Experience of problem-based learning (PBL) in virtual space : a phenomenographical study

This thesis reports the outcomes of an investigation into students’ experience of Problem-based learning (PBL) in virtual space. PBL is increasingly being used in many fields including engineering education. At the same time many engineering education providers are turning to online distance education. Unfortunately there is a dearth of research into what constitutes an effective learning experience for adult learners who undertake PBL instruction through online distance education. Research was therefore focussed on discovering the qualitatively different ways that students experience PBL in virtual space. Data was collected in an electronic environment from a course, which adopted the PBL strategy and was delivered entirely in virtual space. Students in this course were asked to respond to open-ended questions designed to elicit their learning experience in the course. Data was analysed using the phenomenographical approach. This interpretative research method concentrated on mapping the qualitative differences in students’ interpretations of their experience in the course. Five qualitatively different ways of experiencing were discovered: Conception 1: ‘A necessary evil for program progression’; Conception 2: ‘Developing skills to understand, evaluate, and solve technical Engineering and Surveying problems’; Conception 3: ‘Developing skills to work effectively in teams in virtual space’; Conception 4: ‘A unique approach to learning how to learn’; Conception 5: ‘Enhancing personal growth’. Each conception reveals variation in how students attend to learning by PBL in virtual space. Results indicate that the design of students’ online learning experience was responsible for making students aware of deeper ways of experiencing PBL in virtual space. Results also suggest that the quality and quantity of interaction with the team facilitator may have a significant impact on the student experience in virtual PBL courses. The outcomes imply pedagogical strategies can be devised for shifting students’ focus as they engage in the virtual PBL experience to effectively manage the student learning experience and thereby ensure that they gain maximum benefit. The results from this research hold important ramifications for graduates with respect to their ease of transition into professional work as well as their later professional competence in terms of problem solving, ability to transfer basic knowledge to real-life engineering scenarios, ability to adapt to changes and apply knowledge in unusual situations, ability to think critically and creatively, and a commitment to continuous life-long learning and self-improvement.

A surface plasmon resonance-based solution affinity assay for heparan sulfate-binding proteins

A surface plasmon resonance-based solution affinity assay is described for measuring the Kd of binding of heparin/heparan sulfate-binding proteins with a variety of ligands. The assay involves the passage of a pre-equilibrated solution of protein and ligand over a sensor chip onto which heparin has been immobilised. Heparin sensor chips prepared by four different methods, including biotin–streptavidin affinity capture and direct covalent attachment to the chip surface, were successfully used in the assay and gave similar Kd values. The assay is applicable to a wide variety of heparin/HS-binding proteins of diverse structure and function (e.g., FGF-1, FGF-2, VEGF, IL-8, MCP-2, ATIII, PF4) and to ligands of varying molecular weight and degree of sulfation (e.g., heparin, PI-88, sucrose octasulfate, naphthalene trisulfonate) and is thus well suited for the rapid screening of ligands in drug discovery applications.

Problem-based learning (PBL) in Virtual Space : Developing experiences for professional development

This book reports the outcomes of an investigation into discovering the qualitatively different ways that students experience Problem-based learning (PBL)in virtual space. PBL is increasingly being used in many fields including engineering education. At the same time, many engineering education providers are turning to online distance education. Unfortunately there is a dearth of research into what constitutes an effective learning experience for adult learners who undertake PBL instruction through online distance education. Data were collected from a course which adopted the PBL strategy and was delivered entirely in virtual space. Students were asked to respond to open-ended questions designed to elicit their learning experiences. Data were analysed using the phenomenographic approach. Five qualitatively different ways of experiencing PBL in virtual space were discovered. Results indicate that the design of students' online learning experience was responsible for making students aware of deeper ways of experienceing PBL in virtual space. The outcomes imply that pedagogical strategies can be devised for shifting students' focus as they engage in virtual PBL.

Life-cycle management of construction projects based on virtual prototyping technology

Life-cycle management (LCM) has been employed in the management of construction projects for many years in order to reduce whole life cost, time, risk and improve the service to owners. However, owing to lack of an effective information sharing platform, the current LCM of construction projects is not effectively used in the construction industry. Based upon the analysis of the information flow of LCM, a virutal prototyping (VP)-based communication and collaboration information platform is proposed. Following this, the platform is customized using DASSAULT sofware. The whole process of implementing the VP-based LCM are also discussed and, from a simple case study, it is demonstrated that the VP-based communication and collaboration information platform is an effective tool to support the LCM of construction projects.

