718 resultados para Task-based learning
Resumo:
This paper provides a critical overview into a distinctive typology of Learning and Teaching Research developed at a relatively small, research-led UK University. Based upon research into staff perceptions of the relationship between learning and teaching research and practice, the model represents an holistic approach to evidence-based learning and teaching practice in Contemporary Higher Education.
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Teaching Speaking A Holistic Approach brings together theoretical and pedagogical perspectives on teaching speaking within a coherent methodological framework. The framework combines understandings derived from several areas of speaking research and instruction including cognitive and affective processes, oracy for thinking and learning communicative competence, discourse theories, task-based language learning, and self-regulated learning. By explaining, interpreting, evaluating, and synthesizing these diverse perspectives from linguistics and language learning, the text offers a comprehensive and versatile approach for teaching speaking. Samples of authentic classroom data are used for illustrating important concepts to help readers see how theoretical perspectives can be applied in practice. It also includes a pedagogical model for sequencing learning activities with concrete guidelines on planning and conducting speaking lessons. Different types of learning tasks are explained and illustrated with examples, and each chapter includes short tasks and ends with a number of tasks that enable readers to extend their ideas.
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The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.
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This paper presents the design and results of a task-based user study, based on Information Foraging Theory, on a novel user interaction framework - uInteract - for content-based image retrieval (CBIR). The framework includes a four-factor user interaction model and an interactive interface. The user study involves three focused evaluations, 12 simulated real life search tasks with different complexity levels, 12 comparative systems and 50 subjects. Information Foraging Theory is applied to the user study design and the quantitative data analysis. The systematic findings have not only shown how effective and easy to use the uInteract framework is, but also illustrate the value of Information Foraging Theory for interpreting user interaction with CBIR. © 2011 Springer-Verlag Berlin Heidelberg.
Resumo:
The paper proposes an ISE (Information goal, Search strategy, Evaluation threshold) user classification model based on Information Foraging Theory for understanding user interaction with content-based image retrieval (CBIR). The proposed model is verified by a multiple linear regression analysis based on 50 users' interaction features collected from a task-based user study of interactive CBIR systems. To our best knowledge, this is the first principled user classification model in CBIR verified by a formal and systematic qualitative analysis of extensive user interaction data. Copyright 2010 ACM.
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Aston University has been working closely with key companies from within the electricity industry for several years, initially in the development and delivery of an employer-led foundation degree programme in electrical power engineering, and more recently, in the development of a progression pathway for foundation degree graduates to achieve a Bachelors-level qualification. The Electrical Power Engineering foundation degree was developed in close consultation with the industry such that the programme is essentially owned by the sector. Programme delivery has required significant shifts away from traditional HE teaching patterns whilst maintaining the quality requirement and without compromise of the academic degree standard. Block teaching (2-week slots), partnership delivery, off-site student support and work-based learning have all presented challenges as we have sought to maximise the student learning experience and to ensure that the graduates are fit-for purpose and "hit the ground running" within a defined career structure for sponsoring companies. This paper will outline the skills challenges facing the sector; describe programme developments and delivery challenges; before articulating some observations and conclusions around programme effectiveness, impact of foundation degree graduates in the workplace and the significance of the close working relationship with key sponsoring companies. Copyright © 2012, September.
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The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC which is a novel method to model peptide-MHC binding affinities based on support rector machine regression (SVR) is described in this chapter. SVRMHC is among a small handful of quantitative modeling methods that make predictions about precise binding affinities between a peptide and an MHC molecule. As a kernel-based learning method, SVRMHC has rendered models with demonstrated appealing performance in the practice of modeling peptide-MHC binding.
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This article describes the approach adopted and the results obtained by the international team developing WBLST (Web Based Learning in Sciences and Technologies) a Web-based application for e-learning, developed for the students of “UVPL: Université Virtuelle des Pays de la Loire”. The developed e-learning system covers three levels of learning activities - content, exercises, and laboratory. The delivery model is designed to operate with domain concepts as relevant providers of semantic links. The aim is to facilitate the overview and to help the establishment of a mental map of the learning material. The implemented system is strongly based on the organization of the instruction in virtual classes. The obtained quality of the system is evaluated on the bases of feedback form students and professors.
