(AP)CS Principles CE21, CSPrinciples16/4/2014

What? A new first course in computer science Alternative to CS1, not replacement Designed to be an AP course: credit/placement Collaborative: CollegeBoard, NSF, Academia (6-12/University) CE21, CSPrinciples26/4/2014

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 6/4/2014CE21, CSPrinciples3

Who? CE21, CSPrinciples46/4/2014

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 CE21, CSPrinciples56/4/2014

Who? 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 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 CE21, CSPrinciples66/4/2014

Why is this possible now? AP Courses should not be designed solely to replicate introductory college courses (which are not typically exemplary models) – Reflect knowledge of how students learn – Convey content and unifying concepts NRC report 2002, AP Science Redesign 6/4/2014CE21, CSPrinciples7

Engineering a Course and Exam CE21, CSPrinciples86/4/2014

Timeline – Big Ideas, Practices, Claims/Evidence – Pilot I: Five colleges – College Survey – College attestation/support – Test item prototype – Pilot II: 10+ colleges, 10+ high schools CE21, CSPrinciples96/4/2014

Timeline continued Necessary and sufficient conditions to continue – How do we ensure substantial buy-in? , e.g., as part of CE21! – Curricular framework finalized? – Exam format identified Deploy exam and course – 201X (X >= 5) CE21, CSPrinciples106/4/2014

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 … CE21, CSPrinciples116/4/2014

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 CE21, CSPrinciples126/4/2014

Big Ideas 1.Computing is a creative human activity that engenders innovation and promotes exploration. 2.Abstraction reduces information and detail to focus on concepts relevant to understanding and solving problems. CE21, CSPrinciples136/4/2014

Big Ideas Continued 3.Data and information facilitate the creation of knowledge. 4.Algorithms are tools for developing and expressing solutions to computational problems. CE21, CSPrinciples146/4/2014

Big Ideas Continued 5.Programming is a creative process that produces computational artifacts. 6.Digital devices, systems, and the networks that interconnect them enable and foster computational approaches to solving problems. CE21, CSPrinciples156/4/2014

Big Ideas 7.Computing enables innovation in other fields including science, social science, humanities, arts, medicine, engineering, and business. CE21, CSPrinciples166/4/2014

Computational Thinking Practices 1.Analyzing effects of computation 2.Creating computational artifacts 3.Using abstractions and models 4.Analyzing problems and artifacts 5.Communicating processes and results 6.Work effectively in teams csprinciples.org CE21, CSPrinciples176/4/2014

Claims and Evidence bit.ly/csprincbit.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. 6/4/2014CE21, CSPrinciples18

Big Idea>Key Concept>Claim 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: 6/4/2014CE21, CSPrinciples19

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. 6/4/2014CE21, CSPrinciples20

Five Pilots, One Plane Information about Pilot I (thanks to Larry Snyder) 6/4/2014CE21, CSPrinciples21

Five Campuses, Five Teachers The pilot schools and instructors … Metropolitan State College, Denver: Jody Paul UC Berkeley: Dan Garcia UC San Diego: Beth Simon UNC at Charlotte: Tiffany Barnes U Washington: Larry Snyder CE21, CSPrinciples6/4/201422

Cross-Campus Comparison I 6/4/2014 CE21, CSPrinciples 23 Title First Offering Proj Enroll MSCDLiving in a Computing World Fall (S) UC BThe Beauty and Joy of Computing Fall (S) UC SDFluency with Information Technology Fall (Q) UNC CThe Beauty and Joy of Computing Spring (S) U WComputer Science Principles Winter (Q)

Cross-Campus Comparison II 6/4/2014 CE21, CSPrinciples 24 Programming Language LecLabDisWks Total Contact MSCDScratch, HTML/CSS UC BBYOB Scratch UC SDAlice, Excel UNC CBYOB/Scratcy U WProcessing

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 CE21, CSPrinciples256/4/2014

Questions 6/4/2014CE21, CSPrinciples26