1000 resultados para fleixible learning
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This chapter focuses on ‘intergenerational collaborative drawing’, a particular process of drawing whereby adults and children draw at the same time on a blank paper space. Such drawings can be produced for a range of purposes, and based on different curriculum or stimulus subjects. Children of all ages, and with a range of physical and intellectual abilities are able to draw with parents, carers and teachers. Intergenerational collaborative drawing is a highly potent method for drawing in early childhood contexts because it brings adults and children together in the process of thinking and theorizing in order to create visual imagery and this exposes in deep ways to adults and children, the ideas and concepts being learned about. For adults, this exposure to a child’s thinking is a far more effective assessment tool than when they are presented with a finished drawing they know little about. This chapter focuses on drawings to examine wider issues of learning independence and how in drawing, preferred schema in the form of hand-out worksheets, the suggestive drawings provided by adults, and visual material seen in everyday life all serve to co-opt a young child into making particular schematic choices. I suggest that intergenerational collaborative drawing therefore serves to work as a small act of resistance to that co-opting, in that it helps adults and children to collectively challenge popular creativity and learning discourses.
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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.
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Accounting education is critical and any improvements in tertiary education of accounting students should result in better prepared graduates entering the profession. This study evaluates accounting students’ learning styles and the interaction of learning styles and teaching methodologies during degree programmes. Nine classes of accounting students (648 students) spread across four years and two degree programmes were evaluated. Students self-evaluated their learning style, pre-instruction. They were then subject to two separate teaching techniques (one active and one passive) in each course. Learning styles were then re-assessed and teaching techniques evaluated. Accounting students displayed a preference for passive learning, even those far advanced in their degrees. Furthermore, when learning styles matched teaching methods used, usefulness was assessed as high but when learning styles and teaching methods differed, usefulness deteriorated. Overall, the teaching methods were deemed more effective by active rather than passive learners. The implications are significant. To maximise educational benefit for the accounting profession, student learning styles should be assessed before designing appropriate teaching methodologies. This has resource implications which would have to be considered.
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This project develops and evaluates a model of curriculum design that aims to assist student learning of foundational disciplinary ‘Threshold Concepts’. The project uses phenomenographic action research, cross-institutional peer collaboration and the Variation Theory of Learning to develop and trial the model. Two contrasting disciplines (Physics and Law) and four institutions (two research-intensive and two universities of technology) were involved in the project, to ensure broad applicability of the model across different disciplines and contexts. The Threshold Concepts that were selected for curriculum design attention were measurement uncertainty in Physics and legal reasoning in Law. Threshold Concepts are key disciplinary concepts that are inherently troublesome, transformative and integrative in nature. Once understood, such concepts transform students’ views of the discipline because they enable students to coherently integrate what were previously seen as unrelated aspects of the subject, providing new ways of thinking about it (Meyer & Land 2003, 2005, 2006; Land et al. 2008). However, the integrative and transformative nature of such threshold concepts make them inherently difficult for students to learn, with resulting misunderstandings of concepts being prevalent...
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Building a community of shared practice at the classroom level calls for clarity about the important assessment capabilities and dispositions of teachers, especially when teachers are expected to take a direct focus on learning. In this chapter, we present new ways of thinking about teachers’ assessment literacies, offering a formulation of better assessment for the improvement of learning, including three elements, namely (i) assessment criteria and standards; (ii) the teacher’s professional judgment; and (iii) social moderation. The potential of the first element lies in teachers’ classroom practices that deliberately embed assessment criteria and standards in pedagogy in productive ways. The second element involves the engagement of teachers and students in judgment practice, that develops the understanding that judgment involves more than the application of explicit or stated criteria. More fundamental is the matter of how teachers bring to bear stated features of quality and other intellectual and experiential resources in arriving at judgment. That is to say, they range across and orient to explicit (stated), tacit (unstated) and meta-criteria in judgment making. These insights have direct relevance to teachers’ efforts to develop students’ own evaluative experience, especially as this involves students working with stated features of quality for self-assessment and peer-assessment purposes. Further, practices for social moderation are discussed, giving examples of good practice in moderation, how teachers experience moderation and the potential benefits of various types.
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This edition of ALARj has a focus on the contribution of action learning and action research to the development of community services, particularly nonprofits. The landscape of community services has been changing rapidly in recent decades, and can be typified by the notion of complexity. Complexity in the nature of issues that services seek to respond to, complexity in the policy environment and systems of support that have tended to silo and compartmentalise problems and people, and complexity in the institutional location non-profit services occupy in ‘helping’ those who are seen as ‘in need’ or marginalised. In addition to being typified by complexity the environment in which community services are located is dynamic, undergoing profound and ongoing change as neo-liberal approaches to understanding and responding to human need, which emphasise the individualisation of risk, and market principles such as choice, competition and innovation, drive social policy. How can long held values of empowerment, care, inclusivity and benefit to individuals and communities have expression in community services as they grapple with the challenges of being viable and relevant in such a dynamically changing environment? This edition brings together a range of contributions which speak to these challenges. The thematic through these is that processes are needed which engage services and communities in ongoing processes of inquiry about how they can best proceed in contexts typified by complexity and change. Action learning and action research can provide processes of this character.
