Rethinking emergency management and climate adaptation policies

Emergency management and climate change adaptation will increasingly challenge all levels of government because of three main factors. First, Australia is extremely vulnerable to the impacts of climate change, particularly through the increasing frequency and/or intensity of disasters such as floods and bushfires. Second, the system of government that divides powers by function and level can often act as a barrier to a well-integrated response. Third, policymaking processes struggle to cope with such complex inter-jurisdictional issues. This paper discusses these factors and explores the nature of the challenge for Australian governments. Investigations into the 2009 Victorian bushfires, the 2011 Perth Hills bushfires, and the 2011 Brisbane floods offer an indication of the challenges ahead and it is argued that there is a need to: improve community engagement and communication; refocus attention on resilience; improve interagency communication and collaboration; and, develop institutional arrangements that support continual improvement and policy learning. These findings offer an opportunity for improving responses as well as a starting point for integrating disaster risk management and climate change adaptation policies. The paper is based on the preliminary findings of an NCCARF funded research project: The Right Tool for the Job – Achieving climate change adaptation outcomes through improved disaster management policies, planning and risk management strategies involving Griffith University and RMIT.

Kaleidoscope : Reframing learning and teaching evaluation through a shared stakeholder lens

Sector wide interest in Reframe: QUT’s Evaluation Framework continues with a number of institutions requesting finer details as QUT embeds the new approach to evaluation across the university in 2013. This interest, both nationally and internationally has warranted QUT’s collegial response to draw upon its experiences from developing Reframe into distilling and offering Kaleidoscope back to the sector. The word Reframe is a relevant reference for QUT’s specific re-evaluation, reframing and adoption of a new approach to evaluation; whereas Kaleidoscope reflects the unique lens through which any other institution will need to view their own cultural specificity and local context through an extensive user-led stakeholder engagement approach when introducing new approaches to learning and teaching evaluation. Kaleidoscope’s objectives are for QUT to develop its research-based stakeholder approach to distil the successful experience exhibited in the Reframe Project into a transferable set of guidelines for use by other tertiary institutions across the sector. These guidelines will assist others to design, develop, and deploy, their own culturally specific widespread organisational change informed by stakeholder engagement and organisational buy-in. It is intended that these guidelines will promote, support and enable other tertiary institutions to embark on their own evaluation projects and maximise impact. Kaleidoscope offers an institutional case study of widespread organisational change underpinned by Reframe’s (i) evidence-based methodology; (ii) research including published environmental scan, literature review (Alderman, et al., 2012), development of a conceptual model (Alderman, et al., in press 2013), project management principles (Alderman & Melanie, 2012) and national conference peer reviews; and (iii) year-long strategic project with national outreach to collaboratively engage the development of a draft set of National Guidelines. Kaleidoscope’s aims are to inform Higher Education evaluation policy development through national stakeholder engagement, the finalisation of proposed National Guidelines. In correlation with the conference paper, the authors will present a Draft Guidelines and Framework ready for external peer review by evaluation practitioners from the Higher Education sector, as part of Kaleidoscope’s dissemination strategy (Hinton & Gannaway, 2011) applying illuminative evaluation theory (Parlett & Hamilton, 1976), through conference workshops and ongoing discussions (Shapiro, et al., 1983; Jacobs, 2000). The initial National Guidelines will be distilled from the Reframe: QUT’s Evaluation Framework’s Policy, Protocols, and incorporated Business Rules. It is intended that the outcomes of Kaleidoscope are owned by and reflect sectoral engagement, including iterative evaluation through multiple avenues of dissemination and collaboration including the Higher Education sector. The dissemination strategy with the inclusion of Illuminative Evaluation methodology provides an inclusive opportunity for other institutions and stakeholders across the Higher Education sector to give voice through the information-gathering component of evaluating the draft Guidelines, providing a comprehensive understanding of the complex realities experienced across the Higher Education sector, and thereby ‘illuminating’ both the shared and unique lenses and contexts. This process will enable any final guidelines developed to have broader applicability, greater acceptance, enhanced sustainability and additional relevance benefiting the Higher Education sector, and the adoption and adaption by any single institution for their local contexts.

