Longitudinal evaluations of student satisfaction with a postgraduate unit using importance-performance analysis

The Australian tourism tertiary education sector operates in a competitive and dynamic environment, which necessitates a market orientation to be successful. Academic staff and management in the sector must regularly assess the perceptions of prospective and current students and monitor the satisfaction levels of current students. This study is concerned with the setting and monitoring of satisfaction levels of current students, reporting the results of three longitudinal investigations of student satisfaction in a postgraduate unit. The study also addresses a limitation of a university’s generic teaching evaluation instrument. Importance-Performance Analysis (IPA) has been recommended as a simple but effective tool for overcoming the deficiencies of many student evaluation studies, which have generally measured only attribute performance at the end of a semester. IPA was used to compare student expectations of the unit at the beginning of a semester with their perceptions of performance 10 weeks later. The first stage documented key benchmarks for which amendments to the unit based on student feedback could be evaluated during subsequent teaching periods.

Marital loss, mental health and the role of perceived social support : findings from six waves of an Australian population based panel study

Objectives: To investigate the impact of transitions out of marriage (separation, widowhood) on the self reported mental health of men and women, and examine whether perceptions of social support play an intervening role. ---------- Methods: The analysis used six waves (2001–06) of an Australian population based panel study, with an analytical sample of 3017 men and 3225 women. Mental health was measured using the MHI-5 scale scored 0–100 (α=0.97), with a higher score indicating better mental health. Perceptions of social support were measured using a 10-item scale ranging from 10 to 70 (α=0.79), with a higher score indicating higher perceived social support. A linear mixed model for longitudinal data was used, with lags for marital status, mental health and social support. ---------- Results: After adjustment for social characteristics there was a decline in mental health for men who separated (−5.79 points) or widowed (−7.63 points), compared to men who remained married. Similar declines in mental health were found for women who separated (−6.65 points) or became widowed (−9.28 points). The inclusion of perceived social support in the models suggested a small mediation effect of social support for mental health with marital loss. Interactions between perceived social support and marital transitions showed a strong moderating effect for men who became widowed. No significant interactions were found for women. ---------- Conclusion: Marital loss significantly decreased mental health. Increasing, or maintaining, high levels of social support has the potential to improve widowed men's mental health immediately after the death of their spouse.

Measurement of affect during simulation-based training

Training designed to support and strengthen higher-order mental abilities now often involves immersion in Virtual Reality where dangerous real world scenarios can be safely replicated. However despite the growing popularity of advanced training simulations, methods for evaluating their use rely heavily on subjective measures or analysis of final outcomes. Without dynamic, objective performance measures the outcome of training in terms of impact on cognitive skills and ability to transfer newly acquired skills to the real world is unknown. The relationship between affective intensity and cognitive learning provides a potential new approach to ensure the processing of cognitions which occur prior to final outcomes, such as problem-solving and decision-making, are adequately evaluated. This paper describes the technical aspects of pilot work recently undertaken to develop a new measurement tool designed to objectively track individual affect levels during simulation-based training.

Ontology-based image annotation

With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

Paradigm shifters : tricksters and cultural science

This paper seeks to link anthropological and economic treatments of the process of innovation and change, not only within a given ‘complex system’ (e.g. a cosmology; an industry) but also between systems (e.g. cultural and economic systems; but also divine and human systems). The role of the ‘Go-Between’ is considered, both in the anthropological figure of the Trickster (Hyde 1998) and in the Schumpeterian entrepreneur. Both figures parlay appetite (economic wants) into meaning (cultural signs). Both practice a form of creativity based on deception, ‘creative destruction’; renewal by disruption and needs-must adaptation. The disciplinary purpose of the paper is to try to bridge two otherwise disconnected domains – cultural studies and evolutionary economics – by showing that the traditional methods of the humanities (e.g. anthropological, textual and historical analysis) have explanatory force in the context of economic actions and complex-system evolutionary dynamics. The objective is to understand creative innovation as a general cultural attribute rather than one restricted only to accredited experts such as artists; thus to theorise creativity as a form of emergence for dynamic adaptive systems. In this context, change is led by ‘paradigm shifters’ – tricksters and entrepreneurs who create new meanings out of the clash of difference, including the clash of mutually untranslatable communication systems (language, media, culture).

