Financial Statements Analysis Research Paper Example | Topics and Well Written Essays - 1000 words

Financial Statements Analysis - Research Paper Example Financial ratios enable to understand operating performance and financial condition of the company through profitability ratio, liquidity ratio, activity ratio, financial leverage ratio, and shareholders’ ratio. This assignment conducts a financial ratio analysis of two companies of Airline Industry; they are Lufthansa Airline (LH), and Emirates Airlines (EK). Financial ratios are evaluated using information from the income statement and balance sheet. These two documents are obtained from the websites (â€Å"Lufthansa Annual Report 2013†,n.d; â€Å"The Emirates Group Annual Report 2012-2013†). Financial ratios are evaluated for the years 2012, and 2013. Liquidity ratio measures short-term solvency – the ability of the company to meet its debt obligation. It is expressed through the financial ratios, such as Current ratio (CR) = Current assets / Current liabilities, and Quick ratio (QR) = (Cash + Marketable Securities + Receivables) / Current liabilities. It is expected that a company current assets will be higher than the current liability. The values of current ratios in Table 1 shows that Lufthansa can somehow cover its current obligation while Emirates has about 3 times current assets to cover its current liabilities. The quick ratio values show that LH is less liquid than EK; can only manage to repay less than 50% of its current liability using cash and cash equivalents. The industry average quick ratio is 0.4 (â€Å"Airline Industry†, n.d.); it shows that LH is on the line with the industry while EK is in a better position than most companies in the industry These ratios belong to the efficiency category; it shows how efficiently a company is using its assets. This assignment uses Inventory turnover (IT) = Cost of goods sold (COGS) / Inventory, Fixed asset turnover = Revenue / Fixed assets, Assets turnover = Revenue / Total asset, and Day’s sales outstanding (DSO) = 365 / Receivable turnover = 365 / (Revenue / Receivable) to

Truth in the Legality of Income Taxes Essay Example for Free

Truth in the Legality of Income Taxes Essay On April 15 Americans rush to a crowded parking lot, racing against a deadline to file their 1040. These well-intentioned, hard working, honorable Americans believe that they are duty bound and even bound by a law requiring them to pay an income tax on their labor. Also, there exists a populous with like-attributes who do not believe that they are bound by law nor is the payment of such taxes a duty but rather a disservice to the nation. This controversial issue first gained my interest about 1 year ago, when it was brought to my attention in a free speech tax debate. As a well seasoned tax professional of 4  ½ years, and my major concentration of studies being in accounting and taxation, I was compelled to find out the truth about the legality of income tax. After much research, I have not been able to find the law that requires the American people to pay such a tax on their labor nor have I been able to find a provision for such a tax in either the Internal Revenue Code or the United States Constitution. If there is such a law, requiring Americans to pay an income tax on their labor, the United States government should show the people that law.   Ã‚  Ã‚  Ã‚   In order to understand the legality of taxes, we must first refer to both the constitutional provisions for taxes levied and the constitutional context of the terminology used in such provisions. â€Å"On every question of the construction of the Constitution, let us carry ourselves back to the time when the Constitution was adopted, recollect the spirit manifested in the debates, and instead of trying what meaning may be squeezed out of the text, or invented against it, conform to the probable one in which it was passed.† –Thomas Jefferson, Letter to William Johnson, Supreme Court Justice, 1823 While observing the taxation clauses of the United States Constitution, two types of tax can be determined, a direct tax and an indirect tax. Although, the term â€Å"indirect tax† does not actually appear in the Constitution, its meaning is implied here as â€Å"any tax that is not a direct tax.