The adoption of e-learning 2.0 in higher education by teachers and students : an investigation using mixed methods approach

This paper describes an approach to investigate the adoption of Web 2.0 in the classroom using a mixed methods study. By using a combination of qualitative or quantitative data collection and analysis techniques, we attempt to synergize the results and provide a more valid understanding of Web 2.0 adoption for learning by both teachers and students. This approach is expected to yield a better holistic view on the adoption issues associated with the e-learning 2.0 concept in current higher education as opposed to single method studies done previously. This paper also presents some early findings of e-learning 2.0 adoption using this research method

Developing schedules for mixed rail and road cane transport systems

This paper addresses the problem of scheduling a cane transport system involving both rail transport and road transport, where the road transport operates from several sidings in the rail network. An iterative approach for scheduling the rail transport system has been developed using existing rail transport scheduling tools. The assumption that harvesters serviced by road transport are effectively operating from the rail siding from which their bins are supplied seems a reasonable starting point for the analysis. There is a need to manually modify the schedule to take into account the road transport schedule to ensure that full bins are not collected before the road transport system delivers them back to the rail siding.

Generalized-positioning for mixed-frequency of mixed-GNSS and its preliminary applications

Modernized GPS and GLONASS, together with new GNSS systems, BeiDou and Galileo, offer code and phase ranging signals in three or more carriers. Traditionally, dual-frequency code and/or phase GPS measurements are linearly combined to eliminate effects of ionosphere delays in various positioning and analysis. This typical treatment method has imitations in processing signals at three or more frequencies from more than one system and can be hardly adapted itself to cope with the booming of various receivers with a broad variety of singles. In this contribution, a generalized-positioning model that the navigation system independent and the carrier number unrelated is promoted, which is suitable for both single- and multi-sites data processing. For the synchronization of different signals, uncalibrated signal delays (USD) are more generally defined to compensate the signal specific offsets in code and phase signals respectively. In addition, the ionospheric delays are included in the parameterization with an elaborate consideration. Based on the analysis of the algebraic structures, this generalized-positioning model is further refined with a set of proper constrains to regularize the datum deficiency of the observation equation system. With this new model, uncalibrated signal delays (USD) and ionospheric delays are derived for both GPS and BeiDou with a large dada set. Numerical results demonstrate that, with a limited number of stations, the uncalibrated code delays (UCD) are determinate to a precision of about 0.1 ns for GPS and 0.4 ns for BeiDou signals, while the uncalibrated phase delays (UPD) for L1 and L2 are generated with 37 stations evenly distributed in China for GPS with a consistency of about 0.3 cycle. Extra experiments concerning the performance of this novel model in point positioning with mixed-frequencies of mixed-constellations is analyzed, in which the USD parameters are fixed with our generated values. The results are evaluated in terms of both positioning accuracy and convergence time.

Collaborative learning and critical thinking in technology-enhanced environments : an instructional design framework

