Course evaluation : reconfigurations for learning with learning management systems

The introduction of online delivery platforms such as learning management systems (LMS) in tertiary education has changed the methods and modes of curriculum delivery and communication. While course evaluation methods have also changed from paper-based in-class-administered methods to largely online-administered methods, the data collection instruments have remained unchanged. This paper reports on a small exploratory study of two tertiary-level courses. The study investigated why design of the instruments and methods to administer surveys in the courses are ineffective measures against the intrinsic characteristics of online learning. It reviewed the students' response rates of the conventional evaluations for the courses over an eight-year period. It then compared a newly developed online evaluation and the conventional methods over a two-year period. The results showed the response rates with the new evaluation method increased by more than 80% from the average of the conventional evaluations (below 30%), and the students' written feedback was more detailed and comprehensive than in the conventional evaluations. The study demonstrated the possibility that the LMS-based learning evaluation can be effective and efficient in terms of the quality of students' participation and engagement in their learning, and for an integrated pedagogical approach in an online learning environment.

Improving voltage profile of residential distribution systems using rooftop PVs and Battery Energy Storage systems

Large number of rooftop Photovoltaics (PVs) have turned traditional passive networks into active networks with intermittent and bidirectional power flow. A community based distribution network grid reinforcement process is proposed to address technical challenges associated with large integration of rooftop PVs. Probabilistic estimation of intermittent PV generation is considered. Depending on the network parameters such as the R/X ratio of distribution feeder, either reactive control from PVs or coordinated control of PVs and Battery Energy Storage (BES) has been proposed. Determination of BES capacity is one of the significant outcomes from the proposed method and several factors such as variation in PV installed capacity as well as participation from community members are analyzed. The proposed approach is convenient for the community members providing them flexibility of managing their integrated PV and BES systems

Digital Modeling, Integrated Project Delivery and Industry Transformation: An Australian Case Study

This research is focused on realizing productivity benefits for the delivery of transport infrastructure in the Australian construction industry through the use of building information modeling (BIM), virtual design and construction (VDC) and integrated project delivery (IPD). Specific objectives include: (I) building an understanding of the institutional environment, business systems and support mechanisms (e.g., training and skilling) which impact on the uptake of BIM/VDC; (II) gathering data to undertake a cross-country analysis of these environments; and (III) providing strategic and practical outcomes to guide the uptake of such processes in Australia. Activities which will inform this research include a review of academic literature and industry documentation, semi-formal interviews in Australia and Sweden, and a cross-country comparative analysis to determine factors affecting uptake and associated productivity improvements. These activities will seek to highlight the gaps between current-practice and best-practice which are impacting on widespread adoption of BIM/VDC and IPD. Early findings will be discussed with intended outcomes of this research being used to: inform a national public procurement strategy; provide guidelines for new contractual frameworks; and contribute to closing skill gaps. Keywords: building information modeling (BIM); virtual design and construction (VDC); integrated project delivery (IPD); transport infrastructure; Australia; procurement

Conceptual and statistical framework for a water quality component of the integrated report card for the Great Barrier Reef catchments

This report presents the final deliverable from the project titled Conceptual and statistical framework for a water quality component of an integrated report card’ funded by the Marine and Tropical Sciences Research Facility (MTSRF; Project 3.7.7). The key management driver of this, and a number of other MTSRF projects concerned with indicator development, is the requirement for state and federal government authorities and other stakeholders to provide robust assessments of the present ‘state’ or ‘health’ of regional ecosystems in the Great Barrier Reef (GBR) catchments and adjacent marine waters. An integrated report card format, that encompasses both biophysical and socioeconomic factors, is an appropriate framework through which to deliver these assessments and meet a variety of reporting requirements. It is now well recognised that a ‘report card’ format for environmental reporting is very effective for community and stakeholder communication and engagement, and can be a key driver in galvanising community and political commitment and action. Although a report card it needs to be understandable by all levels of the community, it also needs to be underpinned by sound, quality-assured science. In this regard this project was to develop approaches to address the statistical issues that arise from amalgamation or integration of sets of discrete indicators into a final score or assessment of the state of the system. In brief, the two main issues are (1) selecting, measuring and interpreting specific indicators that vary both in space and time, and (2) integrating a range of indicators in such a way as to provide a succinct but robust overview of the state of the system. Although there is considerable research and knowledge of the use of indicators to inform the management of ecological, social and economic systems, methods on how to best to integrate multiple disparate indicators remain poorly developed. Therefore the objective of this project was to (i) focus on statistical approaches aimed at ensuring that estimates of individual indicators are as robust as possible, and (ii) present methods that can be used to report on the overall state of the system by integrating estimates of individual indicators. It was agreed at the outset, that this project was to focus on developing methods for a water quality report card. This was driven largely by the requirements of Reef Water Quality Protection Plan (RWQPP) and led to strong partner engagement with the Reef Water Quality Partnership.

