Analysing mentoring dialogues for developing a preservice teacher’s classroom management practices

Mentors (cooperating classroom teachers) have a shared responsibility with universities for developing preservice teachers’ pedagogical practices, particularly towards becoming reflective practitioners. Preservice teachers need to participate actively in their own learning, by reflecting and acting on the mentor’s constructive feedback provided during planning and feedback dialogue sessions. This case study uses feedback practices outlined within a five-factor mentoring model to analyse dialogue between a mentor and her respective mentee during different stages in their school-based programs (first practicum). This investigation uses multiple data sources such as video and audio-recorded interviews, archival documents from participants such as lesson plans, reflections and reports to examine preservice teacher’s reflections and implementations of practice as a result of her mentor’s feedback (e.g., establish expectations, review lesson plans, observe teaching then provide oral and written feedback, and evaluate progress). Findings indicated that reflective thinking was more apparent when the mentor did not dominate conversations but instead asked astute pedagogical knowledge questions to facilitate the mentee’s reflections on practice.

Analysing mentoring practices to understand how a preservice teacher reflects on practice to advance teaching

Mentors (cooperating classroom teachers) have a shared responsibility with universities for developing preservice teachers’ pedagogical practices, particularly towards becoming reflective practitioners. Preservice teachers need to participate actively in their own learning, by reflecting and acting on the mentor’s constructive feedback provided during planning and feedback dialogue sessions. This case study uses feedback practices outlined within a five-factor mentoring model to analyse dialogue between a mentor and her respective mentee during different stages in their school-based programs (first practicum). This investigation uses multiple data sources such as video and audio-recorded interviews, archival documents from participants such as lesson plans, reflections and reports to examine preservice teacher’s reflections and implementations of practice as a result of her mentor’s feedback (e.g., establish expectations, review lesson plans, observe teaching then provide oral and written feedback, and evaluate progress). Findings indicated that reflective thinking was more apparent when the mentor did not dominate conversations but instead asked astute pedagogical knowledge questions to facilitate the mentee’s reflections on practice.

Improvisation in interactive music systems

This project investigates machine listening and improvisation in interactive music systems with the goal of improvising musically appropriate accompaniment to an audio stream in real-time. The input audio may be from a live musical ensemble, or playback of a recording for use by a DJ. I present a collection of robust techniques for machine listening in the context of Western popular dance music genres, and strategies of improvisation to allow for intuitive and musically salient interaction in live performance. The findings are embodied in a computational agent – the Jambot – capable of real-time musical improvisation in an ensemble setting. Conceptually the agent’s functionality is split into three domains: reception, analysis and generation. The project has resulted in novel techniques for addressing a range of issues in each of these domains. In the reception domain I present a novel suite of onset detection algorithms for real-time detection and classification of percussive onsets. This suite achieves reasonable discrimination between the kick, snare and hi-hat attacks of a standard drum-kit, with sufficiently low-latency to allow perceptually simultaneous triggering of accompaniment notes. The onset detection algorithms are designed to operate in the context of complex polyphonic audio. In the analysis domain I present novel beat-tracking and metre-induction algorithms that operate in real-time and are responsive to change in a live setting. I also present a novel analytic model of rhythm, based on musically salient features. This model informs the generation process, affording intuitive parametric control and allowing for the creation of a broad range of interesting rhythms. In the generation domain I present a novel improvisatory architecture drawing on theories of music perception, which provides a mechanism for the real-time generation of complementary accompaniment in an ensemble setting. All of these innovations have been combined into a computational agent – the Jambot, which is capable of producing improvised percussive musical accompaniment to an audio stream in real-time. I situate the architectural philosophy of the Jambot within contemporary debate regarding the nature of cognition and artificial intelligence, and argue for an approach to algorithmic improvisation that privileges the minimisation of cognitive dissonance in human-computer interaction. This thesis contains extensive written discussions of the Jambot and its component algorithms, along with some comparative analyses of aspects of its operation and aesthetic evaluations of its output. The accompanying CD contains the Jambot software, along with video documentation of experiments and performances conducted during the project.