† A direct tax is a tax that cannot be avoided nor passed on, if it is owed. The Constitution specifically states for the case of a direct tax, that it must be apportioned among the several states according to their population. An example of a direct tax in which the government may levy, is tax on land due to ownership, simply because the land exists. Meaning that regardless of what the land is used for or who owns it, the tax is on the land and the owner of the land is liable for the tax due.   (Constitutional Income: Do You Have Any?) Meaning of Income Although there are sections that mention the term â€Å"income†, term itself is not properly defined in the Internal Revenue Code. There is not clear cut definition with regards to this term. In the Internal Revenue Code’s Section 61a, the term â€Å"income† is vaguely implied. An example of this would be income as defined by IRS agents as (not even) earnings â€Å"from whatever source derived.   Ã‚  Ã‚  Ã‚  Ã‚   The Supreme Court, however, has come up with a legal definition of income for the purposes of taxation. The Supreme Court    does not consider tax as something levied on a person’s earnings through his personal labor. Here are some cases to show an example. SO. PACIFIC v. LOWE, 238 F. 847 (U.S. Dist. Ct.   S.D. N.Y. [1917]; 247 U.S. 330 [1918]cite that   income as used in the statute should be given a meaning so as not to include everything that comes in. The true function of the words gains andprofits is to limit the meaning of the word income†. The case of Staples v. U.S., 21 F Supp 737 U.S. Dist. Ct. ED PA, 1937 likewise has a similar take on the term.   â€Å"Income within the meaning of the 16th Amendment and the Revenue Act, means gain and in such connection gain means profit proceeding from property severed from capital, however invested or employed, and coming in, received, or drawn by the taxpayer, for his separate use, benefit and disposal.   (Legal Minds Community) The Grace Commission Peter Grace and Jack Anderson formed the Grace Commission in 1982. This was a rejoinder to then President Reagan’s PRESIDENTS PRIVATE SECTOR SURVEY ON COST CONTROL.   The Grace Commission made recommendations that would save the taxpayers $424.4 billion over three years. The suggestions made did not compromise essential services or raising taxes. The Grace Commission also accurately predicted the accumulation of multi-trillion dollar government debt by 2000 if the government would do nothing to remedy the present situation.   (Truth in Taxation.US) Furthermore, the Grace Commission revealed that tax collection is not a hundred percent. Only one-third of the total collectibles is collected and the remaining two-thirds is either wasted or not collected. The total amount collected goes to the payment of federal debt. The payment of wage taxes supports global banking but does benefit neither Americans nor the government in any way. In short, the payment of wage taxes goes to nowhere near providing benefits to the American people.   (Truth in Taxation.US) The declaration of Independence defined labor as â€Å"property of the most sacred kind†.   Labor is among the unalienable rights. These include â€Å"the right of men to pursue their happiness, by which is meant, the right any lawful business or vocation, in any manner not inconsistent with the equal rights of others, which may increase their prosperity or develop their faculties, so as to give them their highest enjoyment†.   (Paul) That said collecting income taxes on an individual’s gains from his personal labor is illegal. Works Cited Constitutional Income: Do You Have Any? 2004. 25 October 2007 http://www.constitutionalincome.com/first_chapter.php. Legal Minds Community. The 16th explained. 17 January 1998. 25 October 2007 http://legalminds.lp.findlaw.com/list/fedtax-l/msg01860.html. Paul, Ron. Cases on Income. 2007. 25 October 2007 http://irwinschiff.homestead.com/CasesOnIncome.html. Truth in Taxation.US. Where Do Your Taxes Go? 2003. 25 October 2007 http://truthintaxation.us/?tax_inform=whereTaxesGo.

