Monday, March 23, 2020

A.E. Housman Scholar And Poet Essays - A. E. Housman,

A.E. Housman: Scholar and Poet Alfred Edward Housman, a classical scholar and poet, was born in Fockbury in the county of Worcestershire, England on March 26, 1859. His poems are variations on the themes of mortality and the miseries of human condition (Magill 1411). Most of Housman's poems were written in the 1890's when he was under great psychological stress, which made the tone of his poems characteristically mournful and the mood dispirited (Magill 1411). "In the world of Housman's poetry, youth fades to dust, lovers are unfaithful, and death is the tranquil end of everything (Magill 1412)." Throughout his life, Housman faced many hardships. The loss of his mother at age 12 shattered his childhood and left him with tremendous feelings of loneliness, from which he never fully recovered. His father began to drink as a result of his mother's death and began a long slide into poverty. When Housman went to college, he had a deep and lasting friendship with Moses Jackson. He had developed a passionate attachment and fallen in love with him. When the relationship did not work out, Housman plunged into a suicidal gloom which was to persist at intervals for the rest of his life. His declaration that "I have seldom written poetry unless I was rather out of health," seems to support the opinion that emotional trauma greatly influenced his work. The only way to relieve himself from this state of melancholy was by writing (Magill 1409). As a result of Housman's poor childhood and misfortunes, he devoted most of his life to erudition and poetry. He was educated at Bromsgrove school and won a scholarship to Oxford University, where he studied classical literature and philosophy. After graduating from Oxford, he became a professor of Latin, first at University College and later at Cambridge University. He was a knowledgeable and scholarly individual who was fluent in five languages (Magill 1405). Over a period of fifty years, Housman gave many enlightening lectures, wrote numerous critical papers and reviews, and three volumes of poetry. In all of his poetry, Housman continually returns to certain preferred themes. The most common theme discussed in the poems is time and the inevitability of death. He views time and aging as horrible processes and has the attitude that each day one lives is a day closer to death Cleanth Brooks stated, "Time is, with Housman, always the enemy." The joy and beauty of life is darkened by the shadow of fast approaching death (Discovering Authors 7). He often uses symbolism to express death, therefore the reader has to look into the true meaning of the poem to see it's connection with death. Another frequent theme in Housman's poetry is the attitude that the universe is cruel and hostile, created by a god who has abandoned it. R. Kowalczyk summed up this common theme when he stated: Housman's poetic characters fail to find divine love in the universe. They confront the enormity of space and realize that they are victims of Nature's blind forces. A number of Housman's lyrics scrutinize with cool, detached irony the impersonal universe, the vicious world in which man was placed to endure his fated existence (Discovering Authors 8). Housman believed that God created our universe and left us in this unkind world to fend for ourselves. The majority of Housman's poems are short and simple. It is not difficult to analyze his writing or find the true meaning of his poems. However, the directness and simplicity of much of Housman's poetry were viewed as faults. Many critics view Housman's poetry as "adolescent", thus he is considered a minor poet. The range of meter that Housman uses varies from four to sixteen syllables in length. John Macdonald claims "What is remarkable about Housman's poetry is the amount and the sublety variation within a single stanza, and the almost uncanny felicity with which the stresses of the metrical pattern coincide with the normal accents of the sentence (Discovering Authors 11)." Housman uses monosyllabic and simple words in his poetry, but the words that he chooses to use fit together rhythmically and express the idea with a clear image. To express his vivid images Housman uses epithets, which are words or phrases that state a particular quality about someone or something (English Tradition 1399). Housman uses epithets sparingly, but when he uses them they are creative and original: such phrases as "light-leaved spring," the bluebells of the listless plain," and "golden friends" make his poetry decorative and filled with imagery (British Writers 162). In 1896, A Shropshire Lad was published at the expense of Housman himself.

Friday, March 6, 2020

3 Cases of Not Only . . . but Also Variations

3 Cases of Not Only . . . but Also Variations 3 Cases of Not Only . . . but Also Variations 3 Cases of Not Only . . . but Also Variations By Mark Nichol Sentences that employ the â€Å"not only . . . but also† counterpoint (as in â€Å"I visited not only France but also Spain†) can confound writers, who often fail to apply logical syntax when using this construction. As shown in the examples below, such confusion often occurs in similarly posed statements. Discussion and revision of each sentence explains and illustrates coherent use of related constructions. 1. The idea was not to just construct a new arena, but one that would nod to the roots of the game. Just occupies the same role as only in a â€Å"not only . . . but also† counterpoint, and the principle is the same- when a verb applies to both the â€Å"not only† proposition and the â€Å"but also† proposition, the verb must precede â€Å"not only†: â€Å"The idea was to construct not just a new arena but also one that would nod to the roots of the game.† (Also, note that in this example as well as in the others, internal punctuation is not required to set off the two parts of the sentence.) 2. The above principles are not intended to prescribe specific reporting practices, but rather offer sound direction for the board and management to pursue. Here, as in a â€Å"not only . . . but also† construction of this type, the verb supports both elements of the not/rather counterpoint, so it must precede, not follow, not: â€Å"The above principles are intended not to prescribe specific reporting practices but rather to offer sound direction for the board and management to pursue.† 3. It’s not simply deciding how good or bad an individual playing card is, but rather how consistently the player manages his or her appetite to win and his or her tolerance for losing. This sentence does not have a â€Å"not only . . . but also† counterpoint, but it requires a similar construction to make sense. Because simply implies addition, not replacement, also should replace rather, and the second part of the sentence requires a verb equivalent to deciding: â€Å"It’s not simply deciding how good or bad an individual playing card is but also determining how consistently the player manages his or her appetite to win and his or her tolerance for losing. Want to improve your English in five minutes a day? Get a subscription and start receiving our writing tips and exercises daily! Keep learning! Browse the Style category, check our popular posts, or choose a related post below:5 Uses of InfinitivesDeck the HallsQuiet or Quite?

