875 resultados para implementing flexible learning


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In this article we show that among elementary school students in Brazil there is a negative and significant relationship between within-class age dispersion and pupil’s proficiency. The relationship between the age-grade delay and school proficiency is usually explained by several factors that influence the educational process, since both student’s age-grade and his/her proficiency reflect difficulties implicit in the child's life. However, we show that the negative relation between within-class age dispersion and individual proficiency can be mitigated by the presence of teachers with high levels of certain attributes, such as teaching experience and years of schooling. This relationship supports the hypothesis that the greater the within-class age dispersion, the difficulties of implementing uniform learning projects are more significant, considering that there is a greater diversity of interests. Therefore, under those circumstances the role of the teacher in class seems to be essential to minimize any negative effect that age diversity may have on individual performance.

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The school library is a preferential placefor the contact of students with various informationresources and action of librarians and teachers, likemediators in order to enhance this experience. Thecollaborative relationship between this mediators isessential for planning and implementing activitiesfor learning. This article discusses some aspects ofcollaborative work between teachers and librarianand presents the results of applying a model ofcollaboration with the two librarians in Marília-SP, Brazil. Data collection was conducted withlibrarians from two schools, through interviews.The analysis was performed using the technique ofcontent analysis from four models of collaboration.It is noticed that the models are applicable tothe brazilian context and that there is a model ofcooperation prevailing in the participating schools.KEYWORDS: School library. Librarian. Teacher.Colaboration. Information literacy.

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Análisis de los sistemas de mitigación del riesgo de tráfico en autopistas de peaje en diferentes países de Latinoamérica. This paper presents a cross-country analysis of traffic risk allocation in road concessions of Latin America. It shows that some countries such as Chile, Colombia, and Peru have been greatly concerned with mitigating traffic risk, either by putting into practice public guarantees, implementing flexible term concessions, or through availability payment concessions; whereas other countries such as Mexico and Brazil have assigned traffic risk to the private concessionaire by using fixed-term concession contracts without any traffic guarantees. Based on an analysis of data from 1990 to 2010, the paper finds that shifting traffic risk from the concessionaire to the government or users was not confined to the riskiest projects, as one might expect. The analysis also suggests that the implementation of traffic risk mitigation mechanisms in Latin American toll roads has not been very successful in reducing renegotiation rates or in increasing the number of bidders in the tenders

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Contemporary Higher Education Institutions must adapt to address government funded calls for expansion and widened participation. The adoption of e-learning strategies, such as the use of the podcasts, can facilitate flexible learning around the needs and expectations of students. In this article we outline a number of e-learning developments at Aston University collectively referred to as the Virtual Pedagogy Initiative. Each of the strands, podcasts, vodcasts, mobile telephony and the campus wide remote broadcasts, are described pedagogically as well as technically. Where possible data highlighting the student response and experience are included. The article begins with the contention that contemporary undergraduates may be qualitatively different and can considered „digital natives?.

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Distributed Computing frameworks belong to a class of programming models that allow developers to

launch workloads on large clusters of machines. Due to the dramatic increase in the volume of

data gathered by ubiquitous computing devices, data analytic workloads have become a common

case among distributed computing applications, making Data Science an entire field of

Computer Science. We argue that Data Scientist's concern lays in three main components: a dataset,

a sequence of operations they wish to apply on this dataset, and some constraint they may have

related to their work (performances, QoS, budget, etc). However, it is actually extremely

difficult, without domain expertise, to perform data science. One need to select the right amount

and type of resources, pick up a framework, and configure it. Also, users are often running their

application in shared environments, ruled by schedulers expecting them to specify precisely their resource

needs. Inherent to the distributed and concurrent nature of the cited frameworks, monitoring and

profiling are hard, high dimensional problems that block users from making the right

configuration choices and determining the right amount of resources they need. Paradoxically, the

system is gathering a large amount of monitoring data at runtime, which remains unused.

In the ideal abstraction we envision for data scientists, the system is adaptive, able to exploit

monitoring data to learn about workloads, and process user requests into a tailored execution

context. In this work, we study different techniques that have been used to make steps toward

such system awareness, and explore a new way to do so by implementing machine learning

techniques to recommend a specific subset of system configurations for Apache Spark applications.