Programming for BIG Data Project

Programming for BIG Data Project Liliam Faraon Nowadays, the amount of data generated and stored without an operation has exceeded a data analysis capability without the use of automated analysis techniques. The exponential growth of data is greater than it has ever been seen, extracting useful information from all the data generated and transform it into understandable and usable information is the challenge. There is where data mining assumes an important role, plenty of tools are available for data mining tasks using artificial intelligence, algorithms, machine learning and many others. In the present work two datasets were analysed, one with R and the other one Python. All the analysis was based in the CRISP-DM basic concepts: Business Understanding, Data Understanding, Data Preparation, Modelling, Evaluation and Deployment. The full methodology was not applied in the project, but understanding parts of its process was fundamental, the steps are pretty straight forward and give a very good idea of every stage that data mining has to go through and the feedback brought from every stage. The project scope is limited to identifying patterns in the data rather than predicting future, which could be examined as part of further study of the subject matter. The present Project was divided into two different parts: Part 1: R Dataset Analysis and Part 2: Python Dataset Analysis. It contains also a brief contextualization about the Big Data Context and the importance of data mining. We live in a time when the pursuit of knowledge is indispensable. Today, information assumes a growing importance, and a necessity for any sector of human activity, due to the many transformations we are witnessing. At every moment, we are facing new concepts and trends and we are amazed at how quickly they are occurring and affecting our lives, such as the technology that influences all sectors, social environments and touches every business and life on the planet. The article written by Bernard Marr, and published by Forbes last year brings some statistics that convince that big data really needs attention: More data has been created in the past two year than in the entire history of human race; By 2020 around 1.7 megabytes of new information will be generated every second for every human being on the planet. Every second we create new data, a good example: only on Google 40.000 searches and queries are generated every second, which makes the huge amount of 1.2 trillion searches a year. Facebook users send on average 31.25 million messages and view 2.77 million videos every minute. Only in 2015, 1 trillion photos were taken and billions of them were shared on line. In 2015, over 1.4 billion smart phones were shipped, all capable of collecting different sorts of data and by 2020 the world will have over 6.1 billion smartphone users globally. Within five years there will be over 50 billion smart connected devices worldwide, all developed to collect, analyse and share data. Retailers that leverage the full power of big data would be able to increase their operating by as much as 60%. Now, only less than 0.5% of data is analysed. All the Big Data generated, have some characteristics: Rapid increasing volume, variety, velocity and data storage and transfer, gathering and analysing it all became a huge challenge, but by using specific programs designed to analyse the information on algorithms based will overcome the challenges and the output can be used to enable the decision-making process. For the R Project, a very specific database was analysed: Tourists Visiting the South of Brazil, The information was obtained in the Government website, in the Tourism division. 1.1 Business Understanding Tourism is an important sector that has an impact on development of nation economy. For many countries, the tourism is the most important source of income and jobs generation. Brazil is the fifth biggest country in the world with 8,511,965 sq km of area and the nation is divided into 5 regions: North, Northeast, Central-West, Southeast and South Regions. The Best in Travel 2014, by Lonely Planet guide classified Brazil as the best tourist destination in 2014. According to the official Brazilian Tourism Website Around 6 million people visit the country every year, it is considered the main touristic market in South America and the second in Latin America. It is estimated that only around 17% of all tourists visiting Brazil go to the South region, composed by three States: Parana, Rio Grande do Sul and Santa Catarina. Having in mind those numbers and the knowledge that the most visited places in Brazil do not include the South of the country a dataset was analysed to get some information and find out how many visitors have been there and where they were from. 1.2 Data Understanding Source data: http://www.dadosefatos.turismo.gov.br/estat%C3%ADsticas-e-indicadores.html Format: csv, comma-separated Size: 3.46MB Number of rows: 73.392 Columns: 1 Continent 2 Country 3 State 4 Year 5 Month 6 Count The technologies used were Excel and R Studio. 