Monday, January 20, 2020
Girls: Growing up in the Global Education System Introduction When one thinks of the term Ã¢â¬Å"school educationÃ¢â¬ , one sees it as the golden key to a brighter future, improving employment prospects and earnings but fundamentally we think of a system that serves to stimulate individual talents to the full, regardless of race, gender or social status. The naivete of this thought is huge however, as the majority of people are unaware of the victimization of girls that exists in the schooling system. Reports around the world show examinations of how girls face multiple social and economic barriers to both enrolling in and staying in school. However, in most settings, disparities between initial enrollment rates for girls and boys are much greater than differences in drop out rates, suggesting that the major challenge remains to get girls in school. In this report, I will focus my attention into three areas: the barriers that girls face in enrolling in the schooling system; the inequalities that they receive in school (ultimat ely an inferior education to boys due to gender bias and other issues); as well as the paths taken by administrators towards improving the state of a girlÃ¢â¬â¢s education. Due to the wide range of sources that I used, I will attempt to parallel the elements of a girl's education from various corners of the globe with that of girls living on the border. Barriers Girls face in enrolling in school Factors that affect the percentage of girls who enroll in school are various; poverty, tradition and culture are the primary barriers which girls experience in school enrolment. A familyÃ¢â¬â¢s income is a great determinant of the probability that girls will attend school. If a familyÃ¢â¬â¢s income is low, the son is often chosen to attend school rather than the daughter, as he is more likely to contribute financially to the family income and support their parents, as they grow old. Girls in such an environment are needed to help with household chores and childcare for younger siblings. Since schooling involves substantial costs for fees, books, uniforms and transportation, when available school places or family resources are limited, parents often give higher priority to educating sons. This situation oftentimes accurately depicts the situation facing girls living on the border, as their families can be classed in such a poor social status.
Sunday, January 12, 2020
To participate effectively in todayÃ¢â¬â¢s world, we must recognize that communication is profoundly related to culture. To achieve effectiveness in social and professional life, we need to be sensitive to culture difference and adapt our interaction to people of varied culture background. The following scenario highlights the importance of adapting interaction to people with different culture. Five years ago, when I just came to Singapore, I came across an incident which made me realize that different cultures may influence people behaves differently under the same circumstance. After we finished a school group project, all the team members Wu Gang (Chinese), Samuel (Singaporean) and I (Chinese) decided to have a dinner together at a Chinese restaurant for celebration. When the dinner came to the end, Wu Gang took out his wallet and would like to pay the bill. At that moment, Samuel asked Wu Gang how much he should pay for his share. Ã¢â¬Å"No need, no need! ItÃ¢â¬â¢s my treat.Ã¢â¬ replied by Wu Gang. Seeing this, I tried to took the bill from Wu Gang and insist that I pay the bill this time. Wu Gang stopped me, saying to me Ã¢â¬Å"Leave it to next timeÃ¢â¬ . Meanwhile, he stood up and approached to casher for payment. Samuel still insisted on paying his own share and left the money to him after Wu Gang came back. At the end, Wu Gang accepted SamuelÃ¢â¬â¢s money unhappily. Samuel was confused and uncomfortable with Wu GangÃ¢â¬â¢s reaction. At that time, I didnÃ¢â¬â¢t understand SamuelÃ¢â¬â¢s insistence either because it is so common in China for one to pay for everybody in dinner. People pay the bill for you to treat you as a close friend as if you were a family member. Rejection means that you reject to be a close friend. ThatÃ¢â¬â¢s why Wu Gang was unhappy to Samuel in the above scenario. The appropriate respond in China culture is to treat your friend back next time. Now, after living in Singapore for several years, I understand that Singaporeans are more comfortable to split the bill even they are close friends. In Singapore culture, it reflects respect and fairness to your friend that each one pays his/her own share. In this incident all of us chose our own Ã¢â¬Å"correct wayÃ¢â¬ to deal with the situation but ignore othersÃ¢â¬â¢ different cultural background. Many people evaluate others based on the standards of their own culture. Some people think their standards reflect universal truths. They arenÃ¢â¬â¢t aware that they are imposing the yardstick of their particular culture and ignoring the yardsticks of other cultures. Devaluing whatever differs from our own ways limits human interaction and leads misunderstanding. . In China, one preson usually pays for __6__ . In Western countries, one preson pays if he or she is entertaining clients , but __7__ friends eat together , they usually share the cost. This is called Ã¢â¬Ëgoing DutchÃ¢â¬â¢.