Tuesday, February 18, 2020

Explain the causes and results of the punic wars Research Paper - 1

Explain the causes and results of the punic wars - Research Paper Example The Punic Wars are recorded to be one of the greatest clashes recorded in History. In those times, it took place between the two most powerful empires: The Rome and The Carthage. The Punic wars are said to have extended for almost a century, most likely 264-146BC.1 These wars till date are the most profound evidence of struggle for power and one of the most ancient example of security dilemma. With Romans at the peak of expanding their Empire at this time, and the Carthage with their strongest naval force were bound to come across someday cause growth of one of them was a direct threat for another one. The Punic wars were extremely deadly and there was a reason as to why they were kept such an account of. These wars seem to have started the trend of mighty rivalries and wars that go on for years and years. An event that surely put a stamp on the pages of history, the following paper presents an analysis on the Punic wars and the causes of what brought on this event in History and its repercussions. As far as the Punic wars are concerned, nobody expected them to happen, these wars weren’t anticipated. Surprising as it sounds, the scale on which these wars took place are less likely to take place out of the blue. The Romans and Carthaginians were bounded in peace treaties for almost two centuries2. No problems were witnessed by the commoners; hence it was even the more unsettling as to what caused these wars. (First Punic War, 264-241 BC 2013) That lasted until they realized the security dilemma: to strike first or to wait for sudden strike. However, what happened was witnessed by everyone and its suddenness soon disappeared with the enmity that took over. The Punic wars comprised of three conflict periods, the first and second one being the longer ones lasting for seventeen and twenty-three years. 3 The Punic Wars were instigated with the dispute on the island of Sicily

Monday, February 3, 2020

Poverty and population Essay Example | Topics and Well Written Essays - 1750 words

Poverty and population - Essay Example The results by the UN indicate that Africa is facing a boom in its population, which is almost quadrupling by the end of this century. The current fertility rate of African Women is at 4.7. The question arising is that if Africa is unable to feed a billion people, how then could it be in a position to feed four billion in future? This topic is important in the topic of global reproductive health since with increased population and poverty; access to high-quality hospital services may not be possible. As a result, childbearing women may suffer from various illnesses of the reproductive systems (Avery, 2014). Moreover, such impoverished women living in deplorable conditions suffer from various unwanted pregnancies, sexually transmitted infections, maternal disabilities and even deaths, gender-based violence and other problems that relate to the reproductive system and unhealthy sexual behaviors. Africa needs to adopt various strategies to deal with their increased population growth and poverty. They need to have better infrastructure, education system, and health care system. This is because there is emerging fears that the increasing boom of the population is likely to deplete what is left of the flora and the fauna of such African countries (Birdsall, Kelley, & Sinding, 2011). Thus, it is important for the various strategies to be in place to ensure that poverty is reduced in some of these high population countries. One of the main strategies of poverty reduction is investing in reproductive health of women, educating them and ensuring gender equality. This ensures poverty reduction in several ways. One of them is enabling women to bear fewer children thus contributing to an upward economic mobility. Due to this, they stimulate economic development in their countries. Secondly, women are able to negotiate their reproductive health decisions with their men (Ahlburg, Kelley, & Mason, 2009). This move ensures that women can be in a position

