236 resultados para mobile social learning network


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There is currently a wide range of research into the recent introduction of student response systems in higher education and tertiary settings (Banks 2006; Kay and Le Sange, 2009; Beatty and Gerace 2009; Lantz 2010; Sprague and Dahl 2009). However, most of this pedagogical literature has generated ‘how to’ approaches regarding the use of ‘clickers’, keypads, and similar response technologies. There are currently no systematic reviews on the effectiveness of ‘GoSoapBox’ – a more recent, and increasingly popular student response system – for its capacity to enhance critical thinking, and achieve sustained learning outcomes. With rapid developments in teaching and learning technologies across all undergraduate disciplines, there is a need to obtain comprehensive, evidence-based advice on these types of technologies, their uses, and overall efficacy. This paper addresses this current gap in knowledge. Our teaching team, in an undergraduate Sociology and Public Health unit at the Queensland University of Technology (QUT), introduced GoSoapBox as a mechanism for discussing controversial topics, such as sexuality, gender, economics, religion, and politics during lectures, and to take opinion polls on social and cultural issues affecting human health. We also used this new teaching technology to allow students to interact with each other during class – both on both social and academic topics – and to generate discussions and debates during lectures. The paper reports on a data-driven study into how this interactive online tool worked to improve engagement and the quality of academic work produced by students. This paper will firstly, cover the recent literature reviewing student response systems in tertiary settings. Secondly, it will outline the theoretical framework used to generate this pedagogical research. In keeping with the social and collaborative features of Web 2.0 technologies, Bandura’s Social Learning Theory (SLT) will be applied here to investigate the effectiveness of GoSoapBox as an online tool for improving learning experiences and the quality of academic output by students. Bandura has emphasised the Internet as a tool for ‘self-controlled learning’ (Bandura 2001), as it provides the education sector with an opportunity to reconceptualise the relationship between learning and thinking (Glassman & Kang 2011). Thirdly, we describe the methods used to implement the use of GoSoapBox in our lectures and tutorials, and which aspects of the technology we drew on for learning purposes, as well as the methods for obtaining feedback from the students about the effectiveness or otherwise of this tool. Fourthly, we report cover findings from an examination of all student/staff activity on GoSoapBox as well as reports from students about the benefits and limitations of it as a learning aid. We then display a theoretical model that is produced via an iterative analytical process between SLT and our data analysis for use by academics and teachers across the undergraduate curriculum. The model has implications for all teachers considering the use of student response systems to improve the learning experiences of their students. Finally, we consider some of the negative aspects of GoSoapBox as a learning aid.

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Being across new knowledge is critical to the survival of individual businesses. This study explored the way in which managers of small social services in Queensland identified important new knowledge and brought this into their organisations. New knowledge was found to be highly valued by managers with key resources allocated to knowledge seeking processes particularly in response to regulatory change. Knowledge absorption involved accessing multiple sources, and external professional networks were found to be critical to understanding and integrating new knowledge. The research highlighted the challenges in securing new knowledge and the importance of managers professional links.

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This article explores how universities might engage more effectively with the imperative to develop students’ 21st century skills for the information society, by examining learning challenges and professional learning strategies of successful digital media professionals. The findings of qualitative interviews with professionals from Australian games, online publishing, apps and software development companies reinforce an increasing body of literature that suggests that legacy university structures and pedagogical approaches are not conducive to learning for professional capability in the digital age. Study participants were ambivalent about the value of higher education to digital careers, in general preferring a range of situated online and face-to-face social learning strategies for professional currency. This article draws upon the learning preferences of the professionals in this study to present a model of 21st century learning, as linked with extant theory relating to informal, self-determined learning and communities of practice.

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This research has established a new privacy framework, privacy model, and privacy architecture to create more transparent privacy for social networking users. The architecture is designed into three levels: Business, Data, and Technology, which is based on The Open Group Architecture Framework (TOGAF®). This framework and architecture provides a novel platform for investigating privacy in Social Networks (SNs). This approach mitigates many current SN privacy issues, and leads to a more controlled form of privacy assessment. Ultimately, more privacy will encourage more connections between people across SN services.

