Enhancing students' self-concepts and related constructs: A critical longitudinal analysis capitalising on and combining promising enhancement techniques for educational settings

Enhancing children's self-concepts is widely accepted as a critical educational outcome of schooling and is postulated as a mediating variable that facilitates the attainment of other desired outcomes such as improved academic achievement. Despite considerable advances in self-concept research, there has been limited progress in devising teacher-administered enhancement interventions. This is unfortunate as teachers are crucial change agents during important developmental periods when self-concept is formed. The primary aim of the present investigation is to build on the promising features of previous self-concept enhancement studies by: (a) combining two exciting research directions developed by Burnett and Craven to develop a potentially powerful cognitive-based intervention; (b) incorporating recent developments in theory and measurement to ensure that the multidimensionality of self-concept is accounted for in the research design; (c) fully investigating the effects of a potentially strong cognitive intervention on reading, mathematics, school and learning self-concepts by using a large sample size and a sophisticated research design; (d) evaluating the effects of the intervention on affective and cognitive subcomponents of reading, mathematics, school and learning self-concepts over time to test for differential effects of the intervention; (e) modifying and extending current procedures to maximise the successful implementation of a teacher-mediated intervention in a naturalistic setting by incorporating sophisticated teacher training as suggested by Hattie (1992) and including an assessment of the efficacy of implementation; and (f) examining the durability of effects associated with the intervention.

Paramedic knowledge of infectious disease aetiology and transmission in an Australian Emergency Medical System

Introduction: Paramedics and other emergency health workers are exposed to infectious disease particularly when undertaking exposure-prone procedures as a component of their everyday practice. This study examined paramedic knowledge of infectious disease aetiology and transmission in the pre-hospital care environment.--------- Methods: A mail survey of paramedics from an Australian ambulance service (n=2274) was conducted.--------- Results: With a response rate of 55.3% (1258/2274), the study demonstrated that paramedic knowledge of infectious disease aetiology and modes of transmission was poor. Of the 25 infectious diseases included in the survey, only three aetiological agents were correctly identified by at least 80% of respondents. The most accurate responses for aetiology of individual infectious diseases were for HIV/AIDS (91.4%), influenza (87.4%), and hepatitis B (85.7%). Poorest results were observed for pertussis, infectious mononucleosis, leprosy, dengue fever, Japanese B encephalitis and vancomycin resistant enterococcus (VRE), all with less than half the sample providing a correct response. Modes of transmission of significant infectious diseases were also assessed. Most accurate responses were found for HIV/AIDS (85.8%), salmonella (81.9%) and influenza (80.1%). Poorest results were observed for infectious mononucleosis, diphtheria, shigella, Japanese B encephalitis, vancomycin resistant enterococcus, meningococcal meningitis, rubella and infectious mononucleosis, with less than a third of the sample providing a correct response.--------- Conclusions: Results suggest that knowledge of aetiology and transmission of infectious disease is generally poor amongst paramedics. A comprehensive in-service education infection control programs for paramedics with emphasis on infectious disease aetiology and transmission is recommended.

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

A user driven data mining process model and learning system

This paper deals with the problem of using the data mining models in a real-world situation where the user can not provide all the inputs with which the predictive model is built. A learning system framework, Query Based Learning System (QBLS), is developed for improving the performance of the predictive models in practice where not all inputs are available for querying to the system. The automatic feature selection algorithm called Query Based Feature Selection (QBFS) is developed for selecting features to obtain a balance between the relative minimum subset of features and the relative maximum classification accuracy. Performance of the QBLS system and the QBFS algorithm is successfully demonstrated with a real-world application

