767 resultados para Individualization of learning


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Welcome to this special edition of the Journal of Learning Design which focuses on legal education and curriculum renewal in law. At the outset ,we would like to thank the editors of the Journal, Margaret Lloyd and Nan Bahr for agreeing to host this special edition. The special edition is timely as legal education in Australia is enjoying a lively period of renewal.

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Learning automata arranged in a two-level hierarchy are considered. The automata operate in a stationary random environment and update their action probabilities according to the linear-reward- -penalty algorithm at each level. Unlike some hierarchical systems previously proposed, no information transfer exists from one level to another, and yet the hierarchy possesses good convergence properties. Using weak-convergence concepts it is shown that for large time and small values of parameters in the algorithm, the evolution of the optimal path probability can be represented by a diffusion whose parameters can be computed explicitly.

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Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

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This study addresses four issues concerning technological product innovations. First, the nature of the very early phases or "embryonic stages" of technological innovation is addressed. Second, this study analyzes why and by what means people initiate innovation processes outside the technological community and the field of expertise of the established industry. In other words, this study addresses the initiation of innovation that occurs without the expertise of established organizations, such as technology firms, professional societies and research institutes operating in the technological field under consideration. Third, the significance of interorganizational learning processes for technological innovation is dealt with. Fourth, this consideration is supplemented by considering how network collaboration and learning change when formalized product development work and the commercialization of innovation advance. These issues are addressed through the empirical analysis of the following three product innovations: Benecol margarine, the Nordic Mobile Telephone system (NMT) and the ProWellness Diabetes Management System (PDMS). This study utilizes the theoretical insights of cultural-historical activity theory on the development of human activities and learning. Activity-theoretical conceptualizations are used in the critical assessment and advancement of the concept of networks of learning. This concept was originally proposed by the research group of organizational scientist Walter Powell. A network of learning refers to the interorganizational collaboration that pools resources, ideas and know-how without market-based or hierarchical relations. The concept of an activity system is used in defining the nodes of the networks of learning. Network collaboration and learning are analyzed with regard to the shared object of development work. According to this study, enduring dilemmas and tensions in activity explain the participants' motives for carrying out actions that lead to novel product concepts in the early phases of technological innovation. These actions comprise the initiation of development work outside the relevant fields of expertise and collaboration and learning across fields of expertise in the absence of market-based or hierarchical relations. These networks of learning are fragile and impermanent. This study suggests that the significance of networks of learning across fields of expertise becomes more and more crucial for innovation activities.

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A learning automaton operating in a random environment updates its action probabilities on the basis of the reactions of the environment, so that asymptotically it chooses the optimal action. When the number of actions is large the automaton becomes slow because there are too many updatings to be made at each instant. A hierarchical system of such automata with assured c-optimality is suggested to overcome that problem.The learning algorithm for the hierarchical system turns out to be a simple modification of the absolutely expedient algorithm known in the literature. The parameters of the algorithm at each level in the hierarchy depend only on the parameters and the action probabilities of the previous level. It follows that to minimize the number of updatings per cycle each automaton in the hierarchy need have only two or three actions.

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A cooperative game played in a sequential manner by a pair of learning automata is investigated in this paper. The automata operate in an unknown random environment which gives a common pay-off to the automata. Necessary and sufficient conditions on the functions in the reinforcement scheme are given for absolute monotonicity which enables the expected pay-off to be monotonically increasing in any arbitrary environment. As each participating automaton operates with no information regarding the other partner, the results of the paper are relevant to decentralized control.

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Data-driven approaches such as Gaussian Process (GP) regression have been used extensively in recent robotics literature to achieve estimation by learning from experience. To ensure satisfactory performance, in most cases, multiple learning inputs are required. Intuitively, adding new inputs can often contribute to better estimation accuracy, however, it may come at the cost of a new sensor, larger training dataset and/or more complex learning, some- times for limited benefits. Therefore, it is crucial to have a systematic procedure to determine the actual impact each input has on the estimation performance. To address this issue, in this paper we propose to analyse the impact of each input on the estimate using a variance-based sensitivity analysis method. We propose an approach built on Analysis of Variance (ANOVA) decomposition, which can characterise how the prediction changes as one or more of the input changes, and also quantify the prediction uncertainty as attributed from each of the inputs in the framework of dependent inputs. We apply the proposed approach to a terrain-traversability estimation method we proposed in prior work, which is based on multi-task GP regression, and we validate this implementation experimentally using a rover on a Mars-analogue terrain.