Learning about being effective mentors : professional learning communities and mentoring

This study aimed to explore experienced mentors’ understandings about professional learning communities (PLCs), mentoring and leadership. This research analyses audio-taped transcripts and written responses from 27 experienced mentors who operate in varied roles (e.g., university academics, school executives, teachers, learning support personnel). Findings indicated that PLCs can provide professional renewal for existing teachers and that mentoring within PLCs can further advance knowledge about effective practices. PLCs can include other staff members and key stakeholders (e.g., preservice teachers, teacher aides) who can contribute to the learning within the group. Mentoring and PLCs can be cost-effective strategic levers for advancing professional knowledge.

Exploring cultural, social and psychosocial influences on women's drinking across the life span

Background Changing trends in women's alcohol consumption have demonstrated that women, in both younger and older cohorts, are drinking at increased levels than previously. However, little research investigates these changing trends or the influences behind them. Aims The current research aims to identify influences on women's drinking across a range of age groups, with a focus on multiple level influences (i.e. cultural, social and psychosocial). Methods One hour semi-structured telephone interviews were conducted, in 2011, with 35 women (aged 18-55) residing in Australia. Interview development was guided by an adaptation of Bronfenbrenner's Bioecological Model of Development (BBMD) to assess multiple areas of influences from cultural through to psychosocial. Results Interview findings highlighted the existence of multiple levels of influence on women’s drinking and thus provided support for the BBMD framework. Cultural influences identified related to gender roles and national identity. Exosystem influences (e.g. legislation, infrastructure, and media) and Microsystem influences (e.g. immediate social networks) were also identified. A range of psychosocial factors, such as identity, normative influence and attitude were also found as influencing drinking behaviours. Finally, changes across a woman’s life span, and intergenerational differences, were Chronosystem constructs that also emerged as key influences. Discussion and conclusions This study has provided an in-depth understanding into the key factors, occurring across multiple levels of influence, impacting upon women's drinking across younger and older cohorts. The findings also highlight changes in alcohol-related attitudes and behaviours across a life span and across generations. Future research should extend upon these findings based on larger, quantitative studies based on representative samples. The findings do provide key insights into the influences that need to be addressed within targeted interventions.

Concealing their communication : exploring psychosocial predictors of young drivers’ intentions and engagement in concealed texting

Making a conscious effort to hide the fact that you are texting while driving (i.e., concealed texting) is a deliberate and risky behaviour involving attention diverted away from the road. As the most frequent users of text messaging services and mobile phones while driving, young people appear at heightened risk of crashing from engaging in this behaviour. This study investigated the phenomenon of concealed texting while driving, and utilised an extended Theory of Planned Behaviour (TPB) including the additional predictors of moral norm, mobile phone involvement, and anticipated regret to predict young drivers’ intentions and subsequent behaviour. Participants (n = 171) were aged 17 to 25 years, owned a mobile phone, and had a current driver’s licence. Participants completed a questionnaire measuring their intention to conceal texting while driving, and a follow-up questionnaire a week later to report their behavioural engagement. The results of hierarchical multiple regression analyses showed overall support for the predictive utility of the TPB with the standard constructs accounting for 69% of variance in drivers’ intentions, and the extended predictors contributing an additional 6% of variance in intentions over and above the standard constructs. Attitude, subjective norm, PBC, moral norm, and mobile phone involvement emerged as significant predictors of intentions; and intention was the only significant predictor of drivers’ self-reported behaviour. These constructs can provide insight into key focal points for countermeasures including advertising and other public education strategies aimed at influencing young drivers to reconsider their engagement in this risky behaviour.

Learning in 140 characters : microblogging for professional learning

This thesis investigated how microblogging, a form of online social networking, was being employed by educators to support their professional learning. The study found that educators who participate in microblogging engage in a wide range of behaviours, with certain behaviours and activities commonly exhibited. An advantage of microblogging as a professional learning tool is its ability to link educators globally to exchange ideas from different perspectives and to share resources and teaching practices. Educators who microblog have access to relevant and timely learning that is not constrained by time or distance and can be tailored to meet their individual needs.

