BSCS STUDENTS AND A CONTEMPORARY FIELD: A SPECULATIVE STUDY
TABLE OF CONTENTS
EXECUTIVE SUMMARY……………………………………………………………………….4
HISTORY…………………………………………………………………………………………5-6
MODERN TRENDS………………………………………………………………………………7-8
INTRODUCTION…………………………………………………………………………………8
PROCEDURES……………………………………………………………………………………8
METHADOLOGY--------------------------------------------------------------------------------------------9
THEORY OF COMPUTER
SCIENCE--------------------------------------------------------------------9
THEORY OF
COMPUTATION----------------------------------------------------------------------------10
ALGORITHAM & DATA
STRUCTURE-----------------------------------------------------------------10
PROGRAMMING LANGUAGE
THEORY---------------------------------------------------------------10
FINDINGS…………………………………………………………………………………………11-14
ANALYSIS………………………………………………………………………………………..15
RECOMMENDATIONS………………………………………………………………………….15
CONCLUSION……………………………………………………………………………………15
APPENDIX-STUDY
QUESTIONNAIRE………………………………………………………..16
GLOSSARY………………………………………………………………………………………17
WORKS-CITED………………………………………………………………………………….17-18
LIST OF ILLUSTRATIONS
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Figure
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Department
of Computer Science,
GC
University, Lahore
July 19, 2017
Mr. Shaharyar Haider
Lecturer
GC University, Lahore
Dear Mr. Shaharyar,
Here is the report you requested on BSCS Students and a Contemporary
Field.
I surveyed 50 graduates of BSCS from GC University, to determine how they
feel about their experience in Department of Computer Science. What opinions
they have on syllabus and projects.
The survey results show that majority of the students agreed that the
teaching methods of the professors were not modern enough to tune the students
according to the contemporary field. Many students claimed that the assignments
and projects weren’t productive enough and said DCS, GCU can’t compete with
other universities.
Based on these findings, it is recommended that Department of Computer
Science, GCU needs to improve many factors such as faculty, teaching methods so
that it can produce students which can contribute to Modern Trends of Computer
Science.
Thank you for this opportunity and I hope you find the results valuable.
Cordially,
M. Laeeq Asghar
Student
GCU Lahore
EXECUTIVE SUMMARY:
The purpose of this
study was to investigate the effects of the first-year field test BSCS
University Computer science program on student understanding of the creative,
developmental, testable, and unified nature of
copueter technolgy. Since Computer Science is the ultimate base of
engineering disciplines, and the backbone of entire software industry. Computer
Science is a field that open a world of Modern Technology. Nobody can deny the
importance of Computer in our modern life. A lot of technological innovation is
obliged of Computer science. Technology has a great positive effect on our
lives, making it easier and more comfortable. It has revolutionized out lives.
Computer Science is one of the top most highly paid field in modern Era .The estimate
annual salary of computer engineer is nearly $58,800 – $112,600. This field has
grown exponentially in past recent years. If you look around in nowadays you
can see whole modern world depends on computer.
The experimental group, which was exposed to
the BSCS program, and the control group, which was taught using a more
traditional computer science curriculum, were administered a pretest and
posttest using the Modified Nature of Scientific Knowledge Scale (MNSKS). The
scope of CS field is very wide because a computer scientist is a scientist who has
acquired the knowledge of computer science,
the study of the theoretical foundations of information and computation and
their applications. Analyses of the results showed that the
understanding of students who experienced the BSCS computer science program
decreased significantly in regard to the developmental and testable nature of
science. The understanding of students who experienced the control-group
science program decreased significantly in regard to the creative nature of
science. Implications of these results are related to the constructivist view
of learning, the development of curricula designed to facilitate scientific
literacy, and future research endeavours.
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History of Computer Science:
People have been using mechanical devices to
aid calculation for thousands of years. For example, the abacus probably
existed in Babylonia (present-day Iraq) about 3000 B.C.E. The ancient Greeks
developed some very sophisticated analog computers. In 1901, an ancient Greek
shipwreck was discovered off the island of Antikythera. Inside was a
salt-encrusted device (now called the Antikythera
mechanism) that consisted of rusted metal gears and pointers. When
this c. 80 B.C.E. device was reconstructed, it
produced a mechanism for predicting the motions of the stars and planets. John Napier (1550-1617),
the Scottish inventor of logarithms, invented Napier's rods (sometimes called
"Napier's bones") c. 1610 to simplify the task of multiplication. In
1641 the French mathematician and philosopher Blaise Pascal built
a mechanical adding machine. Similar work was done by Gottfried
Wilhelm Leibniz also advocated use of the binary system for
doing calculations. Joseph-Marie
Jacquard invented a loom that could weave complicated patterns described by
holes in punched cards. Charles Babbage
worked on two mechanical devices: the Difference
Engine and the far more ambitious Analytical Engine (a
precursor of the modern digital computer).