HVAC system size – getting it right

There is evidence that many heating, ventilating & air conditioning (HVAC) systems, installed in larger buildings, have more capacity than is ever required to keep the occupants comfortable. This paper explores the reasons why this can occur, by examining a typical brief/design/documentation process. Over-sized HVAC systems cost more to install and operate and may not be able to control thermal comfort as well as a “right-sized” system. These impacts are evaluated, where data exists. Finally, some suggestions are developed to minimise both the extent of, and the negative impacts of, HVAC system over-sizing, for example: • Challenge “rules of thumb” and/or brief requirements which may be out of date. • Conduct an accurate load estimate, using AIRAH design data, specific to project location, and then resist the temptation to apply “safety factors • Use a load estimation program that accounts for thermal storage and diversification of peak loads for each zone and air handling system. • Select chiller sizes and staged or variable speed pumps and fans to ensure good part load performance. • Allow for unknown future tenancies by designing flexibility into the system, not by over-sizing. For example, generous sizing of distribution pipework and ductwork will allow available capacity to be redistributed. • Provide an auxiliary tenant condenser water loop to handle high load areas. • Consider using an Integrated Design Process, build an integrated load and energy use simulation model and test different operational scenarios • Use comprehensive Life Cycle Cost analysis for selection of the most optimal design solutions. This paper is an interim report on the findings of CRC-CI project 2002-051-B, Right-Sizing HVAC Systems, which is due for completion in January 2006.

Inward exporting of professional services : lessons from an exploratory study of Australian educational firms

Inward export activities for services companies have been largely neglected in the literature. Little is known about how professional service firms export to overseas consumers who travel to the domestic market of the firm. This study utilizes a resource-based perspective (RBV) to explore the main barriers and drivers of export performance for professional education services. A case study of Australia’s education industry, as well as interviews with executives from four Australian education institutions, was conducted. Findings show that inward exporters confront most barriers in the domestic market where the service is provided, and drivers of export performance combine firm- and country-specific resources.

The appeal of the International Baccalaureate in Australia’s educational market: A curriculum of choice for mobile futures

In Australia there is growing interest in a national curriculum to replace the variety of matriculation credentials managed by State Education departments, ostensibly to address increasing population mobility. Meanwhile, the International Baccalaureate (IB) is attracting increasing interest and enrolments in State and private schools in Australia, and has been considered as one possible model for a proposed Australian Certificate of Education. This paper will review the construction of this curriculum in Australian public discourse as an alternative frame for producing citizens, and ask why this design appeals now, to whom, and how the phenomenon of its growing appeal might inform national curricular debates. The IB’s emergence is understood with reference to the larger context of neo-liberal marketization policies, neo-conservative claims on the curriculum and middle class strategy. The paper draws on public domain documents from the IB Organisation and newspaper reportage to demonstrate how the IB is constructed for public consumption in Australia.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Hybrid system simulation of computer control applications over communication networks

Discrete event-driven simulations of digital communication networks have been used widely. However, it is difficult to use a network simulator to simulate a hybrid system in which some objects are not discrete event-driven but are continuous time-driven. A networked control system (NCS) is such an application, in which physical process dynamics are continuous by nature. We have designed and implemented a hybrid simulation environment which effectively integrates models of continuous-time plant processes and discrete-event communication networks by extending the open source network simulator NS-2. To do this a synchronisation mechanism was developed to connect a continuous plant simulation with a discrete network simulation. Furthermore, for evaluating co-design approaches in an NCS environment, a piggybacking method was adopted to allow the control period to be adjusted during simulations. The effectiveness of the technique is demonstrated through case studies which simulate a networked control scenario in which the communication and control system properties are defined explicitly.

Combination strategies for a factor analysis phone-conditioned speaker verification system

This work aims to take advantage of recent developments in joint factor analysis (JFA) in the context of a phonetically conditioned GMM speaker verification system. Previous work has shown performance advantages through phonetic conditioning, but this has not been shown to date with the JFA framework. Our focus is particularly on strategies for combining the phone-conditioned systems. We show that the classic fusion of the scores is suboptimal when using multiple GMM systems. We investigate several combination strategies in the model space, and demonstrate improvement over score-level combination as well as over a non-phonetic baseline system. This work was conducted during the 2008 CLSP Workshop at Johns Hopkins University.