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Background The learning and teaching of epidemiology is core to many public health programs. Many students find the content of epidemiology, and specifically risk of bias assessment, challenging to learn. Howbeit, learning is enhanced when knowledge is able to be acquired from an active-learning, hands-on experience. Methods The innovative use of wireless audience response technology “clickers” was incorporated into the lectures of the university’s post-graduate epidemiology units and the tailored epidemiological modules delivered for professional disciplines (e.g. optometry). Clickers were used to apply several pedagogical approaches of active learning including peer-instruction and real-world simulation. Students were also assessed for their gain in knowledge within the lecture (pre-post) and their perceptions of how the use of clickers helped them learn. The routine university-wide end of semester Insight Survey provided further information of the student’s satisfaction with the approach. Results The technology was useful in identifying deficits of knowledge of key concepts either before or after instruction. Where key concepts were re-tested post-lecture, as expected, knowledge increased significantly and provided immediate feed-back to students. Across the lecture series, typically 85% of students identified the technology helped them learn, increased their opportunity to interact with the lecturer, and recommend their use for future classes. The Insight Survey report identified 93% of respondents identified the unit in which clickers were consistently used provided good learning opportunities. Numerous student comments supported the teaching method. Conclusions Epidemiological subject matter lends itself to incorporation of audience response technology. The use of the technology to facilitate interactive voting provides an instant response and participation of everyone to enhance the classroom experience. The pedagogical approach increases students’ knowledge and increases their satisfaction with the unit.
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The modern day Australian law school is expected to educate and engage law students. Ideally law school will instil a sense of passion (or at least appreciation) for the law, promote a positive professional identity, foster a sense of community, and provide general support to law students. Collectively, the Australian legal academy is struggling with these goals. Significant numbers of students feel isolated, disconnected and unengaged throughout their tertiary legal education. Teaching students from increasingly diverse backgrounds, who spend less time on campus and less face-to-face time in class, many law academics feel ill-equipped to respond to the challenge of engaging law students in time and cost efficient ways. Intentionally learning and using student names has potential to humanise the law school experience, build community, and positively impact upon the wellbeing of students and staff.
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Literacy in the Middle Years: Learning from Collaborative Classroom Research, showcases teachers' innovative literacy work across the curriculum. Classroom practice, teacher thinking and collaborative research are highlighted in ways of working with new curricula and rapidly changing literacy modes and platforms. Connections with place, critical engagement with digital literacies, using polymedia with EAL/D learners, and subject-specific literacies are detailed in teachers' stories of practice. Teacher wellbeing, for a sustainable workforce, underpins the case studies, aimed at equipping 'change ready' teachers with positive examples of literacy approaches and inquiry in practice.
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This case study research investigated the extent to which Vietnamese teachers understood the concept of learner autonomy and how their beliefs about this concept were applied in their teaching practices. Data were collected through two phases of the study and revealed that teachers generally lacked understanding about learner autonomy; there was an alignment between this lack of understanding and teachers' actual teaching practices regarding learner autonomy. The findings of this study will provide teachers and policy-makers new insights into learner autonomy against the backdrop of educational reforms in Vietnam.
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This study set out to investigate the kinds of learning difficulties encountered by the Malaysian students and how they actually coped with online learning. The modified Online Learning Environment Survey (OLES) instrument was used to collect data from the sample of 40 Malaysian students at a university in Brisbane, Australia. A controlled group of 35 Australian students was also included for comparison purposes. Contrary to assumptions from previous researches, the findings revealed that there were only a few differences between the international Asian and Australian students with regards to their perceptions of online learning. Recommendations based on the findings of this research study were applicable for Australian universities which have Asian international students enrolled to study online.
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Several researchers have reported that cultural and language differences can affect online interactions and communications between students from different cultural backgrounds. Other researchers have asserted that online learning is a tool that can improve teaching and learning skills, but its effectiveness depends on how the tool is used. To delve into these aspects further, this study set out to investigate the kinds of learning difficulties encountered by the international students and how they actually coped with online learning. The modified Online Learning Environment Survey (OLES) instrument was used to collect data from the sample of 109 international students at a university in Brisbane. A smaller group of 35 domestic students was also included for comparison purposes. Contrary to assumptions from previous research, the findings revealed that there were only few differences between the international Asian and Australian students with regards to their perceptions of online learning. Recommendations based on the findings of this research study were made for Australian universities where Asian international students study online. Specifically the recommendations highlighted the importance of upskilling of lecturers’ ability to structure their teaching online and to apply strong theoretical underpinnings when designing learning activities such as discussion forums, and for the university to establish a degree of consistency with regards to how content is located and displayed in a learning management system like Blackboard.
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Digital learning has come a long way from the days of simple 'if-then' queries. It is now enabled by countless innovations that support knowledge sharing, openness, flexibility, and independent inquiry. Set against an evolutionary context this study investigated innovations that directly support human inquiry. Specifically, it identified five activities that together are defined as the 'why dimension' – asking, learning, understanding, knowing, and explaining why. Findings highlight deficiencies in mainstream search-based approaches to inquiry, which tend to privilege the retrieval of information as distinct from explanation. Instrumental to sense-making, the 'why dimension' provides a conceptual framework for development of 'sense-making technologies'.
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Background Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. Aims In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Results Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. Conclusion The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.