Computing for All: Labor Projections, CS K-12 Stds., Computational Thinking Friday, May 8, 2015 Bauer-Beaty, Green Lake Center, WI Joe Kmoch

How many of you... How many of you teach computer science? How many of you use computing technologies fairly regularly in your courses? Have heard about / Know something about – Background Polya, Bloom, SCANS, P21 – 21 st Century Skills, Career Clusters – Workforce issues related to CS and IT? – New CSTA CS K-12 Standards – Computational Thinking – CS counting for Math credit 2

B ACKGROUND 3

Polya’s Four Steps to Problem Solving Understand the problem Design and plan a solution Implement that solution Evaluate that solution How to Solve It,1945 4

Bloom’s Taxonomy of Educational Objectives: Cognitive Domain Higher order (eg critical thinking) – Creating – Evaluating – Analyzing Lower order – Applying – Understanding – Remembering 1956,

21 st Century Skills Four C’s – Collaboration – Communication – Creativity and Innovation – Critical Thinking and Problem Solving + Employability and soft skills (learning and career skills) + Basic computing application skills (founded 2002) Similar to (based on?) SCANS Report (1991) 6

Career Cluster project IT Career Cluster and STEM Career Clusters created along with 14 others around 2002 IT has four pathways – Programming and Software Development – Web and Digital Communications – Information Support and Services – Network Systems (see Deborah Seehorn, “Computer Science: The Big Picture”, blog post 5/22/

ACM/CSTA Model Curriculum for K-12 Computer Science ACM (Association of Computing Machinery) is known for developing computer science curricula at the post-secondary level This was ACM’s (Association of Computing Machinery) 1st attempt to create a K-12 curriculum (2003) (after 3 attempts at HS curr) CSTA (Computer Science Teachers Association) became responsible in

W ORKFORCE AND P IPELINE I SSUES 9

Workforce and Pipeline issues Since the “dot-com bubble” burst around 2000, there has been a severe decrease in number of students involved in computing Since around 2004, the career opportunities have increased with a corresponding decrease in courses offered and schools offering high school courses So, Supply is way down, Demand is way up 10

#NAFNext Three Challenges The computing community in the US faces three significant and interrelated challenges in maintaining a robust IT workforce 1.Underproduction 2.Underrepresentation 3.Lack of a presence in K-12 education (Jan Cuny, NSF CS10K Initiative) 11

Where the STEM Jobs Will Be Projected Annual Growth of NEWLY CREATED STEM Job Openings Source: Jobs data are calculated from the Bureau of Labor Statistics (BLS), Employment Projections , available at 12

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Where the STEM Jobs Will Be Degrees vs. Jobs Annually Sources: Degree data are calculated from the National Science Foundation (NSF), Science and Engineering Indicators 2014, available at Annual jobs data are calculated from the Bureau of Labor Statistics (BLS), Employment Projections , available at STEM is defined here to include non-medical degrees and occupations. Physical Social Life Engineering Computing Sciences Mathematics Sciences Annual Job Openings Ph.D. Degrees Master’s Degrees Bachelor’s Degrees Associate’s Degrees Annual Job Openings Ph.D. Degrees Master’s Degrees Bachelor’s Degrees Associate’s Degrees 14

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Computer Science In Wisconsin 9,630 open computing jobs (growing at 3.8x the state average) 781 computer science graduates (BA or better) 67 schools teach computer science In 2014 – 342 Students Took AP Computer Science, out of those, 51 were female, 4 were Black, 9 were Mexican American or Hispanic

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Source: Bureau of Labor Statistics And These Are High Paying Jobs

This is about more than the IT Sector  Computing occupations by sector: 9 percent are in information services, 12 percent are in financial services, 36 percent are in professional and business services, 7 percent are in government and public education, and 12 percent are in manufacturing According to the College Board, studying AP Computer Science can open the pathway to 130 career areas and 48 college majors.

That’s nice data, but so what? *Slide is from Ed Lazowska The instructional practices and assessments discussed or shown are not an endorsement by ACM or the U.S. Department of Education. 21

Biology - Algorithms for DNA sequencing of human genome Brain Science - Modeling the brain as a computer CT/CS in Other Sciences, Math, and Engineering some examples from Jeannette WingJeannette Wing Chemistry - Optimization and searching algorithms identify best chemicals for improving reaction conditions to improve yields 22 Geology - Abstraction boundaries and hierarchies of complexity model the earth and our atmosphere Astronomy - Sloan Digital Sky Server brings a telescope to every child Mathematics - Four-color theorem proof Engineering (electrical, civil, mechanical …) - Boeing 777 tested via computer simulation alone, not in a wind tunnel

CT/CS in Other Areas some examples from Jeannette WingJeannette Wing 23 Economics - Automated mechanism design underlies electronic commerce, e.g., ad placement, on-line auctions Social Sciences - Statistical machine learning is used for recom- mendation and reputation services, e.g., Netflix, affinity card Medicine - Electronic health records require privacy technologies; Robotic Surgery, creating new drugs Law - Approaches include AI, temporal logic, state machines, process algebras, petri nets; Sherlock Project on crime scene investigation Entertainment - Games; Lucas Films uses 2000-node data center to produce Pirates of the Caribbean. Arts - Art (e.g., Robotticelli); Drama, Music, Photography; Programming for Musicians and Digital Artists

CSTA K-12 CS S TANDARDS 24

Context for New Standards 25 We define computer science as: “Computer science (CS) is the study of computers and algorithmic processes, including their principles, their hardware and software designs, their applications, and their impact on society.”

Organizing Structure 26

Learning Outcomes Organized by Strands 27

Five Strands in CS: Collaboration Using technology tools and resources for collaboration Computing as a collaborative endeavor 28

Five Strands in CS: Computational Thinking Problem solving Algorithms Data representation Modeling and Simulation Abstraction Connections to other fields 29

Five Strands in CS: Computing Practice and Programming Using technology resources for learning Using technology tools for the creation of digital artifacts Programming Interacting with remote information Careers Data Collection and Analysis 30

Five Strands in CS: Computers and Communication Devices Computers Troubleshooting Networks Humans vs Computers 31

Five Strands in CS: Community, Global and Ethical Impacts Responsible use Impacts of technology Information accuracy Ethics, Laws and Security Equity 32

Computing Practice and Programming Strand map CSTA K-12 CS Standards Pp

Example Strand for Level 2 Computing Practice & Programming The student will be able to: 1.Select appropriate tools and technology resources to accomplish a variety of tasks and solve problems. (Using technology resources for learning) 2.Use a variety of multimedia tools and peripherals to support personal productivity and learning throughout the curriculum. (Using technology resources for learning) 3.Design, develop, publish, and present products (e.g., webpages, mobile applications, animations) using technology resources that demonstrate and communicate curriculum concepts. (Dig artifacts) 4.Demonstrate an understanding of algorithms and their practical application. (Programming) 5.Implement problem solutions using a programming language, including: looping behavior, conditional statements, logic, expressions, variables, and functions. (Programming) 6.Demonstrate good practices in personal information security using passwords, encryption, and secure transactions. (Interacting with remote information) 7.Identify interdisciplinary careers that are enhanced by computer science. (Careers) 8.Demonstrate dispositions amenable to open-ended problem solving and programming (e.g., comfort with complexity, persistence, brainstorming, adaptability, patience, propensity to tinker, creativity, accepting challenge). (Careers) 9.Collect and analyze data that is output from multiple runs of a computer program. (Data coll and analysis) 34

C OMPUTATIONAL T HINKING 35

#NAFNext Computational Thinking as a critical base for engaging CS in K- 12 The Reason for infusing it into all areas? Computing and computer science are integral to most career paths 36

Critical Thinking + Computing Power = Making Decisions or Innovating Solutions (Think “Create, Produce, Manipulate”) What is CT? 37

The core principles of Computer Science are the basis for Computational Thinking. CT is the use of CS principles in problem domains What is CT? 38

There are 9 concepts Data Collection, Data Analysis, Data Representation Problem Decomposition, Abstraction Algorithms, Automation Simulation and Modeling, Parallelization These are all essential to computer science What are these core principles? 39

There are 5 dispositions –Confidence with complexity –Persistence in working through problems –Ability to deal with open ended problems –Ability to communicate and collaborate to achieve a common goal –Tolerance for ambiguity What are these core principles? 40

The Dispositions are important to preparing solutions to significant problems They also match well to the 8 Common Core State Standards – Mathematical PracticesCommon Core State Standards – Mathematical Practices What are these core principles? 41

Comparing CT Core Dispositions and CCSS Standards for Mathematical Practice CCSS Standards for Math PracticeComputational Thinking core dispositions 1. Make sense of problems and persevere in solving them Confidence with complexity Persistence in working through problems 2. Reason abstractly and quantitativelyAbility to deal with open ended problems 3. Construct viable arguments and critique the reasoning of others Ability to communicate and collaborate to achieve a common goal 4. Model with mathematicsTolerance for ambiguity 5. Use appropriate tools strategicallyAbility to communicate and collaborate to achieve a common goal 6. Attend to precisionPersistence in working through problems 7. Look for and make use of structureAbility to deal with open-ended problems 8. Look for and express regularity in repeated reasoning Ability to deal with open-ended problems < for-mathematical-practice/ 42

Comparing CT Core Concepts and CCSS Standards for Mathematical Practice CCSS Standards for Math PracticeComputational Thinking core concepts 1. Make sense of problems and persevere in solving them Data collection, analysis, representation Problem Decomposition/Analysis 2. Reason abstractly and quantitativelyAbstraction 3. Construct viable arguments and critique the reasoning of others Algorithms and Procedures 4. Model with mathematicsModeling & Simulation 5. Use appropriate tools strategicallyAutomation 6. Attend to precisionData collection, analysis, representation 7. Look for and make use of structureParallelization Algorithms & Procedures 8. Look for and express regularity in repeated reasoning Algorithms & Procedures < for-mathematical-practice/ 43

CCSS: Standards for Mathematical Content High School: Modeling Modeling Standards Modeling is best interpreted not as a collection of isolated topics but rather in relation to other standards. Making mathematical models is a Standard for Mathematical Practice, and specific modeling standards appear throughout the high school standards indicated by a star symbol ( ★ ). < modeling/introduction/ 44

Where do you find CT? In CS CT is a fundamental base for every new curriculum at all levels from K through 12 Code.org K-5 modules Code.org Middle School Modules Exploring CS APCS Principles 45

Here are the 9 CT concepts Data Collection, Data Analysis, Data Representation Problem Decomposition, Abstraction Algorithms, Automation Simulation and Modeling, Parallelization As you think about what you teach, can you think of a lesson, topic, unit where one or more of these concepts would appear? Stop and “chat” 46

CT Operational Definition (handout) 47

CT Building Blocks (handout) 48

CT Building Blocks (handout) 49

CT for All Teachers CT has a shared vocabulary that can be highlighted in lessons from every discipline. 50

Google.com/edu/ect Reworking their site Reworking lessons there for consistency and clarity Rollout early this summer CSTA CT-Taskforce Reworking their website Focused on CT in CS Standards and other courses Assessment ideas Identifying and developing new model lessons Any new developments with CT? 51

Resources: Computational Thinking: This presentation: NCWIT (National Center for Women and Information Technology) and other CS&IT Resources: Thank you! 52