When non-significance may be significant : lessons learned from a study of the development, implementation and evaluation of a fleet risk assessment tool

This paper reports on the development and implementation of a self-report risk assessment tool that was developed in an attempt to increase the efficacy of crash prediction within Australian fleet settings. This study forms a part of a broader program of research into work related road safety and identification of driving risk. The first phase of the study involved a series of focus groups being conducted with 217 professional drivers which revealed that the following factors were proposed to influence driving performance: Fatigue, Knowledge of risk, Mood, Impatience and frustration, Speed limits, Experience, Other road users, Passengers, Health, and Culture. The second phase of the study involved piloting the newly developed 38 item Driving Risk Assessment Scale - Work Version (DRAS-WV) with 546 professional drivers. Factor analytic techniques identified a 9 factor solution that was comprised of speeding, aggression, time pressure, distraction, casualness, awareness, maintenance, fatigue and minor damage. Speeding and aggressive driving manoeuvres were identified to be the most frequent aberrant driving behaviours engaged in by the sample. However, a series of logistic regression analyses undertaken to determine the DRAS-WV scale’s ability to predict self-reported crashes revealed limited predictive efficacy e.g., 10% of crashes. This paper outlines proposed reasons for this limited predictive ability of the DRAS-WV as well as provides suggestions regarding the future of research that aims to develop methods to identify “at risk” drivers.

Dimensions of short break destination attractiveness : a comparison of cognitive, affective and conative perceptions

Although there has been exponential growth in the number of studies of destination image appearing in the tourism literature, few have addressed the role of affective perceptions. This paper analyses the market positions held by a competitive set of destinations, through a comparison of cognitive, affective and conative perceptions. Cognitive perceptions were measured by trialling a factor analytic adaptation of importance-performance analysis. Affective perceptions were measured using an affective response grid. The alignment of the results from these techniques identified leadership positions held by two quite different destinations on two quite different dimensions of short break destination attractiveness.

Pressure ulcers in the adult intensive care unit : a literature review of patient risk factors and risk assessment scales

Background: Critically ill patients are at high risk for pressure ulcer (PrU) development due to their high acuity and the invasive nature of the multiple interventions and therapies they receive. With reported incidence rates of PrU development in the adult critical care population as high as 56%, the identification of patients at high risk of PrU development is essential. This paper will explore the association between PrU development and risk factors. It will also explore PrU development and the use of risk assessment scales for critically ill patients in adult intensive care units. Method: A literature search from 2000 to 2012 using the CINHAL, Cochrane Library, EBSCOHost, Medline (via EBSCOHost), PubMed, ProQuest and Google Scholar databases was conducted. Key words used were: pressure ulcer/s; pressure sore/s; decubitus ulcer/s; bed sore/s; critical care; intensive care; critical illness; prevalence; incidence; prevention; management; risk factor; risk assessment scale. Results: Nineteen articles were included in this review; eight studies addressing PrU risk factors, eight studies addressing risk assessment scales and three studies overlapping both. Results from the studies reviewed identified 28 intrinsic and extrinsic risk factors which may lead to PrU development. Development of a risk factor prediction model in this patient population, although beneficial, appears problematic due to many issues such as diverse diagnoses and subsequent patient needs. Additionally, several risk assessment instruments have been developed for early screening of patients at higher risk of developing PrU in the ICU. No existing risk assessment scales are valid for identification high risk critically ill patient,with the majority of scales potentially over-predicting patients at risk for PrU development. Conclusion: Research studies to inform the risk factors for potential pressure ulcer development are inconsistent. Additionally, there is no consistent or clear evidence which demonstrates any scale to better or more effective than another when used to identify the patients at risk for PrU development. Furthermore robust research is needed to identify the risk factors and develop valid scales for measuring the risk of PrU development in ICU.