1.3 Data Preparation The first downloaded version had 534.792 rows, it included the tourism information from all the 26 states and it was based on data from 1989 to 2015. It was a quite huge dataset that would not be convenient to extract useful outputs as Brazil had been through many economic and social changes in this period. Excel was used to exclude the information from other states as well as the years before 2005. As the dataset was all provided in Portuguese Language the code was used to facilitate visualization: The next step was looking at the data, for a better understanding, Dimensions, Names, Classes and Summaries codes were written: Results: Some table codes were written to count each combination of factor levels: Results: The code round was run to specify number of decimal places: Results: 1.4 Modelling A Linear Model was written to generate a better data visualization and analysis of variance:   Ã‚   Some graphs were generated to have a better understanding about how many tourists visiting each of the states: A Bar plot was generated for better visualisation: The same parameters were used to generate pie charts: Parana with 33,01% and Santa Catarina with 29,48% have a very similar number of visitors and Rio Grande do Sul is the most visited place with 37,51%. With a little bit of research the percentage can be understood, as Rio Grande do Sul is the larger of the three states, having more options for the visitors and Some of the biggest manufacturing industries factories in the country are located in that area. After visualizing where the tourists go it is important to know where they come from. For that reason, some graphs were also generated: Graphic: The same parameters were used to generate some other graphics: After analysing isolated information, a graph relating year and states was generated: It was also generated a graphic listing all countries that visited the South of Brazil in the period: A flowchart was designed to represent the algorithm workflow process: Preparing data for a plot: 1.5 Evaluation Compiling the dataset into graphics and tables facilitated data visualization and brought some very important evidence that can be used for many purposes, specially marketing reasons, on defining an action plan based on what can be done to bring more tourists to the south region. The graphs showing the percentages of tourists, were the ones that caught the attention, Europe had the larger number of visitors with 37,7%, followed by South America with 22%, Asia with 11,7%, Africa with 9,2%, Central America and Caribbean with 8,8%, North America with 5,5% and at last Oceania with 5,1%. Looking at these proportions a few questions were raised and research was necessary. Some important facts showed up: the dataset brings only the number of people travelling for leisure purposes, it does not count the amount of people on business, with could impact on the numbers, especially from North America, as many of them visit the country for business purposes and extend their stay on holidays. Another very important factor is that the information was collected in the first stop in the country, and all the three states in the South do not have a large airport, usually they arrive by connection flights coming from Sà £o Paulo or Rio de Janeiro, where the main international airports are situated. The last very important element that could impact on the number of visitors, is the fact that the south of Brazil does not have a tight control of their borders and many people arrive by land, usually driving from other countries in South America. As said before the tourism sector can be very explored and it can impact in the revenue generation. According to the International Congress Convention Association (ICCA) Brazil is the host of many international events in Latin America and the seventh in the world, so why not leverage on the information brought and attract all those events to the South of Brazil? The numbers in the dataset look a bit too similar for every year related to the count of people visiting the states, but anyway it provides very useful information. It is also very important to observe that Brazil is also accessed by boat and land, specially by tourists coming from Central and South America, as there is no border control some of the numbers might be slightly different. The project scope is limited to identifying patterns in the data rather than predicting future which could be examined as part of further study of the subject matter. 2.1 Business Understanding Every time a famous person passes away the media makes news; some deaths even take the elements of scandals, especially when there is the suspect of a suicide, people follow the reports all over the world. The year of 2016 seemed to be very sad for the famous people, with an unusual number of deaths observed. An article from the 22nd of April, 2016 on BBC News website reported that by April the number of celebrities deaths was double as the previous years, and even said: the number of significant deaths this year has been phenomenal. But comparing to the years before, is it true? Based on a dataset available on kaggle.com, that compiled information available on wikipedia.org, some questions were asked: Did more celebrities die in 2016 than in the last 5 years? Was suicide the most cause of deaths? What were the reasons for the deaths in 2016? Were the reasons different from the 5 years before? What would be the main causes of death for each age group? 