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This paper reports on the outcomes from a preliminary evaluation of technologies and processes intended to support the Assurance of Learning initiative in the business faculty of an Australian university. The study investigated how existing institutional information systems and operational processes could be used to support direct measures of student learning and the attainment of intended learning goals. The levels at which learning outcomes had been attained were extracted from the University Learning Management System (LMS), based on rubric data for three assessments in two units. Spreadsheets were used to link rubric criteria to the learning goals associated with the assessments as identified in a previous curriculum mapping exercise, and to aggregate the outcomes. Recommendations arising from this preliminary study are made to inform a more comprehensive pilot based on this approach, and manage the quality of student learning experiences in the context of existing processes and reporting structures.

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Initial teacher education (ITE) students participate in various workplaces within schools and in doing so, form understandings about the numerous, and at times competing, expectations of teachers’ work. Through these experiences they form understandings about themselves as health and physical education (HPE) teachers. This paper examines the ways communities of practice within HPE subject department offices function as sites of workplace learning for student teachers. In particular this research focused on how ITE students negotiate tacit and contradictory expectations as well as social tasks during the practicum and the ways in which their understandings are mediated through participation in the workspace. Qualitative methods of survey and semi-structured interview were used to collect data on a cohort of student teachers during and following their major (10 week) practicum experience. Analysis was informed by theories of communities of practice (Wenger, 1998), workplace learning (Billett, 2001), and social task systems (Doyle, 1977). It was evident that considerable effort, attention, and energy was expended on various interrelated social tasks aimed at building positive relationships with their supervisor and other HPE teachers at the school. The social dynamics were highly nuanced and required a game-like approach. In our view the complexity that student teachers must negotiate in striving for an excellent evaluation warrants specific attention in physical education teacher education (PETE) programs. This study raises questions regarding our responsibilities in sending student teachers into contexts that might even be described as toxic. We offer some suggestions for how PETE might better support students going into practicum contexts that might be regarded as problematic workplaces.

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Since 2007, close collaboration between the Learning and Teaching Unit’s Academic Quality and Standards team and the Department of Reporting and Analysis’ Business Objects team resulted in a generational approach to reporting where QUT established a place of trust. This place of trust is where data owners are confident in date storage, data integrity, reported and shared. While the role of the Department of Reporting and Analysis focused on the data warehouse, data security and publication of reports, the Academic Quality and Standards team focused on the application of learning analytics to solve academic research questions and improve student learning. Addressing questions such as: • Are all students who leave course ABC academically challenged? • Do the students who leave course XYZ stay within the faculty, university or leave? • When students withdraw from a unit do they stay enrolled on full or part load or leave? • If students enter through a particular pathway, what is their experience in comparison to other pathways? • With five years historic reporting, can a two-year predictive forecast provide any insight? In answering these questions, the Academic Quality and Standards team then developed prototype data visualisation through curriculum conversations with academic staff. Where these enquiries were applicable more broadly this information would be brought into the standardised reporting for the benefit of the whole institution. At QUT an annual report to the executive committees allows all stakeholders to record the performance and outcomes of all courses in a snapshot in time or use this live report at any point during the year. This approach to learning analytics was awarded the Awarded 2014 ATEM/Campus Review Best Practice Awards in Tertiary Education Management for The Unipromo Award for Excellence in Information Technology Management.