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Young drivers represent approximately 20% of the Omani population, yet account for over one third of crash injuries and fatalities on Oman's roads. Internationally, research has demonstrated that social influences play an important role within young driver safety, however, there is little research examining this within Arab gulf countries. This study sought to explore young driver behaviour using Akers' social learning theory. A self-report survey was conducted by 1319 (72.9% male and 27.1% female) young drivers aged 17-25 years. A hierarchical regression model was used to investigate the contribution of social learning variables (norms and behaviour of significant others, personal attitudes towards risky behaviour, imitation of significant others, beliefs about the rewards and punishments offered by risky behaviour), socio-demographic characteristics (age and gender), driving experience (initial training, time driving and previous driving without supervision) and sensitivity to rewards and punishments upon the self-reported risky driving behaviours of young drivers. It was found that 39.6% of the young drivers reported that they have been involved in at least one crash since the issuance of their driving licence and they were considered ‘at fault’ in 60.7% of these crashes. The hierarchical multiple regression models revealed that socio-demographic characteristics and driving experience alone explained 14.2% of the variance in risky driving behaviour. By introducing social learning factors into the model a further 37.0% of variance was explained. Finally, 7.9% of the variance in risky behaviour could be explained by including individual sensitivity to rewards and punishments. These findings and the implications are discussed.

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This demonstration introduces the Connected Learning Analytics (CLA) Toolkit. The CLA toolkit harvests data about student participation in specified learning activities across standard social media environments, and presents information about the nature and quality of the learning interactions.

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Young people aged 17–24 years are at high risk of being killed in road crashes around the world. Road safety interventions consider some influences upon young driver behaviour; for example, imposing passenger restrictions on young novice drivers indirectly minimises the potential negative social influences of peers as passengers. To change young driver risky behaviour, the multitude of psychosocial influences upon its initiation and maintenance must be identified. A study questionnaire was developed to investigate the relationships between risky driving and Akers’ social learning theory, social identity theory, and thrill seeking variables. The questionnaire was completed by 165 participants (105 women,60 men) residing in south-east Queensland, Australia. The sociodemographic variables of age, gender, and exposure explained 19% of the variance in self-reported risky driving behaviour, whilst Akers’ social learning variables explained an additional 42%. Thrill seeking and social identity variables did not explain any significant additional variance. Significant predictors of risky driving included imitation of the driving behaviours of, and anticipated rewards and punishments administered by, parents and peers. Road safety policy that directly considers and incorporates these factors in their design, implementation, and enforcement of young driver road safety interventions should prove more efficacious than current approaches.

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Despite ongoing enhancements to graduated licensing systems, young drivers continue to have a high risk of being killed or injured in car crashes. This study investigated the influence of parents and peers on the risky behaviour of young drivers, utilising Akers’ social learning theory. The specific factors examined related to parent and peer norms perceived by the young driver, and the rewards and punishments anticipated by the young driver from their parents and peers. A questionnaire was completed by 165 young drivers. Regression analysis revealed that these factors explained 54% of the variance in risky driving. The strongest predictor was anticipated parent rewards, followed by peer norms, and anticipated peer rewards. Exploratory analyses however revealed the profile of predictors varied for male and female participants, and for self-reported offenders and non-offenders. The results highlight the role of psychosocial factors in the risky behaviour of young drivers and the need for road safety policies and programs to consider the influence of both parents and peers upon this behaviour.

