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.

Synchronous fluorescence and UV–vis spectroscopic studies of interactions between the tetracycline antibiotic, aluminium ions and DNA with the aid of the Methylene Blue dye probe

Synchronous fluorescence spectroscopy (SFS) was applied for the investigation of interactions of the antibiotic, tetracycline (TC), with DNA in the presence of aluminium ions (Al3+). The study was facilitated by the use of the Methylene Blue (MB) dye probe, and the interpretation of the spectral data with the aid of the chemometrics method, parallel factor analysis (PARAFAC). Three-way synchronous fluorescence analysis extracted the important optimum constant wavelength differences, Δλ, and showed that for the TC–Al3+–DNA, TC–Al3+ and MB dye systems, the associated Δλ values were different (Δλ = 80, 75 and 30 nm, respectively). Subsequent PARAFAC analysis demonstrated the extraction of the equilibrium concentration profiles for the TC–Al3+, TC–Al3+–DNA and MB probe systems. This information is unobtainable by conventional means of data interpretation. The results indicated that the MB dye interacted with the TC–Al3+–DNA surface complex, presumably via a reaction intermediate, TC–Al3+–DNA–MB, leading to the displacement of the TC–Al3+ by the incoming MB dye probe.

Analysis of road potential and bottlenecks based on operating speed

Vehicle detectors have been installed at approximately every 300 meters on each lane on Tokyo metropolitan expressway. Various traffic data such as traffic volume, average speed and time occupancy are collected by vehicle detectors. We can understand traffic characteristics of every point by comparing traffic data collected at consecutive points. In this study, we focused on average speed, analyzed road potential by operating speed during free-flow conditions, and identified latent bottlenecks. Furthermore, we analyzed effects for road potential by the rainfall level and day of the week. It’s expected that this method of analysis will be utilized for installation of ITS such as drive assist, estimation of parameters for traffic simulation and feedback to road design as congestion measures.

Synthesis of 4-arm star poly(L-Lactide) oligomers using an in situ-generated calcium-based initiator

Using an in situ-generated calcium-based initiating species derived from pentaerythritol, the bulk synthesis of well-defined 4-arm star poly(L-lactide) oligomers has been studied in detail. The substitution of the traditional initiator, stannous octoate with calcium hydride allowed the synthesis of oligomers that had both low PDIs and a comparable number of polymeric arms (3.7 – 3.9) to oligomers of similar molecular weight. Investigations into the degree of control observed during the course of the polymerization found that the insolubility of pentaerythritol in molten L-lactide resulted in an uncontrolled polymerization only when the feed mole ratio of L-lactide to pentaerythritol was 13. At feed ratios of 40 and greater, a pseudo-living polymerization was observed. As part of this study, in situ FT-Raman spectroscopy was demonstrated to be a suitable method to monitor the kinetics of the ring-opening polymerization (ROP) of lactide. The advantages of using this technique rather than FT-IR-ATR and 1H NMR for monitoring L-lactide consumption during polymerization are discussed.

Sampling perceptions; testing reality : an evidence-based approach to measurably improve information literacy and student research skills

Do commencing students possess the level of information literacy (IL) knowledge and skills they need to succeed at university? What impact does embedding IL within the engineering and design curriculum have? This paper reports on the self-perception versus the reality of IL knowledge and skills, across a large cohort of first year built environment and engineering students. Acting on the findings of this evaluation, the authors (a team of academic librarians) developed an intensive IL skills program which was integrated into a faculty wide unit. Perceptions, knowledge and skills were re-evaluated at the end of the semester to determine if embedded IL education made a difference. Findings reveal that both the perception and reality of IL skills were significantly and measurably improved.

Contracting for community development : a case study based perspective of a public sector client initiative in Hong Kong

The construction industry is known to be an important contributor towards the gross domestic product of many countries. Moreover, the health of the construction industry is positively correlated to the economic growth of a country and in many economies public sector clients account for a major share of construction works. Given this strength, it is important for public sector clients to initiate innovations aimed at the betterment of the industry. In this context, concern about sustainable development has been a major driver of some innovative initiatives in construction industries worldwide. Furthermore, the Government of Hong Kong regards both sustainability and community development as important criteria when planning and procuring construction projects. This paper is based on a case study of a public sector development project in Hong Kong, and presents the salient features of the procurement and contractual systems adopted in the project, which foster sustainability and community development. The reported interim findings are based on a preliminary document analysis that is part of an ongoing longitudinal case study into the project. The document analysis takes a three-pronged approach in terms of how the procurement and contractual systems foster economic, environmental and social sustainability, and sums up their impact on the community as a whole.