Furthermore, we present an in depth study of Apache Spark executors configuration, which highlight

the complexity in choosing the best one for a given workload.

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The continuous technology evaluation is benefiting our lives to a great extent. The evolution of Internet of things and deployment of wireless sensor networks is making it possible to have more connectivity between people and devices used extensively in our daily lives. Almost every discipline of daily life including health sector, transportation, agriculture etc. is benefiting from these technologies. There is a great potential of research and refinement of health sector as the current system is very often dependent on manual evaluations conducted by the clinicians. There is no automatic system for patient health monitoring and assessment which results to incomplete and less reliable heath information. Internet of things has a great potential to benefit health care applications by automated and remote assessment, monitoring and identification of diseases. Acute pain is the main cause of people visiting to hospitals. An automatic pain detection system based on internet of things with wireless devices can make the assessment and redemption significantly more efficient. The contribution of this research work is proposing pain assessment method based on physiological parameters. The physiological parameters chosen for this study are heart rate, electrocardiography, breathing rate and galvanic skin response. As a first step, the relation between these physiological parameters and acute pain experienced by the test persons is evaluated. The electrocardiography data collected from the test persons is analyzed to extract interbeat intervals. This evaluation clearly demonstrates specific patterns and trends in these parameters as a consequence of pain. This parametric behavior is then used to assess and identify the pain intensity by implementing machine learning algorithms. Support vector machines are used for classifying these parameters influenced by different pain intensities and classification results are achieved. The classification results with good accuracy rates between two and three levels of pain intensities shows clear indication of pain and the feasibility of this pain assessment method. An improved approach on the basis of this research work can be implemented by using both physiological parameters and electromyography data of facial muscles for classification.

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Wydział Studiów Edukacyjnych: Zakład Pedeutologii

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One of the most difficult issues of e-Learning is the students’ assessment. Being this an outstanding task regarding theoretical topics, it becomes even more challenging when the topics under evaluation are practical. ISCAP’s Information Systems Department is composed of about twenty teachers who have been for several years using an e-learning environment (at the moment Moodle 2.3) combined with traditional assessment. They are now planning and implementing a new e-learning assessment strategy. This effort was undertaken in order to evaluate a practical topic (the use of spreadsheets to solve management problems) common to shared courses of several undergraduate degree programs. The same team group is already experienced in the assessment of theoretical information systems topics using the b-learning platform. Therefore, this project works as an extension to previous experiences being the team aware of the additional difficulties due to the practical nature of the topics. This paper describes this project and presents two cycles of the action research methodology, used to conduct the research. The first cycle goal was to produce a database of questions. When it was implemented in order to be used with a pilot group of students, several problems were identified. Subsequently, the second cycle consisted in solving the identified problems preparing the database and all the players to a broader scope implementation. For each cycle, all the phases, its drawbacks and achievements are described. This paper suits all those who are or are planning to be in the process of shifting their assessment strategy from a traditional to one supported by an e-learning platform.

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This chapter aims to demonstrate how PAOL - Unit for Innovation in Education, a project from ISCAP - School of Accounting and Administration of Oporto ....

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This file contains the ontology of patterns of educational settings, as part of the formal framework for specifying, reusing and implementing educational settings. Furthermore, it includes the set of rules that extend the ontology of educational scenarios as well as a brief description of the level of patters of such ontological framework.

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CSCL applications are complex distributed systems that posespecial requirements towards achieving success in educationalsettings. Flexible and efficient design of collaborative activitiesby educators is a key precondition in order to provide CSCL tailorable systems, capable of adapting to the needs of eachparticular learning environment. Furthermore, some parts ofthose CSCL systems should be reused as often as possible inorder to reduce development costs. In addition, it may be necessary to employ special hardware devices, computational resources that reside in other organizations, or even exceed thepossibilities of one specific organization. Therefore, theproposal of this paper is twofold: collecting collaborativelearning designs (scripting) provided by educators, based onwell-known best practices (collaborative learning flow patterns) in a standard way (IMS-LD) in order to guide the tailoring of CSCL systems by selecting and integrating reusable CSCL software units; and, implementing those units in the form of grid services offered by third party providers. More specifically, this paper outlines a grid-based CSCL system having these features and illustrates its potential scope and applicability by means of a sample collaborative learning scenario.

