Personal Epistemologies and Teaching

Over the last three decades, a growing body of research related to epistemic beliefs has been identified as a crucial for understanding teaching and learning (Yadav, Herron, & Samarapungavan, 2011). In particular, research related to beliefs about teaching, learning and knowledge has been considered important for understanding why teachers engage in certain approaches to pedagogy, curriculum and assessment in classrooms (Stromlo & Bråten, 2011). The beliefs held by teachers about knowledge and knowing, otherwise known as personal epistemology (Hofer, 2010), have been shown to influence other knowledge and beliefs (Schommer-Aikens, 2004). Five and Buehl (2012) indicated that because an individual’s understanding of reality is always seen through the lens of existing beliefs, the role of beliefs as a filter is particularly relevant in the context of teacher education. That is, if beliefs influence how individuals interpret new information and experiences, preservice and practicing teachers’ beliefs shape what and how they learn about teaching.” (p. 470-480). It is likely that such beliefs have an important relationship with teacher knowledge and practices...

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

The experiences of teachers teaching children with Down syndrome in the early years of schooling

This innovative collective case study research documented teachers' experiences of teaching children with Down syndrome in the early years of schooling in Australia. Results indicated differences in teachers' conceptualisation of children with Down syndrome as learners and how these variations impacted the way the child was included within the class. Unique to this research was the utilisation of a mind-mapping technique of data collection which effectively captured the individual nature of teachers' experiences, making implicit knowledge explicit through description and interpretation of these experiences. Overall findings indicated that teachers were more likely to include children with Down syndrome into general education classrooms if they operated within a contemporary understanding of disability, had positive support from key stakeholders such as school principals and parents/caregivers, and had access to current information on Down syndrome from professional bodies.

Teaching and assessment of prescribing medicines : a multidisciplinary review

Background Prescribing is a complex task, requiring specific knowledge and skills, and the execution of effective, context-specific clinical reasoning. Prescribing errors can result in significant morbidity and mortality. For all professions with prescribing rights, a clear need exists to ensure students graduate with a well-defined set of prescribing skills, which will contribute to competent prescribing.

Teaching basic finance with Excel, and without pain

The five quantities of interest in elementary finance problems are present value, future value, amount of periodic payment, number of periods and the rate of compound interest per period. A recursive approach to computing each of these five quantities in a modern version of Excel, for the case of ordinary annuities, is described. The aim is to increase student understanding and build confidence in the answer obtained, and this may be achieved with only linear relationships and in cases where student knowledge of algebra is essentially zero. Annuity problems may be solved without use of logarithms and black-box intrinsic functions; these being used only as check mechanisms. The author has had success with the method at Bond University and surrounding high schools in Queensland, Australia.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

1000 voices: reflective online multimodal narrative inquiry as a research methodology for disability research

This article outlines the research approach used in the international 1000 Voices Project. The 1000 Voices project is an interdisciplinary research and public awareness project that uses a customised online multimodal storytelling platform to explore the lives of people with disability internationally. Through the project, researchers and partners have encouraged diverse participants to select the modes of storytelling (e.g. images, text, videos and combinations thereof) that suit them best and to self-define what both ‘disability’ and ‘life story’ mean to them. The online reflective component of the approach encourages participants to organically and reflectively develop story events and revisions over time in ways that suit them and their emerging lives. This article provides a detailed summary of the project's theoretical and methodological development alongside suggestions for future development in social work and qualitative research.

Wicked problems in designing open online learning

This paper will report on the “wicked” problems encountered when designing an online course with bounded content in an unbounded learning environment. It will describe the dilemmas faced and decisions made by academics in an Australian university challenged by an institutional initiative to design radical, disruptive learning experiences making use of readily available online media. This bounded/unbounded environment demands new roles for instructors in adopting innovative pedagogies and teaching and learning strategies. It also creates changing and challenging roles for course designers as they deal with ill-defined parameters and unknown audiences. In this paper, we propose a novel methodology for making curricular decisions in ill-defined spaces.

