292 resultados para collected personal memories
Resumo:
Purpose: The purpose of this paper is to expose the impact of the shortage of senior academics,particularly professors, in Australian accounting schools, to relate the way one school addressed this shortage through a mentoring scheme, and to challenge existing institutional arrangements.----------- Design/methodology/approach: This is a contextualised qualitative case study of a mentoring scheme conducted in an Australian accounting school. Data collected from semi-structured interviews, personal reflections and from Australian university web sites are interpreted theoretically using the metaphor of a “green drought”.---------- Findings: The mentoring scheme achieved some notable successes, but raised many issues and challenges. Mentoring is a multifaceted investment in vocational endeavour and intellectual infrastructure, which will not occur unless creative means are developed over the long term to overcome current and future shortages of academic mentors.---------- Research limitations/implications: This is a qualitative case study, which, therefore, limits its generalisability. However, its contextualisation enables insights to be applied to the wider academic environment. ----------Practical implications: In the Australian and global academic environment, as accounting professors retire in greater numbers, new and creative ways of mentoring will need to be devised. The challenge will be to address longer term issues of academic sustainability, and not just to focus on short-term academic outcomes.---------- Originality/value: A mentoring scheme based on a collegial networking model of mentoring is presented as a means of enhancing academic endeavour through a creative short-term solution to a shortage of accounting professors. The paper exemplifies the theorising power of metaphor in a qualitative study.
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Drivers are known to be optimistic about their risk of crash involvement, believing that they are less likely to be involved in a crash than other drivers. However, little comparative research has been conducted among other road users. In addition, optimism about crash risk is conceptualised as applying only to an individual’s assessment of his or her personal risk of crash involvement. The possibility that the self-serving nature of optimism about safety might be generalised to the group-level as a cyclist or a pedestrian, i.e., becoming group-serving rather than self-serving, has been overlooked in relation to road safety. This study analysed a subset of data collected as part of a larger research project on the visibility of pedestrians, cyclists and road workers, focusing on a set of questionnaire items administered to 406 pedestrians, 838 cyclists and 622 drivers. The items related to safety in various scenarios involving drivers, pedestrians and cyclists, allowing predictions to be derived about group differences in agreement with items based on the assumption that the results would exhibit group-serving bias. Analysis of the responses indicated that specific hypotheses about group-serving interpretations of safety and responsibility were supported in 22 of the 26 comparisons. When the nine comparisons relevant to low lighting conditions were considered separately, seven were found to be supported. The findings of the research have implications for public education and for the likely acceptance of messages which are inconsistent with current assumptions and expectations of pedestrians and cyclists. They also suggest that research into group-serving interpretations of safety, even for temporary roles rather than enduring groups, could be fruitful. Further, there is an implication that gains in safety can be made by better educating road users about the limitations of their visibility and the ramifications of this for their own road safety, particularly in low light.
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Understanding preservice teachers’ memories of their education may aid towards articulating high-impact teaching practices. This study describes 246 preservice teachers’ perceptions of their secondary science education experiences through a questionnaire and 28-item survey. ANOVA was statistically significant about participants’ memories of science with 15 of the 28 survey items. Descriptive statistics through SPSS further showed that a teacher’s enthusiastic nature (87%) and positive attitude towards science (87%) were regarded as highly memorable. In addition, explaining abstract concepts well (79%), and guiding the students’ conceptual development with practical science activities (73%) may be considered as memorable secondary science teaching strategies. Implementing science lessons with one or more of these memorable science teaching practices may “make a difference” towards influencing high school students’ positive long-term memories about science and their science education. Further research in other key learning areas may provide a clearer picture of high-impact teaching and a way to enhance pedagogical practices.