Sunday, January 26, 2020

Data warehouse and data mining

Data warehouse and data mining Abstract Data mining and data warehouse is one of an important issue in a corporate world today. The biggest challenge in a world that is full of information is searching through it to find connections and data that were not previously known. Dramatic advance in data development make the role of data mining and data warehouse become important in order to improve business operation in organization. The scenarios of important data mining and data warehouse in organization are seen in the process of accumulating and integrating of vast and growing amounts of data in various format and various databases. This paper is discuss about data warehouse and data mining, the concept of data mining and data warehouse, the tools and techniques of data mining and also the benefits of data mining and data warehouse to the organizations. Keywords: Data, Data Warehouse, Data Mining, Data Mart Introduction Organizations tend to grow and prosper as they gain a better understanding of their environment. Typically, business managers must be able to track daily transactions to evaluate how the business is performing. By tapping into the operational database, management can develop strategies to meet organizational goals. The process that identified the trends and patterns in data are the factors to accomplish that. By the way, the way to handle the operational data in organization is important because the reason for generating, storing and managing data is to create information that becomes the basis for rational decision making. To facilitate the decision-making process, decision support systems (DSSs) were developed whereas it is an arrangement of computerized tools used to assist managerial decision making within a business. Decision support is a methodology that designed to extract information from data and to use such information as a basis for decision making. However, information re quirements have become so complex that is difficult for a DSS to extract all necessary information from the data structures typically found in an operational database. Therefore, a data mining and data warehouse was developed and become a proactive methodology in order to support managerial decision making in organization. Concept of Data Warehouse A data warehouse is a firms repositories that running the process of updating and storing historical business data of organization whereas the process then transform the data into multidimensional data model for efficient querying and analysis. All the data stored are extracts or obtains its data from multiple operational systems in organization with containing the information of relevant activity that occurred in the past in order to support organizational decision making. A data mart, on the other hand, is a subset of a data warehouse. It holds some special information that has been grouped to help business in making better decisions. Data used here are usually derived from data warehouse. The first organized used of such large database started with OLAP (Online Analytical Processing) whereas the focused is analytical processing of organization. The diffrences between a data mart and a data warehouse is only the size and scope of the problem being solved. According to William H.Inmon (2005), a data warehouse is a subject-oriented, integrated, time-varying, and non-volatile collection of data in support of the managements decision-making process. To understand that definition, the components will be explained more detailed; Integrated Provide a unified view of all data elements with a common definition and representation for all business units. Subject-oriented Data are stored with a subject orientation that facilitates multiple views of the data and facilitates decision making. For example, sales may be recorded by product, by division, by manager, or by region. Time-variant Dates are recorded with a historical perspective in mind. Therefore, a time dimension is added to facilitate data analysis and various time comparisons. Nonvolatile Data cannot be changed. Data are added only periodically from historical systems. Once the data are properly stored, no changes are allowed. Therefore, the data environment is relatively static. In summary, the data warehouse is usually a read-only database optimized for data analysis and query processing. Typically, data are extracted from various sources and are then transformed and integrated, in other words, passed through a data filter, before being loaded into the data warehouse. Users access the data warehouse via front-end tools and end-user application software to extract the data in usable form. The Issues That Arise in Data Warehouse Although the centralized and integrated data warehouse can be a very attractive proposition that yields many benefits, managers may be reluctant to embrace this strategy. Creating a data warehouse requires time, money, and considerable managerial effort. Therefore, it is not surprising that many companies begin their foray into warehousing by focusing on more manageable data sets that are targeted to meet the special needs of small groups within the organization. These smaller data warehouse are called data marts. A data mart is a small, single-subject data warehouse subset that provides decision support to a small group of people. Some organizations choose to implement data marts not only because of the lower cost and shorter implementation time, but also because of the current technological advances and inevitable people issues that make data marts attractive. Powerful computers can provide a customized DSS to small groups in ways that might not be possible with a centralized syste m. Also, a companys culture may predispose its employees to resist major changes, but they might quickly embrace relatively minor changes that lead to demonstrably improved decision support. In addition, people at different organizational levels are likely to require data with different summarization, aggregation, and presentation formats. Data marts can serve as a test vehicle for companies exploring the potential benefits of data warehouses. By migrating gradually from data marts to data warehouses, a specific departments decision support needs can be addressed within a reasonable time frame (six month to one year), as compared to the longer time frame usually required to implement a data warehouse (one to three years). Information Technology (IT) departments also benefit from this approach because their personnel have the opportunity to learn the issues and develop the skills required to create a data warehouse. Concept of Data Mining Data mining is the forecasting techniques and analytical tools that extensively used in industries and corporates to ensure the effectiveness in decision making. Data mining is a tools to analyze the data, uncover problems or opportunities hidden in the data relationships, form computer models based on their findings, and then use the models to predict business behavior by requiring minimal end-user intervention. The way it works is through search of valuable information from a huge amount of data that is collected over time and defined the patterns or relationships of information that present by data. In business field, the organization use data mining to predict the customer behaviour in the business environment. The process of data mining started from analyzed the data from different perspectives and summarized it into useful information, which from the information then created knowledge to address any number of business problems. For the example, banks and credit card companies u se knowledge-based analysis to detect fraud, thereby decreasing fraudulent transactions. In fact, data mining has proved to be very helpful in finding practical relationships among data that help define customer buying patterns, improve product development and acceptance, reduce healthcare fraud, analyze stock markets and so on. Data Mining in Historical Perspective Over the last 25 years or so, there has been a gradual evolution from data processing to data mining. In the 1960s business routinely collected data and processed it using database management techniques that allowed an orderly listing and tabulation of the data as well as some query activity. The OLTP (Online Transaction Processing) became routine, data retrieval from stored data bacame faster and more efficient because of the availability of new and better storage devices, and data processing became quicker and more efficient because of advancement in computer technology. Database management advanced rapidly to include highly sophisticated query systems, and became popular not only in business applications but also in scientific inquiries. Approaches of Data Mining in Various Industries With data mining, a retail store may find that certain products are sold more in one channel of distribution than in the others, certain products are sold more in one geographical location than in others, and certain products are sold when a certain event occurs. With data mining, a financial analyst would like to know the characteristics of a successful prospective employee; credit card departments would like to know which potential customers are more likely to pay back the debt and when a credit card is swiped, which transaction is fraudulent and which one is legitimate; direct marketers would like to know which customers purchase which types of products; booksellers like Amazon would like to know which customers purchase which types of books (fiction, detective stories or any other kind) and so on. With this type of information available, decision makers will make better choices. Human resource people will hire the right individuals. Credit departments will target those prospectiv e customers that are less prone to become delinquent or less likely to involve in fraudulent activities. Direct marketers will target those customers that are likely to purchase their products. With the insight gained from data mining, businesses may wish to re-configure their product offering and emphasize specific features of a product. These are not the only uses of data mining. Police use this tool to determine when and where a crime is likely to occur, and what would be the nature of that crime. Organized stock changes detect fraudulent activities with data mining. Pharmaceutical