2.2 Data Understanding Source data: https://www.kaggle.com/hugodarwood/celebrity-deaths Format: csv, comma-separated Size: 1.47 MB Number of rows: 14.880 Columns: 1 age 2 birth_year 3 cause_of_death 4 death_month 5 death_year 6 famous_for 7 name 8 nationality The technologies used were Excel and Python 3.6 2.3 Data Preparation The original downloaded version had 21.562 rows, with a quick look through the data, a few abnormalities were shown, a number of duplicated cells and rows was observed, also some birth_year did not correspond to real birth year, there were also some animals among humans (specially racehorses and dogs). Excel was used to exclude the duplicated data, to clear some odd information and to exclude the deaths from 2006 to 2010, as the project idea was analyse only the past five years. The first step was reading the table through pandas: Looking at the classes and missing values: As it is clear there are many missing values of cause of death. Looking at the most common causes of death: * It seems like many celebrities tend to die from cancer and heart failure. 2.4 Modelling A bar plot was generated for better visualization: The article from BBC was not entirely wrong, in 2016 more famous people died, compared to the 5 previous years. Looking for the answer for the second question, a bar plot about the suicide rates was generated, was suicide the main cause of deaths? It cannot be said that suicide was the main reason for the deaths. As seen on the previous graphic there is a percentage of celebrities that commit suicide, but comparing 2016 to the five previous years and comparing with natural deaths, a new bar plot was created: Compared to the previous years, 2016 did not seem as bad as the papers and social media claim, as the suicidal rate was only higher than 2014, in this way it cannot be affirmed that the main cause of celebrities deaths in 2016 was self-murder. Just for information a graphic was created to illustrate which is the month when more famous people tend to take their lives: As the bar plot displays September is the month showing a highest level of suicide, while June appears as the lowest. The figures generated from the data set brought a few information so far, proving that 2016 was a sad year for famous people, it also showed that suicide was not the main cause of death. To find out what the main reasons were a bar plot was created: Appears that cancer killed more famous people, at least in the year of 2016. Still comparing 2016 to the five years before an average number of deaths by cause was called, to investigate: The comparison shows that compared to the five years before more famous people died due to more Cancer and Traffic collision, all the other reasons seem to follow the same pattern. Just out of curiosity and to have a better understanding from the facts, the dataset was categorized into age groups: Some pie charts were created to illustrate the cause of death by age group: It is very important to bring to attention that in the child group there were only five rows and that is why the percentages are very high. It is very challenging trying to analyse the deaths related to the age group as there were many missing data specially when it comes to cause of death. As a matter of fact, as common sense, the older people get the age-related diseases appear more in the graphics. A flowchart was designed to represent the algorithm workflow process: In cause_of_death column = suicide 2.5 Evaluation Compiling the dataset into graphics and tables facilitated data visualization and brought some very important information about the celebrity death from 2011 to 2016. The missing values made the difference when trying to get deep information, especially when it comes to cause of death. It was pretty obvious from the data that 2011 the number of dead famous per year increased slightly, however not all the celebrities in the list would actually be considered as such by many people. It was cleared that the suicidal rates are not as high as the media claims and it is not the main cause of death and The increase in the number of news about famous peoples death can also be happening because more people have access to the internet, social media and seem to talk more about it. It is important to remember that the project scope was limited to identifying patterns in the data rather than predicting future. I could not say it was an easy task choosing and analysing two datasets. As I am not a student with any IT background some of my ideas as an outsider were completely mistaken, as I did not know how difficult it can be to write codes and get information from the datasets. It took me a while to understand the basics of how the Python an R work, and I consider I have done a good work. I can tell that I went through an incredible learning journey since I started the Data Analytics course at National College and I have learned a huge volume of new skills. To get the present project done I watched uncountable number of videos, I tried many different environments until I felt comfortable to start the project itself, it also took me a while to find the right dataset and the right questions, but after seeing the graphics and tables I realised I could really get through and do a good project. As our course dedicated more time to Python and have always reading