ePortfolios and eGovernment : from technology to the entrepreneurial self

We analyse the electronic portfolio (ePortfolio) in higher education policy and practice. While evangelical accounts of the ePortfolio celebrate its power as a new eLearning technology, we argue that it allows the mutually-reinforcing couple of neoliberalism and the enterprising self to function in ways in which individual difference can be presented, cultured and grown, all the time within a standardised framework which relentlessly polices the limits of the acceptable and unacceptable. We point to the ePortfolio as a practice of (self-) government, arguing that grander policy coalesces out of a halting, experimental set of technological instruments for thinking about how life should be lived.

Self-presentation and underachievement among young adolescents identified as gifted

Academically gifted students are recognised as possessing considerable achievement potential. Yet many gifted students fail to perform at a level commensurate with their ability. This phenomenon is known as underachievement and may have far-reaching personal and social costs. Underachievement is particularly prevalent during early adolescence, between the ages of 10 to 14 years, when declining levels of academic achievement are often apparent. Grouping for instructional purposes is advocated as a means of reducing underachievement for gifted students by providing opportunities for like-minded and like-ability individuals to learn together. Despite this, some gifted students continue to underachieve. For some, underachievement appears to be a deliberate choice making them a population of learners at-risk. This multiple case study examines the relationship between self-presentation and underachievement as experienced by three gifted adolescents. It reveals how students perceived and explained the discrepancy between their ability and performance. Further, the study identifies those self-presentation strategies adopted in response to underachievement. Findings may assist parents and educators to provide greater support for gifted adolescents.

Becoming a 'Bastion Against Tyranny' : Australian legal education and the government of the self

Research into legal education suggests that many students enter law school with ideals about using the law to achieve social change, but graduate with some cynicism regarding these ideals. It is often argued that law schools provide a negative, competitive, and conservative environment for students, pushing many away from social justice ideals towards more self-interested, vocational concerns. This article uses Michel Foucault’s work on the government of the self to suggest another way of understanding this process. It examines a range of prescriptive texts that provide students with advice about how to study law and ‘survive’ law school. In doing so, it posits that this apparent loss of social ideals does not necessarily always signify that the student has become politically conservative or has had a negative educational experience. While these legal personae may appear outwardly conservative, and indeed still reflect particular gendered or raced perspectives, by examining the messages that these texts offer students, this article suggests that an apparent loss of social ideals can be the result of a productive shaping of the self. The legal persona they fashion can incorporate social justice ideals and necessitate specific ways of acting on those ideals. This analysis adds to the growing body of research that uses Foucault’s work to rethink common narratives of power and the shaping of the self in legal education, and provides legal educators with new ways of reflecting on the effects of legal education.

Facet-controlled Self-assembly of ZnO Nanocrystals by Non-Hydrolytic Aminolysis and their Photodegradation Activities

We report a method for controlling the exposed facets and hence the dimensionality and shape of ZnO nanocrystals using a non-hydrolytic aminolysis synthesis route. The effects of changes to reaction conditions on ZnO formation were investigated and possible self-assembly mechanisms proposed. The crystal facet growth and hence morphologies of the ZnO nanocrystals were controlled by varying reaction temperature and the reactant ratio. Four distinct ZnO nanocrystal types were produced (nanocones, nanobullets, nanorods and nanoplates). The relative photocatalytic activities of the exposed facets of these ZnO nanostructures were also examined, which showed the activities obviously depended on the reactivity of exposed crystal facets in the order: {1011}>>{0001}, {1010}.

The relationship between chronic disease self-efficacy and nutritional status, functional ability and quality of life in older adults at risk of hospital readmission

