948 resultados para Infant development


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Vocational psychology and the practice of career development are important dimensions of the psychology discipline. This paper contains an overview of the Australian career development industry in light of recent trends, particularly the formalisation of professional career development practice. Given the advent of the Professional Standards for Career Development Practitioners, an audit of postgraduate degrees in organisational, developmental and educational, and counselling psychology was conducted to determine their alliance with the competencies of the Standards. The audit revealed significant areas of consistency on generic competencies, however there was a serious lack of training specific to career development. The implications of the audit results are discussed in light of the evolution of the career development industry and the threat to psychologists’ standing in this field.

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We surveyed 506 Australian high school students on career development (exploration, planning, job-knowledge, decision-making, indecision), personal functioning (well-being, self-esteem, life satisfaction, school satisfaction) and control variables (parents’ education, school achievement), and tested differences among work-bound, college-bound and university-bound students. The work-bound students had the poorest career development and personal functioning, the university-bound students the highest, with the college-bound students falling in-between the other two groups. Work-bound students did poorest, even after controlling for parental education and school achievement. The results suggest a relationship between career development and personal functioning in high school students.

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Pitch discrimination skills are important for general musicianship. The ability to name musical notes or produce orally any named note without the benefit of a known reference is called Absolute Pitch (AP) and is comparatively rare. Relative Pitch (RP) is the ability to name notes when a known reference is available. AP has historically been regarded as being innate. This paper will examine the notion that pitch discrimination skill is based on knowledge constructed through a suite of experiences. That is, it is learnt. In particular, it will be argued that early experiences promote the development of AP. Second it will argue that AP and RP represent different types of knowledge, and that this knowledge emerges from different experiences. AP is a unique research phenomenon because it spans the fields of cognition and perception, in that it links verbal labels with physiological sensations, and because of its rarity. It may provide a vantage for investigating the nature/nurture of musicianship; expertise; knowledge structure development; and the role of knowledge in perception. The study of AP may inform educational practice and curriculum design both in music and cross-curriculur. This paper will report an initial investigation into the similarities and differences between the musical experiences of AP possessors and the manifestation of their AP skill. Interview and questionnaire data will be used for the development and proposal of a preliminary model for AP development.

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As an understanding of users' tacit knowledge and latent needs embedded in user experience has played a critical role in product development, users’ direct involvement in design has become a necessary part of the design process. Various ways of accessing users' tacit knowledge and latent needs have been explored in the field of user-centred design, participatory design, and design for experiencing. User-designer collaboration has been used unconsciously by traditional designers to facilitate the transfer of users' tacit knowledge and to elicit new knowledge. However, what makes user-designer collaboration an effective strategy has rarely been reported on or explored. Therefore, interaction patterns between the users and the designers in three industry-supported user involvement cases were studied. In order to develop a coding system, collaboration was defined as a set of coordinated and joint problem solving activities, measured by the elicitation of new knowledge from collaboration. The analysis of interaction patterns in the user involvement cases revealed that allowing users to challenge or modify their contextual experiences facilitates the transfer of knowledge and new knowledge generation. It was concluded that users can be more effectively integrated into the product development process by employing collaboration strategies to intensify the depth of user involvement.