about R as a very difficult data analytics tool I confess I was terrified about it, that is why I decided to start the R Project first, but I had a very good surprise, the program is easier to use than I thought, even with my very little knowledge. Working with a dataset that I am familiar with made it simpler as well, I have always worked in marketing environments and had the curiosity to know more about tourism in the South of Brazil, where I was raised. I consider I found out important information, that maybe could be very valuable for companies investing in services and tourism. For the Python project, I decided to work with the celebrity-deaths dataset just out of curiosity, as almost every single day during the year of 2016 I saw on twitter the #celebritydeaths2016. But after analysing the dataset I found out that there is only a slightly evidence that more famous people died during the year of 2016 it cannot be said that it was the worse year or predict anything for the future. I have also found out that suicide is not the main reason for their deaths as the social media reports. The idea of both projects was to identify and extract patterns in the data, which I believe has happened. References Big Data: 20 Mind-Boggling Facts Everyone Must Read. Available at: http://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-boggling-facts-everyone-must-read/#56eaf8456c1d. [Accessed: 10 December 2016]. Business Dictionary. Available at: http://www.businessdictionary.com. [Accessed: 09 December 2016]. Estatà ­sticas e Indicadores. Available at: http://www.dadosefatos.turismo.gov.br/dadosefatos/home.html   [Accessed: 09 December 2016]. Lantz B., 2013, Machine Learning with R, Packt Publishing IBM, 2011, IBM SPSS Modeler CRISP-DM Guide, IBM Corporation. Available at: http://www-staff.it.uts.edu.au/~paulk/teaching/dmkdd/ass2/readings/methodology/CRISPWP-0800.pdf [Accessed: 11 December 2016]. Ministà ©rio do Turismo. Available at: http://www.turismo.gov.br/ [Accessed: 19 December 2016]. Skill: Data Analysis. Available at: https://15-5103.ca.uts.edu.au/skills/data-analysis/ [Accessed: 09 December 2016]. Why so many celebrities have died in 2016? Available at: http://www.bbc.com/news/entertainment-arts-36108133 [Accessed: 26 December 2016]. Source data: http://www.dadosefatos.turismo.gov.br/estat%C3%ADsticas-e-indicadores.html Source data: https://www.kaggle.com/hugodarwood/celebrity-deaths

Cluster Intersections and the Evolution of the Bay Area Bioinformatics Cluster :: essays research papers

Cluster Intersections and the Evolution of the Bay Area Bioinformatics Cluster The recent establishment California-based bioinformatics industry clusters is a logical consequence of the intersection of existing local Biotechnology, Information Technology and Venture Capital clusters. The very definition of Bioinformatics: â€Å"the science of managing and analyzing biological data using advanced computing techniques, 1† helps to illustrate the nature of this intersection. Research and development for Biotech companies generates volumes of biological data and IT companies provide tools that assist in processing this data. It seems only natural that in light of this mutual dependency and given the proximity of existing IT and Biotech clusters a new, specialized Bioinformatics cluster would emerge. In his article, â€Å"Clusters and the New Economics of Competition,† Porter describes the benefits created by the â€Å"direction and pace of innovation 2† sustained by local competitors in their existing products and technologies. For example, given the already lengthy process of bringing a new pharmaceutical to market, Biotech companies must have realized early on that their ability to stay abreast of competitors was highly dependant on the speed at which they could process massive amounts of genetic information to find therapeutic candidates. Clearly, the incorporation of cutting edge information technologies into Biotech research and development processes was itself a critical innovation, but it was also critical to future innovations within the Biotech industry. Porter would probably argue that the competitive pressures of clustered Biotech firms fostered more urgent and rapid incorporation of advanced computing into genetic research. The proximity of the knowledg e and resources in the IT cluster made it easier to both conceive of these innovations and to access the resources that enabled them. Conversely, innovations in the field of Information Technology were stimulated in response to the both the needs of the Biotech cluster, and the urgent clamoring of IT competitors to capitalize on a new market. Porter asserts that â€Å"vibrant† clusters not only stimulate innovation in established companies but that new businesses and new innovations take shape in response to the competitive environment. Start-up firms have a unique opportunity to observe the incumbents in the cluster and conceive of ways to improve existing products or develop complementary offerings. New firms benefit from an existing local customer base but also may be able to more readily recognize and capitalize on a niche market in the midst of many established competitors 3. The Bioinformatics industry appears to have emerged in a similar manner, filling the gap between the IT and Biotech clusters.