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Violence has always been a part of the human experience, and therefore, a popular topic for research. It is a controversial issue, mostly because the possible sources of violent behaviour are so varied, encompassing both biological and environmental factors. However, very little disagreement is found regarding the severity of this societal problem. Most researchers agree that the number and intensity of aggressive acts among adults and children is growing. Not surprisingly, many educational policies, programs, and curricula have been developed to address this concern. The research favours programs which address the root causes of violence and seek to prevent rather than provide consequences for the undesirable behaviour. But what makes a violence prevention program effective? How should educators choose among the many curricula on the market? After reviewing the literature surrounding violence prevention programs and their effectiveness, The Second Step Violence Prevention Curriculum surfaced as unique in many ways. It was designed to address the root causes of violence in an active, student-centred way. Empathy training, anger management, interpersonal cognitive problem solving, and behavioural social skills form the basis of this program. Published in 1992, the program has been the topic of limited research, almost entirely carried out using quantitative methodologies.The purpose of this study was to understand what happens when the Second Step Violence Prevention Curriculum is implemented with a group of students and teachers. I was not seeking a statistical correlation between the frequency of violence and program delivery, as in most prior research. Rather, I wished to gain a deeper understanding of the impact ofthe program through the eyes of the participants. The Second Step Program was taught to a small, primary level, general learning disabilities class by a teacher and student teacher. Data were gathered using interviews with the teachers, personal observations, staff reports, and my own journal. Common themes across the four types of data collection emerged during the study, and these themes were isolated and explored for meaning. Findings indicate that the program does not offer a "quick fix" to this serious problem. However, several important discoveries were made. The teachers feU that the program was effective despite a lack of concrete evidence to support this claim. They used the Second Step strategies outside their actual instructional time and felt it made them better educators and disciplinarians. The students did not display a marked change in their behaviour during or after the program implementation, but they were better able to speak about their actions, the source of their aggression, and the alternatives which were available. Although they were not yet transferring their knowledge into positive action,a heightened awareness was evident. Finally, staff reports and my own journal led me to a deeper understanding ofhow perception frames reality. The perception that the program was working led everyone to feel more empowered when a violent incident occurred, and efforts were made to address the cause rather than merely to offer consequences. A general feeling that we were addressing the problem in a productive way was prevalent among the staff and students involved. The findings from this investigation have many implications for research and practice. Further study into the realm of violence prevention is greatly needed, using a balance of quantitative and qualitative methodologies. Such a serious problem can only be effectively addressed with a greater understanding of its complexities. This study also demonstrates the overall positive impact of the Second Step Violence Prevention Curriculum and, therefore, supports its continued use in our schools.

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Monográfico con el título: 'Aprendizaje basado en problemas'.Resumen basado en el de la publicación

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Given the complex structure of the brain, how can synaptic plasticity explain the learning and forgetting of associations when these are continuously changing? We address this question by studying different reinforcement learning rules in a multilayer network in order to reproduce monkey behavior in a visuomotor association task. Our model can only reproduce the learning performance of the monkey if the synaptic modifications depend on the pre- and postsynaptic activity, and if the intrinsic level of stochasticity is low. This favored learning rule is based on reward modulated Hebbian synaptic plasticity and shows the interesting feature that the learning performance does not substantially degrade when adding layers to the network, even for a complex problem.

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Systematic evaluation of Learning Objects is essential to make high quality Web-based education possible. For this reason, several educational repositories and e-Learning systems have developed their own evaluation models and tools. However, the differences of the context in which Learning Objects are produced and consumed suggest that no single evaluation model is sufficient for all scenarios. Besides, no much effort has been put in developing open tools to facilitate Learning Object evaluation and use the quality information for the benefit of end users. This paper presents LOEP, an open source web platform that aims to facilitate Learning Object evaluation in different scenarios and educational settings by supporting and integrating several evaluation models and quality metrics. The work exposed in this paper shows that LOEP is capable of providing Learning Object evaluation to e-Learning systems in an open, low cost, reliable and effective way. Possible scenarios where LOEP could be used to implement quality control policies and to enhance search engines are also described. Finally, we report the results of a survey conducted among reviewers that used LOEP, showing that they perceived LOEP as a powerful and easy to use tool for evaluating Learning Objects.