Prediction of adjacent vertebral fracture risk associated with vertebroplasty : a computer-based simulation study

Vertebrplasty involved injecting cement into a fractured vertebra to provide stabilisation. There is clinical evidence to suggest however that vertebroplasty may be assocated with a higher risk of adjacent vertebral fracture; which may be due to the change in material properties of the post-procedure vertebra modifying the transmission of mechanical stresses to adjacent vertebrae.

A Vision Based Target Detection System for Docking of an Autonomous Underwater Vehicle

This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

Effective employment-based training models for childcare workers

Childcare workers play a significant role in the learning and development of children in their care. This has major implications for the training of workers. Under new reforms of the childcare industry the Australian government now requires all workers to obtain qualifications from a vocational education and training provider (eg. Technical and Further Education) or university. Effective models of employment-based training are critical to provide training to highly competent workers. This paper presents findings from a study that examined current and emerging models of employment-based training in the childcare sector, particularly at the Diploma level. Semi-structured interviews were conducted with a sample of 16 participants who represented childcare directors, employers, and workers located in childcare services in urban, regional and remote locations in the State of Queensland. The study proposes a ‘best-fit’ employment-based training approach that is characterised by a compendium of five models instead of a ‘one size fits all’. Issues with successful implementation of the EBT models are also discussed

Evidence-based decision making to strengthen local governance : nutritional health interventions in Bantul and Gunungkidul

Since 2001, district governments have had the main responsibility for providing public health care in Indonesia. One of the main public health challenges facing many district governments is improving nutritional standards, particularly among poorer segments of the population. Developing effective policies and strategies for improving nutrition requires a multi-sectoral approach encompassing agricultural development policy, access to markets, food security (storage) programs, provision of public health facilities, and promotion of public awareness of nutritional health. This implies a strong need for a coordinated approach involving multiple government agencies at the district level. Due to diverse economic, agricultural, and infrastructure conditions across the country, district governments’ ought to be better placed than central government both to identify areas of greatest need for public nutrition interventions, and devise policies that reflect local characteristics. However, in the two districts observed in this study—Bantul and Gunungkidul—it was clear that local government capacity to generate, obtain and integrate evidence about local conditions into the policy-making process was still limited. In both districts, decision-makers tended to rely more on intuition,anecdote, and precedent in formulating policy. The potential for evidence-based decision making was also severely constrained by a lack of coordination and communication between agencies, and current arrangements related to central government fiscal transfers, which compel local governments to allocate funding to centrally determined programs and priorities.

Evidence based decision making to strenghten local governance : nutritional health interventions

Since 2001, district governments have had the main responsibility for providing public health care in Indonesia. One of the main public health challenges facing many district governments is improving nutritional standards, particularly among poorer segments of the population. Developing effective policies and strategies for improving nutrition requires a multi-sectoral approach encompassing agricultural development policy, access to markets, food security (storage) programs, provision of public health facilities, and promotion of public awareness of nutritional health. This implies a strong need for a coordinated approach involving multiple government agencies at the district level. Due to diverse economic, agricultural,and infrastructure conditions across the country, district governments’ ought to be better placed than central government both to identify areas of greatest need for public nutrition interventions, and devise policies that reflect local characteristics. However, in the two districts observed in this study—Bantul and Gunungkidul—it was clear that local government capacity to generate, obtain and integrate evidence about local conditions into the policy-making process was still limited. In both districts, decision-makers tended to rely more on intuition,anecdote, and precedent in formulating policy. The potential for evidence-based decision making was also severely constrained by a lack of coordination and communication between agencies, and current arrangements related to central government fiscal transfers, which compel local governments to allocate funding to centrally determined programs and priorities.