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This study investigated personal and social processes of adjustment at different stages of illness for individuals with brain tumour. A purposive sample of 18 participants with mixed tumour types (9 benign and 9 malignant) and 15 family caregivers was recruited from a neurosurgical practice and a brain tumour support service. In-depth semi-structured interviews focused on participants’ perceptions of their adjustment, including personal appraisals, coping and social support since their brain tumour diagnosis. Interview transcripts were analysed thematically using open, axial and selective coding techniques. The primary theme that emerged from the analysis entailed “key sense making appraisals”, which was closely related to the following secondary themes: (1) Interactions with those in the healthcare system, (2) reactions and support from the personal support network, and (3) a diversity of coping efforts. Adjustment to brain tumour involved a series of appraisals about the illness that were influenced by interactions with those in the healthcare system, reactions and support from people in their support network, and personal coping efforts. Overall, the findings indicate that adjustment to brain tumour is highly individualistic; however, some common personal and social processes are evident in how people make sense of and adapt to the illness over time. A preliminary framework of adjustment based on the present findings and its clinical relevance are discussed. In particular, it is important for health professionals to seek to understand and support individuals’ sense-making processes following diagnosis of brain tumour.
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Background: International data on child maltreatment are largely derived from child protection agencies, and predominantly report only substantiated cases of child maltreatment. This approach underestimates the incidence of maltreatment and makes inter-jurisdictional comparisons difficult. There has been a growing recognition of the importance of health professionals in identifying, documenting and reporting suspected child maltreatment. This study aimed to describe the issues around case identification using coded morbidity data, outline methods for selecting and grouping relevant codes, and illustrate patterns of maltreatment identified. Methods: A comprehensive review of the ICD-10-AM classification system was undertaken, including review of index terms, a free text search of tabular volumes, and a review of coding standards pertaining to child maltreatment coding. Identified codes were further categorised into maltreatment types including physical abuse, sexual abuse, emotional or psychological abuse, and neglect. Using these code groupings, one year of Australian hospitalisation data for children under 18 years of age was examined to quantify the proportion of patients identified and to explore the characteristics of cases assigned maltreatment-related codes. Results: Less than 0.5% of children hospitalised in Australia between 2005 and 2006 had a maltreatment code assigned, almost 4% of children with a principal diagnosis of a mental and behavioural disorder and over 1% of children with an injury or poisoning as the principal diagnosis had a maltreatment code assigned. The patterns of children assigned with definitive T74 codes varied by sex and age group. For males selected as having a maltreatment-related presentation, physical abuse was most commonly coded (62.6% of maltreatment cases) while for females selected as having a maltreatment-related presentation, sexual abuse was the most commonly assigned form of maltreatment (52.9% of maltreatment cases). Conclusion: This study has demonstrated that hospital data could provide valuable information for routine monitoring and surveillance of child maltreatment, even in the absence of population-based linked data sources. With national and international calls for a public health response to child maltreatment, better understanding of, investment in and utilisation of our core national routinely collected data sources will enhance the evidence-base needed to support an appropriate response to children at risk.
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Background: Internationally, research on child maltreatment-related injuries has been hampered by a lack of available routinely collected health data to identify cases, examine causes, identify risk factors and explore health outcomes. Routinely collected hospital separation data coded using the International Classification of Diseases and Related Health Problems (ICD) system provide an internationally standardised data source for classifying and aggregating diseases, injuries, causes of injuries and related health conditions for statistical purposes. However, there has been limited research to examine the reliability of these data for child maltreatment surveillance purposes. This study examined the reliability of coding of child maltreatment in Queensland, Australia. Methods: A retrospective medical record review and recoding methodology was used to assess the reliability of coding of child maltreatment. A stratified sample of hospitals across Queensland was selected for this study, and a stratified random sample of cases was selected from within those hospitals. Results: In 3.6% of cases the coders disagreed on whether any maltreatment code could be assigned (definite or possible) versus no maltreatment being assigned (unintentional injury), giving a sensitivity of 0.982 and specificity of 0.948. The review of these cases where discrepancies existed revealed that all cases had some indications of risk documented in the records. 15.5% of cases originally assigned a definite or possible maltreatment code, were recoded to a more or less definite strata. In terms of the number and type of maltreatment codes assigned, the auditor assigned a greater number of maltreatment types based on the medical documentation than the original coder assigned (22% of the auditor coded cases had more than one maltreatment type assigned compared to only 6% of the original coded data). The maltreatment types which were the most ‘under-coded’ by the original coder were psychological abuse and neglect. Cases coded with a sexual abuse code showed the highest level of reliability. Conclusion: Given the increasing international attention being given to improving the uniformity of reporting of child-maltreatment related injuries and the emphasis on the better utilisation of routinely collected health data, this study provides an estimate of the reliability of maltreatment-specific ICD-10-AM codes assigned in an inpatient setting.