Fuzzy logic to evaluate driving maneuvers: An integrated approach to improve training

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.

Assessing agronomic and environmental implications of different N fertilisation strategies in subtropical grain cropping systems on Oxisols

A multi-season 15N tracer recovery experiment was conducted on an Oxisol cropped with wheat, maize and sorghum to compare crop N recoveries of different fertilisation strategies and determine the main pathways of N losses that limit N recovery in these agroecosystems. In the wheat and maize seasons, 15N-labelled fertiliser was applied as conventional urea (CONV) and urea coated with a nitrification inhibitor (DMPP). In sorghum, the fate of 15N-labelled urea was monitored in this crop following a legume ley pasture (L70) or a grass ley pasture (G100). The fertiliser N applied to sorghum in the legume-cereal rotation was reduced (70 kg N ha−1) compared to the grass-cereal (100 kg N ha−1) to assess the availability of the N residual from the legume ley pasture. Average crop N recoveries were 73 % (CONV) and 77 % (DMPP) in wheat and 50 % (CONV) and 51 % (DMPP) in maize, while in sorghum were 71 % (L70) and 53 % (G100). Data gathered in this study indicate that the intrinsic physical and chemical conditions of Oxisols can be extremely effective in limiting N losses via deep leaching or denitrification. Elevated crop 15N recoveries can be therefore obtained in subtropical Oxisols using conventional urea while in these agroecosystems DMPP urea has no significant scope to increase fertiliser N recovery in the crop. Overall, introducing a legume phase to limit the fertiliser N requirements of the following cereal crop proved to be the most effective strategy to reduce N losses and increase fertiliser N recovery.

FaceXpress : an integrated software suite for facial emotion stimulus manipulation and facial measurement

The characterisation of facial expression through landmark-based analysis methods such as FACEM (Pilowsky & Katsikitis, 1994) has a variety of uses in psychiatric and psychological research. In these systems, important structural relationships are extracted from images of facial expressions by the analysis of a pre-defined set of feature points. These relationship measures may then be used, for instance, to assess the degree of variability and similarity between different facial expressions of emotion. FaceXpress is a multimedia software suite that provides a generalised workbench for landmark-based facial emotion analysis and stimulus manipulation. It is a flexible tool that is designed to be specialised at runtime by the user. While FaceXpress has been used to implement the FACEM process, it can also be configured to support any other similar, arbitrary system for quantifying human facial emotion. FaceXpress also implements an integrated set of image processing tools and specialised tools for facial expression stimulus production including facial morphing routines and the generation of expression-representative line drawings from photographs.

Technoeconomic analysis of an integrated microalgae photobioreactor, biodiesel and biogas production facility

