1. Implementing the Digital Technologies Curriculum in the High School Justification, Issues & Ideas Paul Herring St Peters Lutheran College

2. Digital Technologies embraces Computational Thinking Justification: What is Computational Thinking & why is it important Issues: Tales from the Tablet face doing Computational Thinking in the classroom issues and potential Ideas: The future of Computational Thinking some suggestions Computational Thinking is @ the core: 3. Every era demands--and rewards--different skills. In different times and different places, we have taught our children to grow vegetables, build a house, forge a sword or blow a delicate glass, bake bread, create a souffl, write a story or shoot hoops. Now we are teaching them to code. We are teaching them to code, however, not so much as an end in itself but because our world has morphed: We need to teach coding to help our students craft their future. https://www.edsurge.com/guide/teaching-kids-to-code The 4th R (with no R!): Reading, wRiting, aRithmetic & Computational Thinking 4. Fast forward to 2020. What job skill must you have? Coding What we do know is, for the foreseeable future, coding is one of the most important and desirable skills there is, no matter how it evolves. http://mashable.com/2013/04/30/job-skill-future-coding/ Gary Stager: 3 game changers: fabrication (3D printing); physical computing (robotics); programming - ground swell of coding - see http://www.inventtolearn.com/about-the-book/ Coding is the new black 5. Computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, lets add computational thinking to every child's analytical ability. Computational thinking is an approach to solving problems, building systems, and understanding human behavior that draws on the power and limits of computing. Code the new literacy http://www.youtube.com/watch?v=tfiw511eAB8 Prof. Jeannette M. Wing 6. "Computational Thinking is a fundamental analytical skill that everyone, not just computer scientists, can use to help solve problems, design systems, and understand human behavior. As such, ... computational thinking is comparable to the mathematical, linguistic, and logical reasoning that is taught to all children. This view mirrors the growing recognition that computational thinking (and not just computation) has begun to influence and shape thinking in many disciplines Earth sciences, biology, and statistics, for example. Moreover, computational thinking is likely to benefit not only other scientists but also everyone else bankers, stockbrokers, lawyers, car mechanics, salespeople, health care professionals, artists, and so on. from the preface of COMPUTATIONAL THINKING - REPORT OF A WORKSHOP ON THE SCOPE AND NATURE OF COMPUTATIONAL THINKING - (c) National Academy of Sciences. What is Computational Thinking? 7. "Computational Thinking is the thought processes involved in formulating problems and their solutions so that the solutions are represented in a form that can be effectively carried out by an information-processing agent. - Cuny, Snyder, Wing Computer science is having a revolutionary impact on scientific research and discovery. Simply put, it is nearly impossible to do scholarly research in any scientific or engineering discipline without an ability to think computationally. The impact of computing extends far beyond science, however, affecting all aspects of our lives. To flourish in today's world, everyone needs computational thinking. Center for Computational Thinking at Carnegie Mellon University What is Computational Thinking? 8. Computational Thinking (CT) is a problem-solving process that includes (but is not limited to) the following characteristics: Formulating problems in a way that enables us to use a computer and other tools to help solve them. Logically organizing and analyzing data Representing data through abstractions such as models and simulations Automating solutions through algorithmic thinking (a series of ordered steps) Identifying, analyzing, and implementing possible solutions with the goal of achieving the most efficient and effective combination of steps and resources Generalizing and transferring this problem solving process to a wide variety of problems - International Society for Technology in Education (ISTE) & Computer Science Teachers Association (CSTA), USA Operational Definition for K12 Education 9. These skills are supported and enhanced by a number of dispositions or attitudes that are essential dimensions of CT. These dispositions or attitudes include: Confidence in dealing with complexity Persistence in working with difficult problems Tolerance for ambiguity The ability to deal with open ended problems The ability to communicate and work with others to achieve a common goal or solution - International Society for Technology in Education (ISTE) & Computer Science Teachers Association (CSTA), USA Operational Definition for K12 Education 10. "Computer programming is the new international language of business, and we're not teaching it in schools. Why is that? ... The