One of Babbage's friends, Ada Augusta Byron of early 1800s,
Countess of Lovelace,
sometimes is called the "first programmer" because of a report she
wrote on Babbage's machine. (The programming language Ada was named for her.)
In the early 1900s, Bertrand Russell invented type theory to avoid
paradoxes in a variety of formal logics. He proposed this theory when he
discovered that Gottlob Frege’s version of naive set theory afflicted with Russell’s
paradox. Russell proposed a
solution that avoids Russell’s paradox by first creating a hierarchy of types,
then assigning each mathematical entity to a type. After Russell came the
amazing Alonzo Church who introduced Lambda calculus to the world. Lambda calculus introduced a new way of viewing problems
in Mathematics, and inspired many programming languages. Lambda calculus played
a big part in the development of functional programming languages.
From
experiments with anti-aircraft systems that interpreted radar images to detect
enemy planes, Norbert Wiener coined the term cybernetics from the Greek word for "steersman." He
published "Cybernetics" in 1948, which influenced artificial
intelligence. Wiener also compared computation, computing
machinery, memory devices, and other cognitive similarities with his
analysis of brain waves. Grace Hopper was first exposed to Computer Science when she was assigned a role to
work on the first large-scale digital computer at Harvard. Her task was to
design and implement a method to use computers to calculate the position of
ships. In the early 1950s, she designed the language COBOL, and built the first
program that interprets English code to binary code. Her vision played an
incredible part in the formation of Computer Science and she foresaw a lot of
trends in computing.
In a famous paper that appeared in the journal Mind in 1950, Alan Turing introduced the Turing Test, one of the first efforts in
the field of artificial intelligence. He proposed a definition of
"thinking" or "consciousness" using a game: a tester would
have to decide, based on written conversation, whether the entity in the next
room responding to the tester's queries was a human or a computer. If this
distinction could not be made, then it could be fairly said that the computer
was "thinking". John Backus and
others developed the first FORTRAN compiler in April 1957. LISP, a list-processing language for artificial
intelligence programming, was invented by John McCarthy about
1958. Alan Perlis, John Backus, Peter Naur and others developed Algol.
In the 1960's, computer science came into its own as a discipline.
In fact, the term was coined by George Forsythe, a numerical analyst.
The first computer science department was formed at Purdue
University
in 1962. The first person to receive a Ph. D. from a
computer science department was Richard
Wexelblat, at the University of Pennsylvania, in December 1965.
Operating systems saw major advances. Fred Brooks at IBM designed
System/360, a line of different computers with the same architecture and
instruction set, from small machine to top-of-the-line. Edsger Dijkstra at Eindhoven designed The Multiprogramming
system. At the end of the decade, ARPAnet, a precursor to today's Internet,
began to be constructed. Many new programming languages were invented, such as
BASIC developed in 1964 by John Kemeny and Thomas Kurtz.
Figure
1.0
Modern Trends of Computer Science:
There’s never been a brighter outlook
for young computer
science students than today. As
these recent stats show, computer science graduates have some
of the highest starting salaries out there and are in such high demand that
they can afford to be precise about the type of job and industry they opt for.
Technology
has been growing so exponentially over recent years, there has been a steadily
increasing demand for bright graduates to come in and help to transform areas
ranging from data infrastructure to cyber security. If you are interested in
pursuing a career in computer science, it’s important to stay up to date with
the latest trends in computer science research, to make an informed choice
about where to head next. These are five trends storming the tech industry!
1. Artificial intelligence and robotics:
With the global robotics
industry forecast to
be worth US$38 billion by 2018, a large portion of this growth is down to the
strength of interest and investment in artificial intelligence (AI) – one of
the most controversial and intriguing areas of computer science research. The
technology is still in its early stages, but tech giants like Facebook, Google
and IBM are investing huge amounts of money and resources into AI research.