Background and significance: Older adults with chronic diseases are at increasing risk of hospital admission and readmission. Approximately 75% of adults have at least one chronic condition, and the odds of developing a chronic condition increases with age. Chronic diseases consume about 70% of the total Australian health expenditure, and about 59% of hospital events for chronic conditions are potentially preventable. These figures have brought to light the importance of the management of chronic disease among the growing older population. Many studies have endeavoured to develop effective chronic disease management programs by applying social cognitive theory. However, limited studies have focused on chronic disease self-management in older adults at high risk of hospital readmission. Moreover, although the majority of studies have covered wide and valuable outcome measures, there is scant evidence on examining the fundamental health outcomes such as nutritional status, functional status and health-related quality of life. Aim: The aim of this research was to test social cognitive theory in relation to self-efficacy in managing chronic disease and three health outcomes, namely nutritional status, functional status, and health-related quality of life, in older adults at high risk of hospital readmission. Methods: A cross-sectional study design was employed for this research. Three studies were undertaken. Study One examined the nutritional status and validation of a nutritional screening tool; Study Two explored the relationships between participants. characteristics, self-efficacy beliefs, and health outcomes based on the study.s hypothesized model; Study Three tested a theoretical model based on social cognitive theory, which examines potential mechanisms of the mediation effects of social support and self-efficacy beliefs. One hundred and fifty-seven patients aged 65 years and older with a medical admission and at least one risk factor for readmission were recruited. Data were collected from medical records on demographics, medical history, and from self-report questionnaires. The nutrition data were collected by two registered nurses. For Study One, a contingency table and the kappa statistic was used to determine the validity of the Malnutrition Screening Tool. In Study Two, standard multiple regression, hierarchical multiple regression and logistic regression were undertaken to determine the significant influential predictors for the three health outcome measures. For Study Three, a structural equation modelling approach was taken to test the hypothesized self-efficacy model. Results: The findings of Study One suggested that a high prevalence of malnutrition continues to be a concern in older adults as the prevalence of malnutrition was 20.6% according to the Subjective Global Assessment. Additionally, the findings confirmed that the Malnutrition Screening Tool is a valid nutritional screening tool for hospitalized older adults at risk of readmission when compared to the Subjective Global Assessment with high sensitivity (94%), and specificity (89%) and substantial agreement between these two methods (k = .74, p < .001; 95% CI .62-.86). Analysis data for Study Two found that depressive symptoms and perceived social support were the two strongest influential factors for self-efficacy in managing chronic disease in a hierarchical multiple regression. Results of multivariable regression models suggested advancing age, depressive symptoms and less tangible support were three important predictors for malnutrition. In terms of functional status, a standard regression model found that social support was the strongest predictor for the Instrumental Activities of Daily Living, followed by self-efficacy in managing chronic disease. The results of standard multiple regression revealed that the number of hospital readmission risk factors adversely affected the physical component score, while depressive symptoms and self-efficacy beliefs were two significant predictors for the mental component score. In Study Three, the results of the structural equation modelling found that self-efficacy partially mediated the effect of health characteristics and depression on health-related quality of life. The health characteristics had strong direct effects on functional status and body mass index. The results also indicated that social support partially mediated the relationship between health characteristics and functional status. With regard to the joint effects of social support and self-efficacy, social support fully mediated the effect of health characteristics on self-efficacy, and self-efficacy partially mediated the effect of social support on functional status and health-related quality of life. The results also demonstrated that the models fitted the data well with relative high variance explained by the models, implying the hypothesized constructs under discussion were highly relevant, and hence the application for social cognitive theory in this context was supported. Conclusion: This thesis highlights the applicability of social cognitive theory on chronic disease self-management in older adults at risk of hospital readmission. Further studies are recommended to validate and continue to extend the development of social cognitive theory on chronic disease self-management in older adults to improve their nutritional and functional status, and health-related quality of life.

Transforming habitus: Changing self, changing school

Since 2004, Australian Indigenous (Aboriginal and Torres Strait Islander) students at a low socioeconomic area Australian urban secondary school have used participatory action research to investigate issues of disengagement and absenteeism among their peers. Their research revealed that Indigenous students, who made up about 8% to 10% of the school’s population lacked a sense of belonging to the school. The researchers also revealed an apparent official disregard of the academic or sporting achievements of Indigenous students and, more disturbingly, their presence within the school. The young researchers followed up their findings with action to address the issues. These actions have resulted in a positive change of culture across the whole school, with Indigenous students now able to express pride in their heritage and feel some degree of ownership of the school.

The quantum inspired modelling of changing attitudes and self-organising societies

We utilise the well-developed quantum decision models known to the QI community to create a higher order social decision making model. A simple Agent Based Model (ABM) of a society of agents with changing attitudes towards a social issue is presented, where the private attitudes of individuals in the system are represented using a geometric structure inspired by quantum theory. We track the changing attitudes of the members of that society, and their resulting propensities to act, or not, in a given social context. A number of new issues surrounding this "scaling up" of quantum decision theories are discussed, as well as new directions and opportunities.

