899 resultados para IT intention to learn


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The book aims to introduce the reader to DEA in the most accessible manner possible. It is specifically aimed at those who have had no prior exposure to DEA and wish to learn its essentials, how it works, its key uses, and the mechanics of using it. The latter will include using DEA software. Students on degree or training courses will find the book especially helpful. The same is true of practitioners engaging in comparative efficiency assessments and performance management within their organisation. Examples are used throughout the book to help the reader consolidate the concepts covered. Table of content: List of Tables. List of Figures. Preface. Abbreviations. 1. Introduction to Performance Measurement. 2. Definitions of Efficiency and Related Measures. 3. Data Envelopment Analysis Under Constant Returns to Scale: Basic Principles. 4. Data Envelopment Analysis under Constant Returns to Scale: General Models. 5. Using Data Envelopment Analysis in Practice. 6. Data Envelopment Analysis under Variable Returns to Scale. 7. Assessing Policy Effectiveness and Productivity Change Using DEA. 8. Incorporating Value Judgements in DEA Assessments. 9. Extensions to Basic DEA Models. 10. A Limited User Guide for Warwick DEA Software. Author Index. Topic Index. References.

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The concept of plagiarism is not uncommonly associated with the concept of intellectual property, both for historical and legal reasons: the approach to the ownership of ‘moral’, nonmaterial goods has evolved to the right to individual property, and consequently a need was raised to establish a legal framework to cope with the infringement of those rights. The solution to plagiarism therefore falls most often under two categories: ethical and legal. On the ethical side, education and intercultural studies have addressed plagiarism critically, not only as a means to improve academic ethics policies (PlagiarismAdvice.org, 2008), but mainly to demonstrate that if anything the concept of plagiarism is far from being universal (Howard & Robillard, 2008). Even if differently, Howard (1995) and Scollon (1994, 1995) argued, and Angèlil-Carter (2000) and Pecorari (2008) later emphasised that the concept of plagiarism cannot be studied on the grounds that one definition is clearly understandable by everyone. Scollon (1994, 1995), for example, claimed that authorship attribution is particularly a problem in non-native writing in English, and so did Pecorari (2008) in her comprehensive analysis of academic plagiarism. If among higher education students plagiarism is often a problem of literacy, with prior, conflicting social discourses that may interfere with academic discourse, as Angèlil-Carter (2000) demonstrates, we then have to aver that a distinction should be made between intentional and inadvertent plagiarism: plagiarism should be prosecuted when intentional, but if it is part of the learning process and results from the plagiarist’s unfamiliarity with the text or topic it should be considered ‘positive plagiarism’ (Howard, 1995: 796) and hence not an offense. Determining the intention behind the instances of plagiarism therefore determines the nature of the disciplinary action adopted. Unfortunately, in order to demonstrate the intention to deceive and charge students with accusations of plagiarism, teachers necessarily have to position themselves as ‘plagiarism police’, although it has been argued otherwise (Robillard, 2008). Practice demonstrates that in their daily activities teachers will find themselves being required a command of investigative skills and tools that they most often lack. We thus claim that the ‘intention to deceive’ cannot inevitably be dissociated from plagiarism as a legal issue, even if Garner (2009) asserts that generally plagiarism is immoral but not illegal, and Goldstein (2003) makes the same severance. However, these claims, and the claim that only cases of copyright infringement tend to go to court, have recently been challenged, mainly by forensic linguists, who have been actively involved in cases of plagiarism. Turell (2008), for instance, demonstrated that plagiarism is often connoted with an illegal appropriation of ideas. Previously, she (Turell, 2004) had demonstrated by comparison of four translations of Shakespeare’s Julius Caesar to Spanish that the use of linguistic evidence is able to demonstrate instances of plagiarism. This challenge is also reinforced by practice in international organisations, such as the IEEE, to whom plagiarism potentially has ‘severe ethical and legal consequences’ (IEEE, 2006: 57). What plagiarism definitions used by publishers and organisations have in common – and which the academia usually lacks – is their focus on the legal nature. We speculate that this is due to the relation they intentionally establish with copyright laws, whereas in education the focus tends to shift from the legal to the ethical aspects. However, the number of plagiarism cases taken to court is very small, and jurisprudence is still being developed on the topic. In countries within the Civil Law tradition, Turell (2008) claims, (forensic) linguists are seldom called upon as expert witnesses in cases of plagiarism, either because plagiarists are rarely taken to court or because there is little tradition of accepting linguistic evidence. In spite of the investigative and evidential potential of forensic linguistics to demonstrate the plagiarist’s intention or otherwise, this potential is restricted by the ability to identify a text as being suspect of plagiarism. In an era with such a massive textual production, ‘policing’ plagiarism thus becomes an extraordinarily difficult task without the assistance of plagiarism detection systems. Although plagiarism detection has attracted the attention of computer engineers and software developers for years, a lot of research is still needed. Given the investigative nature of academic plagiarism, plagiarism detection has of necessity to consider not only concepts of education and computational linguistics, but also forensic linguistics. Especially, if intended to counter claims of being a ‘simplistic response’ (Robillard & Howard, 2008). In this paper, we use a corpus of essays written by university students who were accused of plagiarism, to demonstrate that a forensic linguistic analysis of improper paraphrasing in suspect texts has the potential to identify and provide evidence of intention. A linguistic analysis of the corpus texts shows that the plagiarist acts on the paradigmatic axis to replace relevant lexical items with a related word from the same semantic field, i.e. a synonym, a subordinate, a superordinate, etc. In other words, relevant lexical items were replaced with related, but not identical, ones. Additionally, the analysis demonstrates that the word order is often changed intentionally to disguise the borrowing. On the other hand, the linguistic analysis of linking and explanatory verbs (i.e. referencing verbs) and prepositions shows that these have the potential to discriminate instances of ‘patchwriting’ and instances of plagiarism. This research demonstrates that the referencing verbs are borrowed from the original in an attempt to construct the new text cohesively when the plagiarism is inadvertent, and that the plagiarist has made an effort to prevent the reader from identifying the text as plagiarism, when it is intentional. In some of these cases, the referencing elements prove being able to identify direct quotations and thus ‘betray’ and denounce plagiarism. Finally, we demonstrate that a forensic linguistic analysis of these verbs is critical to allow detection software to identify them as proper paraphrasing and not – mistakenly and simplistically – as plagiarism.

