of participants. The fourth aspect of the thesis involves developing a means of analysing these texts in such a way as to allow a 're-description' of the field of art teaching by attempting to foreground the epistemic rules through which such teacher-generated texts come to count as true ie, as propriety in art pedagogy. This analysis drew on Donna Haraway's (1995) understanding of 'ironic' categorisation to hold the tensions within the propositions inside the categories of analysis rather than setting these up as discursive oppositions. The analysis is therefore ironic in the sense that Richard Rorty (1989) understands the term to apply to social scientific research. Three 'ironic' categories were argued to inform the discursive construction of 'proper' art teaching. It is argued that a teacher should (a) Teach without teaching; (b) Manufacture the natural; and (c) Train for creativity. These ironic categories work to undo modernist assumptions about theory/practice gaps and finding a 'balance' between oppositional binary terms. They were produced through a discourse theoretical reading of the texts generated by the participants in the study, texts that these same individuals use as a means of discipline and self-training as they work to teach properly. In arguing the usefulness of such approaches to empirical data analysis, the thesis challenges early childhood research in arts education, in relation to its capacity to deal with ambiguity and to acknowledge contradiction in the work of teachers and in their explanations for what they do. It works as a challenge at a range of levels - at the level of theorising, of method and of analysis. In opening up thinking about normalised categories, and questioning traditional Western philosophy and the grand narratives of early childhood art pedagogy, it makes a space for re-thinking art pedagogy as "a game oftruth and error" (Foucault, 1985). In doing so, it opens up a space for thinking how art education might be otherwise.