fact it's not happening in junior highs and high schools is a shame given the demand for developers. There's a huge talent crunch, and people aren't connecting the dots. Parents and teachers are not talking about the need and encouraging it. Aaron Skonnard, CEO of PluralSight (Trains 250,000 professionals globally -$16 million in revenue p.a) The new international language of business 11. A generation of middle and high school students moves forward without even a cultivated awareness of computational influences on diverse fields of human endeavor. In high schools and college, misconceptions and sheer lack of awareness about computer science, as well as sub-optimal early introductory Computer Science experiences exact a heavy enrollment toll. Exposure to computing in the K-12 ecosystem could remedy this malaise--provided its done right. Shuchi Grover - computer scientist and educator Lack of Computational Thinking in Curriculum 12. A survey for the Guardian (UK) shows that so far 33% of boys and just 17% of girls have learned any computer coding skills at school Computer science must be taught as a subject in schools or the UK could lose its globally competitive position. Mike Short, President, The Institution of Engineering and Technology, UK Programming should be part of the primary maths curriculum. Learning to code should be seen in the same way as learning the skill of handwriting so children can then use it as a tool for solving problems in a wider context. Conrad Wolfram, WolframAlpha.com (From Louise Tickle, The Guardian, Tuesday 21 August 2012) The UK Scene 13. The US Scene In 2012, only 24,782 students in the United States out of over 14 million took the Computer Science Advanced Placement test. This is less than 0.7% of all AP tests taken. This at a time when five of the top ten fastest growing jobs will be in a computer related field and two of the top three top bachelors salaries are in computer science and engineering. - http://tealsk12.org/ In a 2012 report ... noted that the United States must produce 1 million more professionals in the fields of science, technology, engineering, and mathematics (STEM) over the next decade to regain its global competitiveness. Though women make up 50.8 percent of the U.S. population, they only represented 22.6 percent of those earning master's degrees in engineering in 2011. - http://www.usnews.com/education/best-graduate-schools/articles/2013/03/14/revamped-engineering-programs- emphasize-real-world-problem-solving 14. In NSW (2011) < 6% of Year 12s studied any IT subject (in terms of the girls its under 2%). Yet around 67% took Mathematics. No student entering a Science or Engineering degree would even consider avoiding Mathematics. Unfortunately, the same cannot be said for either ICT literacy (the equivalent of numeracy) or Computer Science (the equivalent of Mathematics like algebra and calculus). Dr James Curran, School of Information Technologies, University of Sydney National Computer Science School https://groklearning.com/challenge Australia is worse! 15. Education Secretary Michael Gove sets out plans for the national curriculum (July 2013): Other significant changes .... and perhaps the most significant change of all is the replacement of ICT with computing. Instead of just learning to use programmes created by others, it is vital that children learn to create their own programmes. These changes will reinforce our drive to raise standards in our schools. They will ensure that the new national curriculum provides a rigorous basis for teaching, provides a benchmark for all schools to improve their performance, and gives children and parents a better guarantee that every student will acquire the knowledge to succeed in the modern world. ... schools have a year to prepare to teach it from September 2014. https://www.gov.uk/government/speeches/education-reform-schools How is the UK responding? 16. Career Growth STEM = Science, Technology, Engineering and Mathematics 17. Degrees vs Jobs STEM = Science, Technology, Engineering and Mathematics 18. Degrees vs Jobs USA Stats http://code.org/stats 19. Degrees vs Jobs USA Stats http://code.org/stats 20. This is an amazing time to go into computing, with unprecedented opportunities. Computers are a ubiquitous and growing presence in all aspects of modern society, and thus there is huge and increasing demand for computing professionals that is far from being met by the profile of today's graduates. Computing-related careers are some of the most versatile, creative, and satisfying career choices you can make, and computational thinking and skills are valuable complements to virtually all other career areas. Maggie Eppstein, Ph.D. Chair of Computer Science, University of Vermont Career Prospects: 21. Whether your passion is to uncover the secrets of the human genome, create intelligent robots, bring history alive through mobile apps, prevent terrorism, understand human social phenomena, play the stock market, create digital art, improve health care, or invent the