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The second book in The Converging World series, Media, Ecology and Conservation focuses on global connectivity and the role of new digital and traditional media in bringing people together to protect the world's endangered wildlife and conserve fragile and threatened habitats. New media offers opportunities for like-minded individuals, community groups, businesses and public organisations to learn and work cooperatively for the good of all species. One of the key themes of this book explores the important issue of how new information and communication technologies mediate the natural world, and our understanding of our place in it. By exploring the role of film, television, video, photography and the internet in animal conservation in the USA, India, Africa, Australia and the United Kingdom John Blewitt investigates the politics of media representation surrounding important controversies such as the trade in bushmeat, whaling and habitat destruction. The work and achievements of media/conservation activists are located within a cultural framework that simultaneously loves nature, reveres animals but too often ignores the uncomfortable realities of species extinction and animal cruelty.

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The Multiple Pheromone Ant Clustering Algorithm (MPACA) models the collective behaviour of ants to find clusters in data and to assign objects to the most appropriate class. It is an ant colony optimisation approach that uses pheromones to mark paths linking objects that are similar and potentially members of the same cluster or class. Its novelty is in the way it uses separate pheromones for each descriptive attribute of the object rather than a single pheromone representing the whole object. Ants that encounter other ants frequently enough can combine the attribute values they are detecting, which enables the MPACA to learn influential variable interactions. This paper applies the model to real-world data from two domains. One is logistics, focusing on resource allocation rather than the more traditional vehicle-routing problem. The other is mental-health risk assessment. The task for the MPACA in each domain was to predict class membership where the classes for the logistics domain were the levels of demand on haulage company resources and the mental-health classes were levels of suicide risk. Results on these noisy real-world data were promising, demonstrating the ability of the MPACA to find patterns in the data with accuracy comparable to more traditional linear regression models. © 2013 Polish Information Processing Society.

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This paper examines learning to collaborate in the context of industrial supply relationships. Evidence of collaboration, and individual and organizational learning, from an in-depth case study of a large organization and its relations with two key suppliers is discussed. Analytic methods developed to elicit such evidence and provide insights into learning processes and outcomes are presented. It is argued that it is possible for an organization and individuals to learn to develop resilient collaborative relationships, but this requires a more thorough consideration and understanding of issues such as trust, commitment and teamwork than has been typical to date. Suggestions for future practice and research are presented.

