Making sense of an everyday science text : linguistic, visual and spatial design

In this article, we take a close look at the literacy demands of one task from the ‘Marvellous Micro-organisms Stage 3 Life and Living’ Primary Connections unit (Australian Academy of Science, 2005). One lesson from the unit, ‘Exploring Bread’, (pp 4-8) asks students to ‘use bread labels to locate ingredient information and synthesise understanding of bread ingredients’. We draw upon a framework offered by the New London Group (2000), that of linguistic, visual and spatial design, to consider in more detail three bread wrappers and from there the complex literacies that students need to interrelate to undertake the required task. Our findings are that although bread wrappers are an example of an everyday science text, their linguistic, visual and spatial designs and their interrelationship are not trivial. We conclude by reinforcing the need for teachers of science to also consider how the complex design elements of everyday science texts and their interrelated literacies are made visible through instructional practice.

Teacher-child relationship quality for young children with parent reported language concerns

Previous research has demonstrated the importance of the qualities of the teacher-child relationship on children’s development. Close teacher-child relationships are especially important for children at risk. Positive relationships have been shown to have beneficial effects on children’s social and academic development (Birch & Ladd, 1997; Pianta & Stuhlman, 2004). Children with language difficulties are likely to face increased risks with regard to long term social and academic outcomes. The purpose of the current research was to gain greater understanding of the qualities of teacher-child relationships for young children with parent reported language concerns. The research analyses completed for this thesis involved the use of data from the public-access database of Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC). LSAC is a longitudinal study involving a nationally representative sample of 10,000 Australian children. Data are being collected biennially from 2004 (Wave 1 data collection) until 2010 (Wave 4 data collection). LSAC has a cross-sequential research design involving two cohorts, an infant cohort (0-1 year at age of recruitment) and a kindergarten cohort (4-5 years at age of recruitment). Two studies are reported in this thesis using data for the LSAC Kindergarten Cohort which had 4983 child participants at recruitment. Study 1 used Wave 1 data to identify the differences between teacher-child relationship qualities for children with parent reported language concerns and their peers. Children identified by parents for whom concerns were held about their receptive and expressive language, as measured by items from the Parents’ Evaluation of Developmental Status (PEDS) (Glascoe, 2000) were the target (at risk) group in the study (n = 210). A matched case control group of peers (n = 210), matched on the child characteristics of sex, age, cultural and linguistic differences (CALD), and socio-economic positioning (SEP), were the comparison group for this analysis. Teacher-child relationship quality was measured by teacher reports on the Closeness and Conflict scales from the short version of the Student-Teacher Relationship Scale (STRS) (Pianta, 2001). There were statistically significant differences in the levels of closeness and conflict between the two groups. The target group had relationships with their teachers that had lower levels of closeness and higher levels of conflict than the control group. Study 2 reports analyses that examined the stability of the qualities of the teacher-child relationships at Wave 1 (4-5 years) and the qualities of the teacher-child relationships at Wave 2 (6-7 years). This time frame crosses the period of the children’s transition to school. The study examined whether early patterns in the qualities of the teacher-child relationship for children with parent reported language concerns at Wave 1 predicted the qualities of the teacher-child relationship outcomes in the early years of formal school. The sample for this study consisted of the group of children identified with PEDS language concerns at Wave 1 who also had teacher report data at Wave 2 (n = 145). Teacher-child relationship quality at Wave 1 and Wave 2 was again measured by the STRS scales of Closeness and Conflict. Results from multiple regression models indicated that teacher-child relationship quality at Wave 1 significantly contributed to the prediction of the quality of the teacher-child relationship at Wave 2, beyond other predictor variables included in the regression models. Specifically, Wave 1 STRS Closeness scores were the most significant predictor for STRS Closeness scores at Wave 2, while Wave 1 STRS Conflict scores were the only significant predictor for Wave 2 STRS Conflict outcomes. These results indicate that the qualities of the teacher-child relationship experienced prior to school by children with parent reported language concerns remained stable across transitions into formal schooling at which time the child had a different teacher. The results of these studies provide valuable insight into the nature of teacher-child relationship quality for young children with parent reported language concerns. These children experienced teacher-child relationships of a lower quality when compared with peers and, additionally, the qualities of these relationships prior to formal schooling were predictive of the qualities of the relationships in the early years of formal schooling. This raises concerns, given the increased risks of poorer social and academic outcomes already faced by children with language difficulties, that these early teacher-child relationships have an impact on future teacher-child relationships. Results of these studies are discussed with these considerations in mind and also discussed in terms of the implications for educational theory, policy and practice.

Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Using Trauma Injury Severity Score (TRISS) variables to predict length of hospital stay following trauma in New Zealand

Aim – To develop and assess the predictive capabilities of a statistical model that relates routinely collected Trauma Injury Severity Score (TRISS) variables to length of hospital stay (LOS) in survivors of traumatic injury. Method – Retrospective cohort study of adults who sustained a serious traumatic injury, and who survived until discharge from Auckland City, Middlemore, Waikato, or North Shore Hospitals between 2002 and 2006. Cubic-root transformed LOS was analysed using two-level mixed-effects regression models. Results – 1498 eligible patients were identified, 1446 (97%) injured from a blunt mechanism and 52 (3%) from a penetrating mechanism. For blunt mechanism trauma, 1096 (76%) were male, average age was 37 years (range: 15-94 years), and LOS and TRISS score information was available for 1362 patients. Spearman’s correlation and the median absolute prediction error between LOS and the original TRISS model was ρ=0.31 and 10.8 days, respectively, and between LOS and the final multivariable two-level mixed-effects regression model was ρ=0.38 and 6.0 days, respectively. Insufficient data were available for the analysis of penetrating mechanism models. Conclusions – Neither the original TRISS model nor the refined model has sufficient ability to accurately or reliably predict LOS. Additional predictor variables for LOS and other indicators for morbidity need to be considered.

A comparative study of manufacturing practices and performance variables

The reported study was conducted to compare and contrast current manufacturing practices between two countries, Australia and Malaysia, and identify the practices that significantly influence their manufacturing performances. The results are based on data collected from surveys using a standard questionnaire in both countries. Evidence indicates that product quality and reliability is the main competitive factor for manufacturers. Maintaining a supplier rating system and regularly updating it with field failure and warranty data and making use of product data management are found to be effective manufacturing practices. In terms of the investigated manufacturing performance, Australian manufacturers are marginally ahead of their Malaysian counterparts. However, Malaysian manufacturers came out ahead on most dimensions of advanced quality and manufacturing practices, particularly in the adoption of product data management, effective supply chains and relationships with suppliers and customers.

Generating rules with predicates, terms and variables from the pruned neural networks

Artificial neural networks (ANN) have demonstrated good predictive performance in a wide range of applications. They are, however, not considered sufficient for knowledge representation because of their inability to represent the reasoning process succinctly. This paper proposes a novel methodology Gyan that represents the knowledge of a trained network in the form of restricted first-order predicate rules. The empirical results demonstrate that an equivalent symbolic interpretation in the form of rules with predicates, terms and variables can be derived describing the overall behaviour of the trained ANN with improved comprehensibility while maintaining the accuracy and fidelity of the propositional rules.

Distribution profiles of key weather variables in Australian capital cities : implications for energy efficient building design

Local climate is a critical element in the design of energy efficient buildings. In this paper, ten years of historical weather data in Australia's eight capital cities were profiled and analysed to characterize the variations of climatic variables in Australia. The method of descriptive statistics was employed. Either the pattern of cumulative distribution and/or the profile of percentage distribution are presented. It was found that although weather variables vary with different locations, there is often a good, nearly linear relation between a weather variable and its cumulative percentage for the majority of middle part of the cumulative curves. By comparing the slopes of these distribution profiles, it may be possible to determine the relative range of changes of the particular weather variables for a given city. The implications of these distribution profiles of key weather variables on energy efficient building design are also discussed.