technologies of the future, ... computing is central to these and most modern endeavours. - Maggie Eppstein, Ph.D. Chair of Computer Science, University of Vermont Career Prospects: 22. IT Careers 4 Streams http://www.new s.com.au/techno logy/sci- tech/robots-to- replace-almost- 50-per-cent-of- the-work- force/story- fn5fsgyc- 1226729696075 23. Nobel prize-winner David Hubel of Harvard University (Medicine 1981 -Research on information-processing in the visual system) in 1995: ... This abiding tendency for attributes such as form, colour and movement to be handled by separate structures in the brain immediately raises the question how all the information is finally assembled, say, for perceiving a bouncing red ball. These obviously must be assembled but where and how, we have no idea. http://www.jameslefanu.com/articles/articlesscience-science%E2%80%99s-dead-end Great questions and careers await: 24. Improved technologies for observing and probing biological systems has only led to discoveries of further levels of complexity that need to be dealt with. This process has not yet run its course. We are far away from understanding cell biology, genomes, or brains, and turning this understanding into practical knowledge. The complexity break is very apparent ... Systems biology. Modular biological complexity by Koch C., Science, August 2012 complexity break - the resistance of biological systems to computer analysis. Great questions and careers await 25. (based on global energy consumption trends): 1) Comeback of governments 2) Digitization The Internet of things, Automation everywhere, and Intelligent alarming 3) Everything as a service 4) Sustainability 5) Geographical shift Augmented reality, Wearable devices, and Home automation. - Simon Fuller and Michael Postula, Schneider-Electric (ACS Seminar: Brisbane 21 August) CT & the Top 5 Megatrends 26. Smart cities A safer world A simpler world An emerging world A world of service A greener world The three principal ramifications of these trends are: 1. Business model disruption 2. Competencies and skill sets of your people 3. Segmentation - end-user solutions - customized and personalized - Simon Fuller and Michael Postula, Schneider-Electric (ACS Seminar: Brisbane 21 August) CT & the Top Megatrends 27. Some examples: Monash University - strategic research flagship programs: Computational Biology Machine Learning Modelling, Optimisation and Visualisation University of Queensland: Computational Science now a degree major University of Sydney: Computational Science The School of Physics : Junior levels COSC 1003 Introduction to Computational Science COSC 1903 Introduction to Computational Science (Advanced) Senior level COSC 3011 Scientific Computing COSC 3911 Scientific Computing (Advanced) University Recognition 28. To understand the living world, biologists must analyze and interpret enormous amounts of data and extremely complex systems. Consequently, they are increasingly dependent on computational approaches that evaluate data and model biological processes. The Computational Workshop for the Life Sciences Classroom is designed for teachers and lecturers in the life sciences, to empower them to inspire and inform their students. Monash Uni Courses in Computational Thinking: 29. Understand which aspects of a problem are amenable to computation Evaluate the match between computational tools and techniques and a problem Understand the limitations and power of computational tools and techniques Apply or adapt a computational tool or technique to a new use Recognize an opportunity to use computation in a new way, Apply computational strategies such divide and conquer in any domain. Computational Thinking means being able to: 30. Apply new computational methods to their problems, Reformulate problems to be amenable to computational strategies, Discover new science through analysis of large data Ask new questions that were not thought of or dared to ask because of scale, but which are easily addressed computationally Explain problems and solutions in computational terms. Computational Thinking for scientists, engineers, & other professionals also means being able to: 31. Algorithms in nature: the convergence of systems biology and computational thinking Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. Thinking computationally about biological processes may lead to more accurate models, which in turn can be used to improve the design of algorithms. Similar mechanisms and requirements are shared by computational and biological processes - Being applied to problems related to coordination, network analysis, and tracking and vision. With the rapid accumulation of data detailing the inner workings of biological systems, we expect this direction of coupling biological and computational studies to greatly expand in the future. Saket Navlakha & Ziv Bar-Joseph, Lane Center for Computational Biology and Machine Learning Department, School of Computer Science, Carnegie Mellon University. 