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Previous research has demonstrated the importance of the qualities of the teacher-child relationship on children’s development. Close teacher-child relationships are especially important for children at risk. Positive relationships have been shown to have beneficial effects on children’s social and academic development (Birch & Ladd, 1997; Pianta & Stuhlman, 2004). Children with language difficulties are likely to face increased risks with regard to long term social and academic outcomes. The purpose of the current research was to gain greater understanding of the qualities of teacher-child relationships for young children with parent reported language concerns. The research analyses completed for this thesis involved the use of data from the public-access database of Growing Up in Australia: The Longitudinal Study of Australian Children (LSAC). LSAC is a longitudinal study involving a nationally representative sample of 10,000 Australian children. Data are being collected biennially from 2004 (Wave 1 data collection) until 2010 (Wave 4 data collection). LSAC has a cross-sequential research design involving two cohorts, an infant cohort (0-1 year at age of recruitment) and a kindergarten cohort (4-5 years at age of recruitment). Two studies are reported in this thesis using data for the LSAC Kindergarten Cohort which had 4983 child participants at recruitment. Study 1 used Wave 1 data to identify the differences between teacher-child relationship qualities for children with parent reported language concerns and their peers. Children identified by parents for whom concerns were held about their receptive and expressive language, as measured by items from the Parents’ Evaluation of Developmental Status (PEDS) (Glascoe, 2000) were the target (at risk) group in the study (n = 210). A matched case control group of peers (n = 210), matched on the child characteristics of sex, age, cultural and linguistic differences (CALD), and socio-economic positioning (SEP), were the comparison group for this analysis. Teacher-child relationship quality was measured by teacher reports on the Closeness and Conflict scales from the short version of the Student-Teacher Relationship Scale (STRS) (Pianta, 2001). There were statistically significant differences in the levels of closeness and conflict between the two groups. The target group had relationships with their teachers that had lower levels of closeness and higher levels of conflict than the control group. Study 2 reports analyses that examined the stability of the qualities of the teacher-child relationships at Wave 1 (4-5 years) and the qualities of the teacher-child relationships at Wave 2 (6-7 years). This time frame crosses the period of the children’s transition to school. The study examined whether early patterns in the qualities of the teacher-child relationship for children with parent reported language concerns at Wave 1 predicted the qualities of the teacher-child relationship outcomes in the early years of formal school. The sample for this study consisted of the group of children identified with PEDS language concerns at Wave 1 who also had teacher report data at Wave 2 (n = 145). Teacher-child relationship quality at Wave 1 and Wave 2 was again measured by the STRS scales of Closeness and Conflict. Results from multiple regression models indicated that teacher-child relationship quality at Wave 1 significantly contributed to the prediction of the quality of the teacher-child relationship at Wave 2, beyond other predictor variables included in the regression models. Specifically, Wave 1 STRS Closeness scores were the most significant predictor for STRS Closeness scores at Wave 2, while Wave 1 STRS Conflict scores were the only significant predictor for Wave 2 STRS Conflict outcomes. These results indicate that the qualities of the teacher-child relationship experienced prior to school by children with parent reported language concerns remained stable across transitions into formal schooling at which time the child had a different teacher. The results of these studies provide valuable insight into the nature of teacher-child relationship quality for young children with parent reported language concerns. These children experienced teacher-child relationships of a lower quality when compared with peers and, additionally, the qualities of these relationships prior to formal schooling were predictive of the qualities of the relationships in the early years of formal schooling. This raises concerns, given the increased risks of poorer social and academic outcomes already faced by children with language difficulties, that these early teacher-child relationships have an impact on future teacher-child relationships. Results of these studies are discussed with these considerations in mind and also discussed in terms of the implications for educational theory, policy and practice.

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This paper presents research findings about the use of remote desktop applications to teach music sequencing software. It highlights the successes, shortcomings and interactive issues encountered during a pilot project with a theoretical focus on a specific interactive bottleneck. The paper proposes a new delivery and partnership model to widen this bottleneck, which currently hinders interactions between the technical support, education and professional development communities in music technology.

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'The Millennial Adolescent' offers contemporary, stimulating insights for those currently teaching as well as those preparing to teach. This book investigates the characteristics of Generation Y, using students own voices, generational theory and case studies. The text is structured around the principle that effective teachers need to know who they are teaching as well as what to teach, how to teach it, and how to assess the outcome. Using generational theory, 'The Millennial Adolescent' investigates the characteristics of Generation Y, or the Millennial Generation, and points out what all teachers need to know about working with this current generation of students who are described in a number of ways digital natives, team oriented, confident, multi-taskers, high achievers, and a generation unlike any other. The book contains well-known frameworks for developing understandings about adolescents, blended and contrasted with a contemporary socio-cultural construction of adolescence, set in our particular time, era and society. This book reflects the uniqueness of Australian contexts, while connecting with international trends and global patterns. Engaging and full of insights, this book is essential reading for all professionals dealing with adolescents.