Theorizing why in e-learning – a frontier for cognitive engagement

Asking why is an important foundation of inquiry and fundamental to the development of reasoning skills and learning. Despite this, and despite the relentless and often disruptive nature of innovations in information and communications technology (ICT), sophisticated tools that directly support this basic act of learning appear to be undeveloped, not yet recognized, or in the very early stages of development. Why is this so? To this question, there is no single satisfactory answer; instead, numerous plausible explanations and related questions arise. After learning something, however, explaining why can be revealing of a person’s understanding (or lack of it). What then differentiates explanation from information; and, explanatory from descriptive content? What ICT scaffolding might support inquiry instigated by why-questioning? What is the role of reflective practice in inquiry-based learning? These and other questions have emerged from this investigation and underscore that why-questions often propagate further questions and are a catalyst for cognitive engagement and dialogue. This paper reports on a multi-disciplinary, theoretical investigation that informs the broad discourse on e-learning and points to a specific frontier for design and development of e-learning tools. Probing why reveals that versatile and ambiguous semantics present the core challenge – asking, learning, knowing, understanding, and explaining why.

Scaffolding reflective inquiry - enabling why-questioning while e-Learning

This paper presents some theoretical and interdisciplinary perspectives that might inform the design and development of information and communications technology (ICT) tools to support reflective inquiry during e-learning. The role of why-questioning provides the focus of discussion and is guided by literature that spans critical thinking, inquiry-based and problem-based learning, storytelling, sense-making, and reflective practice, as well as knowledge management, information science, computational linguistics and automated question generation. It is argued that there exists broad scope for the development of ICT scaffolding targeted at supporting reflective inquiry duringe-learning. Evidence suggests that wiki-based learning tasks, digital storytelling, and e-portfolio tools demonstrate the value of accommodating reflective practice and explanatory content in supporting learning; however, it is also argued that the scope for ICT tools that directly support why-questioning as a key aspect of reflective inquiry is a frontier ready for development.

Opening digital learning to deeper inquiry

This chapter presents an historical narrative on the recent evolution of information and communications technology (ICT) that has been, and is, utilized for purposes of learning. In other words, it presents an account of the development of e-learning supported through the Web and other similar virtual environments. It does not attempt to present a definitive account; as such an exercise is fraught with assumptions, contextual bias, and probable conjecture. The concern here is more with contextualizing the role of inquiry in learning and the evolving digital tools that enable interfaces that promote and support it. In tracking this evolution, both multi-disciplinary and trans-disciplinary research has been pursued. Key historical developments are identified as well as interpretations of the key drivers of e-learning over time and into what might be better described as digital learning. Innovations in the development of digital tools are described as dynamic and emergent, evolving as a consequence of multiple, sometimes hidden drivers of change. But conflating advancements in learning technologies with e-learning seems to be pervasive. As is the push for the “open” agenda – a growing number of initiatives and movements dominated by themes associated with access, intellectual property, public benefit, sharing and technical interoperability. Openness is also explored in this chapter, however, more in terms of what it means when associated with inquiry. By investigating opportunities for the stimulation and support of questioning online – in particular, why-questioning – this chapter is focused on “opening” content – not just for access but for inquiry and deeper learning.

Tablets (iPad) for M-Learning in the context of social constructivism to institute an effective learning environment

With the proliferation of mobile devices, educational institutions have experimented with various mobile devices to implement mobile learning (M-Learning). Mobile devices have been used to facilitate, support, and enhance and extend the reach of teaching and learning. Although there are very few empirically evaluated studies on M-Learning projects, these studies reported that mobile devices brought a transformation to the educational process. To be able to view M-Learning as a rich, collaborative and conversational experience, whether in the classroom or outside we need good mobile applications. Studies have revealed that effective learning happens when teachers and learners are actively participating in the knowledge building process. Therefore, there is a need for applications that create effective learning environments which are learner-centred, knowledge-centred, assessment-centred and community-centred.