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As a consequence of the increased incidence of collaborative arrangements between firms, the competitive environment characterising many industries has undergone profound change. It is suggested that rivalry is not necessarily enacted by individual firms according to the traditional mechanisms of direct confrontation in factor and product markets, but rather as collaborative orchestration between a number of participants or network members. Strategic networks are recognised as sets of firms within an industry that exhibit denser strategic linkages among themselves than other firms within the same industry. Based on this, strategic networks are determined according to evidence of strategic alliances between firms comprising the industry. As a result, a single strategic network represents a group of firms closely linked according to collaborative ties. Arguably, the collective outcome of these strategic relationships engineered between firms suggest that the collaborative benefits attributed to interorganisational relationships require closer examination in respect to their propensity to influence rivalry in intraindustry environments. Derived in large from the social sciences, network theory allows for the micro and macro examination of the opportunities and constraints inherent in the structure of relationships in strategic networks, establishing a relational approach upon which the conduct and performance of firms can be more fully understood. Research to date has yet to empirically investigate the relationship between strategic networks and rivalry. The limited research that has been completed utilising a network rationale to investigate competitive patterns in contemporary industry environments has been characterised by a failure to directly measure rivalry. Further, this prior research has typically embedded investigation in industry settings dominated by technological or regulatory imperatives, such as the microprocessor and airline industries. These industries, due to the presence of such imperatives, are arguably more inclined to support the realisation of network rivalry, through subscription to prescribed technological standards (eg., microprocessor industry) or by being bound by regulatory constraints dictating operation within particular market segments (airline industry). In order to counter these weaknesses, the proposition guiding research - Are patterns of rivalry predicted by strategic network membership? – is embedded in the United States Light Vehicles Industry, an industry not dominated by technological or regulatory imperatives. Further, rivalry is directly measured and utilised in research, thus distinguishing this investigation from prior research efforts. The timeframe of investigation is 1993 – 1999, with all research data derived from secondary sources. Strategic networks were defined within the United States Light Vehicles Industry based on evidence of horizontal strategic relationships between firms comprising the industry. The measure of rivalry used to directly ascertain the competitive patterns of industry participants was derived from the traditional Herfindahl Index, modified to account for patterns of rivalry observed at the market segment level. Statistical analyses of the strategic network and rivalry constructs found little evidence to support the contention of network rivalry; indeed, greater levels of rivalry were observed between firms comprising the same strategic network than between firms participating in opposing network structures. Based on these results, patterns of rivalry evidenced in the United States Light Vehicle Industry over the period 1993 – 1999 were not found to be predicted by strategic network membership. The findings generated by this research are in contrast to current theorising in the strategic network – rivalry realm. In this respect, these findings are surprising. The relevance of industry type, in conjunction with prevailing network methodology, provides the basis upon which these findings are contemplated. Overall, this study raises some important questions in relation to the relevancy of the network rivalry rationale, establishing a fruitful avenue for further research.

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Design and Technology has become an important part of the school curriculum. In Queensland, Australia, Technology (which encompasses Design) is one of the Key Learning Areas (KLAs) for students in the first ten years of schooling. This KLA adopts a student-centred, hands-on constructivist approach to teaching and learning. The ability to conceptualise and implement appropriate learning experiences, however, has been a challenge for some early career teachers. This paper describes how Design and Technology is being taught to pre-service primary teachers at an Australian University through their involvement in a range of authentic problem-solving activities supported by social learning tools such as wikis and blogs. An interview with a sample from this group (N=5) provides an insight into how these social software tools enhanced their knowledge and learning. This paper will describe how these social learning tools impact on the agency of learning.

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This paper reports on a large, long-term mobile wireless sensor network deployment. The trial was part of an animal study involving 45 animals. During the trial, 15 animals were equipped with wireless sensor nodes for a week. The paper discusses various issues with such a deployment including electronic design, software design, animal ethics clearance, logistics, and wearable computing equipment for animals. The paper also presents some preliminary analysis of the data obtained from the deployment, both from the perspective of network parameters and animal movement behavior.

