850 resultados para Unsupervised learning


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This study explored the relationship among student approaches to learning and teaching methods on critical thinking in two business units. Key findings included differences in critical thinking scores between student approaches to learning and some evidence of an interaction between student approaches to learning and critical thinking teach method (immersion vs. infusion). Possible explanations for the results are examined and implications for developing critical thinking skills across a degree discussed. What is apparent is that as Universities move towards program-wide level assessment of critical thinking, further work is required in terms of the design of critical thinking teaching interventions and assessment at the unit, school, and degree level. The session will discuss the challenges in developing critical thinking programs in individual units and at the Faculty level.

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The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

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A collaborative research project conducted by five Australian universities inquired into the philosophy and motivation for Assurance of Learning (AoL) as a process of education evaluation. Associate Deans Teaching and Learning representing Business schools from twenty-five universities across Australia participated in telephone interviews. Data was analysed using NVIVO9. Results indicated that articulated rationale for AoL was both ensuring that students had acquired the attributes and skills the universities claimed they had, and the philosophy of continuous improvement. AoL was motivated both by ritualistic objectives to satisfy accreditation requirements and virtuous agendas for quality improvement. Closing-the-loop was emphasised, but was mostly wishful thinking for next steps beyond data collection and reporting. AoL was conceptualised as one element within the larger context of quality review, but there was no evidence of comprehensive frameworks or strategic plans.

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Assurance of learning (AoL) is an important process in quality education, designed to measure the accomplishment of educational aims at the core of an institution’s programs, whilst encouraging faculty to continuously develop and improve the programs and courses. This paper reports on a study of Australian business schools to investigate current AoL practices through semi structured interviews with senior faculty leaders followed by focus group interviews with groups of senior program leaders and groups of academic teaching staff. Initial findings indicate there are significant challenges in encouraging academic staff to commit to the process and recognise the benefits of assuring learning. The differences in understanding between the various leaders and the academics were highlighted through the different focus groups. Leaders’ stressed strategic issues such as staff engagement and change, while academics focussed on process issues such as teaching graduate attributes and external accreditation. Understanding the differences in the perspectives of leaders and faculty is important, as without a shared understanding between the two groups, there is likely to be limited engagement, which creates difficulties in developing effective assurance of learning processes. Findings indicate that successful strategies developed to foster shared values on assurance of learning include: strong senior leaders’ commitment; developing champions among program and unit level staff; providing professional development opportunities; promoting and celebrating success and effectiveness; and ensuring an inclusive process with academics of all levels collaborating in the development and implementation of the process.

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The aim of this paper is to contribute to our understanding of the link between HR practices, learning orientation and types of innovation in knowledge-intensive firms (KIFs). To this end, we first compiled a comprehensive overview of the existing literature on HR practices aimed at supporting innovation. On the basis of this literature, we then collected and analyzed data from a qualitative study of 19 Danish KIFs recognized for their innovation performance, focusing on links between the HR practices they use to support exploratory and exploitive learning behaviors to enhance incremental and/or radical innovation. The findings from this study demonstrate that KIFs utilize a range of HR practices that enable different learning orientations, based on the type of innovation compatible with their organizational goals.

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In 2008 the introduction of the National Assessment Program – Literacy and Numeracy (NAPLAN), combined with the publication of the international comparative analyses of student achievement data (such as the Programme of International Student Assessment (PISA) developed by the Organisation for Economic Co-operation and Development (OECD) and the Trends in International Mathematics and Science Study (TIMSS) of the International Association for the Evaluation of Educational Achievement (IEA)) highlighted a significant priority for Australian education by identifying low levels of equity.

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