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.

Automatic classification of free-text radiology reports to identify limb fractures using machine learning and the SNOMED CT ontology

Objective To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. Materials and Methods 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician resolved disagreements. These assessors found that, of the 99 reports, 48 referred to fractures or abnormalities of limb structures. Automated methods were then used to extract features from these reports that could be useful for their automatic classification. The Naive Bayes classification algorithm and two implementations of the support vector machine algorithm were formally evaluated using cross-fold validation over the 99 reports. Result Results show that the Naive Bayes classifier accurately identifies fractures and other abnormalities from the radiology reports. These results were achieved when extracting stemmed token bigram and negation features, as well as using these features in combination with SNOMED CT concepts related to abnormalities and disorders. The latter feature has not been used in previous works that attempted classifying free-text radiology reports. Discussion Automated classification methods have proven effective at identifying fractures and other abnormalities from radiology reports (F-Measure up to 92.31%). Key to the success of these techniques are features such as stemmed token bigrams, negations, and SNOMED CT concepts associated with morphologic abnormalities and disorders. Conclusion This investigation shows early promising results and future work will further validate and strengthen the proposed approaches.

Effects of corporate support of a charity on public perceptions of the charity

A quasi-experimental design (N=517) was used to investigate the effect on audience response to a supported charity if corporate support is featured in an advertisement. The results indicate that corporate support of a charity appears not to influence audience attitudes and donation intentions for the charity. A small portion of the audience may be motivated to donate when learning of a large corporate donation to the charity. The level of individual's favourability for the charity was the strongest predictor of their attitudes and intentions. Gender was also a predictor of more positive charity attitudes, with females reporting more positive attitudes than males for three of four charities. Managerial implications and areas for future research are discussed.

Building and sustaining a culture to support peer review of teaching

1. Background/context This presentation will report on emerging results from a two phase project funded by the Australian Learning and Teaching Council (ALTC). The project was designed in partnership with five universities and aimed to embed peer review within the local teaching and learning culture by using a distributive leadership framework. 2. The initiative/practice The presentation will highlight research outcomes that bring together both the fundamentals of peer review of teaching with the broader contextual elements of Integration, Leadership and Development. It will be demonstrated that peer review of teaching can be implemented and have advantages for academic staff, teaching evaluation and an organisation if attention is given to strategies that influence the contexts and cultures of teaching. Peer review as a strategy to develop excellence in teaching is considered from a holistic perspective that by necessity encompasses all elements of an educational environment. Results demonstrate achievements that can be obtained through working to foster conditions needed for sustainable leadership and change. The work has implications for policy, research, teaching development and student outcomes and has potential application world-wide. 3. Method(s) of evaluative data collection and analysis The 2 phase project collected focus group and questionnaire data to inform research results that were analysed using a thematic qualitative approach and statistical exploration. 4. Evidence of effectiveness The presentation will demonstrate the effectiveness of distributive leadership and strategic approaches to working for cultural change through the presentation of project findings.

Developing a culture to support peer review of teaching in higher education

This presentation addresses issues related to leadership, academic development and scholarship of teaching and learning, and highlights research funded by the Australian Office of Learning and Teaching (OLT) designed to embed and sustain peer review of teaching within the culture of 5 Australian universities: Queensland University of Technology, University of Technology, Sydney, University of Adelaide, Curtin University, and Charles Darwin University. Peer review of teaching in higher education will be emphasised as a professional process for providing feedback on teaching and learning practice, which if sustained, can become an effective ongoing strategy for academic development (Barnard et al, 2011; Bell, 2005; Bolt and Atkinson, 2010; McGill & Beaty 2001, 1992; Kemmis & McTaggart, 2000). The research affirms that using developmental peer review models (Barnard et al, 2011; D'Andrea, 2002; Hammersley-Fletcher & Orsmond, 2004) can bring about successful implementation, especially when implemented within a distributive leadership framework (Spillane & Healey, 2010). The project’s aims and objectives were to develop leadership capacity and integrate peer review as a cultural practice in higher education. The research design was a two stage inquiry process over 2 years. The project began in July 2011 and encompassed a development and pilot phase followed by a cascade phase with questionnaire and focus group evaluation processes to support ongoing improvement and measures of outcome. Leadership development activities included locally delivered workshops complemented by the identification and support of champions. To optimise long term sustainability, the project was implemented through existing learning and teaching structures and processes within the respective partner universities. Research outcomes highlight the fundamentals of peer review of teaching and the broader contextual elements of integration, leadership and development, expressed as a conceptual model for embedding peer review of teaching within higher education. The research opens a communicative space about introduction of peer review that goes further than simply espousing its worth and introduction. The conceptual model highlights the importance of development of distributive leadership capacity, integration of policies and processes, and understanding the values, beliefs, assumptions and behaviors embedded in an organizational culture. The presentation overviews empirical findings that demonstrate progress to advance peer review requires an ‘across-the-board’ commitment to embed change, and inherently demands a process that co-creates connection across colleagues, discipline groups, and the university sector. Progress toward peer review of teaching as a cultural phenomenon can be achieved and has advantages for academic staff, scholarship, teaching evaluation and an organisation, if attention is given to strategies that influence the contexts and cultures of teaching practice. Peer review as a strategy to develop excellence in teaching is considered from a holistic perspective that by necessity encompasses all elements of an educational environment and has a focus on scholarship of teaching. The work is ongoing and has implication for policy, research, teaching development and student outcomes, and has potential application world-wide.