companies mine data to predict the efficacy of compounds as well as to uncover new chemical entities that may be useful for a particular disease. The airline industry uses it to predict which flights are likely to be delayed (well before the flight is scheduled to depart). Weather analyst determine weather patterns with data mining to predict when there will be rain, sunshine, a hurricane, or snow. Bes ide that, nonprofit companies use data mining to predict the likelihood of individuals making a donation for a certain cause. The uses of data mining are far reaching and its benefits may be quite significant. Data Mining Tools and Techniques Data mining is the set of tools that learn the data obtained and then using the useful information for business forecasting. Data mining tools use and analyze the data that exist in databases, data marts, and data warehouse. A data mining tools can be categorized into four categories of tools which are prediction tools, classification tools, clustering analysis tools and association rules discovery. Below are the elobaration of data mining tools: Prediction Tools A prediction tool is a method that derived from traditional statistical forecasting for predicting a value of the variable. Classification Tools The classification tools are attempt to distinguish the differences between classes of objects or actions. Given the example is an advertiser may want to know which aspect of its promotion is most appealing to consumers. Is it a price, quality or reliability of a product? Or maybe it is a special feature that is missing on competitive products. This tools help give such information on all the products, making possible to use the advertising budget in a most effective manner. Clustering Analysis Tools This is very powerful tools for clustering products into groups that naturally fall together which are the groups are identified by the program. Most of the clusters discovered may not be useful in business decision. However, they may find one or two that are extremely important which the ones the company can take advantage of. The most common use is market segmentation which in this process, a company divides the customer base into segments dependent upon characteristics like income, wealth and so on. Each segment is then treated with different marketing approach. Association Rules Discovery This tool discover associations which are like what kinds of books certain groups of people read, what products certain groups of people purchase and so on. Businesses use such information in targeting their markets. For instance, recommends movies based on movies people have watched and rated in the past. There are four general phases in data mining which are data preparation, data analysis and classification, knowledge acquisition and prognosis. Data Preparation In the data preparation phase, the main data sets to be used by the data mining operation are identified and cleaned of any data impurities. Because the data in the data warehouse are already integrated and filtered, the data warehouse usually is the target set for data mining operations. Data Analysis The data anlysis and classification phase studies the data to identify common data characteristics or patterns. During this phase, the data mining tool applies specific algorithm to find: Data groupings, classifications, clusters, or sequences. Data dependencies, links, or relationships. Data patterns, trends, and deviations. Knowledge Acquisition The knowledge-acquisition phase uses the results of the data analysis and classification phase. During the knowledge-acquisition phase, the data mining tool (with possible intervention by the end user) selects the appropriate modeling or knowledge-acquisition algorithms. The most common algorithms used in data mining are based on neural networks, decision trees, rules induction, genetic algorithms, classification and regression trees, memory-based reasoning, and nearest neighbor and data visualization. A data mining tool may use many of these algorithms in any combination to generate a computer model that reflects the behavior of the target data set. Prognosis Although many data mining tools stop at the knowledge-acquisition phase, others continue to the prognosis phase. In that phase, the data mining findings are used to predict future behavior and forecast business outcomes. Examples of data mining findings can be: 65% of customers who did not use a particular credit card in the last six months are 88% likely to cancel that account. 82% of customers who bought a 27-inch or larger TV are 90% likely to buy an entertainment center within the next four weeks. If age < 30 and income < = 25,000 and credit rating 25,000, then the minimum loan term is ten years. The complete set of findings can be represented in a decision tree, a neural net, a forecasting model, or a visual presentation interface that is used to project future events or results. For example, the prognosis phase might project the likely outcome of a new product rollout or a new marketing promotion. The Benefit and Weaknesess of Data Warehouse to Organization Data warehouse is the one of powerful techniques that applies in organization in order to assist managerial decision making within a business. This methodology becomes a crucial asset in modern business enterprise. It is designed to extract information from data and to use such information as a basis for decision making. The organization will get more benefit with application of data warehouse because the features of data warehouse itself is its a central repositories that stores historical information, meaning say that eventhough the data come from differ location and various points in time but all the relevant data are assembled in one location and was organized in efficient manner. Indirectly, it makes a profit to company because it greatly reduces the computing cost. One of the advantage of using data warehouse is it allows the accessible of large volume information whereas the information will be used in problem solving that arise in business organization. All the data that are from multiple sources that located in central repository will be analyze in order to allow them come out with a choice of solutions. However there are also having weaknesses that need to concern as well. The processes of data warehouse actually take a long period of time bacause before all the data can be stored into warehouse, they need to cleaned, extracted and loaded. The process of maintaining the data is one of the problems in data warehouse because it is not easy to handle. The compatibility may be the isssued in order to implement the data warehouse in organization because the new transaction system that tried to implement may not work with the system that already used. Beside that, the user that works with the system must be trained to use the system because without having a proper training may cause a problem. Furthermore, if the data warehouse can be accessed via the internet, the security problem might be the issue. The biggest problem that related with the data warehouse is the costs that must taken into consideration especially for their maintenance. Any organization that is considering using a data w arehouse must decide if the benefits outweigh the costs. Conclusion Successfully supporting managerial decision-making is significantly dependent upon the availability of integrated, high quality information organized and presented in a timely and in simply way to understand. Data mining and data warehouse have emerged to meet this need. The application of data mining and data warehouse will be apart of crucial element in organization in order to assist the managerial running the operation smoothly and at the same time will help them to accomplish the business goal. It is because both of these techniques are the foundation of decision support system. Today data mining and data warehouse are an important tools and more companies will begin using them in the future. REFERENCES Bonifati, A., Cattaneo, F., Ceri, F., Fuggetta, A., and Paraboschi, S., (2001). Designing data marts for data warehouse. ACM Transactions On Software Engineering And Methodology, 10, 452-483. Retrieved February 15, 2010 from: http://www.emeraldinsight.com.ezaccess.library.uitm.edu.my/Insight/viewPDF.jsp?contentType=ArticleFilename=html/Output/Published/EmeraldAbstractOnlyArticle/Pdf/2810110103.pdf Chaplot, P., (2007). An introduction to data warehousing. Retrieved February 14, 2010 from: http://www.emeraldinsight.com.ezaccess.library.uitm.edu.my/Insight/viewPDF.jsp?contentType=ArticleFilename=html/Output/Published/EmeraldFullTextArticle/Pdf/0291000304.pdf Roiger, R.,J., (2005). Teaching an introductory course in data mining. Retrieved February 13, 2010 from: http://delivery.acm.org/10.1145/1070000/1067620/p415-roiger.pdf?key1=1067620key2=7107846621coll=ACMdl=ACMCFID=76668031CFTOKEN=26856088 Santos, R., J., and Bernandino, J. Real-time data warehouse loading methodology. Retrieved February 13, 2010 from: http://www.emeraldinsight.com.ezaccess.library.uitm.edu.my/Insight/viewPDF.jsp?contentType=ArticleFilename=html/Output/Published/EmeraldFullTextArticle/Pdf/0291010105.pdf Chowdhury, S., Chan, J.,O., (2007). Data warehousing and data mining: a course in mba and msis program from uses perspective. Data Warehousing And Data Mining. 7. Retrieved February 15, 2010 from: http://www.emeraldinsight.com.ezaccess.library.uitm.edu.my/Insight/viewPDF.jsp?contentType=ArticleFilename=html/Output/Published/EmeraldFullTextArticle/Pdf/1640150202.pdf Ranjan, J., Malik, K., (2007). Effective educational process: a data mining approach. The Journal Of Information And Knowledge Management Systems. 37, 502-515. Retrieved February 16, 2010 from: http://www.emeraldinsight.com.ezaccess.library.uitm.edu.my/Insight/viewPDF.jsp?contentType=ArticleFilename=html/Output/Published/EmeraldFullText Mora, S., L., Trujillo, J., Song, I, Y., (2006). A uml profile for multidimensional modeling in data warehouses. Data Knowledge Engineering. 59, 725-769. Retrieved February 20, 2010 from: http://www.sciencedirect.com.ezaccess.library.uitm.edu.my/science?_ob=MImg_imagekey March, S., T., Hevner, A., R., (2005). Integrated decision support systems: a data warehousing perspective. Retrieved February 21, 2010 from: http://delivery.acm.org/10.1145/1460000/1451949/p49santos.pdf?key1=1451949key2=1956846621coll=ACMdl=ACMCFID