Composite SaaS placement and resource optimization in Cloud computing using evolutionary algorithms

Software as a Service (SaaS) is gaining more and more attention from software users and providers recently. This has raised many new challenges to SaaS providers in providing better SaaSes that suit everyone needs at minimum costs. One of the emerging approaches in tackling this challenge is by delivering the SaaS as a composite SaaS. Delivering it in such an approach has a number of benefits, including flexible offering of the SaaS functions and decreased cost of subscription for users. However, this approach also introduces new problems for SaaS resource management in a Cloud data centre. We present the problem of composite SaaS resource management in Cloud data centre, specifically on its initial placement and resource optimization problems aiming at improving the SaaS performance based on its execution time as well as minimizing the resource usage. Our approach differs from existing literature because it addresses the problems resulting from composite SaaS characteristics, where we focus on the SaaS requirements, constraints and interdependencies. The problems are tackled using evolutionary algorithms. Experimental results demonstrate the efficiency and the scalability of the proposed algorithms.

Clustering composite SaaS components in cloud computing using a grouping genetic algorithm

Recently, Software as a Service (SaaS) in Cloud computing, has become more and more significant among software users and providers. To offer a SaaS with flexible functions at a low cost, SaaS providers have focused on the decomposition of the SaaS functionalities, or known as composite SaaS. This approach has introduced new challenges in SaaS resource management in data centres. One of the challenges is managing the resources allocated to the composite SaaS. Due to the dynamic environment of a Cloud data centre, resources that have been initially allocated to SaaS components may be overloaded or wasted. As such, reconfiguration for the components’ placement is triggered to maintain the performance of the composite SaaS. However, existing approaches often ignore the communication or dependencies between SaaS components in their implementation. In a composite SaaS, it is important to include these elements, as they will directly affect the performance of the SaaS. This paper will propose a Grouping Genetic Algorithm (GGA) for multiple composite SaaS application component clustering in Cloud computing that will address this gap. To the best of our knowledge, this is the first attempt to handle multiple composite SaaS reconfiguration placement in a dynamic Cloud environment. The experimental results demonstrate the feasibility and the scalability of the GGA.

The relationship between cognitive ability, insight and self-regulatory behaviors: Findings from the older driver population

Self-regulation is often promoted as a coping strategy that may allow older drivers to drive safely for longer. Self-regulation depends upon drivers making an accurate assessment of their own ability and having a willingness to practice self-regulatory behaviors to compensate for changes in ability. The current study explored the relationship between older drivers’ cognitive ability, their driving confidence and their use of self-regulation. An additional study aim was to explore the relationship between these factors and older drivers’ interest in driving programs. Seventy Australian drivers aged 65 years and over completed a questionnaire about their driving and a brief screening measure of cognitive ability (an untimed Clock Drawing Test). While all participants reported high levels of confidence regarding their driving ability, and agreed that they would continue driving in the foreseeable future, a notable proportion performed poorly on the Clock Drawing Test. Compared to older drivers who successfully completed the Clock Drawing Test, those who failed the cognitive test were significantly less likely to report driving self-regulation, and showed significantly less interest in being involved in driving programs. Older drivers with declining cognitive abilities may not be self-regulating their driving. This group also appears to be unlikely to self-refer to driving programs.

A parallel cooperative co-evolutionary genetic algorithm for the composite SaaS placement problem in Cloud computing

A composite SaaS (Software as a Service) is a software that is comprised of several software components and data components. The composite SaaS placement problem is to determine where each of the components should be deployed in a cloud computing environment such that the performance of the composite SaaS is optimal. From the computational point of view, the composite SaaS placement problem is a large-scale combinatorial optimization problem. Thus, an Iterative Cooperative Co-evolutionary Genetic Algorithm (ICCGA) was proposed. The ICCGA can find reasonable quality of solutions. However, its computation time is noticeably slow. Aiming at improving the computation time, we propose an unsynchronized Parallel Cooperative Co-evolutionary Genetic Algorithm (PCCGA) in this paper. Experimental results have shown that the PCCGA not only has quicker computation time, but also generates better quality of solutions than the ICCGA.