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We investigate the relationship between bricolage – an approach to a firm’s resource development – and the firm’s strategic resource position as depicted by the resource-based view (RBV). The RBV is concerned with the resource characteristics of firms that lead to sustainable competitive advantage. Alternatively, bricolage is a process of resource use and development characterised by using resources at hand, recombining resources and making do. Based on a sample of approximately 700 nascent and 700 young firms we find that higher levels of bricolage behaviour tend to lead to more advantageous strategic resource positions.

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We investigate the relationship between bricolage – an approach to a firm’s resource development – and the firm’s strategic resource position as depicted by the resource-based view (RBV). The RBV is concerned with the resource characteristics of firms that lead to sustainable competitive advantage. Alternatively, bricolage is a process of resource use and development characterised by using resources at hand, recombining resources and making do. Based on a sample of 1,329 entrepreneurial start-ups we find that higher levels of bricolage behaviour tend to lead to more advantageous strategic resource positions.

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It has previously been found that complexes comprised of vitronectin and growth factors (VN:GF) enhance keratinocyte protein synthesis and migration. More specifically, these complexes have been shown to significantly enhance the migration of dermal keratinocytes derived from human skin. In view of this, it was thought that these complexes may hold potential as a novel therapy for healing chronic wounds. However, there was no evidence indicating that the VN:GF complexes would retain their effect on keratinocytes in the presence of chronic wound fluid. The studies in this thesis demonstrate for the first time that the VN:GF complexes not only stimulate proliferation and migration of keratinocytes, but also these effects are maintained in the presence of chronic wound fluid in a 2-dimensional (2-D) cell culture model. Whilst the 2-D culture system provided insights into how the cells might respond to the VN:GF complexes, this investigative approach is not ideal as skin is a 3-dimensional (3-D) tissue. In view of this, a 3-D human skin equivalent (HSE) model, which reflects more closely the in vivo environment, was used to test the VN:GF complexes on epidermopoiesis. These studies revealed that the VN:GF complexes enable keratinocytes to migrate, proliferate and differentiate on a de-epidermalised dermis (DED), ultimately forming a fully stratified epidermis. In addition, fibroblasts were seeded on DED and shown to migrate into the DED in the presence of the VN:GF complexes and hyaluronic acid, another important biological factor in the wound healing cascade. This HSE model was then further developed to enable studies examining the potential of the VN:GF complexes in epidermal wound healing. Specifically, a reproducible partial-thickness HSE wound model was created in fully-defined media and monitored as it healed. In this situation, the VN:GF complexes were shown to significantly enhance keratinocyte migration and proliferation, as well as differentiation. This model was also subsequently utilized to assess the wound healing potential of a synthetic fibrin-like gel that had previously been demonstrated to bind growth factors. Of note, keratinocyte re-epitheliasation was shown to be markedly improved in the presence of this 3-D matrix, highlighting its future potential for use as a delivery vehicle for the VN:GF complexes. Furthermore, this synthetic fibrin-like gel was injected into a 4 mm diameter full-thickness wound created in the HSE, both keratinocytes and fibroblasts were shown to migrate into this gel, as revealed by immunofluorescence. Interestingly, keratinocyte migration into this matrix was found to be dependent upon the presence of the fibroblasts. Taken together, these data indicate that reproducible wounds, as created in the HSEs, provide a relevant ex vivo tool to assess potential wound healing therapies. Moreover, the models will decrease our reliance on animals for scientific experimentation. Additionally, it is clear that these models will significantly assist in the development of novel treatments, such as the VN:GF complexes and the synthetic fibrin-like gel described herein, ultimately facilitating their clinical trial in the treatment of chronic wounds.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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This is a review of the book titled 'Rebuilding Native Nations. Strategies Governance and Development', edited by Miriam Jorgensen.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.