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Mistaken eyewitness identifications of innocent lead to more false convictions in the United States than any other cause. In response to concerns about the reliability of eyewitness evidence, the National Institute of Justice (NIJ) in 1999 published a Guide for the gathering and preservation of eyewitness evidence by law enforcement personnel. Previous research has shown that eyewitness identifications are more accurate when obtained using procedures recommended in the NIJ Guide. This experiment assessed whether informing jurors about the Guide can improve their ability to discriminate between eyewitness identifications likely to be accurate and those likely to be inaccurate and, if so, how to most effectively provide jurors with such information. ^ Seven hundred sixteen U.S. citizens who reported for criminal jury duty participated. Half of the participant jurors read a summary of an armed robbery trial in which the police followed the NIJ Guide when obtaining an eyewitness identification of the defendant. The other half read about an identical case in which the police did not follow the Guide. Jurors received information about the Guide from a court-appointed expert witness, one of the attorneys in the case, the trial judge, the judge in combination with one of the attorneys, or from no one (in the control groups). Jurors then rendered a verdict in the case and answered questions about the evidence in the case. ^ When an expert witness or the judge (either alone or in combination with one of the attorneys) informed jurors about the Guide, the jurors voted to convict defendants likely to be guilty and to acquit defendants likely to be innocent more often than did uninformed jurors assigned to a control group. These data suggest that informing jurors about the NIJ Guide using expert testimony or instructions from a judge will improve the quality and accuracy of jurors' verdict decisions in cases involving eyewitness identification evidence. However, more research is needed to determine whether the judge will remain an effective source of information about the Guide in a longer, more detailed trial scenario and to learn more about the underlying psychological processes governing the effects observed in this experiment. ^

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This work chronicles how queer individuals politicized their same-sex desires from the post-World War II era to the mid-1990s. Using Miami as a site of exploration, this work demonstrates the shift from understanding homosexuality as a same-sex "desire" to a distinct form of "civil rights." It argues that by no means was it inevitable that queer issues entered the American political mainstream. This project pays particular attention to Miami's Cuban exile community, as it managed to garner great socio-political power in the city. Like others in the city's power structure, Miami's Cuban exiles were also fundamentally traditionalists. Together, these phenomena crystallized into a matrix of obstacles that stunted the growth of the gay rights movement. This work demonstrates the historical dynamics of sexuality and politics by contextualizing immigration, ethnicity, race, consumerism, and Cold War domestic and foreign policy.

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The impact of information technology (IT) is far-reaching and driving dramatic shifts in business paradigms. Trends suggest greater adoption of IT will continue and develop at accelerating rates. Hence, hotel operators and executives must learn how to embrace IT and capitalize on the many capabilities it has to offer while minimizing the threats. The authors attempt to provide a sense of focus and a roadmap to help hoteliers understand the issues, see the future, and find an appropriate on ramp to the information superhighway.

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Social responsibility (SR) is becoming an increasingly significant component of many firms’ strategic planning decisions. Research has shown that consumers tend to reward socially responsible behavior. However, there has been little testing of the construct in the hospitality industry. Additionally, when other important variables that influence consumer brand loyalty are considered, will brand social responsibility image (BSRI) still play a significant role? This study investigates the importance of SR and its impact on brand loyalty, relative to product quality and service quality in the quick-service restaurant industry. The authors were also interested to learn whether BSRI impacted consumers' image of product and service quality. It was found that BSRI had a positive impact on brand loyalty, product quality, and service quality. However, product quality was a significantly stronger predictor of brand loyalty than BSRI. Where the vast majority of studies of SR have utilized scenario analysis of hypothetical firms, this study utilizes consumers' perceptions of a real-world firm.