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Objective: The Brief Michigan Alcoholism Screening Test (bMAST) is a 10-item test derived from the 25-item Michigan Alcoholism Screening Test (MAST). It is widely used in the assessment of alcohol dependence. In the absence of previous validation studies, the principal aim of this study was to assess the validity and reliability of the bMAST as a measure of the severity of problem drinking. Method: There were 6,594 patients (4,854 men, 1,740 women) who had been referred for alcohol-use disorders to a hospital alcohol and drug service who voluntarily participated in this study. Results: An exploratory factor analysis defined a two-factor solution, consisting of Perception of Current Drinking and Drinking Consequences factors. Structural equation modeling confirmed that the fit of a nine-item, two-factor model was superior to the original one-factor model. Concurrent validity was assessed through simultaneous administration of the Alcohol Use Disorders Identification Test (AUDIT) and associations with alcohol consumption and clinically assessed features of alcohol dependence. The two-factor bMAST model showed moderate correlations with the AUDIT. The two-factor bMAST and AUDIT were similarly associated with quantity of alcohol consumption and clinically assessed dependence severity features. No differences were observed between the existing weighted scoring system and the proposed simple scoring system. Conclusions: In this study, both the existing bMAST total score and the two-factor model identified were as effective as the AUDIT in assessing problem drinking severity. There are additional advantages of employing the two-factor bMAST in the assessment and treatment planning of patients seeking treatment for alcohol-use disorders. (J. Stud. Alcohol Drugs 68: 771-779,2007)

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At the centre of this research is an ethnographic study that saw the researcher embedded within the fabric of inner city life to better understand what characteristics of user activity and interaction could be enhanced by technology. The initial research indicated that the experience of traversing the city after dark unified an otherwise divergent user group through a shared concern for personal safety. Managing this fear and danger represented an important user need. We found that mobile social networking systems are not only integral for bringing people together, they can help in the process of users safely dispersing as well. We conclude, however, that at a time when the average iPhone staggers under the weight of a plethora of apps that do everything from acting as a carpenter’s level to a pregnancy predictor, we consider the potential for the functionality of a personal safety device to be embodied within a stand alone artifact.

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Current graduates in education are entering a very different profession to the one in which most of their “baby-boomer” colleagues started. It is a profession in which accountability and national high-stakes testing (e.g. NAPLAN) have become catch-cries, and where the interpretation and use of educational data is an additional challenge. This has led to schools focusing on performance, and teachers now have to analyse test data and apply the findings to their teaching.