Learning routines used by firms during construction of infrastructure projects using the alliance procurement method

Collaborative contracting has emerged over the past 15 years as an innovative project delivery framework that is particularly suited to infrastructure projects. Australia leads the world in the development of project and program alliance approaches to collaborative delivery. These approaches are considered to promise superior project results. However, very little is known about the learning routines that are most widely used in support of collaborative projects in general and alliance projects in particular. The literature on absorptive capacity and dynamic capabilities indicates that such learning enhances project performance. The learning routines employed at corporate level during the operation of collaborative infrastructure projects in Australia were examined through a large survey conducted in 2013. This paper presents a descriptive summary of the preliminary findings. The survey captured the experiences of 320 practitioners of collaborative construction projects, including public and private sector clients, contractors, consultants and suppliers (three per cent of projects were located in New Zealand, but for brevity’s sake the sample is referred to as Australian). The majority of projects identified used alliances (78.6%); whilst 9% used Early Contractor Involvement (ECI) contracts and 2.7% used Early Tender Involvement contracts, which are ‘slimmer’ types of collaborative contract. The remaining 9.7% of respondents used traditional contracts that employed some collaborative elements. The majority of projects were delivered for public sector clients (86.3%), and/or clients experienced with asset procurement (89.6%). All of the projects delivered infrastructure assets; one third in the road sector, one third in the water sector, one fifth in the rail sector, and the rest spread across energy, building and mining. Learning routines were explored within three interconnected phases: knowledge exploration, transformation and exploitation. The results show that explorative and exploitative learning routines were applied to a similar extent. Transformative routines were applied to a relatively low extent. It was also found that the most highly applied routine is ‘regularly applying new knowledge to collaborative projects’; and the least popular routine was ‘staff incentives to encourage information sharing about collaborative projects’. Future research planned by the authors will examine the impact of these routines on project performance.

Can we text you? A qualitative exploration of young unemployed job-seekers’ attitudes to receiving resilience-building SMS messages

A significant minority of young job-seekers remain unemployed for many months, and are at risk of developing depression. Both empirical studies and theoretical models suggest that cognitive, behavioural and social isolation factors interact to increase this risk. Thus, interventions that reduce or prevent depression in young unemployed job-seekers by boosting their resilience are required. Mobile phones may be an effective medium to deliver resilience-boosting support to young unemployed people by using SMS messages to interrupt the feedback loop of depression and social isolation. Three focus groups were conducted to explore young unemployed job-seekers’ attitudes to receiving and requesting regular SMS messages that would help them to feel supported and motivated while job-seeking. Participants reacted favourably to this proposal, and thought that it would be useful to continue to receive and request SMS messages for a few months after commencing employment as well.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Incorporating anchored learning in a C# Intelligent Tutoring System

Learning programming is known to be difficult. One possible reason why students fail programming is related to the fact that traditional learning in the classroom places more emphasis on lecturing the material instead of applying the material to a real application. For some students, this teaching model may not catch their interest. As a result they may not give their best effort to understand the material given. Seeing how the knowledge can be applied to real life problems can increase student interest in learning. As a consequence, this will increase their effort to learn. Anchored learning that applies knowledge to solve real life problems may be the key to improving student performance. In anchored learning, it is necessary to provide resources that can be accessed by the student as they learn. These resources can be provided by creating an Intelligent Tutoring System (ITS) that can support the student when they need help or experience a problem. Unfortunately, there is no ITS developed for the programming domain that has incorporated anchored learning in its teaching system. Having an ITS that supports anchored learning will not only be able to help the student learn programming effectively but will also make the learning process more enjoyable. This research tries to help students learn C# programming using an anchored learning ITS named CSTutor. Role playing is used in CSTutor to present a real world situation where they develop their skills. A knowledge base using First Order Logic is used to represent the student's code and to give feedback and assistance accordingly.