There’s certainly no shortage of opportunities to develop real-world
applications of the technology, and there’s immense scope for break-through
moments in this field.
complex real-world data.
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2. Big data analytics:
There has been a surge in demand for
experts in this field and doubled efforts on the part of brands and agencies to
boost salaries and attract data science talents. From banking to healthcare,
big data analytics is everywhere, as companies increasingly attempt to make better
use of the enormous datasets they have, in order to personalize and improve
their services.
3. Computer-assisted education:
The use of
computers and software to assist education and/or training, computer-assisted
education brings many benefits and has many uses. For students with learning
disabilities, for instance, it can provide personalized instruction and enable
students to learn at their own pace, freeing the teacher to devote more time to
each individual. The field is still growing but promising, with many educators
praising its ability to allow students to engage in active, independent, and
play-based learning.
4. Bioinformatics:
A
fascinating application of big data, bioinformatics, or the use of programming
and software development to build enormous datasets of biological information
for research purposes, carries enormous potential. Linking big pharma companies
with software companies, bioinformatics is growing in demand and offers good
job prospects for computer science researchers and graduates interested in
biology, medical technology, pharmaceuticals, and computer information science.
5. Cyber security:
According to 2014 data from Burning Glass, cyber security jobs
in the US grew by 74% between 2007 and 2013 – more than twice the rate of IT
jobs overall, and raising concerns about the shortfall in qualified graduates.
In February 2015, President Barack Obama spoke of the need to “collaborate and
explore partnerships that will help develop the best ways to bolster our cyber
security.” It’s not hard to understand why he might think so. We live in a
hyper-connected world, in which absolutely everything – from banking to dating
to governmental infrastructure – is done online. In today’s world, data
protection is no longer optional, for either individuals or nations, making
this another growing strand of computer science research.
6. Virtual Reality and Augmented Reality:
There
are existing commercial products on the market and increasing research in this
area. More research is taking place in the follow-on technologies.
Applications
of Computational Science:
Problem domains for computational
science/scientific computing include:
Numerical simulations:
Numerical
simulations have different objectives depending on the nature of the task being
simulated:
o Reconstruct
and understand known events (e.g., earthquake, tsunamis and other natural
disasters).
o Predict
future or unobserved situations (e.g., weather, sub-atomic particle behaviour,
and primordial explosions).
Model fitting and data
analysis:
o Appropriately
tune models or solve equations to reflect observations, subject to model
constraints (e.g. oil exploration geophysics, computational linguistics).
o Use
graph theory to model networks, such as those connecting individuals,
organizations, websites, and biological systems.
Computational
optimization:
o Optimize known scenarios (e.g.,
technical and manufacturing processes, front-end engineering).
o Machine learning.
INTRODUCTION
Intro:
Computer Science is the
ultimate base of engineering disciplines, and the backbone of entire software
industry. Computer Science is a field that open a world of Modern Technology.
Computational science
Computational science (or scientific computing) is the field of study concerned with
constructing mathematical models and quantitative analysis techniques and using computers to
analyze and solve scientific problems. In practical use, it is
typically the application of computer simulation and other forms of computation to problems in various scientific
disciplines.
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Background:
The back ground has divided in two parts:
A.
The methodologies of CS field and its theory.
METHODOLGY:
The
Algorithms & Methamatical Methods Of Computational Study Are
Following.
Numerical Analysis
Application
Of Taylor Series As Convergent And Asymptotic Series
Computing
Derivatives By Automatic Differentiation (Ad)
Computing
Derivatives By Finite Differences
Finite
Element Method
Graph
Theoretic Suites
Monte carlo METHODS
Molecular dynamics
Linear programming
Branch and cut
Branch and Bound
Numerical linear algebra
Computing the LU factors by Gaussian elimination
Discrete Fourier transform and applications.
Newton's method
Space mapping
Time stepping methods for dynamical systems.
Theoretical computer science:
Theoretical Computer Science is mathematical and abstract in spirit,
but it derives its motivation from practical and everyday computation. Its aim
is to understand the nature of computation and, as a
consequence of this understanding, provide more efficient methodologies. All
papers introducing or studying mathematical, logic and formal concepts and
methods are welcome, provided that their motivation is clearly drawn from the
field of computing.