Learning to read

Reading is one of the complex tasks accomplished by students. Paradoxically one can learn to read by reading. Reading is an interesting past time or hobby for those who like it. It broadens one’s knowledge. Letter’s in the books talk to the reader. Reading teaches a child many things. It may be good or it may be bad. It should be guided learning. Reading is a subtle and complex process that involves sensation, perception, comprehension, application, and integration. Reading is the magic key to the world of enlightenment and enjoyment. It is the basic tool for learning in all the subject areas. Reading is the process of making and getting from printed word symbols. Efficient reading is an active dialogue between author and reader. Reading can be one of man’s deepest pleasures. It enables man to ponder the mysteries of the world, explore accumulated knowledge, and contemplate the unknown. One significant point of learning to read is to understand how written language and oral language correspond. The English writing system is based on the alphabetic principle that written words are made up of letters that have approximate matches with the sounds heard in the words we speak. Therefore, to understand the alphabetic principle, one must recognize that spoken words consist of a sequence of sounds and this understanding is called phonemic awareness (McCormick, 1999). Phonemic awareness is not reading. It does not deal with alphabetical letters. It does not phonics. It does not replace the school’s reading program and it is not an all-out cure for reading problems (Kang, 19997). Phonemic awareness is recognizing sounds within words. It is the ability of the child to focus on sounds of words. It is an understanding that speech is composed of individual sounds called phonemes. Phoneme is the smallest unit of speech that carries a definite meaning when put together. The phonemic awareness task requires children to analyze, manipulate the units of speech rather than focus on meaning; and the reader’s task is to understand the relationship of the letter in the writing system to the phonemes in the language. Readers should also recognize that speech could be segmented into smaller units-the readers to become phonemically aware (Yopp, 1992). This gives children functional practice in phonemic segmentation or breaking a word down into component sounds. The four basic skills of Phonemic Awareness are rhyming sounds, blending sounds, matching sounds, and segmenting sounds. Such skills are the building blocks for reading. Therefore, in order to benefit from formal reading instruction, children must have a certain level of phonemic awareness.  Phonemic Awareness could be taught as early as kindergarten throughout kindergarten and into Grade I; to continue in Grades II and III and with those children who remain weak in reading. Kang (1997) suggests the following key points to keep in mind: 1. Skills should be taught in specific lessons. 2. Try to practice phonemic awareness about 10-15 minutes a day, three to four times a week. 3. The more consistent the lesson structure is, the more improvement you will observe in   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   your young learners. 4. Regroup children upon getting to know their skills. Place in one group those who are successful in phonemic awareness and sustain their skills with lessons once a week. Phonemic awareness is a possible reason why many children struggle in reading (Rasinski & Padak, 2000). It is a fact that when we speak we only rarely pay conscious attention to the sound we make, rather we are simply concerned with getting our messages across. Therefore, the concept that words are made up of sounds is not necessarily an easy one for students to grasp. Phonemic awareness is not really critical to our purposes in spoken language but rather central in learning to read. A large body of research conducted in the U.S. and other countries indicate that one of the most significant coordinators between good and poor readers is poor readers’ lack of phonemic awareness (McCormick, 1999). This holds true regardless of the intelligence level of socioeconomic status of the students. On the strength of this research, there is little doubt that lack of phonemic awareness is a cause of reading disabilities in a large portion of students whose difficulties lie with word recognition. Research studies indicate that one aid to the development of adequate phonemic awareness occurs when young children listen to storybooks read aloud by their parents, an advantage enjoyed by some children, but not all. Others suggest that good or poor phonemic awareness may have a genetic origin. Direct evidence indicates that lack of phonemic awareness is a major cause of word identification difficulties. Likewise, phonemic awareness permits students to use letter-sound correspondences, employ phonemic strategies and identify unknown words more quickly. It also may have a bearing on whole word learning. In addition, it is a prerequisite to spelling and writing, which also require hearing (McCormick, 1999). Further research has shown that phonemic awareness is a more powerful determiner than intelligence in predicting whether students will succeed in reading and also a stronger predictor of â€Å"general† language proficiency (McCormick, 1999) and a very powerful predictor of later reading achievement (Griffith, et al., 1992). Phonemic awareness is now viewed as a critical variable in emergent literacy and beginning reading acquisition (McCormick, 1999). Recognizing that, words can be broken down into phonemes and syllables, and being able to manipulate these, has a high correlation with reading achievement. Thus, it is a central factor in learning to read and a prerequisite in learning to read. Irregularities of English demand careful handling to avoid confusion. Regular spelling should be presented in the early stages before teaching words with semi-irregular patterns like cake, bread, etc. and those with complete irregularities forms such as cough, bough. This may be another complete