What factors influence nurses’ assessment practices? Development of the Barriers to Nurses’ use of Physical Assessment Scale

Aim To develop and psychometrically test the Barriers to Nurses’ use of Physical Assessment Scale. Background There is growing evidence of failure to recognise hospitalised patients at risk of clinical deterioration, in part due to inadequate physical assessment by nurses. Yet, little is known about the barriers to nurses’ use of physical assessment in the acute hospital setting and no validated scales have been published. Design Instrument development study. Method Scale development was based on a comprehensive literature review, focus groups, expert review and psychometric evaluation. The scale was administered to 434 acute care registered nurses working at a large Australian teaching hospital between June and July 2013. Psychometric analysis included factor analysis, model fit statistics and reliability testing. Results The final scale was reduced to 38 items representing seven factors, together accounting for 57.7% of the variance: (1) reliance on others and technology, (2) lack of time and interruptions, (3) ward culture, (4) lack of confidence, (5) lack of nursing role models, (6) lack of influence on patient care, and; (7) specialty area. Internal reliability ranged from .70 to .86. Conclusion Findings provide initial evidence for the validity and reliability of the Barriers to Nurses’ use of Physical Assessment Scale and point to the importance of understanding the organisational determinants of nurses’ assessment practices. The new scale has potential clinical and research applications to support nursing assessment in acute care settings.

Recursive pathways to marginal likelihood estimation with prior-sensitivity analysis

We investigate the utility to computational Bayesian analyses of a particular family of recursive marginal likelihood estimators characterized by the (equivalent) algorithms known as "biased sampling" or "reverse logistic regression" in the statistics literature and "the density of states" in physics. Through a pair of numerical examples (including mixture modeling of the well-known galaxy dataset) we highlight the remarkable diversity of sampling schemes amenable to such recursive normalization, as well as the notable efficiency of the resulting pseudo-mixture distributions for gauging prior-sensitivity in the Bayesian model selection context. Our key theoretical contributions are to introduce a novel heuristic ("thermodynamic integration via importance sampling") for qualifying the role of the bridging sequence in this procedure, and to reveal various connections between these recursive estimators and the nested sampling technique.

Using the Driver Behaviour Questionnaire to predict crashes and demerit point loss : does it get better with larger sample sizes?

The Driver Behaviour Questionnaire (DBQ) continues to be the most widely utilised self-report scale globally to assess crash risk and aberrant driving behaviours among motorists. However, the scale also attracts criticism regarding its perceived limited ability to accurately identify those most at risk of crash involvement. This study reports on the utilisation of the DBQ to examine the self-reported driving behaviours (and crash outcomes) of drivers in three separate Australian fleet samples (N = 443, N = 3414, & N = 4792), and whether combining the samples increases the tool’s predictive ability. Either on-line or paper versions of the questionnaire were completed by fleet employees in three organisations. Factor analytic techniques identified either three or four factor solutions (in each of the separate studies) and the combined sample produced expected factors of: (a) errors, (b) highway-code violations and (c) aggressive driving violations. Highway code violations (and mean scores) were comparable across the studies. However, across the three samples, multivariate analyses revealed that exposure to the road was the best predictor of crash involvement at work, rather than DBQ constructs. Furthermore, combining the scores to produce a sample of 8649 drivers did not improve the predictive ability of the tool for identifying crashes (e.g., 0.4% correctly identified) or for demerit point loss (0.3%). The paper outlines the major findings of this comparative sample study in regards to utilising self-report measurement tools to identify “at risk” drivers as well as the application of such data to future research endeavours.

Cost-effectiveness of hospital infection control interventions in resource-limited settings

The aim of this project was to evaluate the cost-effectiveness of hand hygiene interventions in resource-limited hospital settings. Using data from north-east Thailand, the research found that such interventions are likely to be very cost-effective in intensive care unit settings as a result of reduced incidence of methicillin-resistant Staphylococcus aureus bloodstream infection alone. This study also found evidence showing that the World Health Organization's (WHO) multimodal intervention is effective and when adding either goal-setting, reward incentives, or accountability strategies to the WHO intervention, compliance could be further improved.

Economic evaluation of the upselling prevention pilot

The aim of this report was to present findings of an economic evaluation of the UP Pilot. A decision analytic model was used to examine the monetary cost of offering each of the four interventions in the UP Pilot against success measures. The evaluation also included subgroup analysis by demographic groups to offer insights into groups that are more resistant to undertaking preventive actions, with the possibility of further research to better understand client motivation for undertaking preventive behaviour. Based on the evaluation, this report makes recommendations for further investment and implementation of the UP Pilot.