Friday, January 3, 2020
I. Introduction: The purpose of this paper is to evaluate evidence-based medicine for treatment protocols, treatment guidelines, and outcomes for Obesity and provide the perspective of conventional medicine, complementary and alternative health, and integrative medicine (IM) to determine new standards for medical treatment. A. Obesity - is an excessive accumulation of fat cell within the body that impairs a personÃ¢â¬â¢s health and is called malnutrition or undernutrition. Malnutrition includes wasting, stunting, underweight, inadequate vitamins or minerals, overweight, obesity, and diet-related noncommunicable diseases (Ã¢â¬Å"WHO | Obesity,Ã¢â¬ 2014). Provide statistical data. There are 50 states that currently have an obesity rating 20% or higher.Ã¢â¬ ¦show more contentÃ¢â¬ ¦Based on past research efforts and their success rate I will determine, which medical model will most combat the obesity epidemic. C. Conclusion - The data provides proof that obesity has only increased over the past couple of decades. It shows that there hasnÃ¢â¬â¢t been any fluctuations in both adult and childhood obesity. The best practices for the disease/condition would be to understand how different foods affect different body types. It is my belief that the human body is unique to each individual. Foods and their effects on the body needs to be further researched and understood. There are different types of bodies and each body many require special attention when it comes to diet and nutrition. The goal of treatment will be to gain more knowledge of how various herbs, vitamins, and foods affect individuals differently how to incorporate these methods successfully. A clinical care model will include a comprehensive understanding of common foods available to the general public, how often the foods are purchased, and the effects that they have on the general public. Healthier foods will then be integrated that are proven to reduce weight gain and obesity. The clinical model will prove that when lower calorie healthy plant based foods and vegetables are integrated into the diet weight loss is inevitable. II. Review of Evidence-Based Medicine i. The standard of care for the treatment of obesity
Thursday, December 26, 2019
Sample details Pages: 25 Words: 7366 Downloads: 9 Date added: 2017/06/26 Category Education Essay Type Research paper Did you like this example? Chapter 2. Background and Related Work Introduction During the last decade the amount of literature published in the field of eLearning has grown noticeably, as has the diversity in attitudes and viewpoints of people who work on this subject. The general background presented here with regard to eLearning includes the definition, details of different types and the concept of quality. DonÃ¢â¬â¢t waste time! Our writers will create an original "eLearning" essay for you Create order Information quality within information systems (IS), web mining and information extracting techniques are the main areas on which supporting literature is primarily focused. However, an in-depth explanation of each branch of these research fields is outside the scope of this literature review. The literature presented here is particularly focused on the subtopics of these large research areas which are directly applicable to this research. The structure of this chapter is divided into three main parts: a general view of eLearning including definitions of eLearning, an overview of eLearning types and the concept of quality in eLearning; information quality (IQ) within ISs; and information extraction methods. Each section includes a number of subsections which address the factors that are relevant to this research. ELearning In this part of the literature review, we focus on eLearning by providing a discussion about the definitions of eLearning, eLearning types and the concept of quality in eLearning. Moreover, in this section we lay the foundation for the general concept of quality in eLearning upon which the research will be based. This section also presents a discussion about the relationships between technology, users and content in an eLearning context. ELearning Definition The term eLearning is used in the literature and in business to describe many fields, such as online learning, web-based training, distance learning, distributed learning, virtual learning, or technology-based training. During recent decades, eLearning has been defined in several instances in different ways. In any publication in the field of eLearning, it is important to ensure that the authors understanding exactly matches that of the majority of the readers, therefore, the specific definition used should be stated first. Moreover, to reach a clearer understanding of what eLearning is, in this part of the thesis we present numerous definitions of eLearning as mentioned in the literature. In general, most of the definitions of the term eLearning are used to express the exploitation of technologies which can be used to deliver learning (or learning materials) in an electronic format, most likely via the World Wide Web (WWW). Psaromiligkos and Retalis consider eLearning to be the systems which utilise the WWW as a delivery medium for static learning resources, such as instructional files, or as an interface onto interactive The previous definitions look at eLearning in general; in more detail, eLearning can be in the form of courses or in the form of modules and smaller learning materials it also could take various forms. Romiszowski takes these details into account and summarises the definitions encountered in the literature in a way that emphasises that eLearning can be a solitary, individual activity, or a collaborative group activity. It also suggests that both synchronous and asynchronous interactive forms can be engaged. Naidu also takes into consideration the differences in the forms of interaction when trying to formulate a general definition of eLearning: educational processes that utilize information and communications technology to mediate asynchronous as well as synchronous learning and teaching activities. The position adopted in thi s research is that eLearning entails the technology used to distribute the learning materials, the quality of these materials, and the interaction with learners. The definition of eLearning used in this research addresses these dimensions in terms of: the use of new multimedia technologies and the Internet to improve the quality of learning by facilitating access to resources and services as well as remote exchange and collaborations ELearning Types As mention earlier, eLearning takes many different forms and includes numerous types of systems. In the extant literature eLearning types are defined following two main axes: the user context (individuals, groups or a community of users) and users engagement and interactivity. Romiszowski takes these details into account and summarises the definitions encountered in the following table, which emphasises that eLearning can be a solitary, individual activity, or a