lesson for the actual reading phase after learning the letter shapes and names. Eventually, with increasing speed, the child works through the page of the teaching materials. In the schools, reading as a subject should be given emphasis for it is the springboard in learning other areas. Learning reading is open to a lot of words for children. Early childhood cognitive development will not develop the building blocks of language for children, unless parents know the importance of good reading. Children, whose parents are not aware that reading plays a role in the child’s development, are not disposed to learn reading. Their opportunities in learning are limited. Reading to every citizen is a new civil right. A child should be ready to read and ready to get a clear understanding of what he sees and reads in order to provide him a good early experience. Early language and early pre-learning reading activities contribute to the development of feeling of a child. Absence of this development will stifle learning and understanding sounds, letters, and language. Language in reading is the building block of speech. Likewise, the child’s ability to grasp ideas and sounds has a linkage in learning to read letters. Knowing how to read is important in interactive learning. It affects the heart and soul of a child. A child should have a strong language and a good pre-reading education.  For children to learn to read is a challenge posed to parents and educators. No matter how busy parents are, they should have time left for their children. Parents should develop good relationships with their children at their early stage of learning. Education begins before birth. Thus, the most important word that should be learned and practiced by a child is credibility according to the First Lady of U.S. President Bush, who was once a teacher herself.  High quality teachers are needed in the classroom to guide and teach children to learn. One important aim in reading is to learn to choose, analyze, and read good materials. There are teachers who change a child’s life negatively or positively. Subsequently, teachers should teach a child to be a worthy citizen in thought, in word, and in deed. To make teaching more effective, it should be integrated with subjects like art and music education, character education, and all other subject areas in the school curriculum. Reading is the right key to spiritual, social, intellectual, esthetical, mental, moral, and academic success.  It is hoped that after a thorough understanding of the various conditions leading to reading readiness through study, the reading program will be better handled. References: Griffith, P., et al. (1992). â€Å"Phonemic awareness helps beginning readers break  Ã‚  the code†. The Reading Teacher. Vol. 56, No. 7, pp.517-523: March 1992. Kang, H. (1997). Phonemic awareness: Listening activities to develop  pre-reading skills: USA: Fearon Teachers Aid; Division of Frank Schaffer Publications, Inc. McCormick, S. (1999). Instructing students who have literacy problem. New Jersey: Prentice-Hall, Inc. Simon & Schuster, A Viacom Company. Rasinski, T., & Padak, N. (2000). Effective reading strategies: Teaching children who  find reading difficult. 2nd Ed. Prentice Hall, Inc. NJ. Yopp, H.K. (1992). â€Å"Developing phonemic awareness in young children†. The Reading  Teacher. Vol. 9: May 1992.      

How to Find an Excellent Topic for an English Literature Term Paper

How to Find an Excellent Topic for an English Literature Term Paper How to Find an Excellent Topic for an English Literature Term Paper One of the most rewarding paper types that you will ever write for an English class is a literature term paper. Its main point is to get you to take a hard and analytical look at a piece of literature. When you are developing your term paper, the topic is vital in the overall success of your piece. You will want to utilize the following advice to be ensured that it turns out successfully. Brainstorming One of the easiest ways to make sure that you select a good topic is by brainstorming some of the literary works that you can remember. Something about these pieces stood out to you and that can make writing about them more interesting. Think back to the various books that you have read. You don’t have to recall the exact name and author for this part of the process. Just simply get the general ideas down so that you know which piece you are discussing. The name and title are not important. Enhancing the List After the brainstorming process, you will have a starting list of ideas that you can write your paper on. However, you don’t want to stop there. Use your knowledge from the course to think about pieces that have excessive significance. You can use your notes for this list. Your paper is going to have to talk about themes, plots, motifs, and the like. Therefore, the pieces that have a lot of these characteristics are perfect for your paper. Identify at least three that your instructor has emphasized in the class or that possess these important features and add them to your list. Narrowing down Your Diamond in the Rough Now that you have this extensive list of options, go through each one and jot down some aspects that you can write the paper about. They can deal with any of the literary characteristics. This part is vital. Create a short outline for each and then use the one with the most â€Å"stuff† as your topic. Why is that so? Because if you have already something to say about the potential subject of your English literature term paper, it means that you are interested in the topic and will conduct a great research on it. You now have 3 vital steps you need to take in order to choose a great topic, so get to work and choose a piece that means something to you and one that you enjoy because to write a substantial term paper, you will surely have to read it again. If you are not a reading person by nature, consider short stories that won’t take much time. Anyway, you need to be comfortable with the literary work and its peculiarities if you want to succeed in writing an excellent English term paper.