45 resultados para software systems for mobile learning


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Background: We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives: The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods: Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results: The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content-based design outperforms the traditional VLE-based design. © 2011 Wessa et al.

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The goal of this roadmap paper is to summarize the state-of-the-art and to identify critical challenges for the systematic software engineering of self-adaptive systems. The paper is partitioned into four parts, one for each of the identified essential views of self-adaptation: modelling dimensions, requirements, engineering, and assurances. For each view, we present the state-of-the-art and the challenges that our community must address. This roadmap paper is a result of the Dagstuhl Seminar 08031 on "Software Engineering for Self-Adaptive Systems," which took place in January 2008. © 2009 Springer Berlin Heidelberg.

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Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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For a very large number of adults, tasks such as reading. understanding, and using everyday items are a challenge. Although many community-based organizations offer resources and support for adults with limited literacy skills. current programs have difficulty reaching and retaining those that would benefit most. In this paper we present the findings of an exploratory study aimed at investigating how a technological solution that addresses these challenges is received and adopted by adult learners. For this, we have developed a mobile application to support literacy programs and to assist low-literacy adults in today's information-centric society. ALEX© (Adult Literacy support application for Experiential learning) is a mobile language assistant that is designed to be used both in the classroom and in daily life in order to help low-literacy adults become increasingly literate and independent. Through a long-term study with adult learners we show that such a solution complements literacy programs by increasing users' motivation and interest in learning, and raising their confidence levels both in their education pursuits and in facing the challenges of their daily lives.

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The primary questions addressed in this paper are the following: what are the factors that affect students’ adoption of an e-learning system and what are the relationships among these factors? This paper investigates and identifies some of the major factors affecting students’ adoption of an e-learning system in a university in Jordan. E-learning adoption is approached from the information systems acceptance point of view. This suggests that a prior condition for learning effectively using e-learning systems is that students must actually use them. Thus, a greater knowledge of the factors that affect IT adoption and their interrelationships is a pre-cursor to a better understanding of student acceptance of e-learning systems. In turn, this will help and guide those who develop, implement, and deliver e-learning systems. In this study, an extended version of the Technology Acceptance Model (TAM) was developed to investigate the underlying factors that influence students’ decisions to use an e-learning system. The TAM was populated using data gathered from a survey of 486 undergraduate students using the Moodle based e-learning system at the Arab Open University. The model was estimated using Structural Equation Modelling (SEM). A path model was developed to analyze the relationships between the factors to explain students’ adoption of the e-learning system. Whilst findings support existing literature about prior experience affecting perceptions, they also point to surprising group effects, which may merit future exploration.

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Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive applications. However, implementations for such heterogeneous systems are often hand-crafted and optimised to one computation scenario, and it can be challenging to maintain high performance when application parameters change. In this paper, we demonstrate that machine learning can help to dynamically choose parameters for task scheduling and load-balancing based on changing characteristics of the incoming workload. We use a financial option pricing application as a case study. We propose a simulation of processing financial tasks on a heterogeneous system with GPUs and FPGAs, and show how dynamic, on-line optimisations could improve such a system. We compare on-line and batch processing algorithms, and we also consider cases with no dynamic optimisations.

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Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.

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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.

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As machine tools continue to become increasingly repeatable and accurate, high-precision manufacturers may be tempted to consider how they might utilise machine tools as measurement systems. In this paper, we have explored this paradigm by attempting to repurpose state-of-the-art coordinate measuring machine Uncertainty Evaluating Software (UES) for a machine tool application. We performed live measurements on all the systems in question. Our findings have highlighted some gaps with UES when applied to machine tools, and we have attempted to identify the sources of variation which have led to discrepancies. Implications of this research include requirements to evolve the algorithms within the UES if it is to be adapted for on-machine measurement, improve the robustness of the input parameters, and most importantly, clarify expectations.

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Based on an unprecedented need of stimulating creative capacities towards entrepreneurship to university students and young researchers, this paper introduces and analyses a smart learning ecosystem for encouraging teaching and learning on creative thinking as a distinct feature to be taught and learnt in universities. The paper introduces a mashed-up authoring architecture for designing lesson-plans and games with visual learning mechanics for creativity learning. The design process is facilitated by creativity pathways discerned across components. Participatory learning, networking and capacity building is a key aspect of the architecture, extending the learning experience and context from the classroom to outdoor (co-authoring of creative pathways by students, teachers and real-world entrepreneurs) and personal spaces. We anticipate that the smart learning ecosystem will be empirically evaluated and validated in future iterations for exploring the benefits of using games for enhancing creative mindsets, unlocking the imagination that lies within, practiced and transferred to multiple academic tribes and territories.

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Social software is increasingly being used in higher and further education to support teaching and learning processes. These applications provide students with social and cognitive stimulation and also add to the interaction between students and educators. However, in addition to the benefits the introduction of social software into a course environment can also have adverse implications on students, educators and the education institution as a whole, a phenomenon which has received much less attention in the literature. In this study we explore the various implications of introducing social software into a course environment in order to identify the associated benefits, but also the potential drawbacks. We draw on data from 20 social software initiatives in UK based higher and further education institutions to identify the diverse experiences and concerns of students and educators. The findings are presented in form of a SWOT analysis, which allows us to better understand the otherwise ambiguous implications of social software in terms of its strengths, weaknesses, opportunities and threats. From the analysis we have derived concrete recommendations for the use of social software as a teaching and learning tool.

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This paper describes the use of Bluetooth and Java-Based technologies in developing a multi-player mobile game in ubiquitous computing, which strongly depends on automatic contextual reconfiguration and context-triggered actions. Our investigation focuses on an extended form of ubiquitous computing which game software developers utilize to develop games for players. We have developed an experimental ubiquitous computing application that provides context-aware services to game server and game players in a mobile distributed computing system. Obviously, contextual services provide useful information in a context-aware system. However, designing a context-aware game is still a daunting task and much theoretical and practical research remains to be done to reach the ubiquitous computing era. In this paper, we present the overall architecture and discuss, in detail, the implementation steps taken to create a Bluetooth and Java based context-aware game. We develop a multi-player game server and prepare the client and server codes in ubiquitous computing, providing adaptive routines to handle connection information requests, logging and context formatting and delivery for automatic contextual reconfiguration and context-triggered actions. © 2010 Binary Information Press.

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Right across Europe technology is playing a vital part in enhancing learning for an increasingly diverse population of learners. Learning is increasingly flexible, social and mobile and supported by high quality multi-media resources. Institutional VLEs are seeing a shift towards open source products and these core systems are supplemented by a range of social and collaborative learning tools based on web 2.0 technologies. Learners undertaking field studies and those in the workplace are coming to expect that these off-campus experiences will also be technology-rich whether supported by institutional or user-owned devices. As well as keeping European businesses competitive, learning is seen as a means of increasing social mobility and supporting an agenda of social justice. For a number of years the EUNIS E-Learning Task Force (ELTF) has conducted snapshot surveys of e-learning across member institutions, collected case studies of good practice in e-learning see (Hayes, et al., 2009) in references, supported a group looking at the future of e-learning, and showcased the best of innovation in its e-learning Award. Now for the first time the ELTF membership has come together to undertake an analysis of developments in the member states and to assess what this might mean for the future. The group applied the techniques of World Café conversation and Scenario Thinking to develop its thoughts. The analysis is unashamedly qualitative and draws on expertise from leading universities across eight of the EUNIS member states. What emerges is interesting in terms of the common trends in developments in all of the nations and similarities in hopes and concerns about the future development of learning.