collaborative group activity. It also suggests that both synchronous and asynchronous interactive forms can be engaged. Looking more deeply at the division of the forms of interactivity used in eLearning systems, there are two main types of eLearning: asynchronous and synchronous, depending on learning and teaching activities. Synchronous eLearning environments require tutors and learners, or the online classmates, to be online at the same time, where live interactions take place between them. In this context, Doherty describes an Asynchronous Learning Network (ALN) as a variety of eLearning systems which distribute learning materials and concepts in one direction at a time. Moreover, Spencer and Hiltz express ALN as a place where learners can interact with learning materials, tutors and other learners, through the WWW at different times and from different places. The focus of this research will be on a case where students log-in to and use the system independently of other students and staff members, as well as using asynchronous methods regarding learning content, quality management and delivery which fit firmly into the general definition of the asynchronous eLearning environment. Quality Concept in ELearning The definition of eLearning adopted in this thesis represents three fundamental dimensions: technology, access and quality. The focus in this research will be on quality, which is considered a crucial issue for education in general, and for eLearning in particular. This section of the literature review will discuss concepts of quality in eLearning generally, and highlight the importance of content as the most critical factor for the overall quality. Currently, there are two recognised challenges in eLearning: the demand for overall interoperability and the request for (high) quality. However, quality cannot be expressed and set by a simple definition, since in itself quality is a very abstract notion. In fact, it is much easier to notice the absence of quality than its presence. Despite efforts to reach a comprehensive, universal definition of quality in eLearning, there is still a fundamental ambiguity surrounding the issue. One position is to consider quality as an evaluati on of excellence, a stance which is primarily adopted by universities and education institutions. For example, in universities quality teaching and learning are promoted as the top priority, giving less attention to criteria or measurements regarding teaching input into courses, the learning outcomes, and the interactivity with the system. Another trend is to consider the improvement in quality, where quality is improved by moving beyond the set conceptions applied, and generally moving in the direction of a flexible process of negotiation, which needs a very high level of quality capability from those involved. Furthermore, quality can be viewed and considered from different aspects. Here, the SunTrust Equitable report illustrates what they perceive to be the value chain in eLearning in the form of a pyramid. The content is the most critical factor of eLearning. Indeed, to be able to use the internet as a tool to improve learning, the content should not distract learners, but increase their interest for learning. Learning tools and enablers are also important in the learning procedure. In reality, providers of learning platforms and knowledge management systems are key in the successful delivery of content. These companies provide the necessary infrastructure to deliver learning content. Moreover, learning service providers (LSP) are the distribution channels for content providers. One of the challenges facing these knowledge hubs and LSPs is to ensure that the learners are receiving fresh content. Companies focused on educational e-tailing then complete the value pyramid of eLearning. Looking at the pyramid it can be clearly observed that content is the most critical component of learning through the internet. In a similar manner, Henry stated that eLearning is composed of three main aspects: content, technology and services, he also emphasised that content is the most significant factor. Although this thesis will focus on the quality of content delivered by eLearning as the most important criteria and the most influential in the overall level of learning quality, the specified context and the perspectives of users also need to be taken into account when defining quality in eLearning. It is also essential to classify suitable criteria to address this quality. ELearning Technology, Users and Content Although most eLearning explanations focus on the technology and not on the learning, it is important to keep the people eLearning is designed for in mind. Moreover, individual learning styles and required learning materials should be addressed first. Then a suitable electronic delivery method can be adopted. On their website (agelesslearner.com), Karl and Marcia Conner commented, in this regard, that Maybe the e should actually follow the word learning'. Henry describes the content in a way that includes all delivered materials, including the materials which are usually offered in classroom-based learning and that are tailored for eLearning, in addition to any other knowledge the developer might offer. In fact, eLearning systems are considered to be user-adaptive systems, where systems are designed to react with user performance and choices. Webber, Pesty and Balacheff express user modelling as a central issue in the development of user-adaptive systems, whose behaviour is u sually based on the users preferences, goals, interests and knowledge. Moreover, they declare that a system can be considered user-adaptive when changes in its functionality, structure or interface can be monitored, in order to consider the different needs of users and, ultimately, their changing needs. In the area of eLearning Heift and Nicholson believe that eLearning systems as adaptive systems are designed to meet the diverse requirements of students who have different levels of knowledge and backgrounds . There is a significant base of literature and research in the area of adaptive systems, which usually base their behaviour on user models. In more detail, Kobsa explained that the user model often depends on one user or a group of users sharing the same profile and it characterises users preferences, goals, interests and knowledge. Webber, Pesty and Balacheff notice that with regard to this point there are two main problems relating to user modelling: to identify the re levant information to be modelled and to decide which method is more suitable to apply in order to determine the relevant information about the user. In fact, personalisation plays an important role in all areas of the e-era, especially in eLearning, as stated by Esposito, Licchelli and Semeraro, where the main issue is student modelling. This is the analysis of student behaviour and the prediction of future activities and learning performance . Furthermore, Ong and Ramachandran perceive that the literature on adaptive systems shows that by