Project-based IHRM : the emerging approach for the post-GFC world?

This paper reviews some past emphases in IHRM, and recommends that IHR teachers and practitioners consider using project management methodologies to tighten the focus of our diverse activities.

Numerical evaluation of pollutant dispersion at a toll plaza based on system dynamics and Computational Fluid Dynamics models

The health of tollbooth workers is seriously threatened by long-term exposure to polluted air from vehicle exhausts. Using traffic data collected at a toll plaza, vehicle movements were simulated by a system dynamics model with different traffic volumes and toll collection procedures. This allowed the average travel time of vehicles to be calculated. A three-dimension Computational Fluid Dynamics (CFD) model was used with a k–ε turbulence model to simulate pollutant dispersion at the toll plaza for different traffic volumes and toll collection procedures. It was shown that pollutant concentration around tollbooths increases as traffic volume increases. Whether traffic volume is low or high (1500 vehicles/h or 2500 vehicles/h), pollutant concentration decreases if electronic toll collection (ETC) is adopted. In addition, pollutant concentration around tollbooths decreases as the proportion of ETC-equipped vehicles increases. However, if the proportion of ETC-equipped vehicles is very low and the traffic volume is not heavy, then pollutant concentration increases as the number of ETC lanes increases.

Unaided stereo vision based pose estimation

This paper presents the development of a low-cost sensor platform for use in ground-based visual pose estimation and scene mapping tasks. We seek to develop a technical solution using low-cost vision hardware that allows us to accurately estimate robot position for SLAM tasks. We present results from the application of a vision based pose estimation technique to simultaneously determine camera poses and scene structure. The results are generated from a dataset gathered traversing a local road at the St Lucia Campus of the University of Queensland. We show the accuracy of the pose estimation over a 1.6km trajectory in relation to GPS ground truth.

Knowledge-based development for cities and societies : integrated multi-level approaches

Over the past twenty years, the conventional knowledge management approach has evolved into a strategic management approach that has found applications and opportunities outside of business, in society at large, through education, urban development, governance, and healthcare, amongst others. Knowledge-Based Development for Cities and Socieities: Integrated Multi-Level Approaches enlightens the concepts and challenges of knowledge management for both urban environments and entire regions, enhancing the expertise and knowledge of scholars, resdearchers, practitioners, managers and urban developers in the development of successful knowledge-based development policies, creation of knowledte cities and prosperous knowledge societies. This reference creates large knowledge base for scholars, managers and urban developers and increases the awareness of the role of knowledge cities and knowledge socieiteis in the knowledge era, as well as of the challenges and opportunities for future research.

Pattern-Based Evaluation of Scientific Workflow Management Systems

In recent years several scientific Workflow Management Systems (WfMSs) have been developed with the aim to automate large scale scientific experiments. As yet, many offerings have been developed, but none of them has been promoted as an accepted standard. In this paper we propose a pattern-based evaluation of three among the most widely used scientific WfMSs: Kepler, Taverna and Triana. The aim is to compare them with traditional business WfMSs, emphasizing the strengths and deficiencies of both systems. Moreover, a set of new patterns is defined from the analysis of the three considered systems.

An evidence-based approach to professional development planning in large state educational systems

This paper presents a systems-level approach for adjudicating the prioritization, selection, and planning of inservcie professional development (PD) for teachers. We present a step-by-step model for documenting and assessing system-wide 'bids' for professional development programs

Theoretical analysis of serrated chip formation based on ideal models in high speed cutting

In this paper, two ideal formation models of serrated chips, the symmetric formation model and the unilateral right-angle formation model, have been established for the first time. Based on the ideal models and related adiabatic shear theory of serrated chip formation, the theoretical relationship among average tooth pitch, average tooth height and chip thickness are obtained. Further, the theoretical relation of the passivation coefficient of chip's sawtooth and the chip thickness compression ratio is deduced as well. The comparison between these theoretical prediction curves and experimental data shows good agreement, which well validates the robustness of the ideal chip formation models and the correctness of the theoretical deducing analysis. The proposed ideal models may have provided a simple but effective theoretical basis for succeeding research on serrated chip morphology. Finally, the influences of most principal cutting factors on serrated chip formation are discussed on the basis of a series of finite element simulation results for practical advices of controlling serrated chips in engineering application.

