(AP)CS Principles

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(AP)CS Principles

• www.csprinciples.org
• www.collegeboard.com/html/computerscience/

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What?

• A new first course in computer science

Collaborative CollegeBoard, NSF, Academia
(6-12/University)
Designed to be an AP course credit/placement
Alternative to CS1, not replacement
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Why toward APCSprinciples?

• Why isnt this CSPrinciples, why AP?
• Entry into high schools and colleges
• 2,000 audited AP(CS) teachers
• National standard for curriculum/test
• Single point of national leverage
• States are very, very, very different

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Who?
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Process and Content

• How are we designing and building this course?
• Who is behind the development
• What is the process used
• What will be in this course?
• Computational Thinking Skills
• Content
• Pedagogy

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Who?

• Dan Garcia
• Joanna Goode
• Susanne Hambrusch
• Michelle Hutton
• Deepak Kumar
• Jim Kurose
• Andrea Lawrence
• Richard Pattis
• Katie Siek
• Beth Simon
• Larry Snyder
• Lynn Stein
• Fran Trees
• Lien Diaz
• Cameron Wilson
• Jan Cuny
• Kathy Haynie

• Don Allen
• Christine Alvarado
• Owen Astrachan
• Stacey Armstrong
• Tiffany Barnes
• Amy Briggs
• Charmaine Bentley
• Mark Guzdial
• Rich Kick
• Jody Paul
• Chris Stephenson
• Duane Bailey
• Gail Chapman
• Tom Cortina
• Stephen Edwards

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Timeline

• 2009-2010
• Big Ideas, Practices, Claims/Evidence
• 2010-11
• Pilot I Five colleges
• College Survey
• College attestation/support
• Test item prototype
• 2011-12
• Pilot II 10 colleges, 10 high schools

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Timeline continued

• Necessary and sufficient conditions to continue
• How do we ensure substantial buy-in?
• 2012-2013, e.g., as part of CE21!
• Curricular framework finalized?
• Exam format identified
• Deploy exam and course
• 201X (X gt 5)

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From Process to Product

• What will be in this course?
• Pilot courses are exemplars
• Seven big ideas
• Six computational thinking practices
• 30 claims each with 2-5 evidence statements,
  total of 117
• From bits to NP to modeling to

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Wheres the Programming?

• To that end solving computational problems and
  exploring creative endeavors, the course
  highlights programming as one of the seven big
  ideas of computer science, because programming is
  among the creative processes that help transform
  ideas into reality.
• Course rational, csprinciples.org

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Big Ideas

• Computing is a creative human activity that
  engenders innovation and promotes exploration.
• Abstraction reduces information and detail to
  focus on concepts relevant to understanding and
  solving problems.

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Big Ideas Continued

• Data and information facilitate the creation of
  knowledge.
• Algorithms are tools for developing and
  expressing solutions to computational problems.

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Big Ideas Continued

• Programming is a creative process that produces
  computational artifacts.
• Digital devices, systems, and the networks that
  interconnect them enable and foster computational
  approaches to solving problems.

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Big Ideas

• Computing enables innovation in other fields
  including science, social science, humanities,
  arts, medicine, engineering, and business.

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Computational Thinking Practices

• Analyzing effects of computation
• Creating computational artifacts
• Using abstractions and models
• Analyzing problems and artifacts
• Communicating processes and results
• Work effectively in teams
• csprinciples.org

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Claims and Evidence bit.ly/csprinc

• Big Idea Abstraction reduces information and
  detail to focus on concepts relevant to
  understanding and solving problems.
• Key Concept II.A. Computational systems and
  problems are developed, analyzed, and solved
  using multiple levels of abstraction.

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Big IdeagtKey ConceptgtClaim

• Claim 5 The student can use abstractions and
  models to solve computational problems and
  analyze systems.
• Evidence for Claim 5 Student work is
  characterized by

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Evidence statements for 5

• 5a. Explanation of how data, information or
  knowledge are represented at different levels of
  abstraction.
• 5b. Use of simulation and randomness to analyze
  and solve problems.
• 5c. Explanation of how abstractions are used in
  software systems at many levels, ranging from
  programming languages to operating systems to the
  Internet.
• 5d. Explanation of the abstractions comprising
  the physical layers of computing hardware,
  including gates, chips, and components.

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Future work

• Oversee pilot courses, analyze the outcomes of
  the pilots, prepare for next, larger pilot,
  LARGER PILOT
• Gain consensus on claims and evidence
• Develop prototype exam questions
• Gather support for next phase of project, letters
  of attestation

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Questions

• http//www.csprinciples.org/pilots