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Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.
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This study explored youth caregiving for a parent with multiple sclerosis (MS) from multiple perspectives, and examined associations between caregiving and child negative (behavioural emotional difficulties, somatisation) and positive (life satisfaction, positive affect, prosocial behaviour) adjustment outcomes overtime. A total of 88 families participated; 85 parents with MS, 55 partners and 130 children completed questionnaires at Time 1. Child caregiving was assessed by the Youth Activities of Caregiving Scale (YACS). Child and parent questionnaire data were collected at Time 1 and child data were collected 12 months later (Time 2). Factor analysis of the child and parent YACS data replicated the four factors (instrumental, social-emotional, personal-intimate, domestic-household care), all of which were psychometrically sound. The YACS factors were related to parental illness and caregiving context variables that reflected increased caregiving demands. The Time 1 instrumental and social-emotional care domains were associated with poorer Time 2 adjustment, whereas personal-intimate was related to better adjustment and domestic-household care was unrelated to adjustment. Children and their parents exhibited highest agreement on personal-intimate, instrumental and total caregiving, and least on domestic-household and social-emotional care. Findings delineate the key dimensions of young caregiving in MS and the differential links between caregiving activities and youth adjustment.
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Comparison are required to understand transport benefits of Transit Oriented Developments (TODs). Mode shares of TOD users need to be understood. Accurate travel demand models for TODs are needed.
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Transit Oriented Developments (TODs) are often designed to promote the use of sustainable modes of transport and reduce car usage. This paper investigates the effect of personal and transit characteristics on travel choices of TOD users. Binary logistic regression models were developed to determine the probability of choosing sustainable modes of transport including walking, cycling and public transport. Kelvin Grove Urban Village (KGUV) located in Brisbane, Australia was chosen as case study TOD. The modal splits for employees, students, shoppers and residents showed that 47% of employees, 84% of students, 71% of shoppers and 56% of residents used sustainable modes of transport.
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The project is working towards building an understanding of the personal interests and experiences of children with the aim of designing appropriate, usable and, most importantly, inspirational educational technology. kidprobe, an adaptation of the technology probe concept, has been used as a lightweight method of gaining contextual information about children's interactions with 'fun' technology. kidprobe has produced design inspiration which focuses primarily on the social and emotional connections children made. The use of kidprobe has generated some important ideas for improving the use of probes with children. It is an important first step in understanding how to effectively adapt probing techniques to inspire the design of technology for children.
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Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.
Resumo:
Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.
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Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.
Resumo:
Item folksonomy or tag information is a kind of typical and prevalent web 2.0 information. Item folksonmy contains rich opinion information of users on item classifications and descriptions. It can be used as another important information source to conduct opinion mining. On the other hand, each item is associated with taxonomy information that reflects the viewpoints of experts. In this paper, we propose to mine for users’ opinions on items based on item taxonomy developed by experts and folksonomy contributed by users. In addition, we explore how to make personalized item recommendations based on users’ opinions. The experiments conducted on real word datasets collected from Amazon.com and CiteULike demonstrated the effectiveness of the proposed approaches.