Theory
of computation:
According to Peter Denning,
the fundamental question underlying computer science is, "What can be
(efficiently) automated] Theory of computation is
focused on answering fundamental questions about what can be computed and what
amount of resources are required to perform those computations. In an effort to
answer the first question, computability theory examines which
computational problems are solvable on various theoretical models
of computation.
The second question is addressed by computational
complexity theory,
which studies the time and space costs associated with different approaches to
solving a multitude of computational problems.
The famous P =
NP? problem,
one of the Millennium
Prize Problems. is
an open problem in the theory of computation.
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P = NP?
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GNITIRW-TERCES
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Algorithms and data
structures:
Algorithms and data structures is the study of commonly used
computational methods and their computational efficiency.
O(n2)
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Programming language
theory:
Programming language theory
is a branch of computer science that deals with the design, implementation, analysis,
characterization, and classification of programming languages and
their individual features. It falls within the discipline of
computer science, both depending on and affecting mathematics, software
engineering, and linguistics.
It is an active research area, with numerous dedicated academic
journals.
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B.
This survey was conducted in order to
identify the core problems BSCS Students face in GCU.
Statement of the Problem:
The focus of the study was to determine:
1.
What is the importance of CS field .
2.
What students felt after graduating from
GCU & what problems they faced
during their time in GCU.
3.
The problems of the students that they
faced in Practical field.
4.
Improvements that could be made in
Department of Computer Science, GCU.
Purposes of the Study:
The
purposes of this study were as follows:
1)
To Recognize with the importance of CS
field & the revolution due to IT in present ERA.
2)
To analyze what problems were being faced
by the students in achieving suitable professional education.
3)
To determine the core reasons behind why
BSCS students of GCU can or cannot resonate with the contemporary professional
life.
4)
To bring forward solutions to the problems
faced by them.
Scope:
The
scope of this study was limited to the students who graduated from DCS, GCU.
PROCEDURES
A. 50
students were taken as sample who graduated last year. The procedures followed
included these:
B.
A questionnaire was developed that
contained simple questions, checklists, and semantic differential scale. The
students willingly filled the questionnaire.
C.
The date tabulated using a computerized
statistical package.
D. The
results were analyzed by the team created and this report prepared.
FINDINGS
These findings are
presented using the study objectives as frame work. The following sections
include information about demographic information describing the student’s time
in GCU and their views on teaching methods, assignments, and their confidence
level after graduating whether they could contribute in the contemporary or
not.
Job after Graduation:
As
indicated in Figure 1. 38.7% students claimed that they found a job immediately
after graduation and without any problems. 35.5% said they couldn’t get a job.
Figure 1.
Problem Solving:
Figure 2
show that majority of the students failed to tackle the problems they faced in
Professional Life where as 37.5% were confident about themselves.
Figure 2.
Courses Following the Modern Trends of Computer
Science:
The figure shown below indicates that 75% students
said the courses taught in GCU do not follow the modern trends of computer
science.
Figure 3.
Professors adapting new teaching methods:
The figure below shows that only 9.7% of the students agreed that
teachers adapted new teaching methods, the majority didn’t agree.
Figure 4.
Assignments improving practical experience:
60% students said the assignments given by the teachers improved their
practical experience. While about 0% were unsure about it.
Figure
5.
Making
students sharp enough to challenge other universities:
Majority of the students
said that the courses taught at DCS, GCU didn’t make them sharp enough to
challenge other universities. While a balance was seen between students who
said yes and those who were uncertain about the answer.
Figure 6.
ANALYSIS
The analysis of above discussion is that Computer
Science is one of the most technical field in the disciplinary sciences. The
main reason is that you have to learn tough programming languages, think like a
computer, need a lot of practice and have to transform your ideas in a program
which is very difficult. This field is open for everyone, but many people have
failed to maintain a career at computer sciences. Computer science demands a
lot of passion and interest. Computer science should be taught at all universities
with responsible, highly qualified faculty & staff. It is the revolutionary
field which brings about constant changes every day in our daily lifes so
students should be interact with multiadvance modes such as artificial
intelligence or cyber works. And made him capable so he/she would design his
own sotwares and Apps.
RECOMMENDATIONS
SHORT
TERM RECOMMENDATION:
1. Teachers qualification must be PHD in computer
sciences.
2. Students must be taught practically so they `ill
know well about programming.
3. Young teachers hired, as they are fresh minded and
know well about technology.
4. Assignment and projects must be productive which
can contribute modern trend to computer.