modelling the learner, the human tutor and the knowledge domain of instructional content, powerful pedagogical outcomes can be obtained. Although eLearning systems are considered types of adaptive systems, the difference between the concept of the user and the concept of the student creates a fundamental problem in the eLearning area. In this context, Esposito, Licchelli and Semeraro believe that in a general web system the user is free to sur f and the system attempts to predict future user steps using the user model in order to improve the interaction between the user and the system, while in the eLearning system the modelling has to improve the educational route, adapting it to the model of the student. As a result it is essential to control and to assess student browsing. The systems should not give the students absolute freedom to decide their way through the content and learning materials, rather, the system should provide a specific educational path and offer a continuous evaluation activity of student performance, towards a defined pedagogical goal. Although delivering web-based educational materials can be very useful as the same content is distributed to a number of students and can be accessed regardless of time and place, this delivery would not be beneficial from a pedagogical point of view if the students, their level of knowledge and their learning style was not known. In fact, Sanatally and Senteni obse rve that the widely held principle of using the web simply as a form of distributed medium for learning materials does not add significant value to the learning process. This argument leads to the conviction of the importance of developing adaptive eLearning systems. Even if adaptive systems are focused on the interaction with users and changing the course and the content dynamically with their needs, and not on controlling the set sequence of a course, eLearning can exploit adaptive technologies to build learning environments that form user-specific sequencing. Tang and McCalla use the example of the Paper Recommender System as a good example of this exploitation: the system was designed to give recommendations to students about what conference or journal papers to read, based on their level of understanding and knowledge. We can see more clearly, as suggested by Conati and VanLehn, that the aim of adaptive systems is to build precise, interactively changing models of individual student learning, in order to use them as representations of how learners are progressing within the content of the course. Moreover, Papanikolaou et al. describe adaptivity as being system-controlled and in most cases assists in: planning the content, planning the delivery and presentation of the learning materials, supporting student navigation throughout the field of knowledge and problem solving. From this, it can be deduced that learner models generally characterise learner knowledge levels on the concepts of domain knowledge, pedagogical goals and learning preferences towards diverse styles of learning materials. In this context, they suggest that the domain model should be used in parallel with the learner model to provide a structure for the representation of learner knowledge of the defined domain. Using this procedure, tailored learning materials can be distributed to specific learners to be consistent with their requirements. This corresponds with the vision of Mittal et al., who realised that by creating several broad groups into which it is possible to segment target learners, it can be ensured that the content of learning materials for an absolute beginner student is not the same for that of a student getting ready for an exam. Nowadays, most student modelling systems follow the same method, in which the systems starting point is to create a reference template for a student, thus, the expertise or intelligence encoded into the system can adapt the course organisation and content to the individual student. The use of this method to decide the style and level of content that a student should be offered, according to how students interact with the system, will lead to a more personalised learning experience. In the case of this research, the student and domain model did not entail the complexity of those built in adaptive systems; however, several of the underlying principles of available student and domain modelling techniques proved to be usef ul. The key issue in most adaptive systems that feature student and domain modelling is a sequence of complex data repositories that give highly precise values about student performance and completion against learning materials. The focus in this research will be on measuring the quality of the content of learning materials distributed via eLearning systems, and establishing how the student will interact with the materials, how they will be able to extract the relevant information from the content and how the context of the online materials will help students to recognise the underlying structure of the content and easily access the parts in which they are interested. This research will gather empirical evidence using online questionnaires, which can be used to directly ask students about their preferences and perspectives. Summary This part of the literature review provided a general overview of eLearning, including definitions of eLearning, a note of eLearning types and consideration of the concept of quality in eLearning. It also identified the definition adopted for eLearning in this study and considered the type upon which this research will focus. Moreover, in this section we laid the foundation for the general concept of quality in eLearning upon which the research will be based. Finally, it presented a brief discussion about the relationships between technology, users and content in an eLearning context. The next part of this chapter will discuss the concept of IQ within ISs; this will be used later on to set standards for IQ in the context of eLearning systems. Information Quality in Information Systems In this part of the literature review we will start with a brief discussion of the terms data quality and information quality, and will shed some light on the concept of IQ within ISs and how it could be defined. We will also provide a comprehensive review of the major historical developments of IQ frameworks. Data Quality(DQ) vs. Information Quality During recent years, much work has been done to build quality frameworks for IQ dimensions. In the past, research focused on DQ, but due to the recent development of internet technologies, ISs today are providing users with information, not only data. Therefore, research attention has shifted to focus on IQ frameworks. While, some researchers explicitly distinguish between the terms data and information and explain information as data which has been processed in some way, sometimes, it may be difficult to discriminate between them in practice . Still, in some studies the term information is interchangeable with data. Likewise, the term data quality is often used