Refining a teaching pattern: Reflection around artefacts

This book is about understanding the nature and application of reflection in higher education. It provides a theoretical model to guide the implementation of reflective learning and reflective practice across multiple disciplines and international contexts in higher education. The book presents research into the ways in which reflection is both considered and implemented in different ways across different professional disciplines, while maintaining a common purpose to transform and improve learning and/or practice. Chapter 13 'Refining a Teaching Pattern: Reflection Around Artefacts' explores reflective practices of an artefact, in this case fashion design garment samples.

Teaching for quality learning at university

by J. Biggs and C. Tang, Maidenhead, England, Open University Press, 2007, 360 pp., £29.99, ISBN-13: 978-0-335-22126-4

Biodiesel production from non-edible beauty leaf (Calophyllum Inophyllum) oil : process optimization using response surface methodology (RSM)

In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

A robust methodology for developing an operational systems view of mine water interactions

The Minerals Council of Australia’s (MCA) Water Accounting Framework (WAF) is an industry lead initiative to enable cross company communication and comparisons of water management performance. The WAF consists of two models, the Input-Output Model that represents water interactions between an operation and its surrounding environment and the Operational Model that represents water interactions within an operation. Recently, MCA member companies have agreed to use the Input-Output Model to report on their external water interactions in Australian operations, with some adopting it globally. The next step will be to adopt the Operational Model. This will expand the functionality of the WAF from corporate reporting to allowing widespread identification of inefficiencies and to connect internal and external interactions. Implementing the WAF, particularly the Operational Model, is non-trivial. It can be particularly difficult for operations that are unfamiliar with the WAF definitions and methodology, lack information pertaining to flow volumes or contain unusual configurations. Therefore, there is a need to help industry with its implementation. This work presents a step-by-step guide to producing the Operational Model. It begins by describing a methodology for implementing the Operational Model by describing the identification of pertinent objects (stores, tasks and treatments), quantification of flows, aggregation of objects and production of reports. It then discusses how the Operational Model can represent a series of challenging scenarios and how it can be connected with Input-Output Model to improve water management.

Making meaning in mathematics problem solving using the Reciprocal Teaching approach

This paper examines the application of the Reciprocal Teaching instructional approach to Mathematical word problems in the middle years. The Reciprocal Teaching process is extended from the four traditional strategies of predicting, clarifying, questioning and summarising, to include further cognitive reading comprehension strategies applied to the context of solving Mathematical word problems.

The development and evaluation of a medical imaging training immersive environment

Introduction A novel realistic 3D virtual reality (VR) application has been developed to allow medical imaging students at Queensland University of Technology to practice radiographic techniques independently outside the usual radiography laboratory. Methods A flexible agile development methodology was used to create the software rapidly and effectively. A 3D gaming environment and realistic models were used to engender presence in the software while tutor-determined gold standards enabled students to compare their performance and learn in a problem-based learning pedagogy. Results Students reported high levels of satisfaction and perceived value and the software enabled up to 40 concurrent users to prepare for clinical practice. Student feedback also indicated that they found 3D to be of limited value in the desktop version compared to the usual 2D approach. A randomised comparison between groups receiving software-based and traditional practice measured performance in a formative role play with real equipment. The results of this work indicated superior performance with the equipment for the VR trained students (P = 0.0366) and confirmed the value of VR for enhancing 3D equipment-based problem-solving skills. Conclusions Students practising projection techniques virtually performed better at role play assessments than students practising in a traditional radiography laboratory only. The application particularly helped with 3D equipment configuration, suggesting that teaching 3D problem solving is an ideal use of such medical equipment simulators. Ongoing development work aims to establish the role of VR software in preparing students for clinical practice with a range of medical imaging equipment.

A multidisciplinary review of the teaching and assessment of prescribing : how do professions perform?

Aim To investigate the methods employed to teach and assess the principles of effective prescribing across five non-medical professions in a tertiary institution. Methods The National Prescribing Service MedicineWise Prescribing Competencies Framework was employed as the prescribing standard. A curriculum mapping exercise was undertaken to determine whether the prescribing articulated in the competency standards were addressed within the following courses: Master of Nursing Science (Nurse Practitioner), Bachelor of Vision Science, Master of Optometry, Bachelor of Pharmacy, Bachelor of Podiatry, Bachelor of Paramedic Science. The methods employed to teach and assess prescribing principles were documented. For each profession, identified gaps in teaching and/or assessment were noted.