Saturday, January 18, 2020

Comparing Schools Essay

This report provides advice on the collection and reporting of information about the performances of Australian schools. The focus is on the collection of nationally comparable data. Two purposes are envisaged: use by education authorities and governments to monitor school performances and, in particular, to identify schools that are performing unusually well or unusually poorly given their circumstances; and use by parents/caregivers and the public to make informed judgements about, and meaningful comparisons of, schools and their offerings. Our advice is based on a review of recent Australian and international research and experience in reporting on the performances of schools. This is an area of educational practice in which there have been many recent developments, much debate and a growing body of relevant research. Our work is framed by recent agreements of the Council of Australian Governments (COAG), in particular, at its meeting on 29 November 2008: C OAG agreed that the new Australian Curriculum, Assessment and Reporting Authority will be supplied with the information necessary to enable it to publish relevant, nationally-comparable information on all schools to support accountability, school evaluation, collaborative policy development and resource allocation. The Authority will provide the public with information on each school in Australia that includes data on each school’s performance, including national testing results and school attainment rates, the indicators relevant to the needs of the student population and the school’s capacity including the numbers and qualifications of its teaching staff and its resources. The publication of this information will allow comparison of like schools (that is, schools with similar student populations across the nation) and comparison of a school with other schools in their local community. (COAG Meeting Outcomes) Our work also has been framed by the recently endorsed MCEETYA Principles for Reporting Information on Schooling (see Section 1. 4). Before summarising our specific recommendations, there are some general conclusions that we have reached from our review of international research and experience. The specific recommendations that follow are best understood in the context of these general conclusions: †¢ Vigilance is required to ensure that nationally comparable data on individual schools does not have the unintended consequence of focusing attention on some aspects of the purposes of schooling at the expense of other outcomes that are as important but not as easily measurable. Parents/caregivers and the public are interested in a broad range of information about schools, and nationally comparable data should be reported in the context of this broader information. †¢ Although it has become popular in education systems in some other parts of the world to use statistical models to develop ‘measures’ of school performance and to report these measures publicly in league tables, we believe that there are very v Reporting and Comparing School Performances  sound technical and educational reasons why school measures of this kind should not be used for public reporting and school comparisons. †¢ Related to this point, we are not convinced of the value of reporting ‘adjusted’ measures of student outcomes publicly. Measures of student outcomes should be reported without adjustment. †¢ To enable the comparison of unadjusted student outcomes across schools, we believe that a ‘like-schools’ methodology should be used. This methodology would allow parents/caregivers, the public, and education systems to compare outcomes for schools in similar circumstances. †¢ While point-in-time measures of student outcomes often are useful, it is difficult to establish the contributions that teachers and schools make to point-in-time outcomes. In general, measures of student gain/growth across the years of school provide a more useful basis for making judgements about the value that schools are adding. †¢ Measures of gain/growth are most appropriately based on measurement scales that can be used to monitor student progress across the years of school. The NAPLAN measurement scales are an example and provide educational data superior to that available in most other countries. Consideration should be given to developing national measurement scales for early literacy learning and in some subjects of the national curriculum. †¢ Initially reporting should build on the understandings that parents and the public have already developed. For example a school’s NAPLAN results should be reported in forms that are consistent with current NAPLAN reports for students. Although much work needs to be done in defining the most appropriate measures, the principle should be to build on the representations of data that are already familiar to people. Recommendations Our report makes the following specific recommendations: student outcome measures †¢ Nationally comparable data should be collected on the literacy and numeracy skills of students in each school, using NAPLAN (Years 3, 5, 7 and 9). †¢ Nationally comparable data should be collected on the tertiary entrance results of students in each senior secondary school. These data could be reported as the percentage of students achieving tertiary entrance ranks of 60 or above, 70 or above, 80 or above, and 90 or above (calculated as a percentage of the students achieving tertiary entrance ranks). †¢ Nationally comparable data should be collected on the percentage of students in each senior secondary school completing Year 12 or equivalent; the percentage of students applying to all forms of post-school education; and the percentage of students completing VET studies. vi Reporting and Comparing School Performances †¢ Nationally comparable data should be collected on the achievements of students in core national curriculum subjects (English, mathematics, science and history), beginning in 2010. National assessments could be developed initially at Year 10. †¢ Nationally comparable data should be collected on the early literacy learning of children in each primary school. These assessments will need to be developed and should be administered upon entry to school and used as a baseline for monitoring progress across the first few years of school. physical and human resources †¢ Nationally comparable data should be collected about sources and amounts of funding received by each school, including all income to the school from State and Commonwealth governments, as well as details of fees payable by parents, including those that are mandatory and any voluntary levies that parents are expected to pay. †¢ Nationally comparable data should be collected on the numbers and qualifications of teaching staff in each school. Basic data would include academic qualifications, details of pre-service teacher education, and details of any advanced certification (eg, Advanced Skills Teacher; Level 3 Teacher). student intake characteristics †¢ Nationally comparable data should be collected on the socio-economic backgrounds of students in each school. Data should be based on information collected at the individual student level, using at least parental occupation and, possibly, parental education levels, under the agreed MCEETYA definitions. †¢ Nationally comparable data should be collected on the percentage of students in each school of Aboriginal and/or Torres Strait Islander background under the agreed MCEETYA definition. †¢ Nationally comparable data should be collected on the percentage of students in each school identified as having a language background other than English (LBOTE) under the agreed MCEETYA definition. †¢ Nationally comparable data should be collected on the geo-location of each school using a 3-category scale: metropolitan, provincial, and remote. †¢ Nationally comparable data should be collected on the percentage of students in each school with special educational needs. A nationally agreed definition of this category will need to be developed. like-school comparisons †¢ In reporting student outcome data for a school, data for like-schools should be provided as a point of comparison. Like-schools will be schools in similar circumstances and facing similar challenges. †¢ In determining ‘like-schools’, account should be taken of the percentage of students with Indigenous backgrounds, the socio-economic backgrounds of the students in the school, and the percentage of students from language backgrounds other than English. vii Reporting and Comparing School Performances †¢ For each school separately, like-schools should be identified as the schools most similar to that school on the above characteristics (rather than pre-defining a limited number of like-school categories). †¢ Work should commence as soon as possible on the development of an appropriate like-schools methodology. public reporting †¢ For the purpose of providing public information about schools, a common national website should be used to provide parents/caregivers and the public with access to rich information about individual schools. †¢ The national website should provide information about each school’s programs, philosophies, values and purposes, provided by the school itself, as well as nationally comparable data, provided centrally. †¢ Nationally comparable student outcome data should, wherever possible, provide information about current levels of attainment (ie, status), gain/growth across the years of school, and improvement in a school over time. †¢ The complete database for each state/territory should be made available to the relevant state/territory departments of education and other employing authorities, enabling them to interrogate data for their schools and to make judgments about school performances using aggregated data and national summary statistics. We believe that almost all nationally comparable data collected centrally could be reported publicly. The exceptions would arise when the public reporting of data may have negative and unintended consequences for schools. For example, we can envisage negative consequences arising from the reporting of the socio-economic backgrounds of students in a school, or of the financial circumstances of struggling, small schools (both government and non-government). We also believe that data reported publicly should be factual data about a school, and not the results of secondary analyses and interpretations that are open to debate (eg, value-added measures). viii Reporting and Comparing School Performances 1. INTRODUCTION In education, good decision making is facilitated by access to relevant, reliable and timely information. Dependable information is required at all levels of educational decision making to identify areas of deficiency and special need, to monitor progress towards goals, to evaluate the effectiveness of special interventions and initiatives, and to make decisions in the best interests of individual learners. The focus of this  paper is on the provision and use of information about individual schools. The starting point is the observation that relevant and reliable information about schools is required by a range of decision makers – including parents and caregivers, school principals and school leadership teams, system managers and governments, and the general public – all of whom require dependable information that they can use to maximise opportunities and outcomes for students. 