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Workshop on ACARA Digital Technologies Curriculum:

Workshop on ACARA Digital Technologies Curriculum:. Paul Herring Curriculum Leader - IT St Peters Lutheran College Brisbane, Queensland. Background Narrative. My Tassie connection The Hutchins School – 85-87 Tasmanian Computing Curriculum second to none

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Workshop on ACARA Digital Technologies Curriculum:

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  1. Workshop on ACARA Digital Technologies Curriculum: Paul HerringCurriculum Leader - IT St Peters Lutheran College Brisbane, Queensland

  2. Background Narrative • My Tassie connection • The Hutchins School – 85-87 • Tasmanian Computing Curriculum second to none • Many firsts – teaching 1 & 2’s complement arithmetic to year 10! • New Computing Labs – 16k sideways RAM! • Awesome caring community • AIP – Tasmania Branch – Prof.Delbourgo - father & sons • My qualifications • Physics; MACS CP, • Professional Programmer & IS Designer – EDOMS – 25k+ code • Teaching – 33+ yrs; Christchurch, Hobart, Kooralbyn, Brisbane • My interest in Computational Thinking • & the new Digital Technologies Curriculum • ELH – August 2013, Lorne, Vic. – thanks Jill!Personal – married, 5 kids, 6 grandchildren In 1994, I created The Kooralbyn International School’s School Achievement Program inDigital TechnologiesThis initiative was awarded a Federal Award in 1996 for ‘Best Practice in IT’

  3. Why ‘ACARA Digital Technologies’? And why is Computational Thinking/Coding so foundational to this new curriculum? Overview of Curriculum Practical Session 1 - Coding with Visual ‘Blocky’ Interfaces An introduction to strategies for implementation Practical Session 2 - Coding with Textual/Scripting Interfaces Group Forum Introduction to Design and Pedagogical Issues Practical Session 3 – Algorithm Design environments Implications & Action Plans -Brainstorming & Sharing/Reflection Conclusion – take home message & resources Computational Thinking is @ the core:

  4. A desire for National Standards A new to update the curriculum to reflect the significant changes in the whole ICT and ICTE environment A growing awareness of the impact of Computational Thinking • 3 Game Changers: • fabrication (3D printing); • physical computing (robotics); • programming - ground swell of coding See Gary Stager - http://www.inventtolearn.com/about-the-book/ My humble opinion is that if we work with our young people to develop their skills in innovation, design and "needs" analysis in combination with computational thinking skills then we are facilitating the development of a generation of visionaries and problem solvers not just "code monkeys". Danielle Neale - Serial Entrepreneur | Innovation Consultant Why ‘ACARA Digital Technologies’?

  5. “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 soufflé, 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 Ultimately, what is needed is a shift in mindsets, so that people begin to see coding not only as a pathway to good jobs, but as a new form of expression and a new context for learning. - Mitchel Resnick The 4th R (with no R!): Reading, wRiting, aRithmetic & Computational Thinking

  6. The 4th R (with no R!): Reading, wRiting, aRithmetic& Computational Thinking These is a potential tsunami coming • of needed change; • of lack of qualifications; • of serious redefinition of some of what we teach, not just how we teach. Challenges: • how many IT teachers; • how many Maths, Science or Engineering? • How many disliked Mathsat school • do you have similar feelings towards coding?

  7. “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/ “Positioning coders as artists, and programming as painting, students can be taught the skills and given the encouragement to produce individual work, enabling them to see the personal benefit and reward. We must encourage Britain’s young people to innovate and aspire to coding careers, with the same aspiration that people pursue the dream of becoming a footballer.” • DJ Adams - Enterprise Architect & Open Source Programmer Coding is the new black

  8. Coding is the new black • “Computational thinking encompasses • logical thinking, • precision, • rigour and • creativity • Those last two terms are not what some people might put together, but there is a lot of creativity in what some folk class as a science, and others, like me, class as a craft” • “With computational thinking skills a person can better get to grips with problems, find solutions, be creative and find expression – all at the same time. • And it gives them a fighting chance of not just surviving, but blossoming in the data tsunami that is brewing under the covers of the everyday world.” • Pat Nice, CEO, open source and cloud provider Reconnix

  9. “Computational thinking will be a fundamental skill used by everyone in the world. To reading, writing, and arithmetic, let’s 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- Hour of Code Video (5 min. version)- in Edmodo Folder Prof. Jeannette M. Wing

  10. "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?

  11. "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?