synonymously with information quality. Consequently, in this study, the concept of information will be used in a broad sense, which covers the concept of data. Before reviewing the researches that were conducted to formulate (data/information) quality frameworks within ISs, first we will discuss the meaning of IQ a nd how it could be defined. How Information Quality Could be Defined Although it is important to set standards for IQ, it is a difficult and complex issue, particularly in the area of ISs, because there is no formal definition of IQ, as quality is dependent on the criteria applied to it. Furthermore, it is dependent on the targets, the environment and from which viewpoint we look at the IQ, that is, from the provider or the consumer perspective. Moreover, IQ is both a task-dependent and a subjective concept. Juran summarises these aspects of quality in his quality definition as fitness for use. Similarly, Wang described DQ (which could apply to IQ) as data that is fit-for-use. This description has been adopted by researchers because it brings to light the fact that IQ cannot be defined and evaluated without knowing its context. Defining IQ in a contextual approach seems to be logical because quality criteria, which could be used to assess IQ, can differ according to the context. In fact, IQ is expressed in the literature to be a multi-dimensional concept with varying attributed characteristics depending on the context of the information. However, taking into account the complexity of the IQ concept and that its measurement is expected to be multi-dimensional in nature, the prime issue in defining the quality of any IS is identifying the criteria by which the quality is determined. The criteria result from the multi-dimensional and interdependent nature of quality in ISs, and are dependent on the objectives and the context of the system. Thus, it is common to define IQ on the internet by identifying the main dimensions of the quality, for that purpose IQ frameworks are widely used to identify the important quality dimensions in a specific context, these dimensions can be used as benchmark to improve the effectiveness of information systems, as described by Porter. Information Quality Frameworks Today, for any IS to be judged successfully it has first to satisfy additional predefined quality criteria. An eLearning system is a special type of IS so it is important to examine the literature relating to the traditional IS success models and the proposed quality frameworks, in order to test the possibility of extending these success models to identify eLearning content quality criteria in an eLearning context. Much of the work done in IS success has its origins in the well-known DeLone and McLean (DM) IS Success Model.This model provided a comprehensive taxonomy on IS success based on the analysis of more than 180 studies on IS success and it identified over 100 IS success measures during the analysis. It established that system quality, IQ, use, user satisfaction, individual and organisational impact were the most distinct elements of the IS success equation. In a later work, the authors confirmed the original taxonomy and their conclusion, namely that IS success was a mul tidimensional and interdependent construct. Their model makes two important contributions to the understanding of IS success. First, it provides a scheme for categorising the multitude of IS success measures that have been used in the literature. Second, it suggests a model of temporal and causal interdependencies between the categories. The updated model, which was proposed in 2003, consists of six dimensions: Information quality, which concerns the system content issue. Web content should be personalised, complete, relevant, easy to understand and secure. System quality, which measures the desired characteristics of a web based system such as usability, availability, reliability and adaptability. Service quality Usage, which measures visits to a website, navigation within the site and information retrieval. User satisfaction, which measures users opinions of the system and should cover the entire user experience cycle. Net benefits, which capture the balance of positive and negative impacts of the system on the users. Although this success measure is very important, it cannot be analysed and understood without system quality and IQ measurements. In their model, DeLone and McLean defined three main dimensions for the quality: IQ, systems quality and service quality. Each one has to be measured separately, because singularly or jointly, they will affect subsequent system usage and user satisfaction. In 1996, Wang and Strong proposed their DQ framework, which will be discussed in more detail in the following section. In their framework they categorised characteristics/attributes in to four main types/factors: intrinsic, accessibility, contextual and representational. This method of categorising IQ factors and attributes proved to be a valuable methodology for defining IQ. Lately, several quality management projects in business and government have successfully used this framework. After Wang Strong DQ framework, diverse research efforts were spent in order to identify IQ dimensions in deference contexts. Although these frameworks varied in their approach and application, they shared some of the same characteristics conc erning their classifications of the dimensions of quality. In 1996, Gertz focused on finding possible solutions for the problems regarding modeling and managing data quality and integrity of integrated data. H proposed a taxonomy of data quality characteristics that includes important attributes such as timeliness and completeness of local information sources. While Redmans work aimed to set up practical guidelines to analyze and improve information quality within business processes, h proposed a number of quality attributes grouped into six categories: Privacy, Content, Quality of Values, Presentation, Improvement and Commitment. In the same year, Zeist Hendricks identified 32 IQ sub-characteristics grouped in 6 main IQ characteristics which covered functionality, reliability, efficiency, usability, maintainability and portability. Unlike general purpose IQ framework, in 1997 Jarke proposed a special purpose framework where he used the same hierarchical design established by Wang Strong. He defined IQ criteria depending on the context and requirements for specific application; Data Warehouse Quality (DWQ). In his framework, Jarke linked each operational quality goals for data warehouses to the criteria which describe this goal. The main defined criteria are accessibility, interpretability, usefulness, believability, and validation. In 1998, Chen gave a list of IQ criteria with no special taxonomy. He, however, proposed a goal-oriented framework focusing mainly on time-oriented criteria such as response time and network delay. One year later, Alexander Tate proposed their framework for IQ IN Web environment. This framework consisted of 6 main