The nature and characteristics of how learners learn today are changing. As technology use in learning and teaching continues to grow, its integration to facilitate deep learning and critical thinking becomes a primary consideration. The implications for learner use, implementation strategies, design of integration frameworks and evaluation of their effectiveness in learning environments cannot be overlooked. This study specifically looked at the impact that technology-enhanced learning environments have on different learners’ critical thinking in relation to eductive ability, technological self-efficacy, and approaches to learning and motivation in collaborative groups. These were explored within an instructional design framework called CoLeCTTE (collaborative learning and critical thinking in technology-enhanced environments) which was proposed, revised and used across three cases. The field of investigation was restricted to three key questions: 1) Do learner skill bases (learning approach and eductive ability) influence critical thinking within the proposed CoLeCTTE framework? If so, how?; 2) Do learning technologies influence the facilitation of deep learning and critical thinking within the proposed CoLeCTTE framework? If so, how?; and 3) How might learning be designed to facilitate the acquisition of deep learning and critical thinking within a technology-enabled collaborative environment? The rationale, assumptions and method of research for using a mixed method and naturalistic case study approach are discussed; and three cases are explored and analysed. The study was conducted at the tertiary level (undergraduate and postgraduate) where participants were engaged in critical technical discourse within their own disciplines. Group behaviour was observed and coded, attributes or skill bases were measured, and participants interviewed to acquire deeper insights into their experiences. A progressive case study approach was used, allowing case investigation to be implemented in a "ladder-like" manner. Cases 1 and 2 used the proposed CoLeCTTE framework with more in-depth analysis conducted for Case 2 resulting in a revision of the CoLeCTTE framework. Case 3 used the revised CoLeCTTE framework and in-depth analysis was conducted. The findings led to the final version of the framework. In Cases 1, 2 and 3, content analysis of group work was conducted to determine critical thinking performance. Thus, the researcher used three small groups where learner skill bases of eductive ability, technological self-efficacy, and approaches to learning and motivation were measured. Cases 2 and 3 participants were interviewed and observations provided more in-depth analysis. The main outcome of this study is analysis of the nature of critical thinking within collaborative groups and technology-enhanced environments positioned in a theoretical instructional design framework called CoLeCTTE. The findings of the study revealed the importance of the Achieving Motive dimension of a student’s learning approach and how direct intervention and strategies can positively influence critical thinking performance. The findings also identified factors that can adversely affect critical thinking performance and include poor learning skills, frustration, stress and poor self-confidence, prioritisations over learning; and inadequate appropriation of group role and tasks. These findings are set out as instructional design guidelines for the judicious integration of learning technologies into learning and teaching practice for higher education that will support deep learning and critical thinking in collaborative groups. These guidelines are presented in two key areas: technology and tools; and activity design, monitoring, control and feedback.

Consumers' behavioural responses toward technology-based social products

This thesis examined the determinants of consumers’ use of emerging mental health services delivered via mobile phone technology, which promise to provide cost-effective psychotherapeutic support where and when needed. It builds on the Model of Goal-Directed Behaviour by recognising the role that competition between behavioural alternatives plays in influencing consumers’ decision to use these services. The research employed a three-study, mixed-methodological approach.

Feeding attitudes, practices and traditional dietary beliefs of Chinese mothers with young children in Australia : a mixed methods study