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In an Australian context, the term hooning refers to risky driving behaviours such as illegal street racing and speed trials, as well as behaviours that involve unnecessary noise and smoke, which include burn outs, donuts, fish tails, drifting and other skids. Hooning receives considerable negative media attention in Australia, and since the 1990s all Australian jurisdictions have implemented vehicle impoundment programs to deal with the problem. However, there is limited objective evidence of the road safety risk associated with hooning behaviours. Attempts to estimate the risk associated with hooning are limited by official data collection and storage practices, and the willingness of drivers to admit to their illegal behaviour in the event of a crash. International evidence suggests that illegal street racing is associated with only a small proportion of fatal crashes; however, hooning in an Australian context encompasses a broader group of driving behaviours than illegal street racing alone, and it is possible that the road safety risks will differ with these behaviours. There is evidence from North American jurisdictions that vehicle impoundment programs are effective for managing drink driving offenders, and drivers who continue to drive while disqualified or suspended both during and post-impoundment. However, these programs used impoundment periods of 30 – 180 days (depending on the number of previous offences). In Queensland the penalty for a first hooning offence is 48 hours, while the vehicle can be impounded for up to 3 months for a second offence, or permanently for a third or subsequent offence within three years. Thus, it remains unclear whether similar effects will be seen for hooning offenders in Australia, as no evaluations of vehicle impoundment programs for hooning have been published. To address these research needs, this program of research consisted of three complementary studies designed to: (1) investigate the road safety implications of hooning behaviours in terms of the risks associated with the specific behaviours, and the drivers who engage in these behaviours; and (2) assess the effectiveness of current approaches to dealing with the problem; in order to (3) inform policy and practice in the area of hooning behaviour. Study 1 involved qualitative (N = 22) and quantitative (N = 290) research with drivers who admitted engaging in hooning behaviours on Queensland roads. Study 2 involved a systematic profile of a large sample of drivers (N = 834) detected and punished for a hooning offence in Queensland, and a comparison of their driving and crash histories with a randomly sampled group of Queensland drivers with the same gender and age distribution. Study 3 examined the post-impoundment driving behaviour of hooning offenders (N = 610) to examine the effects of vehicle impoundment on driving behaviour. The theoretical framework used to guide the research incorporated expanded deterrence theory, social learning theory, and driver thrill-seeking perspectives. This framework was used to explore factors contributing to hooning behaviours, and interpret the results of the aspects of the research designed to explore the effectiveness of vehicle impoundment as a countermeasure for hooning. Variables from each of the perspectives were related to hooning measures, highlighting the complexity of the behaviour. This research found that the road safety risk of hooning behaviours appears low, as only a small proportion of the hooning offences in Study 2 resulted in a crash. However, Study 1 found that hooning-related crashes are less likely to be reported than general crashes, particularly when they do not involve an injury, and that higher frequencies of hooning behaviours are associated with hooning-related crash involvement. Further, approximately one fifth of drivers in Study 1 reported being involved in a hooning-related crash in the previous three years, which is comparable to general crash involvement among the general population of drivers in Queensland. Given that hooning-related crashes represented only a sub-set of crash involvement for this sample, this suggests that there are risks associated with hooning behaviour that are not apparent in official data sources. Further, the main evidence of risk associated with the behaviour appears to relate to the hooning driver, as Study 2 found that these drivers are likely to engage in other risky driving behaviours (particularly speeding and driving vehicles with defects or illegal modifications), and have significantly more traffic infringements, licence sanctions and crashes than drivers of a similar (i.e., young) age. Self-report data from the Study 1 samples indicated that Queensland’s vehicle impoundment and forfeiture laws are perceived as severe, and that many drivers have reduced their hooning behaviour to avoid detection. However, it appears that it is more common for drivers to have simply changed the location of their hooning behaviour to avoid detection. When the post-impoundment driving behaviour of the sample of hooning offenders was compared to their pre-impoundment behaviour to examine the effectiveness of vehicle impoundment in Study 3, it was found that there was a small but significant reduction in hooning offences, and also for other traffic infringements generally. As Study 3 was observational, it was not possible to control for extraneous variables, and is, therefore, possible that some of this reduction was due to other factors, such as a reduction in driving exposure, the effects of changes to Queensland’s Graduated Driver Licensing scheme that were implemented during the study period and affected many drivers in the offender sample due to their age, or the extension of vehicle impoundment to other types of offences in Queensland during the post-impoundment period. However, there was a protective effect observed, in that hooning offenders did not show the increase in traffic infringements in the post period that occurred within the comparison sample. This suggests that there may be some effect of vehicle impoundment on the driving behaviour of hooning offenders, and that this effect is not limited to their hooning driving behaviour. To be more confident in these results, it is necessary to measure driving exposure during the post periods to control for issues such as offenders being denied access to vehicles. While it was not the primary aim of this program of research to compare the utility of different theoretical perspectives, the findings of the research have a number of theoretical implications. For example, it was found that only some of the deterrence variables were related to hooning behaviours, and sometimes in the opposite direction to predictions. Further, social learning theory variables had stronger associations with hooning. These results suggest that a purely legal approach to understanding hooning behaviours, and designing and implementing countermeasures designed to reduce these behaviours, are unlikely to be successful. This research also had implications for policy and practice, and a number of recommendations were made throughout the thesis to improve the quality of relevant data collection practices. Some of these changes have already occurred since the expansion of the application of vehicle impoundment programs to other offences in Queensland. It was also recommended that the operational and resource costs of these laws should be compared to the road safety benefits in ongoing evaluations of effectiveness to ensure that finite traffic policing resources are allocated in a way that produces maximum road safety benefits. However, as the evidence of risk associated with the hooning driver is more compelling than that associated with hooning behaviour, it was argued that the hooning driver may represent the better target for intervention. Suggestions for future research include ongoing evaluations of the effectiveness of vehicle impoundment programs for hooning and other high-risk driving behaviours, and the exploration of additional potential targets for intervention to reduce hooning behaviour. As the body of knowledge regarding the factors contributing to hooning increases, along with the identification of potential barriers to the effectiveness of current countermeasures, recommendations for changes in policy and practice for hooning behaviours can be made.