1. 1 Audiences and Purposes  Parents and caregivers require valid and reliable information to evaluate the quality of the education their children are receiving, to make informed decisions in the best interests of individual students, and to become active partners in their children’s learning. They require dependable information about the progress individuals have made (the knowledge, skills and understandings developed through instruction), about teachers’ plans for future learning, and about what they can do to assist. There is also considerable evidence that parents and caregivers want information about how their children are performing in comparison with other children of the same age. And, if they are to make judgements about the quality of the education their children are receiving, they require information that enables meaningful comparisons across schools. School leaders require reliable information on student and school performances for effective school management. Research into factors underpinning school  effectiveness highlights the importance of the school leader’s role in establishing an environment in which student learning is accorded a central focus, and goals for improved performance are developed collaboratively by staff with a commitment to achieving them. School managers require dependable pictures of how well students in a school are performing, both with respect to school goals for improvement and with respect to past achievements and achievements in other, comparable schools. Governments and system managers require dependable information on the performance and progress of individual schools if they are to exercise their responsibilities for the delivery of quality education to all students. Effective management depends on an ability to monitor system-wide and school performances over time, to gauge the effectiveness of special programs and targeted resource allocations, to monitor the impact of policies, and to evaluate the success of initiatives aimed at traditionally disadvantaged and underachieving sections of the student population. Accurate, reliable information allows system managers to measure progress against past performances, to identify schools and issues requiring special attention, to target resources appropriately, and to set goals for future improvement. 1 Reporting and Comparing School Performances 1. 2 Forms of Information Because there are multiple audiences and purposes for information about schools, the forms of information required for effective decision making are different for different stakeholders. Parents and caregivers require a wide range of information, including information relating to their immediate needs (eg, Is the school easily accessible by public transport? Does it have an after-school program? What fees and/or levies does it charge? ); the ethos of the school (eg, What evidence is there of bullying/harassment? What are the espoused values of the school? Do students wear uniforms? What level of discipline is imposed? Who is the principal? ); their child’s likely educational experience (eg, Who will be my child’s teacher next year? Will they be in a composite class? How large will the class be? Does the school have a literacy intervention program? What extra-curricular activities are provided? ); and the school’s educational results (eg, Does the school achieve outstanding Year 12 results? ). School leaders require other forms of information, including information relating to staffing and resources (eg, What resources are available for music next year? How many beginning children have special learning needs? ); the effectiveness of initiatives (eg, Is there any evidence that the extra class time allocated to literacy this year made a difference?); and academic results (eg, How many Year 5 students did not meet the minimum performance standard in Reading? Have our results improved since last year? Are we still below the state average? How did last year’s Year 12 results compare with those of the neighbouring school? ). System managers and governments require still other forms of information, including information to monitor system-wide trends over time, to evaluate the effectiveness of attempts to raise standards and close gaps, and to identify schools that are performing unusually well or unusually poorly given their circumstances. In general, the schoollevel information required by system managers and governments is less fine-grained than the information required by parents, teachers and school leaders. Figure 1 displays schematically various forms of information that could be made available about a school, either publicly or to specific audiences (eg, system managers). The forms of evidence represented in Figure 1 are: A: student outcome measures that a school could choose to report Most schools report a wide range of information about the achievements of their students to their school communities. This information is reported in school newsletters, local and community newspapers, school websites, and at school events. The information includes details of Year 12 results, analyses of postschool destinations, results in national mathematics and science competitions, language certificates, awards, prizes, extra-curricular achievements, community recognition, and so on. Most schools take every opportunity to celebrate the achievements of their students and to announce these achievements publicly. 2 Reporting and Comparing School Performances Figure 1. Forms of information that could be made available about a school B:a sub-set of student outcome measures on which it is agreed to collect nationally comparable data Within the set of student outcome information that might be reported for a school, there could be a sub-set of outcomes on which it was agreed to collect nationally comparable data. A reason for identifying such a sub-set would be to ensure some common measures to facilitate school comparisons – within a local geographical area, across an entire education system, nationally, or within a group of ‘like’ schools. Inevitably, nationally comparable data would be collected for only some of the outcomes that schools, parents and communities value. Performances on common literacy and numeracy tests in Years 3, 5, 7 and 9 are an example of nationally comparable data currently in this category. C. physical and human resources measures that a school could choose to report Schools provide information in various forms and to various audiences about their physical and human resources. Information of this kind includes details of staff qualifications and teaching experience, staff turnover rates, school global budgets, computers and other technology, newly constructed facilities, bequests, results of fundraising drives, and so on. Some of this information may be reported to the school community; some may be kept confidential to the school, education system or government departments. D: a sub-set of physical and human resources measures on which it is agreed to collect nationally comparable data Within the set of physical and human resources measures reported for a school, there could be a sub-set of measures on which it was agreed to collect nationally comparable data. For example, there have been recent calls for greater consistency and transparency in the reporting of school funding arrangements (Dowling, 2007; 2008) and for more consistent national approaches to assessing and recognising teacher quality (Dinham, et al, 2008). 3 Reporting and Comparing School Performances E. student intake measures that a school could choose to report Most schools have considerable information about their students. For example, they may have information about students’ language backgrounds, Indigenous status, socio-economic backgrounds, learning difficulties and disabilities. This information usually is reported only within education systems or to governments and is not reported publicly, although schools sometimes provide information to their communities about the range of languages spoken by students in the school, the countries from which they come, the percentage of Indigenous students in the school and the school’s special Indigenous programs, or the number of severely disabled students and the facilities and support provided for these students. F: a sub-set of student intake measures on which it is agreed to collect nationally comparable data. Within the set of student intake characteristics reported for a school, there could be a sub-set of measures on which it was agreed to collect nationally comparable data. Some progress has been made toward nationally consistent definitions and nationally consistent data collections on student background characteristics. G. all other information that a school could choose to make available Beyond information about student outcomes, student backgrounds and their physical and human resources, schools provide a range of other information to the communities they serve. 1. 3 Nationally Comparable Data Acknowledging the many purposes and audiences for information about schools, and the various forms that this information can take, the specific focus of this paper is on the collection and reporting of nationally comparable data for the purposes of evaluating and comparing school performances. In other words, the focus is on categories B, D and F in Figure 1. We envisage three broad uses of such data: †¢ use by parents and caregivers in judging the quality of educational provision and in making informed decisions in the best interests of individual students; †¢ use by school leaders in monitoring a school’s improvement and benchmarking the school’s performance against other, comparable schools; and †¢ use by education systems and governments in identifying schools that are performing unusually well or unusually poorly given their circumstances. As noted above, these three stakeholder groups are likely to have different needs. The ways in which nationally comparable data are analysed, combined and reported may be different for different purposes. We see the process of reaching agreement on the core data that should be available about a school as a national collaborative process, and see little value in arriving at different conclusions about these data for different parts of the country. 