criteria; authority, accuracy, objectivity, currency, orientation and navigation. In the same year, Katerattanakul Siau adapted Wang Strong DQ framework to propose their four categories IQ framework of individual websites. Furthermore, Shanks Corbitt recommended a semiotic-based quality framework for inform ation on the Web. This framework includes four semiotic levels. Syntactic level to insure that information is consistent whiles the Semantic level focuses on the information completion and accuracy. Pragmatic level is the third level which covers the usability and the usefulness of the information. The forth level is the social level ensures information understandability. Within their framework there are 11 quality dimension distributed within the identified levels. Dedeke in 2000 developed a conceptual IS quality framework that includes 5 categories; ergonomic, accessible, transactional, contextual and representational quality. Each category consists of number of quality dimensions such as; availability, relevancy and conciseness. Whilst Zhu Gauch described 6 quality metrics for information retrieval on the web; these are availability, authority, currency, information-to-noise ratio and cohesiveness. Leung adapted Zeist Hendrickss quality framework in 2001 and applied it to Intranet applications. He defined 6 main IQ characteristics; functionality, reliability, usability, efficiency, maintainability and portability. Each quality characteristic in the proposed framework includes numbers of sub-characteristics. Several research in IS quality were undertaken in 2002, Eppler Muenzenmayer suggested two main manifestations for their proposed framework; content quality and media quality. The content quality is focused on the quality of the presented information and it consists of two categories; relevant information and sound information. Whereas media quality is focused on the quality of the medium used to deliver the information and it includes optimized process category and reliable infrastructure category. Each category in the framework contains number of quality dimensions. Khan categorised IQ depending on the context of the system. The framework divided IQ into two main quality types; product and service quality. Moreover, it divided these two type s into 4 quality classifications and each classification into number of quality dimensions. The quality classifications are sound information, useful information, dependable information and usable information. In addition, Klein conducted a research in the same year to identify five IQ dimensions chosen Wang Strongs DQ framework to measure IQ in Web context; accuracy, completeness, relevance, timeliness and amount of data. Mecella also proposed an initial framework for quality management in Cooperative Information System (CIS). This framework includes a model for quality data exported by cooperating organizations and the design of an infrastructure service and improving quality. More recent, in 2005 Liu Huang mentioned 6 key dimensions for IQ; source (focused on information availability), content (focused on information completeness), format and presentation (focused on information consistency), currency (focused on information currency and timeliness), accuracy (focused on information accuracy and reliability) and speed (focused on how easily information is downloadable). Besiki et all introduced in 2007 a general framework for IQ assessment. This framework consists of a comprehensive taxonomy of IQ dimensions, and provides a straightforward and powerful predictive method to study IQ problems and reason through them in a systematic and meaningful way. Lately, Kimberly et all presented in 2009 a model for how to think about IQ depending on the application context; they identified number of common IQ metrics. Kargar Azimzadeh also presented an original experimental framework for ranking IQ on the Web log. The results of their research revealed 7 IQ dimensions for IQ in Web log. For each quality dimension, quality variables associated coefficients were calculated and used so that the proposed framework is able to automatically assess IQ of Web logs. In the same year Thi Helfert conducted a research aimed to propose a quality framework based on IS architecture. In their research they identified quality factors for different construct levels of IS architecture. Moreover, they also presented impacts amongst different quality factors which help to analyze the cause of IS defects. In this part we gave a brief review of the researches conducted to formulate (data/information) quality frameworks within ISs. However in the next section we will focus on Wang and Strongs DQ framework as we will use it as a base for this research to measure IQ in eLearning systems along the dimensions of the framework. Wang and Strongs Data Quality Framework Wang Strongs DQ framework, one of the most comprehensive, popular, remarkable and cited DQ frameworks, was established by Richard Wang and Diana Strong in 1996. Their framework was designed empirically by asking users to give their viewpoints about the relevance of the IQ dimensions to capture the most important aspects of DQ to the data consumer. In their framework, Wang and Strong classified quality dimensions into four groups: Intrinsic DQ: refers to the quality dimensions originating from the data on its own. This aspect of quality is independent of the users perspective and context. Contextual DQ: focuses on the aspect of IQ within the context of the task at hand. In this group, the quality dimensions are subjective preferences of the user. Contrary to the first group, DQ dimensions cannot be assessed without considering the users viewpoint about their use of provided information. Representational DQ: is related to the representation of information within the systems. Accessibility DQ: refers to the quality aspects concerned with accessing distributed information. The defining feature of this particular study is that quality attributes of data were collected from the data consumer instead of being defined theoretically or being based on the researchers own experiences. Their research can provide a basis for measuring DQ/IQ along the dimensions of this framework. Summary In this part of the literature review we shed some light on the use of the terms data quality and information quality, we also discussed the concept of IQ within ISs and considered how it could be defined. We also gave a historical review of the researches conducted to formulate (data/information) quality frameworks within ISs, focusing on Wang and Strongs DQ framework which will provide a good basis for this research to measure IQ in eLearningsystems along the dimensions of this framework. However, this research will also investigate the possibility of integrating a web-mining approach, a data gathering technique, in order to automate the evaluation process. It seems logical, therefore, that the available methods for web-mining and information extraction are now reviewed. These will be discussed in the next section. Information extraction and