8 November 2011 Computational Thinking & Biology 32. Two significant areas: Biosemiotics: Biosemiotics is the characterization of the symbolic representations within life, which is filled with digitally-coded symbolic messages. Biocybernetics: Biocybernetics involves self-sustaining systems that integrate different levels of information and its processing, including controls and feedback, within biological systems. CT & Bioinformatics: 33. For functional communication (including controls) to occur, both sender and receiver of each communication step must know the communication protocol and how to handle the message. In each cell, there are multiple OSs, multiple programming languages, encoding/ decoding hardware and software, specialized communications systems, error detection and correction mechanisms, specialized input/output channels for organelle control and feedback, and a variety of specialized devices to accomplish the tasks of life Programming of Life Dr. Donald E Johnson CT & Bioinformatics 34. Here, we report on the design, synthesis, and operation of a rotaxane-based small-molecule machine in which a functionalized macro-cycle operates on a thread containing building blocks in a predetermined order to achieve sequence-specific peptide synthesis. The design of the artificial molecular machine is based on several elements that have analogs in either ribosomal or non-ribosomal protein synthesis: Reactive building blocks (the role played by tRNA-bound amino acids) are delivered in a sequence determined by a molecular strand (the role played by mRNA). Sequence-Specific Peptide Synthesis by an Artificial Small-Molecule Machine Science, Vol. 339 no. 6116 pp. 189-193 (11 January 2013) They write that their machine "is a primitive analog of the ribosome." Computational Biology & Reverse Engineering 35. All known life is cybernetic. The key to understanding life is controls, not constraints.... Sophisticated functions must be instructed or actually computed by prescriptive information . Prescriptive information most often presents as a linear digital string of symbols representing decision node, logic gate, or configurable switch-setting choices. 'Constraints vs Controls' by David L. Abel, The Open Cybernetics & Systemics Journal, 2010, 4, 14-27 CT & Cybernetics 36. Prescriptive information is an algorithmic subset of functional information. Prescriptive information contains instructions to accomplish objectives based on data supplied during the execution of an algorithm Biological systems have multiple semiotic coding systems for transcription communication translation ... These message systems use techniques such as overlapping genes, messages within messages, multi-level encryption etc. Prescriptive information 37. From the information perspective, the genetic system is a pre- existing operating system of unknown origin that supports the storage and execution of a wide variety of specific genetic programs (the genome applications), each program being stored in DNA. Donald Johnson http://www.scienceintegrity.org/FirstGeneCh10.pdf CT & Over-Lapping Gene Coding 38. Romans 3:20 For by works of the law no human being will be justified in his sight, since through the law comes knowledge of sin. Classic algorithmic selection, or if-then-else construct. This phrase has the logical form: For , since or more clearly, is true because of . That is, leads to the conclusion of . Now we can analyse this passage by inserting our alternative understandings of works of the law into this logical construct, and see whether any actually make sense logically. - see Defending the Apostle Paul: Weighing the Evidence Computational Thinking in Theology 39. When a time difference of 0.8 millisec makes a significant impact on your financial world, a person with some competence in Computational Thinking is surely better able to appreciate this impact and act on that appreciation. It takes you 500,000 microseconds just to click a mouse. But if youre a Wall Street algorithm and youre five microseconds behind, youre a loser. Were running through the United States with dynamite and rock saws so that an algorithm can close the deal three microseconds faster, all for a communications framework that no human will ever know; thats a kind of manifest destiny. Kevin Slavin TED Talk - http://www.ted.com/talks/kevin_slavin_how_algorithms_shape_our_world.html Computational Thinking & Business 40. Many of the concepts, skills, and dispositions are not new. So how is Computational Thinking different from say, critical thinking or mathematical thinking? It is a unique combination of thinking skills that, when used together, provide the basis of a new and powerful form of problem solving. It is more tool oriented. It makes use of familiar problem solving skills such as: trial and error, iteration, and even guessing in contexts where they were previously impractical but which are now possible because they can be automated and implemented at much higher speeds. How then is CT Different? 