As fossil fuel prices increase and environmental concerns gain prominence, the development of alternative fuels from biomass has become more important. Biodiesel produced from microalgae is becoming an attractive alternative to share the role of petroleum. Currently it appears that the production of microalgal biodiesel is not economically viable in current environment because it costs more than conventional fuels. Therefore, a new concept is introduced in this article as an option to reduce the total production cost of microalgal biodiesel. The integration of biodiesel production system with methane production via anaerobic digestion is proved in improving the economics and sustainability of overall biodiesel stages. Anaerobic digestion of microalgae produces methane and further be converted to generate electricity. The generated electricity can surrogate the consumption of energy that require in microalgal cultivation, dewatering, extraction and transesterification process. From theoretical calculations, the electricity generated from methane is able to power all of the biodiesel production stages and will substantially reduce the cost of biodiesel production (33% reduction). The carbon emissions of biodiesel production systems are also reduced by approximately 75% when utilizing biogas electricity compared to when the electricity is otherwise purchased from the Victorian grid. The overall findings from this study indicate that the approach of digesting microalgal waste to produce biogas will make the production of biodiesel from algae more viable by reducing the overall cost of production per unit of biodiesel and hence enable biodiesel to be more competitive with existing fuels.

On Merging Business Process Management and Geographic Information Systems : Modeling and Execution of Ecological Concerns in Processes

Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

A framework for qualitative analysis of focus group data in information systems

Focus groups are a popular qualitative research method for information systems researchers. However, compared with the abundance of research articles and handbooks on planning and conducting focus groups, surprisingly, there is little research on how to analyse focus group data. Moreover, those few articles that specifically address focus group analysis are all in fields other than information systems, and offer little specific guidance for information systems researchers. Further, even the studies that exist in other fields do not provide a systematic and integrated procedure to analyse both focus group ‘content’ and ‘interaction’ data. As the focus group is a valuable method to answer the research questions of many IS studies (in the business, government and society contexts), we believe that more attention should be paid to this method in the IS research. This paper offers a systematic and integrated procedure for qualitative focus group data analysis in information systems research.

Visualization of complex biological systems: An immune response model using OpenGL

In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

A framework for understanding and generating integrated solutions for residential peak energy demand

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

Reviewing in-vehicle systems to improve fuel efficiency and road safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behavior change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, it is crucial to understand the human factors related theories and practices which will inform the design of an in-vehicle Human Machine Interface (HMI) that could provide real-time driver feedback and consequently improve both fuel efficiency and safety. This paper provides a comprehensive review of the current state of published literature on in-vehicle systems to identify and evaluate the impact of eco-driving and safety feedback systems. This paper also discusses how these factors may conflict with one another and have a negative effect on road safety, while also exploring possible eco-driving practices that could encourage more sustainable, environmentally-conscious and safe driving behavior. The review revealed a lack of comprehensive theoretical research integrating eco-driving and safe driving, and no current available HMI covering both aspects simultaneously. Furthermore, the review identified that some eco-driving in-vehicle systems may enhance fuel efficiency without compromising safety. The review has identified a range of concepts which can be developed to influence driver acceptance of safety and eco-driving systems within the area of HMI. This can promote new research aimed at enhancing our understanding of the relationship between eco-driving and safety from the human factors viewpoint. This provides a foundation for developing innovative, persuasive and acceptable in-vehicle HMI systems to improve fuel efficiency and road safety.

An integrated framework for theories of individual attitudes toward technology

Theories of individual attitudes toward IT include task technology fit (TTF), technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT), cognitive fit, expectation disconfirmation, and computer self-efficacy. Examination of these theories reveals three main concerns. First, the theories mostly ‘‘black box’’ (or omit) the IT artifact. Second, appropriate mid-range theory is not developed to contribute to disciplinary progress and to serve the needs of our practitioner community. Third, theories are overlapping but incommensurable. We propose a theoretical framework that harmonizes these attitudinal theories and shows how they can be specialized to include relevant IS phenomenon.

Design theory for innovation of classroom-based information systems

This research used design science research methods to develop, instantiate, implement, and measure the acceptance of a novel software artefact. The primary purpose of this software artefact was to enhance data collection, improve its quality and enable its capture in classroom environments without distracting from the teaching activity. The artefact set is an iOS app, with supporting web services and technologies designed in response to teacher and pastoral care needs. System analysis and design used Enterprise Architecture methods. The novel component of the iOS app implemented proximity detection to identify the student through their iPad and automatically link to that student's data. The use of this novel software artefact and web services was trialled in a school setting, measuring user acceptance and system utility. This integrated system was shown to improve the accuracy, consistency, completeness and timeliness of captured data and the utility of the input and reporting systems.