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The purpose of this qualitative case study was to gain an understanding of the phenomenon of academic orientation by seeking the insights into an inner-city Haitian-American middle school student's attitudes and world view toward education and life. A phenomenological approach was used in order to explore the way in which Cindy, a minority student, gives meaning to her lived-experiences in terms of her desire to meet academic expectations and her ability to overcome social adversity and/or other risk factors.^ The study attempted to answer the following two research questions: (1) What provides the focus for Cindy's (the subject's) approach to her school work and/or life? (2) What are the processes that give meaning and direction to academic orientation and life for Cindy? In-depth interviewing was the primary method of data collection. In addition, journal and sketchbook entries and school district records were used and classroom observations made.^ The nature of the study to understand lived-experience facilitated the use of the case study method and a phenomenological method of description. Data analysis was conducted by means of an adapted form of the constant comparative approach. Patterns in the data which emerged were coded and categorized according to underlying generative themes. Phenomenological reflection and analysis were used to grasp the experiential structures of Cindy's experience. The following textural themes were identified and confirmed to be essential themes to Cindy's experience: personal challenge to do her best, personal challenge to want to learn, having a sense of determination, being able to think for self, having a disposition to like self, achieving self-respect through performance, seeing a need to help others, being intrinsically motivated, being an independent learner, attending more to academic pressure and less to peer pressure, having motivational catalysts in her life, learning and support opportunities, and having a self-culture. Using Mahrer's humanistic theory of experiencing, Cindy's development was interpreted in terms of her progression through a sequence of developmental plateaus: externalized self, internalized self, and integrating and actualizing self.^ The findings of this study were that Cindy's desire to meet academic expectations is guided by a meaning construction internal frame of reference. High expectations of self in conjunction with other protective factors found in Cindy's home and school environments were also found to be linked to her educational resilience and success. Cindy's lived-experiences were also found to be related to Mahrer's theory of human development. In addition, it was concluded that "minority" students do not all fit into social categories and labels. ^

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It has long been known that vocabulary is essential in the development of reading. Because vocabulary leading to increased comprehension is important, it necessary to determine strategies for ensuring that the best methods of teaching vocabulary are used to help students make gains in vocabulary leading to reading comprehension. According to the National Reading Panel, multiple strategies that involve active engagement on the part of the student are more effective than the use of just one strategy. The purpose of this study was to determine if students' use of visualization, student-generated pictures of onset-and-rime-patterned vocabulary, and story read-alouds with discussion, would enable diverse first-grade students to increase their vocabulary and comprehension. In addition, this study examined the effect of the multimodal framework of strategies on English learners (ELs). This quasi-experimental study (N=69) was conducted in four first-grade classrooms in a low socio-economic school. Two treatment classes used a multimodal framework of strategies to learn weekly vocabulary words and comprehension. Two comparison classrooms used the traditional method of teaching weekly vocabulary and comprehension. Data sources included Florida Assessments for Instruction in Reading (FAIR), comprehension and vocabulary scores, and weekly MacMillan/McGraw Hill Treasures basal comprehension questions and onset-and-rime vocabulary questions. This research determined that the treatment had an effect in adjusted FAIR comprehension means by group, with the treatment group (adj M = 5.14) significantly higher than the comparison group ( adj M = -8.26) on post scores. However, the treatment means did not increase from pre to post, but the comparison means significantly decreased from pre to post as the materials became more challenging. For the FAIR vocabulary, there was a significant difference by group with the comparison adjusted post mean higher than the treatment's, although both groups significantly increased from pre to post. However, the FAIR vocabulary posttest was not part of the Treasures vocabulary, which was taught using the multimodal framework of strategies. The Treasures vocabulary scores were not significantly different by group on the assessment across the weeks, although the treatment means were higher than those of the comparison group. Continued research is needed in the area of vocabulary and comprehension instructional methods in order to determine strategies to increase diverse, urban students' performance.

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The necessity of the view of the Youth and Adults Education (EJA) subjects beyond of their academic failures becomes imperative for a reconfiguration of this teaching modality. Thus, the compromise of this study is to go into these subjects‘ universe, give them a voice and, therefore, understand, in general, the web of relationships between these subjects and the school. It is understood that it is not possible to figure out the means attributed by the subjects without consideration, as an essential element, the social context in which such means has been built. For the development of this study, the methodology adopted was the ethnographic research. The procedures used for the data construction were the participative observation, the semi-structured interviews with a focal group, and the individualized semi-structured interviews. For the understanding of the data constructed in the field, the content analysis technique was used, which reach the expectations of an interpretative analysis. The observation occurred mainly in the classrooms, on a public school, located in a City of Natal/RN. The interviews were taken with a sample of eight students, males and females, with 25 to 60 year-olds. Such interviews highlight that for the young adult students, the school is much more than a place to learn. They realize such space as enabler of social interaction, as well as the possibility of rising through new professional horizons and, therefore achieve a social mobility. For the older students, mainly among women, the return to the school benches brings into the learning discourse, the desire of making new friends, having moments of meeting, chatting and relaxation, finally, to forget the problems of the day by day. The school quotidian observation allows a better understanding of the action of the subjects in relationship with the school practices. Finally, it can be affirmed that seeking for the school has not only the intention to recover the time lost in the childhood. Learning remains as a secondary goal. It does not matter whether they will be retained or promoted to the next level at the end of the academic year, what really matters is to be in school.

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A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

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A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

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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.