5. Students focus must be on their related field &
they have to take interest in it as their passion.
LONG
TERM RECOMMENDATION:
1.
Proper labs should be maintained.
2. Practical implementation made.
3. Daily labs lecture should be maintain for students.
4. Workshops should be organized for students to aware
students about new technology.
5. Study tours should be arranged for the students.
6. Faculty of the department should be highly
qualified, so it should be able to
compete with other universities.
7. Turn the old method of study to modern trends , so
that students should be able compete in the field.
APPENDIX
STUDY QUESTIONNAIRE
1. Were you able
to get a job without a hitch after graduating from GCU?
a. Yes
b. No
c. Maybe
2. Could you
tackle all the problems you faced in Professional Life after graduating from
GCU?
a. Yes
b. No
c. Maybe
3. Do you think
the courses taught at GCU follow the "Modern Trends of Computer
Science"?
a. Yes
b. No
c. Maybe
4. Did the
Professors adapt new teaching methods?
a. Yes
b. No
c. Maybe
5. Do you agree
that the Assignments/Projects assigned improved you Practical Experience?
a. Yes
b. No
c. Maybe
6. Do you think
studying in GCU makes students sharp enough to challenge other universities?
a. Yes
b. No
c. Maybe
7. What type of
improvements should GCU make in order to achieve a higher rank among Computer
Science Universities?
a. Yes
b. No
c. Maybe
GLOSSARY
The Antikythera mechanism: is an
ancient mechanical analog computer designed specifically to predict and
calculate the positions and movements of stars and planets. It is among the
oldest forms of computer, and was designed by Greeks in 86 BC.
Logarithms: a quantity representing the power to which a fixed number (the
base) must be raised to produce a given number.
Paradox: a seemingly absurd or contradictory statement or proposition which
when investigated may prove to be well founded or true. "the uncertainty
principle leads to all sorts of paradoxes, like the particles being in two
places at once"
Hierarchy: a system in which members of an organization or society are ranked
according to relative status or authority.
Lambda calculus: (also
written as λ-calculus) is a formal system in mathematical logic for expressing
computation based on function abstraction and application using variable
binding and substitution.
Functional Programming: In computer
science, functional programming is a programming paradigm—a style of building
the structure and elements of computer programs—that treats computation as the
evaluation of mathematical functions and avoids changing-state and mutable
data.
Cybernetics: the science of
communications and automatic control systems in both machines and living
things.
COBOL: a computer programming
language designed for use in commerce
Afflict: afflicted (of a problem or illness) cause pain or trouble to;
affect adversely.
Artificial Intelligence: the theory
and development of computer systems able to perform tasks normally requiring
human intelligence, such as visual perception, speech recognition,
decision-making, and translation between languages.
Cognition: the mental action or
process of acquiring knowledge and understanding through thought, experience,
and the senses.
FORTAN: a high-level computer
programming language used especially for scientific calculations.
ALGOL: an early high-level
computer programming language devised to carry out scientific calculations.
ARPANET: The Advanced Research
Projects Agency Network (ARPANET) was an early packet switching network and the
first network to implement the protocol suite TCP/IP. Both technologies became
the technical foundation of the Internet.
Precursor: a person or thing that
comes before another of the same kind; a forerunner.
Posttest.
: a test given to students after completion of an instructional program.
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Eisenkraft,
A. 2003. Expanding the SE model. The Science
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D.W., and R.T. Johnson. 1987. Learning together and
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Englewood Cliffs, NJ: Prentice Hall.
Lawson, A.,
M. Abraham, and J. Renner. 1989. A theory of
instruction:
Using the learning cycle to teach science
concepts and
thinking skills. Cincinnati, OH: Notional
Association
for Research in Science Teaching.
Marek, E.,
and A. Cavallo. 1997. The learning cycle: Elementary
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science and beyond. Portsmouth, NH: Heinemann.
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Research Council (NRC). 19990. How people learn:
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National
Academies Press.
https://cs.uwaterloo.ca/~shallit/Courses/134/history.html
Book: Modern Trends and
Techniques in Computer Science. 3rd Computer Science On-line Conference 2014
(CSOC 2014) Editors: Silhavy,
R., Senkerik, R., Oplatkova,
Z.K., Silhavy, P., Prokopova, Z.
(Eds.)
https://www.topuniversities.com/courses/computer-science-information-systems/5-trends-computer-science-research
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