Web-Mining This study focuses not only on the evaluation of IQ in the context of eLearning systems, but also it will investigate the possibility of integrating a web-mining approach, a data extraction technique, in order to automate the evaluation process. This part of the literature review will provide a brief overview of the information represented on the web. It will also focus on web-mining definitions and categories, and the idea of information extraction. Information on the Web Today, the web is becoming more popular and interactive information publishing mediums and the levels of web information are growing rapidly. Moreover, the web holds a huge amount of distributed information for news, education, government, e-commerce and various other information services. Also, the web contains a rich and dynamic collection of hyperlink information and webpage access and usage information, all of which raise an information overload issue. In fact, today web users can access vast amounts of information, however, it becomes ever more difficult to weed out the irrelevant and discover the relevant information which has drawn attention to a fundamental issue: information overload. The nature of web information is unstructured, thus it can only be understood by humans, but the massive amount of available information means that it can only be processed efficiently by machines. A lack of metadata, data about data, represents another challenge when dealing with the publ ished information. To be able to cope with these challenges researchers started to apply techniques from data-mining and machine learning to web data and documents. Web-mining applications help users in finding, sorting and filtering the available information, while the Semantic Web aims to make the data machine understandable as well. Web-Mining Extracting useful or valuable information from the web is usually referred to as web-mining. It refers to the application of data-mining methods for the discovery of useful information on the web. In the literature, several definitions exist relating to web-mining. It could be generally defined as the automated discovery and analysis of useful information published in web documents and services using data-mining methods. It is a large and new area converging from several research districts, such as database, information extraction and artificial intelligence. Web-mining techniques could be used to solve the information overload problem. Web-Mining Categories There are three categories for web-mining according to the different sources of the target data: Web-content mining: which addresses the discovery of knowledge from the content of web pages, thus, it includes the target data contained in a web page as text, images, multimedia, etc. Web-usage mining: which addresses the discovery of knowledge from user navigation data while surfing the web, thus, this includes the target data contained in users log files. Web-structure mining: which addresses the discovery of knowledge from hyperlinks on the web. This broadly used categorisation of web-mining started in 1997 when Cooley, Srivastava and Mobasher introduced web-content mining and web-usage mining, while web-structure mining was added in 2000 by Kosala and Blockeel. The focus in this research will be on web-content mining as a technique to automate the extraction process of the information needed in the quality measurement. Web-Mining and Information Extraction (IE) Natural language (NL) texts are used mostly as digital information storage mediums. The main goal of information extraction (IE) is to find the required information in NL texts and store this information in a way that is suitable for automatic querying and processing. IE involves defining output representations or templates and searching only for information that fits the defined representations. Summary Within this section of the literature review a brief idea of information representation on the web was provided. It also shed some light on the web-mining definition and considered the categories of web-mining, finally, the idea of information extraction was noted. Conclusion The literature review provided a general background to the subject of eLearning, including the definitions, types and the concepts of quality, IQ within ISs, and web-mining as an information extracting technique. The literature offered here mainly focused on the sub-topics of the larger research areas which will be directly applicable to this research. References Paulsen, M.F., (2002) Online education systems: Discussion and definition of terms. NKI Distance Education, Romiszowski, A., (2004) Hows the e-learning baby? Factors leading to success or failure of an educational technology innovation. Educational Technology. 44(1): p. 5-27 Gerhard, J. and Mayr, P.(2002) Competing in the e-learning environmentstrategies for universities. Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS02). 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Wednesday, December 18, 2019
Introduction Steve Jobs and Bill Gates are two of the most well-known names of our generation for being the co-founders of two very large corporations. Steve Jobs being the co-founder of Apple, also the founder of Pixar and NeXT. Bill Gates, most known for being the co-founder of Microsoft, which is the biggest software company in the world. Though, without a doubt, both of these men were very successful in their professional lives for mainly the same thing and similar in their ways, but very different. Bill Gates Bill Gates was born on October 28, 1955, in Seattle, Washington. At the age of 13, was when he first found his love for computers His senior year, he and his friend, Paul Allen developed their own company called theÃ¢â¬ ¦show more contentÃ¢â¬ ¦In 1986, Microsoft went public with 24.7 million shares, that of which Gates owned 45 percent of. Microsoft was racking up $520 million, and of that money, Gates was getting $243 million. A year later was in the list of the top 400 wealthiest people in America. Because of his great wealth, Gates decided to help out in education. In 1994, he created the Ã¢â¬Å"William H. Gates FoundationÃ¢â¬ . By 1999, Bill Gates wealth had reached $101 billion. Gates was always checking out the competition, making sure Microsoft was on top. When Gates heard of International Business Machines Corporations (IBM) making an operating system called OS/2, he immediately began working on updates for Microsoft. In 1989, Microsoft released Office adding on Word and Excel. The new version of Microsoft sold quickly and OS/2 failed. In the 1990Ã¢â¬â¢s, Microsoft got in trouble with the Federal Trade Commissions for unfair marketing practice. Thankfully, Microsoft settle it without having to breakup. In 2000, handed over the position of being Microsoft CEO to his friend, Steve Ballmer, but still remained being the chairman. In 2006, Gates went to full time at Microsoft in order to devote more time to what was now called the Ã¢â¬Å"Gates and Melinda FoundationÃ¢â¬ . Over the years, Gates racked up on many awards and honorable mentions. In 2005, Times Magazine mentioned Bill Gates as one of the Ã¢â¬Å"People of the yearÃ¢â¬ . June 27, 2008, Gates begin to spend more time with his foundation and his educationalShow MoreRelatedEssay on A Comparsion of Bill Gates and Steve Jobs1612 Words Ã |Ã 7 PagesIntroduction Bill Gates and Steve Jobs are intelligent innovative thinkers who have always new things to show and give to the world, and both of them are known as the best-known entrepreneurs of the personal computer revolution in the modern age. These two entrepreneurs may both work in the field of technology, but they also have many differences to distinguish themselves from one another. Early Life Bill Gates grew up in a wealthy area in Seattle, Washington, with his parents and two sisters. As
