956 resultados para collaborative online international learning


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The aim of this paper is to analyse and present cloud- link as well as campus-linked students’ perceptions of collaborative learning and design based learning in engineering. Project oriented design based learning (PODBL) is a learning and teaching approach, where students learn through design activities while being driven by project(s). PODBL enhances cloud-linked and campus-linked students’ ability to acquire career essential skills that fulfill future industry needs. A paper-based survey is used to recognise a cohort of students' experience of collaborative learning and design based learning in engineering. The paper-based survey was given to 30 students from an engineering discipline. The quantitative analysis of the survey results shows that more than 50% of the students view collaborative learning to have a large benefit in design-based learning.

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This article reports on the findings of senior leadership interviews in a nationally funded project on distributed leadership in the quality management of online learning environments (OLEs) in higher education. Questions were framed around the development of an OLE quality management framework and the situation of the characteristics of distributed leadership at the core of the framework. The project’s premise is that distributed leadership is a descriptive reality of managing OLEs given the various leadership parties involved and the complexities of the contemporary technological landscape. Leaders’ understandings of distributed leadership were examined—its nature, value and potential for advancing the quality management of OLEs. There was confirmatory evidence of its reality, but its meaning and value were not uncritically accepted. It can be concluded that building distributed leadership must start through deliberative formal leadership commitment and action starting at the highest levels of the institution.

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Critical analysis and problem-solving skills are two graduate attributes that are important in ensuring that graduates are well equipped in working across research and practice settings within the discipline of psychology. Despite the importance of these skills, few psychology undergraduate programmes have undertaken any systematic development, implementation, and evaluation of curriculum activities to foster these graduate skills. The current study reports on the development and implementation of a tutorial programme designed to enhance the critical analysis and problem-solving skills of undergraduate psychology students. Underpinned by collaborative learning and problem-based learning, the tutorial programme was administered to 273 third year undergraduate students in psychology. Latent Growth Curve Modelling revealed that students demonstrated a significant linear increase in self-reported critical analysis and problem-solving skills across the tutorial programme. The findings suggest that the development of inquiry-based curriculum offers important opportunities for psychology undergraduates to develop critical analysis and problem-solving skills. © 2013 The Australian Psychological Society.

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In this paper, we present an analysis on transfer learning using the Fuzzy Min-Max (FMM) neural network with an online learning strategy. Transfer learning leverages information from the source domain in solving problems in the target domain. Using the online FMM model, the data samples are trained one at a time. In order to evaluate the online FMM model, a transfer learning data set, based on data samples collected from real landmines, is used. The experimental results of FMM are analyzed and compared with those from other methods in the literature. The outcomes indicate that the online FMM model is effective for undertaking transfer learning tasks.

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In this paper, a hybrid online learning model that combines the fuzzy min-max (FMM) neural network and the Classification and Regression Tree (CART) for motor fault detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, incorporates the advantages of both FMM and CART for undertaking data classification (with FMM) and rule extraction (with CART) problems. In particular, the CART model is enhanced with an importance predictor-based feature selection measure. To evaluate the effectiveness of the proposed online FMM-CART model, a series of experiments using publicly available data sets containing motor bearing faults is first conducted. The results (primarily prediction accuracy and model complexity) are analyzed and compared with those reported in the literature. Then, an experimental study on detecting imbalanced voltage supply of an induction motor using a laboratory-scale test rig is performed. In addition to producing accurate results, a set of rules in the form of a decision tree is extracted from FMM-CART to provide explanations for its predictions. The results positively demonstrate the usefulness of FMM-CART with online learning capabilities in tackling real-world motor fault detection and diagnosis tasks. © 2014 Springer Science+Business Media New York.

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In this chapter you will learn
• Key success factors for work-based learning students across cultures
• The importance of learning another way to think, write and act to be a successful work-based learning student in a multi-cultural context
• How to build your own personal learning network and wider environment, which will be essential in helping and motivating you through your studies
• How to continually improve your academic performance through self-reflection and self-leadership
• How to plan for and manage