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In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning implementation, which are used in some contemporary web-interfaced Learning Management Systems (LMSs). The problem is not how to create electronic learning materials, but how to locate and utilize the available information in personalized way. Different attitudes to personalization are briefly described in section 1. The real personalization requires a user profile containing information about preferences, aims, and educational history to be stored and used by the system. These issues are considered in section 2. A method for development and design of adaptive learning content in terms of learning strategy system support is represented in section 3. Section 4 includes a set of innovative personalization services that are suggested by several very important research projects (SeLeNe project, ELENA project, etc.) dated from the last few years. This section also describes a model for role- and competency-based learning customization that uses Web Services approach. The last part presents how personalization techniques are implemented in Learning Grid-driven applications.
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It is presented a research on the application of a collaborative learning and authoring during all delivery phases of e-learning programmes or e-courses offered by educational institutions. The possibilities for modelling of an e-project as a specific management process based on planned, dynamically changing or accidentally arising sequences of learning activities, is discussed. New approaches for project-based and collaborative learning and authoring are presented. Special types of test questions are introduced which allow test generation and authoring based on learners’ answers accumulated in the frame of given e-course. Experiments are carried out in an e-learning environment, named BEST.
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This paper addresses the task of learning classifiers from streams of labelled data. In this case we can face the problem that the underlying concepts can change over time. The paper studies two mechanisms developed for dealing with changing concepts. Both are based on the time window idea. The first one forgets gradually, by assigning to the examples weight that gradually decreases over time. The second one uses a statistical test to detect changes in concept and then optimizes the size of the time window, aiming to maximise the classification accuracy on the new examples. Both methods are general in nature and can be used with any learning algorithm. The objectives of the conducted experiments were to compare the mechanisms and explore whether they can be combined to achieve a synergetic e ect. Results from experiments with three basic learning algorithms (kNN, ID3 and NBC) using four datasets are reported and discussed.
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The paper describes a classification-based learning-oriented interactive method for solving linear multicriteria optimization problems. The method allows the decision makers describe their preferences with greater flexibility, accuracy and reliability. The method is realized in an experimental software system supporting the solution of multicriteria optimization problems.
Resumo:
A concept of educational game for learning programming languages is presented. The idea of learning programming languages and improving programming skills through programming game characters’ behavior is described. The learning course description rules for using in games are suggested. The concept is implemented in a game for learning C# programming language. A common game architecture is modified for using in the educational game. The game engine is built on the base of the graphical engine Ogre3D and extended with game logic. The game has been developed as an industry level commercial product and is planned for sale to educational institutions.
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In this paper we present a blended learning scenario for training of students in master program “ICT in primary school” carried out in South-West University “Neofit Rilski”. Our approach is based on “face to face” lectures and seminars, SCORM compatible e-learning content with a lot of simulation demonstrations, trainings and self assessment, group problem based learning. Also we discuss the results of the course and attitude of the participants in the course towards used methods and possibilities of application of e-learning in primary schools.
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Increased global uptake of entertainment gaming has the potential to lead to high expectations of engagement and interactivity from users of technology-enhanced learning environments. Blended approaches to implementing game-based learning as part of distance or technology-enhanced education have led to demonstrations of the benefits they might bring, allowing learners to interact with immersive technologies as part of a broader, structured learning experience. In this article, we explore how the integration of a serious game can be extended to a learning content management system (LCMS) to support a blended and holistic approach, described as an 'intuitive-guided' method. Through a case study within the EU-Funded Adaptive Learning via Intuitive/Interactive, Collaborative and Emotional Systems (ALICE) project, a technical integration of a gaming engine with a proprietary LCMS is demonstrated, building upon earlier work and demonstrating how this approach might be realized. In particular, how this method can support an intuitive-guided approach to learning is considered, whereby the learner is given the potential to explore a non-linear environment whilst scaffolding and blending provide guidance ensuring targeted learning objectives are met. Through an evaluation of the developed prototype with 32 students aged 14-16 across two Italian schools, a varied response from learners is observed, coupled with a positive reception from tutors. The study demonstrates that challenges remain in providing high-fidelity content in a classroom environment, particularly as an increasing gap in technology availability between leisure and school times emerges.