Background and Objectives Obesity and some dietary related diseases are emerging health problems among Chinese immigrants and their children in developed countries. These health problems are closely linked to eating habits, which are established in the early years of life. Young children’s eating habits are likely to persist into later childhood and youth. Family environment and parental feeding practices have a strong effect on young children’s eating habits. Little information is available on the early feeding practices of Chinese mothers in Australia. The aim of this study was to understand the dietary beliefs, feeding attitudes and practices of Chinese mothers with young children who were recent immigrants to Australia. Methods Using a sequential explanatory design, this mixed methods study consisted of two distinct phases. Phase 1 (quantitative): 254 Chinese immigrant mothers of children aged 12 to 59 months completed a cross-sectional survey. The psychometric properties and factor structure of a Chinese version of the Child Feeding Questionnaire (CFQ, by Birch et al. 2001) were assessed and used to measure specific maternal feeding attitudes and controlling feeding practices. Other questions were developed from the literature and used to explore maternal traditional dietary beliefs and feeding practices related to their beliefs, perceptions of picky eating in children and a range of socioeconomic and acculturation factors. Phase 2 (qualitative): 21 mothers took part in a follow-up telephone interview to assist in explaining and interpreting some significant findings obtained in the first phase. Results Chinese mothers held strong traditional dietary beliefs and fed their children according to these beliefs. However, children’s consumption of non-core foods was high. Both traditional Chinese and Australian style foods were consumed by their children. Confirmatory factor analysis revealed that the original 7-factor model of the CFQ provided an acceptable fit to the data with minor modification. However, an alternative model with eight constructs in which two items related to using food rewards were separated from the original restriction construct, not only provided an acceptable fit to the data, but also improved the conceptual clarity of the constructs. The latter model included 24 items loading onto the following eight constructs: restriction, pressure to eat, monitoring, use of food rewards, perceived responsibility, perception of own weight, perception of child’s weight, and concern about child becoming overweight. The internal consistency of the constructs was acceptable or desirable (Cronbach’s α = .60 - .93). Mothers reported low levels of concern about their child overeating or becoming overweight, but high levels of controlling feeding practices: restriction, monitoring, pressure to eat and use of food rewards. More than one quarter of mothers misinterpreted their child’s weight status (based on mothers’ self-reported data). In addition, mothers’ controlling feeding practices independently predicted half of the variance and explained 16% of the variance in child weight status: pressuring the child to eat was negatively associated with child weight status (β = -0.30, p < .01) and using food rewards was positively associated with child weight status (β = 0.20, p < .05) after adjusting for maternal and child covariates. Monitoring and restriction were not associated with child weight status. Mothers’ perceptions of their child’s weight were positively associated with child weight status (β = 0.33, p < .01). Moreover, mothers reported that they mostly decided what (65%) and how much (80%) food their child ate. Mothers who decided what food their child ate were more likely to monitor (β = -0.17, p < .05) and restrict (β = -0.17, p < .05) their child’s food consumption. Mothers who let their child decide how much food their child ate were less likely to pressure their child to eat (β = -0.38, p < .01) and use food rewards (β = -0.24, p < .01). Mothers’ perceptions of picky eating behaviour were positively associated with their use of pressure (β = 0.21, p < .01) and negatively associated with monitoring (β = -0.16, p < .05) and perceptions of their child’s weight status (β = -0.13, p < .05). Qualitative data showed that pressuring to eat, monitoring and restriction of the child’s food consumption were common practices among these mothers. However, mothers stated that their motivation for monitoring and restricting was to ensure the child’s general health. Mothers’ understandings of picky eating behaviour in their children were consistent with the literature and they reported multiple feeding strategies to deal with it. Conclusion Chinese immigrant mothers demonstrated strong traditional dietary beliefs, a low level of concern for child weight, misperceptions of child weight status, and a high overall level of control in child feeding in this study. The Chinese version of the CFQ, which consists of eight constructs and distinguishes between the constructs using food rewards and restriction, is an appropriate instrument to assess feeding attitudes and controlling feeding practices among Chinese immigrant mothers of young children in Australia. Mothers’ feeding attitudes and practices were associated with children’s weight status and mothers’ perceptions of picky eating behaviour in children after adjusting for a range of socio-demographic maternal and child characteristics. Monitoring and restriction of children’s food consumption according to food selection may be positive feeding practices, whereas pressuring to eat and using food rewards appeared to be negative feeding practices in this study. In addition, the results suggest that these young children have high exposure to energy-dense, nutrient-poor food. There is a need to develop and implement nutrition interventions to improve maternal feeding practices and the dietary quality among children of Chinese immigrant mothers in Australia.

Director competencies for effective enterprise technology governance

In relation to enterprise technology governance (ETG), opinions differ between there being no need for board of director involvement to there being an urgent need for such involvement. This research highlights the need for boards to provide ETG oversight of technology-related strategy, investment and risk, and to be competent in doing so. We identify a large gap between board’s awareness of the importance of ETG, their taking action and the competency requirements for effective ETG. Further, while there is considerable research and literature about operational IT governance frameworks and operational IT competencies, there is no known research into the specific competencies boards of directors need to effectively govern enterprise technology. This research focuses on and develops a board-level ETG competency set using a mixed methods approach within a recognised competency development framework. Further development is tracked using a rigour scale to demonstrate a medium to high level of competency validity for the derived set. This research contributes to practice by providing the first known industry validated ETG competency set situated within new and emerging technology. It contributes to the body of knowledge in the modification and application of competency development and competency validation frameworks not previously applied to the role of board director.

Professional development and technology in second language learning : do best practices work?

