Most Difficult Topics a Computer Science Student Encounters
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
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