Transcript My Life as a Prof - MAPLE Lab

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Computer Science Principles:
A New AP Concept
Marie desJardins
Google CS4HS Professional Development
Workshop
UMBC, August 6, 2012
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Overview
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What is “CS Principles??
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Goals and motivation
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Six Computational Thinking Practices
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Seven Big Ideas of Computer Science
Status
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Phase I pilot courses (2011-2012)
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Phase II pilot courses (2012-2013)
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Implementation/adoption timeline
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Resources
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Hands-on time!
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Example active learning activities from pilot courses / UMBC
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What is CS Principles?
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What’s Wrong with AP CS?
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AP CS A(B)
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AP CS is the only AP course whose numbers have declined in
recent years
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The College Board dropped AP CS B after 2009
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Completely counterintuitive given the job demand!!
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Gender balance of current AP CS A is the lowest of any exam
(below 20%)
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Why is this the case?
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AP CS A(B) = Java programming
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Not what computer science is really all about
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Not appealing to many students (especially girls and minorities)
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Not tied to real problems
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Not related to bigger ideas in computer science
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AP CS Principles:
Goals and Motivation
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Only 9 states (not Maryland...) allow CS to fulfill a math or
science requirement at the HS level (none have a CS
requirement)
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Difficult for students to gain enough experience to make it into AP
CS; students need intrinsic interest to try CS as an elective
Idea: Develop an AP class focused on getting students
excited about computer science
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Especially: appeal to female and minority students
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Not just a programming class
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Relevant to the real world
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Broad view of the discipline of computer science
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Computational Thinking Practices
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Connecting computing...
to applications and problems that matter to students and society
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Developing computational artifacts...
that require creativity and problem solving
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Abstracting...
at multiple levels, from logic gates to the human genome
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Analyzing problems and artifacts...
to understand tradeoffs, strategies, and alternative solutions
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Communicating...
about problems, designs, solutions, and behaviors
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Collaborating...
to combine diverse viewpoints and skills to solve problems
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Big Ideas of Computer Science
1.
Computing is a creative activity.
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Abstraction reduces information and detail to facilitate
focus on relevant concepts.
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Data and information facilitate the creation of
knowledge.
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Algorithms are used to develop and express solutions
to computational problems.
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Programming enables problem solving, human
expression, and creation of knowledge.
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The Internet pervades modern computing.
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Computing has global impacts.
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AP CS Principles:
Status and Timeline
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Phase I Pilot Courses
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Five pilot sites in 2010-2011:
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Metropolitan State College of Denver: Living in a Computing World
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UC Berkeley: The Beauty and Joy of Computing
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UC San Diego: Fluency with Information Technology
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UNC Charlotte: The Beauty and Joy of Computing
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University of Washington: Computer Science Principles
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Ten high schools paired with ten colleges in 2011-2012
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Pilot efforts included:
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Recruitment plan for increasing enrollment of women and
underrepresented minorities
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Detailed, fine-grained course evaluation
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Phase II Pilot Courses
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Phase II pilots include:
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Portfolio component for assessment (may be used as part of the
AP exam)
Nine(?) Phase II paired university/high school pilots:
http://www.csprinciples.org/home/pilot-sites
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None in Maryland
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U Penn (South Philadelphia High School)
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Virginia Tech (Patrick Henry High School)
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AP CS Principles:
Topics and Resources
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UC Berkeley
Beauty and Joy of Computing
http://inst.eecs.berkeley.edu/~cs10/
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Abstraction
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Artificial intelligence
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3D graphics and computer
games
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Distributed computing
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Algorithms
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Limitations and future of
computing
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Programming in Scratch
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Concurrency, complexity, and
recursion
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Social implications of
computing
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University of Washington
Computer Science Principles
http://www.cs.washington.edu/education/courses/cse120/
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Image representations
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CPU / instruction execution
“Digitization” (binary
representations)
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Universal computation
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Social networking
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Algorithm design and
recursion
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Programming in Processing
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The Internet/World Wide Web
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HTML and XML
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Databases
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Lightbot 2.0 (programming
game environment)
Networks and digital
communication
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UMBC
Intro. to Computers and Programming
http://www.csee.umbc.edu/courses/undergraduate/100/Fall12/
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Grand challenges for CS
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Networks and the Internet
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Deconstructing Google
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Databases and data abstraction
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Deconstructing a computer
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Computer security and privacy
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Binary representations and
digital encoding
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Artificial intelligence
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Computer graphics and digital
entertainment
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Ethical and social implications of
computing
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The future of computing
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Programming with Scratch
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Problem solving with
algorithms
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Resources
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ACM Inroads, volume 3, number 2, June 2012
(special sections on CS Principles)
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http://csprinciples.org
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Curriculum, pilot sites
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Attesting schools:
http://www.csprinciples.org/home/about-the-project/attestation
(UMBC was the second school to sign up...)
http://collegeboard.org/csprinciples
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Active Learning Activities
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Exercise #1: Google
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Computational thinking practices: Connecting computing;
analyzing problems and artifacts
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Big ideas: Internet; data and information; global impacts
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Activity: Googlewhack, Googlefights, PageRank, Googlefail
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Create your own googlefail!
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Discussion: What happens when we post the googlefail to
our site? How long until it shows up in google? What’s
happening in between? How does PageRank work?
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Followup lab/project: Bonus points to the first student who
spots the googlefail results; compute PageRank for a simple
example network; implement PageRank on a graph
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Exercise #2: Huffman Coding
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Computational practices: Abstracting; developing
computational artifacts
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Big ideas: Abstraction; data and information
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Activity: Encode a passage from “Sam I Am” using a Huffman
encoding (preliminary exercise: translate from Huffman code)
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Discussion: Why are frequency-based encodings useful?
How much space could one potentially save? What are some
practical applications? Is Morse code a Huffman (optimal)
encoding? Does gzip use Huffman encoding?
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Followup lab/project: Implement a Huffman encoding and
print out length statistics for non-encoded and Huffmanencoded text. Find text sources that would compress a lot,
and text sources that wouldn’t compress very much.
a
l
t
o
SPC
y
w
e
!
c
m
p
s
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Decode the Message: 0111110010100101011011100011110111110110 010 00111111110 010
0110001110 010 0110001110 010 0110001110 010
0001100000100100000000110 010 011111001000000 01110
r
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Green Eggs and Ham
I am Sam
I am Sam
Do you like
green eggs and ham?
Sam I am
That Sam-I-am!
That Sam-I-am!
I do not like them,
Sam-I-am.
I do not like
I do not like
that Sam-I-am!
green eggs and ham.
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Exercise #3: Map Coloring
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Computational thinking practices: Abstracting and
collaborating
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Big ideas: Creativity; algorithms
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Activity: Find a way to color each map region (person) so
that no neighbors have the same color
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Discussion: Why is this a hard problem? How many colors
do you really need? What are some strategies? What are
some real-world problems that might require similar
strategies?
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Lab/project: Implement a backtracking search algorithm to
color a map; optionally integrate into drawing tool to let
students create their own map
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