Working together for Toby : early childhood student teachers engaging in collaborative problem-based learning around child abuse and neglect

Early childhood teacher education programs have a responsibility, amongst many, to prepare teachers for decision-making on real world issues, such as child abuse and neglect. Their repertoire of skills can be enhanced by engaging with others, either face-to-face or online, in authentic problem-based learning. This paper draws on a study of early childhood student teachers who engaged in an authentic learning experience, which was to consider and to suggest how they would act upon a real-life case of child abuse encountered in an early childhood classroom in Queensland. This was the case of Toby (a pseudonym), who was suspected of being physically abused at home. Students drew upon relevant legislation, policy and resource materials to tackle Toby’s case. The paper provides evidence of students grappling with the complexity of a child abuse case and establishing, through collaboration with others, a proactive course of action. The paper has a dual focus. First, it discusses the pedagogical context in which early childhood student teachers deal with issues of child abuse and neglect in the course of their teacher education program. Second, it examines evidence of students engaging in collaborative problem-solving around issues of child abuse and neglect and teachers’ responsibilities, both legal and professional, to the children and families they work with. Early childhood policy-makers, practitioners and teacher educators are challenged to consider how early childhood teachers are best equipped to deal with child protection and early intervention.

Structure of selected basic zinc/copper (II) phosphate minerals based upon near-infrared spectroscopy : implications for hydrogen bonding

The NIR spectra of reichenbachite, scholzite and parascholzite have been studied at 298 K. The spectra of the minerals are different, in line with composition and crystal structural variations. Cation substitution effects are significant in their electronic spectra and three distinctly different electronic transition bands are observed in the near-infrared spectra at high wavenumbers in the 12000-7600 cm-1 spectral region. Reichenbachite electronic spectrum is characterised by Cu(II) transition bands at 9755 and 7520 cm-1. A broad spectral feature observed for ferrous ion in the 12000-9000 cm-1 region both in scholzite and parascholzite. Some what similarities in the vibrational spectra of the three phosphate minerals are observed particularly in the OH stretching region. The observation of strong band at 5090 cm-1 indicates strong hydrogen bonding in the structure of the dimorphs, scholzite and parascholzite. The three phosphates exhibit overlapping bands in the 4800-4000 cm-1 region resulting from the combinations of vibrational modes of (PO4)3- units.

Developing a knowledge-based urban development analysis framework : the case of multimedia super corridor, Malaysia

Purpose: In the global knowledge economy, investment in knowledge-intensive industries and information and communication technology (ICT) infrastructures are seen as significant factors in improving the overall socio-economic fabric of cities. Consequently knowledge-based urban development (KBUD) has become a new paradigm in urban planning and development, for increasing the welfare and competitiveness of cities and regions. The paper discusses the critical connections between KBUD strategies and knowledge-intensive industries and ICT infrastructures. In particular, it investigates the application of the knowledge-based urban development concept by discussing one of South East Asia’s large scale manifestations of KBUD; Malaysia’s Multimedia Super Corridor. ----- ----- Design/methodology/approach: The paper provides a review of the KBUD concept and develops a knowledge-based urban development assessment framework to provide a clearer understanding of development and evolution of KBUD manifestations. Subsequently the paper investigates the implementation of the KBUD concept within the Malaysian context, and particularly the Multimedia Super Corridor (MSC). ----- ----- Originality/value: The paper, with its KBUD assessment framework, scrutinises Malaysia’s experince; providing an overview of the MSC project and discussion of the case findings. The development and evolution of the MSC is viewed with regard to KBUD policy implementation, infrastructural implications, and the agencies involved in the development and management of the MSC. ----- ----- Practical implications: The emergence of the knowledge economy, together with the issues of globalisation and rapid urbanisation, have created an urgent need for urban planners to explore new ways of strategising planning and development that encompasses the needs and requirements of the knowledge economy and society. In light of the literature and MSC case findings, the paper provides generic recommendations, on the orchestration of knowledge-based urban development, for other cities and regions seeking to transform to the knowledge economy.