The document discusses perceptions of foundational knowledge among computer science students. It notes high attrition rates in CS programs and debates why this occurs. Some argue the theoretical content is not relevant, while the authors' survey found most students are satisfied with theory. It explores making theoretical topics more interesting, relevant, and motivated to students. The goal is understanding student perceptions to reduce attrition in CS.
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Perceptions of Foundational Knowledge by CS students - WCCCE 2012
1. Perceptions of Foundational Knowledge by CS
Students
Katharine Blanchard & Michael Soltys
McMaster University
May 4, 2012
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Title - 1/30
2. At McMaster our enrollment is very good
→ not easy to get in our program
→ full capacity in 1st and 2nd year
But . . .
→ CS attrition rates as high as 30%
We are in the faculty of engineering (PEng)
There is a push to make CS more “relevant”
→ replace theory with more programming
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Intro - 2/30
3. Guzdial & Soloway: “Nintendo Generation” views CS as creating
media.
Beaubouef & Mason: the problem of high attrition and the need of
math
Knuth: “CS = problem solving”
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Intro - 3/30
4. Each generation of students is different, shaped by:
Family/cultural tradition
High school experiences
Economic factors
Societal pressures
World headlines
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5. Possible reasons for student attrition:
Juggle school and a job
Limited time management skills
Misconceptions on entering the program
Poor math skills & poor problem solving skills
Poorly designed CS1 lab courses
Lack of practice / feedback
Grad student teachers
. . .
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6. Time management skills
David Allen’s, Getting things done
Stephen Covey’s, 7 Habits
Plus, working with a team, starting early, documenting, . . .
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Habits - 6/30
7. Diagnosis of high attrition:
What we teach is often impractical
→ computability, Turing machines, algorithms, . . .
Students “know” they won’t find a job with what we teach
Students intensely dislike theory
Solution:
→ more Java programming
→ more systems
→ less theory
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8. Problem is viewed as:
The Nintendo generation is taught CS by a generation of faculty
that views CS as applied mathematics.
For Nintendo generation CS = Facebook, Warcraft, Internet, . . .
For faculty CS = floating point arithmetic, . . .
→ need to make curriculum au courant.
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9. Guzdial & Soloway:
Fight the “Hello, World” approach to CS
Instead: Xerox PARC “Dynabook”
→ learn CS by creating media
→ sound synthesis with “Squeak”
Teach “old concepts” with “new media”
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Solutions - 9/30
10. We ask the question:
is it true that our students are theory averse?
We surveyed 100 students at McMaster and found that:
75% are satisfied or very satisfied with learning
theoretical/foundational material
65% agree or strongly agree that theoretical content is very
relevant to their field of study
(CS, SE, mechatronics, embedded systems)
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Our study - 10/30
11. Satisfaction by intended career path
Full study: http://goo.gl/56n9B
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Our study - 11/30
12. True we examined seniors; but . . .
Reges, Back to basics in CS1 and CS2, SIGCSE 2006.
Study from University of Washington, CS majors.
New approach that emphasizes problem solving
→ increased student satisfaction
(other things: replaced “objects early” with “traditional procedural
approach”)
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13. The 3/4 satisfaction & approval of theory was admittedly a
surprise.
The 1/4 unhappy students:
Teaching failure
“Mercenary reasons” or just plain poor students
“Legacy prejudice”
“Customer mentality”
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14. The instructor can make the material more:
Interesting
Relevant
Motivated
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15. Interesting:
An alphabet is a finite, non-empty set of distinct symbols, denoted
usually by Σ.
e.g., Σ = {0, 1} (binary alphabet)
Σ = {a, b, c, . . . , z} (lower-case letters alphabet)
A string, also called word, is a finite ordered sequence of symbols
chosen from some alphabet.
e.g., 010011101011
|w| denotes the length of the string w.
e.g., |010011101011| = 12
The empty string, ε, |ε| = 0, is in any Σ by default.
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16. Since long ago “markings” have been used to store & process
information. The following pictures are from the Smithsonian
Museum of Natural History, Washington D.C.
Engraved ocher plaque
Blombos Cave, South Africa
77,000–75,000 years old
Ishango bone
Congo, 25,000–20,000 years old
leg bone from a baboon; 3 rows of
tally marks, to add or multiply (?)
Reindeer antler with tally marks
La Madeleine, France
17,000–11,500 years old
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17. About 8,000 years ago, humans were using symbols to represent
words and concepts. True forms of writing developed over the next
few thousand years.
Cylinder seals were rolled
across wet clay tablets to
produce raised designs
cylinder seal in lapis lazuli,
Assyrian culture, Babylon,
Iraq, 4,100–3,600 years ago
Cuneiform symbols stood for
concepts and later for sounds and
syllables
cuneiform clay tablet, Chakma,
Chalush, near Babylon, Iraq,
4,000–2,600 years ago
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Interesting - 17/30
22. Relevant:
Bellman-Ford vs Dijkstra as routing algorithms
RIP - Routing Internet Protocol (RFC 2453)
vs
OSPF - Open Shortest Path First (RFC 2328)
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23. In 2010, 28,833 Terabytes of data were transmitted over the
CANARIE Network, a 50% increase from the year before.
That’s equivalent to:
5,689,951 hours of CD quality audio
the images collected by 642 Hubble Telescopes
20 times the annual residential Internet traffic in Canada
Perceptions - Blanchard & Soltys May 4, 2012 - v1.1 Relevant - 23/30
25. Virgin Islands — huge data hub
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26. Two functions of routing protocols:
1. They compute the set of shortest paths.
2. Respond to network failure & topology changes by continually
updating routing information.
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27. Example Of Distance-Vector Update
Destination Distance Route
Net 1
Net 2
Net 4
Net 17
Net 24
Net 30
Net 42
0
0
8
5
6
2
2
direct
direct
Router L
Router M
Router J
Router Q
Router J
Destination Distance
Net 1
Net 4
Net 17
Net 21
Net 24
Net 30
Net 42
2
3
6
4
5
10
3
(a) (b)
(a) is existing routing table
(b) incoming update (marked items cause change)
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28. Motivation:
Why prove correctness of algorithms?
As far as the fundamental science is concerned, we still certainly do
not know how to prove programs correct. We need a lot of steady
progress in this area, which one can foresee, and a lot of
breakthroughs where people suddenly find there’s a simple way to
do something that everybody hitherto has thought to be far too
difficult
C.A.R. Hoare
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29. Software engineers know many examples of things going terribly
wrong because of program errors; their particular favorites are the
following two
The blackout in the American North-East during the summer
of 2003
The Ariane 5, flight 501, the maiden flight of the rocket in June 4,
1996, ended with an explosion 40 seconds into the flight
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30. Questions?
∗ ∗ ∗
References:
Blanchard, Undergraduate Computer Science Students: Measuring
Perception, Marketing and Satisfaction, 2011
available at http://goo.gl/56n9B
Guzdial & Soloway, Teaching the Nintendo Generation to Program,
Communications of the ACM, 2002
Beaubouef, Why CS students need math, SIGCSE, Vol 34, No 4,
2002.
Howles, Preliminary results of a longitudinal study of computer
science student trends, behaviors and preferences, Consortium of
Computing Sciences in Colleges, 2007.
Reges, Back to Basics in CS1 and CS2, SIGCSE 2006.
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