41. algorithms sequences, loops/iterations parallelism, events, conditionals/selection operators, & data cryptography machine intelligence computational biology search recursion heuristics Critical Thinking skills Entrepreneurial enabling (innovation) for more detail see ACEC 2012 Presentation The Elements of Computational Thinking: 42. A return of sorts to the old road, to the traditional Computer Science course, plus new areas such as: Game Design, Cryptography & Computational Biology Students are powerfully enabled to be creative producers, not just passive users. Computational Thinking is therefore expanding horizons & opening new avenues for creativity Where this is leading 43. One of the two Technology subjects are core to end of Yr 8 Optional at Year 9 & 10 ICT for users (embedded/integrated) Digital Technology for creators/developers Only 4% of curriculum time wise same as Geography! Application of computational thinking & use of information systems as well as critical thinking skills. May include some online cyber-safety ACARA Digital Technologies 44. Computational Thinking in the Classroom 45. Uses LUA 46. A new version of SCRATCH called 'Scratch Jr': "... Children can code scenes in which characters utter words in cartoonlike thought bubbles and that may entice children to try to read them but programming the computer to advance the scenes action does not require that children know how to read. Scratch Jr 47. Computational Thinking in the Classroom Scratch, Stencyl ... 48. Googles Blockly see the code 49. Agent Sheets http://www.agentsheets.com/ 50. CT in the Classroom Corona/Lua & Unity 3D 51. Edmodo & LearnStreet Javascript & Python 52. Code Remix/Transfer Issues 53. Decades of research with children suggests that young learners who may be programming dont necessarily learn problem solving well. And many, in fact, struggle with algorithmic concepts especially if they are left to tinker in programming environments, or if the learning is not scaffolded and designed using the right problems and pedagogies. Recent research studies suggest that tween and teen student projects may point to apparent fluency as evidenced by the computational concepts used in their projects. However, probing deeper sometimes reveals significant conceptual chasms in their understanding of the computing constructs that their programs employ. Shuchi Grover, Computer Scientist & Educator Not just about Coding Algorithmic Design 54. Scratch: Pong vs Giving Change 55. Scratch implementation Change algorithm 56. SDCs & NS Charts: add nss charts http://structorizer.fisch.lu/ 57. 1. Do I really understand the problem? (a) What exactly does the input consist of? (b) What exactly are the desired results or output? (c) Can I construct an input example small enough to solve by hand? What happens when I try to solve it? (d) How important is it to my application that I always nd the optimal answer? Can I settle for something close to the optimal answer? ... 2. Can I nd a simple algorithm or heuristic for my problem? (a) Will brute force solve my problem correctly by searching through all subsets or arrangements and picking the best one? i. If so, why am I sure that this algorithm always gives the correct answer? ii. How do I measure the quality of a solution once I construct it? ... Algorithmic Design & asking the right questions: 58. Junior High Scratch algorithmic design with SDCs or NS Charts Stencyl Python Robotics; Conceptual Schema & Information Systems; Flash/HTML 5 animations Create Augmented Reality apps Maker world (Not about learning apps like Word; Excel, etc) Senior High Visual Studio (VB or C++) .Net; Lua; Unity 3D, Filemaker/Access scripting AI; Computational Biology & Cybernetics; Cryptography & Encryption Big Data analysis search sort algorithms machine learning Create Augmented Reality apps Gesture Based Apps Leap Motion Statistical analysis net traffic eg. Google Adwords (Not about learning software tools like Photoshop; & Access though may include some multimedia tools like Adobe After Effects.) What a curriculum might look like 59. Ciphertext becomes: ANOCNIEVETTNWOYAESPXRTSEHUPEETMRAZITOZZN Cryptography 60. Working with weak AI 61. Students: Code for Mobile Apps; Games Design; Computational Biology Cryptography & Encryption algorithmic design Big Data algorithms Augmented Reality development This is why using games as an example is so powerful: If you tell students that theyll learn how to create a video game, they wont focus on the math, or the skills they have to learn to get there. Theyre going to focus on what they need to do to make the games. If the goal is exciting enough, the steps to get there cease to be serious barriers. Les Miller, Professor of Computer Science at Iowa State University Create not consume: 62. ACS recommendations to assist in achieving a steady production of skilled and qualified entrants into the profession: In order to convey the in-dispensible role of ICT in our daily lives ICT should be recognized as subject in its own right (from Kindergarten through to Year 12) ICT should be a mandatory subject up to Year 10. from ACS ACARA Submission ACS Recommendations: 63. 