4 Reporting and Comparing School Performances 1. 4 Principles for Reporting The Principles for Reporting Information on Schooling (see pages 6-7) adopted by the Ministerial Council for Education, Employment, Training and Youth Affairs (MCCETYA) provide an important point of reference for any proposed collection and use of nationally comparable data on schools. These principles recognise the multiple audiences and purposes for information about schools, the need to collect broad evidence about student and school performances, and the desirability of monitoring intended and unintended consequences of reporting information on schools. Australian governments have undertaken to ensure that data provided for the purposes of comparing schools are reliable and fair and take into account the contexts in which schools work. Governments also have undertaken not to develop simplistic league tables of school performances. 1. 5 Structure of Paper This paper first considers the kinds of nationally comparable data that might be collected about schools for the purposes outlined above. We draw on national and international research and experience, attempt to anticipate the likely requirements of different audiences, and take into account what measures currently exist and what additional measures might be desirable in the future. Each of the three data categories in Figure 1 is considered in turn: †¢ †¢ †¢ student outcome measures physical and human resources measures student intake measures (sections 2-3) (section 4) (section 5) We then consider alternative ways of evaluating and comparing school performances. Two broad methodologies are discussed: †¢ †¢ the direct comparison of student outcomes the construction of measures of school performance (section 6) (section 7) Finally, we consider issues in reporting publicly on the performances of schools: †¢ †¢ audiences and purposes for reporting options for public reporting on schools (section 8) (section 9) 5 Reporting and Comparing School Performances MCEETYA PRINCIPLES FOR REPORTING INFORMATION ON SCHOOLING There is a vast amount of information on Australian schooling and individual schools. This includes information about the educational approach of schools, their enrolment profile, staffing, facilities and programs, and the education environment they offer, as well as information on the performance of students, schools and systems. Different groups, including schools and their students, parents and families, the community and governments, have different information needs. The following principles provide guidance on requirements for information on schooling, including the types of information that should be made readily available to each of the groups noted above. These principles will be supported by an agreed set of national protocols on the access to and use of information on schooling. Good quality information on schooling is important: FOR SCHOOLS AND THEIR STUDENTS. Principle 1: Schools need reliable, rich data on the performance of their students because they have the primary accountability for improving student outcomes. Good quality data supports each school to improve outcomes for all of their students. It supports effective diagnosis of student progress and the design of quality learning programs. It also informs schools’ approaches to provision of programs, school policies, pursuit and allocation of resources, relationships with parents and partnerships with community and business. Schools should have access to: †¢ Comprehensive data on the performance of their own students that uses a broad set of indicators †¢ Data that enables each school to compare its own performance against all schools and with schools of similar characteristics †¢ Data demonstrating improvements of the school over time †¢ Data enabling the school to benchmark its own performance against that of the bestperforming schools in their jurisdiction and nationally FOR PARENTS AND FAMILIES. Principle 2: Information about schooling, including data on the performance of individuals, schools and systems, helps parents and families to make informed choices and to engage with their children’s education and the school community. Parents and families should have access to: †¢ Information about the philosophy and educational approach of schools, and their staffing, facilities, programs and extra-curricular activities that enables parents and families to compare the education environment offered by schools †¢ Information about a school’s enrolment profile, taking care not to use data on student 1  characteristics in a way that may stigmatise schools or undermine social inclusion. †¢ Data on student outcomes that enables them to monitor the individual performance of their child, including what their child knows and is able to do and how this relates to what is expected for their age group, and how they can contribute to their child’s progress †¢ Information that allows them to assess a school’s performance overall and in improving student outcomes, including in relation to other schools with similar characteristics in their jurisdiction and nationally. 1 Any use or publication of information relating to a school’s enrolment profile should ensure that the privacy of individual students is protected. For example, where the small size of a school population or of a specific student cohort may enable identification of individual students, publication of this information should be avoided. 6 Reporting and Comparing School Performances FOR THE COMMUNITY. Principle 3: The community should have access to information that enables an understanding of the decisions taken by governments and the status and performance of schooling in Australia, to ensure schools are accountable for the results they achieve with the public funding they receive, and governments are accountable for the decisions they take. Students are an important part of our society and take up a variety of roles within it after leaving school. The community is therefore a direct and indirect consumer of the product of our schools, as well as providing the means of public funding. Information about schools in the public domain fulfils the requirement that schools be accountable for the results they achieve with the public funding they receive, including relative to other ‘like’ schools; it should also give the community a broad picture of school performance and a sense of confidence in our school systems. The community should have access to: †¢ Information about the philosophy and educational approach of schools, and their staffing, facilities, programs and extra-curricular activities that enables the community to compare the education environment offered by schools. †¢ Information about individual schools’ enrolment profile, taking care not to use data on student characteristics in a way that may stigmatise schools or undermine social inclusion †¢ National reporting on the performance of all schools with data that allows them to view a school’s performance overall and in improving student outcomes, including in relation to other schools with similar characteristics RESPONSIBLE PROVISION OF SCHOOLING INFORMATION Australian Governments will ensure that school-based information is published responsibly so that: †¢ any public comparisons of schools will be fair, contain accurate and verified data, contextual information and a range of indicators to provide a more reliable and complete view of performance (for example, information on income, student body characteristics, the spread of student outcomes and information on the value added by schools) †¢ governments will not devise simplistic league tables or rankings and will put in place strategies to manage the risk that third parties may seek to produce such tables or rankings, and will ensure that privacy will be protected. †¢ reports providing information on schooling for parents and families and the community will be developed based on research on what these groups want to know and the most effective ways the information can be presented and communicated. FOR GOVERNMENTS Principle 4: Governments need sound information on school performance to support ongoing improvement for students, schools and systems. Government also need to monitor and evaluate the impacts (intended and unintended) of the use and release of this information to improve its application over time. Good quality information on schooling enables governments to: †¢ analyse how well schools are performing †¢ identify schools with particular needs †¢ determine where resources are most needed to lift attainment †¢ identify best practice and innovation in high-performing schools that can be mainstreamed and used to support improvements in schools with poorer performance †¢ conduct national and international comparisons of approaches and performance †¢ develop a substantive evidence base on what works. This will enable future improvements in school performance that support the achievement of the agreed education outcomes of both the Ministerial Council for Education, Employment, Training and Youth Affairs and the Council of Australian Governments. 7 Reporting and Comparing School Performances 2. STUDENT OUTCOMES Information about the outcomes of a school’s efforts is key information for parents and caregivers if they are to judge the quality of educational provision; for school leaders to monitor a school’s performance and improvement; and for education systems and governments to identify schools in need of additional support. However, schools work to promote many different kinds of outcomes for their students. For some schools, an important objective is to improve school attendance rates. For others, assisting students to make successful transitions into the workforce is a high priority. Some schools are more focused than others on supporting the social, spiritual and emotional development of students. Still others measure their success in terms of entry rates into highly sought-after university courses. Decisions about the outcomes to be reported publicly for schools are important because they influence judgements about how well individual schools are performing. This is particularly true when education systems and governments attempt to construct ‘measures’ of school performance: Perverse incentives can arise when the [school] performance measure has both a large impact upon actors and focuses on an aspect of schooling that does not reflect the true or overall purpose and objectives of schools. Unfortunately, this can be common in school performance measures if the performance measure is too narrowly defined. (OECD, 2008, 26).