The Connor-Davidson Resilience Scale (CD-RISC): Dimensionality and age-related measurement invariance with Australian cricketers

Objective This study explored the dimensionality and measurement invariance of the 25-item Connor-Davidson Resilience Scale (CD-RISC; Connor & Davidson, 2003) across samples of adult (n = 321; aged 20–36) and adolescent (n = 199; aged 12–18) Australian cricketers. Design Cross-sectional, self-report survey Methods An online, multi-section questionnaire. Results Confirmatory factor and item level analyses supported the psychometric superiority of a revised 10-item, unidimensional model of resilience over the original 25-item, five-factor measurement model. Positive and moderate correlations with hardiness as well as negative and moderate correlations with burnout components were evidenced thereby providing support for the convergent validity of the unidimensional model. Measurement invariance analyses of the unidimensional model across the two age-group samples supported configural (i.e., same factor structure across groups), metric (i.e., same pattern of factor loadings across the groups), and partial scalar invariance (i.e., mostly the same intercepts across the groups). Conclusion Evidence for a psychometrically sound measure of resilient qualities of the individual provides an important foundation upon which researchers can identify the antecedents to and outcomes of resilience in sport contexts.

The cost-effectiveness of exercise referral schemes

Background Exercise referral schemes (ERS) aim to identify inactive adults in the primary care setting. The primary care professional refers the patient to a third party service, with this service taking responsibility for prescribing and monitoring an exercise programme tailored to the needs of the patient. This paper examines the cost-effectiveness of ERS in promoting physical activity compared with usual care in primary care setting. Methods A decision analytic model was developed to estimate the cost-effectiveness of ERS from a UK NHS perspective. The costs and outcomes of ERS were modelled over the patient's lifetime. Data were derived from a systematic review of the literature on the clinical and cost-effectiveness of ERS, and on parameter inputs in the modelling framework. Outcomes were expressed as incremental cost per quality-adjusted life-year (QALY). Deterministic and probabilistic sensitivity analyses investigated the impact of varying ERS cost and effectiveness assumptions. Sub-group analyses explored the cost-effectiveness of ERS in sedentary people with an underlying condition. Results Compared with usual care, the mean incremental lifetime cost per patient for ERS was £169 and the mean incremental QALY was 0.008, generating a base-case incremental cost-effectiveness ratio (ICER) for ERS at £20,876 per QALY in sedentary individuals without a diagnosed medical condition. There was a 51% probability that ERS was cost-effective at £20,000 per QALY and 88% probability that ERS was cost-effective at £30,000 per QALY. In sub-group analyses, cost per QALY for ERS in sedentary obese individuals was £14,618, and in sedentary hypertensives and sedentary individuals with depression the estimated cost per QALY was £12,834 and £8,414 respectively. Incremental lifetime costs and benefits associated with ERS were small, reflecting the preventative public health context of the intervention, with this resulting in estimates of cost-effectiveness that are sensitive to variations in the relative risk of becoming physically active and cost of ERS. Conclusions ERS is associated with modest increase in lifetime costs and benefits. The cost-effectiveness of ERS is highly sensitive to small changes in the effectiveness and cost of ERS and is subject to some significant uncertainty mainly due to limitations in the clinical effectiveness evidence base.

Modeling of the sea surface for daylight imagery studies

Plastic-coated paper is shown to possess reflectivity characteristics quite similar to those of the surface of water. This correspondence has been used with a conversion factor to model a sea surface by means of plastic-coated paper. Such a paper model is then suitably illuminated and photographed, yielding physically simulated daylight imagery of the sea surface under controlled conditions. A simple example of sinusoidal surface simulation is described.

Rotor - Stator broadband noise prediction

In this paper a semi analytic model for rotor - stator broadband noise is presented. The work can be split into two sections. The first examines the distortion of the rotor wake in mean swirling flow, downstream of the fan. Previous work by Cooper and Peake4 is extended to include dissipative effects. In the second section we consider the interaction of this gust with the downstream stator row. We examine the way in which an unsteady pressure field is generated by the interaction of this wake flow with the stator blades and obtain estimates for the radiated noise. A new method is presented to extend the well known LINSUB code to the third dimension to capture the effect of the spanwise wavenumber and stator lean and sweep. Copyright © 2008 by Adrian Lloyd and Nigel Peake.