Most Difficult Topics a Computer Science Student Encounters

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I. INTRDUCTION

This research entitled, “A study on The Most Difficult Topic a Computer Science Student Encounters”, was made in partial fulfillment of the requirements in Operations Research I. Guided by my Professor, Mrs. Realinixa Krishnan, I am trying to cite the topic which most Computer Science Student perceive as the most difficult in order for me to show computer educators which topics to focus and give more time to. Because of the fact that every year level receives different amounts of knowledge, I made my research vary according to year level.

II. RELATED LITERATURE
As the research continued I gathered several related articles as completion to the given format of the said research. Dan Zambonini said on his web blog at http://onlamp.com that he looked at the list of modules Computer Science students studied, and although they sound very interesting, there seems to be little relevance to the current job market: neural networks, computer vision, artificial intelligence, robotics, compiler engineering, machine learning, quantum computing, Bayesian networks, embedded systems... How many of these graduates will go on to regularly use this information? And these aren't dodgy establishments teaching these modules; I took this list of modules from the curricula of the 'Top 5' computer science departments in the UK (graded by a respectable national newspaper). He also added that part of this mismatch (between education and skills) could be caused by the misguided notion that 'Computer Science' graduates don't necessarily go into 'Software Engineering', so are taught a more scientific approach, rather than vocational. However, the Computer Science graduates have software/programming careers, not science. “The 'science' bias could also account for the large number of mandatory math modules in these courses”, he continued one of the top 5 universities has 25% of its mandatory modules dedicated to mathematics (including 1 mainly on 3D math). Another top university states that the final year project is to 'Develop a game'. It was really great for attracting students, maybe not a great idea for getting them a job? He just did a search on monster.com; there were 31 'games programmer' vacancies and more than 1000 for 'software developer’ and more than 1000 for 'web programmer'. Not much use knowing how to handle three dimensional diffuse lighting vectors when you're trying to create a customer feedback form for an insurance company. On the other hand, a blogger and article writer dictated on her article at a well-known article site, the methodology and format of an effective dissertation of Computer Science students. Eva Mason said on articlebase.com that the writing portion of computer science dissertation is divided into different sections. You start with introduction, followed by literature review and research methodology. After that comes the analysis part followed by your conclusion and recommendation. She also added that, it is a standard writing format which is applicable for both BSc and MSc computer science dissertation. One thing that you need to keep in mind before writing is your target audience. Normally computer science dissertation is full of technical terms and formal. It focuses on various programming theories that are difficult to understand for a layman. She also said that never try to make it too technical as then it takes away the complete essence of dissertation writing. Try to make it as simple and easy to understand as possible. When you start writing, keep in mind the main factors. Remember if you are critically analyzing a research then it’s all about the evidence. Place your strong arguments at the start to back your claim. Step by step describe in detail your research and facts that you have gathered.

III. DESCRIPTION OF DATA GATHERING PROCEDURE
In order for me to make this research possible, I have made data gathering paraphernalia and let it be filled up by different Computer...
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