Friday, January 10, 2020

Virgin Atlantic Case Study

Atlantics primary problem is that they were operating in the middle of the optimal utility model. Their slogan had become â€Å"Offering a First Class service at less than First Class fares†. In which Virgin Atlantic Is offering high quality at a low cost, which keeps them In the middle and not profitable. It seems that Virgin Atlantic did not take Into account that offering a premium service as they were would come at a premium cost for them and when throwing In low cost fares Into the mix they were reading a loss and expectations they will not be able to sustain for a long time.Starting off as a low cost premium airline aimed towards the business class may have been there way into the market and obtain market share but at some point they needed to work their way out of the middle of the optimal utility model and shift either towards high quality or low cost, not both simultaneously to stay profitable. Seeing that there number one goal was to provide premium innovative servic es/ products they could have gone the route that Apple Inc. As done by providing innovative premium products at a premium prices rather than setting themselves up for future losses.A recommendation for Virgin Atlantics primary problem of operating In the middle of the optimal utility model, In which consumers want either high quality or low cost products and services. Virgin should keep moving forward with innovation and providing a premium experience for all of their passengers but do it at a higher price so that they do not create any losses. Another route to go in would be to become a upper low cost provider for their business class niche and stop spending on infilling entertainment and amenities and focus only on cutting costs which would allow them to be profitable as a low cost air transportation provider.Another secondary problem is that during Virgin Atlantics pursuit to be innovative, top management neglected to make innovations that would help the company in terms of lower ing costs and Increasing profit. They only focused on innovations that benefited the consumers and not any self-interest. For example when Virgin Alertness management team decided that they did not want passengers to feel bored, they came up with innovative ways to keep them entertained during their flights such as pioneering individual video screens for every seat.But innovations like that did not help them cut any costs or increase fares significantly enough to increase profits or reduce costs. A recommendation in regards to creating innovations to help reduce costs and increase profits would be for Virgin Atlantic Airways to partner with small shipping impasses who could buy cargo space on Virgin Atlantic flights that are not at full capacity, so that they can generate more revenue on flights that are not traveling full of passengers.Another Innovative Idea would be to use the Individual video screens that they pioneered as ad space in the Mid and Economy class section of their p lanes. By doing so Vulgar Atlantic would be able generate additional revenues by selling ad space to advertisers, which would allow them to lower their cost per route,