Repeat participation in colorectal cancer screening utilizing fecal occult blood testing : a community-based project in a rural setting

Background and Aim: To investigate participation in a second round of colorectal cancer screening using a fecal occult blood test (FOBT) in an Australian rural community, and to assess the demographic characteristics and individual perspectives associated with repeat screening. ---------- Methods: Potential participants from round 1 (50–74 years of age) were sent an intervention package and asked to return a completed FOBT (n = 3406). Doctors of participants testing positive referred to colonoscopy as appropriate. Following screening, 119 participants completed qualitative telephone interviews. Multivariable logistic regression models evaluated the association between round-2 participation and other variables.---------- Results: Round-2 participation was 34.7%; the strongest predictor was participation in round 1. Repeat participants were more likely to be female; inconsistent screeners were more likely to be younger (aged 50–59 years). The proportion of positive FOBT was 12.7%, that of colonoscopy compliance was 98.6%, and the positive predictive value for cancer or adenoma of advanced pathology was 23.9%. Reasons for participation included testing as a precautionary measure or having family history/friends with colorectal cancer; reasons for non-participation included apathy or doctors’ advice against screening.---------- Conclusion: Participation was relatively low and consistent across rounds. Unless suitable strategies are identified to overcome behavioral trends and/or to screen out ineligible participants, little change in overall participation rates can be expected across rounds.

Feasibility of brief psychological distress screening by a community-based telephone helpline for cancer patients and carers

Background Up to one-third of people affected by cancer experience ongoing psychological distress and would benefit from screening followed by an appropriate level of psychological intervention. This rarely occurs in routine clinical practice due to barriers such as lack of time and experience. This study investigated the feasibility of community-based telephone helpline operators screening callers affected by cancer for their level of distress using a brief screening tool (Distress Thermometer), and triaging to the appropriate level of care using a tiered model. Methods Consecutive cancer patients and carers who contacted the helpline from September-December 2006 (n = 341) were invited to participate. Routine screening and triage was conducted by helpline operators at this time. Additional socio-demographic and psychosocial adjustment data were collected by telephone interview by research staff following the initial call. Results The Distress Thermometer had good overall accuracy in detecting general psychosocial morbidity (Hospital Anxiety and Depression Scale cut-off score ≥ 15) for cancer patients (AUC = 0.73) and carers (AUC = 0.70). We found 73% of participants met the Distress Thermometer cut-off for distress caseness according to the Hospital Anxiety and Depression Scale (a score ≥ 4), and optimal sensitivity (83%, 77%) and specificity (51%, 48%) were obtained with cut-offs of ≥ 4 and ≥ 6 in the patient and carer groups respectively. Distress was significantly associated with the Hospital Anxiety and Depression Scale scores (total, as well as anxiety and depression subscales) and level of care in cancer patients, as well as with the Hospital Anxiety and Depression Scale anxiety subscale for carers. There was a trend for more highly distressed callers to be triaged to more intensive care, with patients with distress scores ≥ 4 more likely to receive extended or specialist care. Conclusions Our data suggest that it was feasible for community-based cancer helpline operators to screen callers for distress using a brief screening tool, the Distress Thermometer, and to triage callers to an appropriate level of care using a tiered model. The Distress Thermometer is a rapid and non-invasive alternative to longer psychometric instruments, and may provide part of the solution in ensuring distressed patients and carers affected by cancer are identified and supported appropriately.

Neural network-based detection of virtual environment anomalies

The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.

Students' experience of problem-based learning in virtual space

This paper reports outcomes of a study focussed on discovering qualitatively different ways students' experience problem-based learning in virtual space. A well accepted and documented qualitative research method was adopted for this study. Five qualitatively different conceptions are described, each revealing characteristics of increasingly complex student experiences. Establishing characteristics of these more complex experiences assists teachers in facilitating students engagement and encouraging deeper learning.

Virtual resistance based active damping solution for constant power instability in AC microgrids

With ever-increasing share of power electronic loads constant power instability is becoming a significant issue in microgrids, especially when they operate in the islanding mode. Transient conditions like resistive load-shedding or sudden increase of constant power loads (CPL) might destabilize the whole system. Modeling and stability analysis of AC microgrids with CPLs have already been discussed in literature. However, no effective solutions are provided to stabilize this kind of system. Therefore, this paper proposes a virtual resistance based active damping method to eliminate constant power instability in AC microgrids. Advantages and limitations of the proposed method are also discussed in detail. Simulation results are presented to validate the proposed active damping solution.

Application of fragment-based screening to the design of inhibitors of Escherichia coli DsbA

The thiol-disulfide oxidoreductase enzyme DsbA catalyzes the formation of disulfide bonds in the periplasm of Gram-negative bacteria. DsbA substrates include proteins involved in bacterial virulence. In the absence of DsbA, many of these proteins do not fold correctly, which renders the bacteria avirulent. Thus DsbA is a critical mediator of virulence and inhibitors may act as antivirulence agents. Biophysical screening has been employed to identify fragments that bind to DsbA from Escherichia coli. Elaboration of one of these fragments produced compounds that inhibit DsbA activity in vitro. In cell-based assays, the compounds inhibit bacterial motility, but have no effect on growth in liquid culture, which is consistent with selective inhibition of DsbA. Crystal structures of inhibitors bound to DsbA indicate that they bind adjacent to the active site. Together, the data suggest that DsbA may be amenable to the development of novel antibacterial compounds that act by inhibiting bacterial virulence.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.