This study was undertaken to examine the influence that a set of Professional Development (PD) initiatives had on faculty use of Moodle, a well known Course Management System. The context of the study was a private language university just outside Tokyo, Japan. Specifically, it aimed to identify the way in which the PD initiatives adhered to professional development best practice criteria; how faculty members perceived the PD initiatives; what impact the PD initiatives had on faculty use of Moodle; and other variables that may have influenced faculty in their use of Moodle. The study utilised a mixed methods approach. Participants in the study were 42 teachers who worked at the university in the academic year 2008/9. The online survey consisted of 115 items, factored into 10 constructs. Data was collected through an online survey, semi-structured face-to-face interviews, post-workshop surveys, and a collection of textual artefacts. The quantitative data were analysed in SPSS, using descriptive statistics, Spearman's Rank Order correlation tests and a Kruskal-Wallis means test. The qualitative data was used to develop and expand findings and ideas. The results indicated that the PD initiatives adhered closely to criteria posited in technology-related professional development best practice criteria. Further, results from the online survey, post workshop surveys, and follow up face-to-face interviews indicated that while the PD initiatives that were implemented were positively perceived by faculty, they did not have the anticipated impact on Moodle use among faculty. Further results indicated that other variables, such as perceptions of Moodle, and institutional issues, had a considerable influence on Moodle use. The findings of the study further strengthened the idea that the five variables Everett Rogers lists in his Diffusion of Innovations model, including perceived attributes of an innovation; type of innovation decision; communication channels; nature of the social system; extent of change agents' promotion efforts, most influence the adoption of an innovation. However, the results also indicated that some of the variables in Rogers' DOI seem to have more of an influence than others, particularly the perceived attributes of an innovation variable. In addition, the findings of the study could serve to inform universities that have Course Management Systems (CMS), such as Moodle, about how to utilise them most efficiently and effectively. The findings could also help to inform universities about how to help faculty members acquire the skills necessary to incorporate CMSs into curricula and teaching practice. A limitation of this study was the use of a non-randomised sample, which could appear to have limited the generalisations of the findings to this particular Japanese context.

The use of artificial MicroRNA technology to control gene expression in Arabidopsis thaliana

In plants, double-stranded RNA (dsRNA) is an effective trigger of RNA silencing, and several classes of endogenous small RNA (sRNA), processed from dsRNA substrates by DICER-like (DCL) endonucleases, are essential in controlling gene expression. One such sRNA class, the microRNAs (miRNAs) control the expression of closely related genes to regulate all aspects of plant development, including the determination of leaf shape, leaf polarity, flowering time, and floral identity. A single miRNA sRNA silencing signal is processed from a long precursor transcript of nonprotein-coding RNA, termed the primary miRNA (pri-miRNA). A region of the pri-miRNA is partially self-complementary allowing the transcript to fold back onto itself to form a stem-loop structure of imperfectly dsRNA. Artificial miRNA (amiRNA) technology uses endogenous pri-miRNAs, in which the miRNA and miRNA*(passenger strand of the miRNA duplex) sequences have been replaced with corresponding amiRNA/ amiRNA*sequences that direct highly efficient RNA silencing of the targeted gene. Here, we describe the rules for amiRNA design, as well as outline the PCR and bacterial cloning procedures involved in the construction of an amiRNA plant expression vector to control target gene expression in Arabidopsis thaliana. © 2014 Springer Science+Business Media New York.

Characterising an ECG signal using statistical modelling : a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.

Paper-based mixed reality sketch augmentation as a conceptual design support tool

This undergraduate student paper explores usage of mixed reality techniques as support tools for conceptual design. A proof-of-concept was developed to illustrate this principle. Using this as an example, a small group of designers was interviewed to determine their views on the use of this technology. These interviews are the main contribution of this paper. Several interesting applications were determined, suggesting possible usage in a wide range of domains. Paper-based sketching, mixed reality and sketch augmentation techniques complement each other, and the combination results in a highly intuitive interface.

Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

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.

Organisational culture, leadership behaviour and job satisfaction among primary health care professionals in Saudi Arabia : a mixed-methods study

The purpose of this study was to improve individual and organisational performance in primary health care (PHC) by identifying the relationship between organisational culture, leadership behaviour and job satisfaction. The study used a sequential explanatory mixed methods design, to investigate the relationships between organisational culture, leadership behaviour, and job satisfaction among 550 PHCC professionals in Saudi Arabia. From surveying the PHC professionals, the results highlighted the importance of human caring qualities, including praise and recognition, consideration, and support, with respect to their perceptions of job satisfaction, leadership behaviour, and organisational culture. As a consequence a management framework was proposed to address these issues.

Modelling busway operation with mixed stopping and non-stopping buses

This thesis investigated the complexity of busway operation with stopping and non-stopping buses using field data and microscopic simulation modelling. The proposed approach made significant recommendations to transit authorities to achieve the most practicable system capacity for existing and new busways. The empirical equations developed in this research and newly introduced analysis methods will be ideal tools for transit planners to achieve optimal reliability of busways.