Context-based chemistry : creating opportunities for fluid transitions between concepts and context

Nationally and internationally, context-based programs have been implemented in an attempt to engage students in chemistry through connecting the canonical science with the real-world. In Queensland, a context-based approach to chemistry was trialled in selected schools from 2002 but there is little research that investigates how students learn in a context-based setting. This paper presents one significant finding from an ethnographic study that explored the learning that occurred in an 11th grade context-based chemistry classroom in Queensland. The study found that by providing students with the opportunity to write, fluid transitions (or to-ing and fro-ing) between concepts and context were an outcome of context-based learning.

Rough set-based reasoning and pattern mining for information filtering

An information filtering (IF) system monitors an incoming document stream to find the documents that match the information needs specified by the user profiles. To learn to use the user profiles effectively is one of the most challenging tasks when developing an IF system. With the document selection criteria better defined based on the users’ needs, filtering large streams of information can be more efficient and effective. To learn the user profiles, term-based approaches have been widely used in the IF community because of their simplicity and directness. Term-based approaches are relatively well established. However, these approaches have problems when dealing with polysemy and synonymy, which often lead to an information overload problem. Recently, pattern-based approaches (or Pattern Taxonomy Models (PTM) [160]) have been proposed for IF by the data mining community. These approaches are better at capturing sematic information and have shown encouraging results for improving the effectiveness of the IF system. On the other hand, pattern discovery from large data streams is not computationally efficient. Also, these approaches had to deal with low frequency pattern issues. The measures used by the data mining technique (for example, “support” and “confidences”) to learn the profile have turned out to be not suitable for filtering. They can lead to a mismatch problem. This thesis uses the rough set-based reasoning (term-based) and pattern mining approach as a unified framework for information filtering to overcome the aforementioned problems. This system consists of two stages - topic filtering and pattern mining stages. The topic filtering stage is intended to minimize information overloading by filtering out the most likely irrelevant information based on the user profiles. A novel user-profiles learning method and a theoretical model of the threshold setting have been developed by using rough set decision theory. The second stage (pattern mining) aims at solving the problem of the information mismatch. This stage is precision-oriented. A new document-ranking function has been derived by exploiting the patterns in the pattern taxonomy. The most likely relevant documents were assigned higher scores by the ranking function. Because there is a relatively small amount of documents left after the first stage, the computational cost is markedly reduced; at the same time, pattern discoveries yield more accurate results. The overall performance of the system was improved significantly. The new two-stage information filtering model has been evaluated by extensive experiments. Tests were based on the well-known IR bench-marking processes, using the latest version of the Reuters dataset, namely, the Reuters Corpus Volume 1 (RCV1). The performance of the new two-stage model was compared with both the term-based and data mining-based IF models. The results demonstrate that the proposed information filtering system outperforms significantly the other IF systems, such as the traditional Rocchio IF model, the state-of-the-art term-based models, including the BM25, Support Vector Machines (SVM), and Pattern Taxonomy Model (PTM).

Mixing colours: An ICT tool based on a semiotic framework for mathematical meaning-makng about ratio and fractions

This paper reports on the research and development of an ICT tool to facilitate the learning of ratio and fractions by adult prisoners. The design of the ICT tool was informed by a semiotic framework for mathematical meaning-making. The ICT tool thus employed multiple semiotic resources including topological, typological, and social-actional resources. The results showed that individual semiotic resource could only represent part of the mathematical concept, while at the same time it might signify something else to create a misconception. When multiple semiotic resources were utilised the mathematical ideas could be better learnt.

Improved GMM-based speaker verification using SVM-driven impostor dataset selection

The problem of impostor dataset selection for GMM-based speaker verification is addressed through the recently proposed data-driven background dataset refinement technique. The SVM-based refinement technique selects from a candidate impostor dataset those examples that are most frequently selected as support vectors when training a set of SVMs on a development corpus. This study demonstrates the versatility of dataset refinement in the task of selecting suitable impostor datasets for use in GMM-based speaker verification. The use of refined Z- and T-norm datasets provided performance gains of 15% in EER in the NIST 2006 SRE over the use of heuristically selected datasets. The refined datasets were shown to generalise well to the unseen data of the NIST 2008 SRE.