Tuesday, December 10, 2019
My work is devoted to the methods of teaching English. Language came Into life as a mean of communication. It exists and Is alive only through speech. When we speak about teaching a foreign language, we first of all have in mind teaching it as a mean of communication. In teaching speech the teacher has to cope with two tasks. They are: to teach his pupils to understand the foreign language and to teach them to speak the language. So, speech is a bilateral process.It includes hearing, on the one hand, and speaking, on the other. When we say hearing we mean adding or listening and comprehension. Speaking exists in wow forms: dialogue and monologue. My purpose here is to explore the Interactive methods of teaching English that have attracted the attention of the teachers in recent years, to show reason for interest in them, in what they are exploring, in what they accomplish, the principles and ideas that guide them. We will write a custom essay sample on Interactive Methods of Teaching English or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page I shall make a lesson plan and during the lesson I shall experience the interactive methods of teaching which give the foreign language teacher the possibility to master some new techniques of communicative methods of foreign language training. Teacher has to organize different forms of activity at the foreign engage classes that is individual, pair, group and team. I shall present the most well known form of pair and group work the following kinds should be mentioned: inside (outside) circles, brainstorm, line-ups, Jigsaw reading, think-pair-share, debate, and so on.Audio-Visual Methods in Teaching. Audio-visual methods in teaching can improve classroom instruction and student understanding. Hearing students are more focused on spoken than written. The recordings of lectures and films are useful for students to auditory and nuances of the language, like the timbre and tone of the gathering. Brainstorming method. Brainstorming with a group of people is a powerful technique. Brainstorming creates new ideas, solves problems, motivates and develops teams.Use Brainstorming well and you will see excellent results in improving the organization, performance, and developing the team. Your Job as facilitator Is to encourage everyone to participate, to dismiss nothing, and to prevent others from pouring scorn on the wilder suggestions Debate method. Debate or stressing Is a method of Interactive and representational argument. The major goal of the study of debate as a method or art is to develop ones ability to play from either position with equal ease. Jigsaw reading method. Students of an average sized class (26 to 33 students) are divided into competency groups of four to six students, each of which is given a list of subtopics to research. Individual members of each group then break off to work with the experts from other groups, researching a part of the material being studied, after which they return to their starting group In the role of instructor for their subcategory. The strategy is an efficient teaching method that also encourages listening, engagement, interaction, peer teaching, and cooperation. Graded Readers.Teaching English can be pretty dull if you don t incorporate some reading and discussion in your classes that can handle an activity like this. You can have your students read them for pleasure, or as a class assignment. Be sure to have your students choose a book that they are Interested In, easily understand 95% of the vocabulary or more. Reading should t be a struggle of looking up words in the dictionary. Movie Projects One enjoyable project you can do with students that are advanced enough is a movie project. You can either assign it as homework or do it in class.
Monday, December 2, 2019
The Fear Of Fear The Fear of Fear In The Lord of the Flies, fear is the cause of all destruction and violence, which leads to savagery, and disobeying of human morals. Throughout the entire book fear is what drives these young innocent boys into savagery, and what also pulls most of them away from expectable human behavior. Without the normal rules of society helping to guide them, they become disoriented with the new surroundings, therefore freighting them into savage ways. After the traumatic plane crash the boys became frightened because their world of comfort was no longer visible, and a dark scary place awaited their arrival. Fear inside of them became greater but the boys did not to show their fear. While struggling to get through the jungle Piggy gets caught up in tree vines, frustrated he yelled out I cant hardly move with all these creeper things. (Pg.7 Golding) With out even realizing it Piggy shows how his fear turns things that are beautiful in nature into things to beware. Now with the danger of many creatures / animals, they decide to hunt. Hunt because in the mind of the hunters getting rescued is not in the future, and to survive is to kill, and to kill is to stay alive. So fear of not getting rescued sets in and the children start to hunt and destroy. With the threat of the beastie the hunters are extra cautious so they build a fire on the beach and they hold a gathering. The fire represent the safeness of light and the gathering keeps everyone together, so as a group, are not scared. They start to dance and circle around the fire, meanwhile Simon knowing the truth about the beastie hurries to tell the boys, The circle became a horseshoe. A thing was crawling out of the forest. It came darkly, uncertainly. The shrill screaming that rose before the beast was like a pain. The beast stumbled into the horseshoe. Kill the beast! Cut his throat! Spill his blood! Do him in!(Pg.152 Golding) The beast was now turned into innocent Simon and because of the fear inside the jungle, and inside themselves, Simon was brutally beaten and killed by the other boys as the mother pig was with her young. The killing of Simon showed how fear caused disorientation in reality. Simon having no fear, was the one who had the answer. The beast is within us; t here is nothing to fear. Simon used no violence and came face to face with the beast. He knew the truth. Bibliography The book Lord of the Flies English Essays