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This research is connected with an education development project for the four-year-long officer education program at the National Defence University. In this curriculum physics was studied in two alternative course plans namely scientific and general. Observations connected to the later one e.g. student feedback and learning outcome gave indications that action was needed to support the course. The reform work was focused on the production of aligned course related instructional material. The learning material project produced a customized textbook set for the students of the general basic physics course. The research adapts phases that are typical in Design Based Research (DBR). The research analyses the feature requirements for physics textbook aimed at a specific sector and frames supporting instructional material development, and summarizes the experiences gained in the learning material project when the selected frames have been applied. The quality of instructional material is an essential part of qualified teaching. The goal of instructional material customization is to increase the product's customer centric nature and to enhance its function as a support media for the learning process. Textbooks are still one of the core elements in physics teaching. The idea of a textbook will remain but the form and appearance may change according to the prevailing technology. The work deals with substance connected frames (demands of a physics textbook according to the PER-viewpoint, quality thinking in educational material development), frames of university pedagogy and instructional material production processes. A wide knowledge and understanding of different frames are useful in development work, if they are to be utilized to aid inspiration without limiting new reasoning and new kinds of models. Applying customization even in the frame utilization supports creative and situation aware design and diminishes the gap between theory and practice. Generally, physics teachers produce their own supplementary instructional material. Even though customization thinking is not unknown the threshold to produce an entire textbook might be high. Even though the observations here are from the general physics course at the NDU, the research gives tools also for development in other discipline related educational contexts. This research is an example of an instructional material development work together the questions it uncovers, and presents thoughts when textbook customization is rewarding. At the same time, the research aims to further creative customization thinking in instruction and development. Key words: Physics textbook, PER (Physics Education Research), Instructional quality, Customization, Creativity

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The starting point of this thesis is the notion that in order for organisations to understand what customers value and how customers experience service, they need to learn about customers. The first and perhaps most important link in an organisation-wide learning process directed at customers is the frontline contact person. Service- and sales organisations can only learn about customers if the individual frontline contact persons learn about customers. Even though it is commonly recognised that learning about customers is the basis for an organisation’s success, few contributions within marketing investigate the fundamental nature of the phenomenon as it occurs in everyday customer service. Thus, what learning about customers is and how it takes place in a customer-service setting is an issue that is neglected in marketing research. In order to explore these questions, this thesis presents a socio-cultural approach to understanding learning about customers. Hence, instead of considering learning equal to cognitive processes in the mind of the frontline contact person or learning as equal to organisational information processing, the interactive, communication-based, socio-cultural aspect of learning about customers is brought to the fore. Consequently, the theoretical basis of the study can be found both in socio-cultural and practice-oriented lines of reasoning, as well as in the fields of service- and relationship marketing. As it is argued that learning about customers is an integrated part of everyday practices, it is also clear that it should be studied in a naturalistic and holistic way as it occurs in a customer-service setting. This calls for an ethnographic research approach, which involves direct, first-hand experience of the research setting during an extended period of time. Hence, the empirical study employs participant observations, informal discussions and interviews among car salespersons and service advisors at a car retailing company. Finally, as a synthesis of theoretically and empirically gained understanding, a set of concepts are developed and they are integrated into a socio-cultural model of learning about customers.

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In a time when Technology Supported Learning Systems are being widely used, there is a lack of tools that allows their development in an automatic or semi-automatic way. Technology Supported Learning Systems require an appropriate Domain Module, ie. the pedagogical representation of the domain to be mastered, in order to be effective. However, content authoring is a time and effort consuming task, therefore, efforts in automatising the Domain Module acquisition are necessary.Traditionally, textbooks have been used as the main mechanism to maintain and transmit the knowledge of a certain subject or domain. Textbooks have been authored by domain experts who have organised the contents in a means that facilitate understanding and learning, considering pedagogical issues.Given that textbooks are appropriate sources of information, they can be used to facilitate the development of the Domain Module allowing the identification of the topics to be mastered and the pedagogical relationships among them, as well as the extraction of Learning Objects, ie. meaningful fragments of the textbook with educational purpose.Consequently, in this work DOM-Sortze, a framework for the semi-automatic construction of Domain Modules from electronic textbooks, has been developed. DOM-Sortze uses NLP techniques, heuristic reasoning and ontologies to fulfill its work. DOM-Sortze has been designed and developed with the aim of automatising the development of the Domain Module, regardless of the subject, promoting the knowledge reuse and facilitating the collaboration of the users during the process.