  12. “The tinkering approach is characterized by a playful, experimental, iterative style of engagement, in which makers are continually reassessing their goals, exploring new paths, and imagining new possibilities. Tinkering is undervalued (and even discouraged) in many educational settings today, but it is well aligned with the goals and spirit of the progressive-constructionist tradition—and, in our view, it is exactly what is needed to help young people prepare for life in today’s society.”‘DESIGNING FOR TINKERABILITY’ - MITCHEL RESNICK AND ERIC ROSENBAUM Tinkering – part of the Computational Thinking continuum

  13. “Computational Thinking (CT) is a problem-solving process thatincludes (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. Logicallyorganizing and analyzing data Representing data through abstractions such as models and simulations Automating solutions through algorithmic thinking 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 K–12 Education

  14. “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 Persistence leads to resilience – the most importance character attribute that is predictive of future success in business Operational Definition for K–12 Education

  15. "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

  16. 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 it’s done right. • Shuchi Grover- computer scientist and educator Lack of Computational Thinking in Curriculum

  17. ‘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 mathscurriculum. 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

  18. The US Scene • In 2012, only 24,782 students in the United States out of over 14million 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 (STEMx) 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

  19. In NSW (2011) < 6% of Year 12’s studied any IT subject (in terms of the girls it’s 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 Schoolhttps://groklearning.com/challenge Australia is worse!

  20. ‘Education Secretary Michael Gove sets out plans for thenational 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?

  21. Career Growth STEM= Science, Technology, Engineering and Mathematics

  22. Degrees vs Jobs STEM= Science, Technology, Engineering and Mathematics

  23. Degrees vsJobs – USA Stats http://code.org/stats

  24. Degrees vsJobs – USA Stats http://code.org/stats

  25. “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:

  26. “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:

  27. IT Careers – 4 Streams http://www.news.com.au/technology/sci-tech/robots-to-replace-almost-50-per-cent-of-the-work-force/story-fn5fsgyc-1226729696075

  28. 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:

  29. “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

  30. (based on global energy consumption trends): • Comeback of governments • Digitization • The Internet of things, • Automation everywhere, and • Intelligent alarming • Everything as a service • Sustainability • Geographical shift • Augmented reality, • eg. Central QldUniuses augmented reality to coach train drivers • Wearable devices, and • Home automation. - Simon Fuller and Michael Postula, Schneider-Electric (ACS Seminar: Brisbane 21 August) CT & the Top 5 Megatrends

  31. 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: • Business model disruption • Competencies and skill sets of your people • Segmentation - end-user solutions - customized and personalized - Simon Fuller and Michael Postula, Schneider-Electric (ACS Seminar: Brisbane 21 August) CT & the Top Megatrends

  32. 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

  33. “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.” • MonashUni Courses in Computational Thinking:

  34. 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 as divide and conquer in any domain. Computational Thinking means being able to:

  35. Apply new computational methods to their problems, Reformulate problems to be amenable to computational strategies, Discover new science through analysis of ‘big’ data • eg. Learning Analytics 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:

  36. 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.” • SaketNavlakha& ZivBar-Joseph, Lane Center for Computational Biology and Machine Learning Department, School of Computer Science, Carnegie Mellon University. 8 November 2011 Computational Thinking & Biology

  37. Two significant areas: Biosemiotics: Biosemioticsis the characterization of the symbolic representations within life, which is filled with digitally-coded symbolic messages. Biocybernetics: Biocyberneticsinvolves self-sustaining systems that integrate different levels of information and its processing, including controls and feedback, within biological systems.  CT & Bioinformatics:

  38. “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

  39. “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

  40. “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 informationmost 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

  41. 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

  42. “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

  43. “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 <condition B>, since <cause A>” or more clearly, “<Condition B> is true because of <Cause A>”. That is, <Cause or Reason A> leads to the conclusion of <Condition or Statement B>. 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 senselogically. “ - see ‘Defending the Apostle Paul: Weighing the Evidence’ Computational Thinking in Theology

  44. 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 you’re a Wall Street algorithm and you’re five microseconds behind, you’re a loser.” “We’re 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; that’s a kind of manifest destiny.” • Kevin SlavinTED Talk - http://www.ted.com/talks/kevin_slavin_how_algorithms_shape_our_world.html Computational Thinking & Business

  45. Many of the concepts, skills, and dispositions are not new. So how is Computational Thinkingdifferent 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?

  46. algorithms • sequences, • loops/iterations • parallelism, • events, • conditionals/selection • operators, & data cryptography & encryption machine intelligence computational biology search recursion heuristics Critical Thinking skills Entrepreneurial enabling (innovation) • are these skills & disciplines currently taught in the KLAs? • for more detail see ACEC 2012 Presentation The Elements of Computational Thinking:

  47. A return of sorts 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

  48. 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 • details and Year Level breakdown in another session ACARA Digital Technologies – Summary:

  49. Computational Thinking in the Classroom

  50. Uses LUA

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