21st Century Fluency Project: Problem Solving Creativity Analytical Thinking Collaboration Communication Ethics, Action, Accountability - from Literacy is Not enough Lee Crockett, Ian Jukes & Andrew Churches These are long term goals are our students developing these skills; are they mandated in the curriculum? What skills will students most need to succeed in the 21st century? 64. The one thing that I wish I had known about computer science (and programming more generally) earlier is that it is a profoundly creative and interdisciplinary pursuit. What you choose to apply your problem-solving to is something that demands great ingenuity in how one transforms patterns of the physical world into a digital distillation. Coding is a process of both synthesis and genesis; not only is it guided by rules and syntax, but also something you create from scratch (like you would with a painting or a novel). Jasmine Tsai Software Engineer, Hackbright Academy Profoundly Creative 65. Ultimately, the most effective motivators are autonomy (the ability to chart your own course), mastery (the ability to become an expert at something), and purpose (the idea that what you are doing serves a purpose larger than yourself). Dan Pink see Ted Talk 2009 Computational Thinking as a discipline/approach to problem solving can offer all three of these motivators Autonomy, mastery, and purpose 66. How do we fit Digital Technologies into the Curriculum? What other subjects need a revolution? How do we get the teachers with the skills or potential to attain these skills? Near Peer Coaching National & State Mentors & Consultants Computational Thinking & Digital Technologies Conferences More research on teaching of CT across the Primary & Lower Secondary years New Coding/Social Media apps Australian versions of CodeSchool, LearnStreet, Scratch Forum focussed on relevant year levels Small Business Units Where to from here? 67. Today's math curriculum is teaching students to expect -- and excel at -- paint-by-numbers classwork, robbing kids of a skill more important than solving problems: formulating them. "Rather than topics like solving quadratic equations or factorizing polynomials, Computer-Based Math focuses on using the power of math to solve real-world problems like should I insure my mobile, how long will I live, or what makes a beautiful shape, with all their rich and challenging context. see http://computerbasedmath.org/ A Maths Revolution/Reduction would help: 68. Traditionalists lost the battle professionally in the mathematical revolution that occurred a century ago but won in education. Meanwhile, computer science went ahead and got created from the insights of that revolution and turned into the world we now live in. The result? Most K-12 math students and their teachers, us, are unaware of the nature of the mathematical thinking that went on in the 20th century while the technology that surrounds us was built from it! The ultimate irony - we use 21st century technology, made possible by 20th century math and physics, to teach students how to do 19th century mathematics that they will never use! - http://climeconnections.blogspot.com.au/2013/08/the-spirit-of-math-20-computational.html A Maths Revolution 69. Computational Thinking is now being recognized as vital to our students and our worlds future progress. Computational Thinking needs to be a core part of the curriculum in our schools It is time to get serious in supporting the implementation of the ACARA Digital Technologies Curriculum It is time to help raise up teachers who are willing and able to pick up the baton and become teachers of Computational Thinking What can YOU do talk about it; share the vision; share resources; incorporate Computational Thinking into your own learning journey. Inspire and be inspired! Conclusion: 70. You should now have some idea of What is Computational Thinking & why is it important How we are implementing Computational Thinking in the classroom & some ideas to perhaps follow-up on in this regard Some sense of the likely future of Computational Thinking as part of the ACARA Digital Technologies curriculum and its extension into Years 11 & 12 Summary 71. Scoop it my collection of Computational Thinking Resources http://www.scoop.it/t/computational-thinking-in-digital-technologies ELH/Computelec Presentation: http://www.slideshare.net/StrategicITbyPFH/elh-school-tech-2013-computational- thinking QSITE Computational Thinking Presentation 2012 my first presentation on this topic http://prezi.com/pgig8-2dguqs/computational-thinking-in-digital-technologies/ ACEC Computational Thinking Presentation 2012 Perth 12 months ago http://www.slideshare.net/StrategicITbyPFH/computational-thinking-14629222 ISE Network Blog: http://isenet.ning.com/profiles/blogs/why-it-should-be-a-foundational-subject-for-all- students-in-the "Fun" Reading for Students Starting a Computer Science Related Course http://www.eecs.qmul.ac.uk/~pc/research/education/puzzles/reading/ Further Commentary: