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A New Computer Science Curriculum for All School Levels in Poland Maciej M. Sysło University of Wrocław, University of Toruń, syslo@mat.umk.plsyslo@mat.umk.pl, http://mmsyslo.pl/http://mmsyslo.pl/

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Contents 2 Maciej M. Sysło School system in Poland and informatics education Informatics versus ICT Is Computer Science Education in crisis? Informatics education – shifts in approach Computational thinking (CT) A new curriculum The role of programming Introducing computer science concepts – examples Supporting activities

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The School System in Poland (2008) 1st stage integrated Pre-school year 7 - 9 6 10 - 12 2nd stage 13 - 15 16 - 18 Primary education Secondary education 19 - 18 Upper – high school Lower – gimnazjum, middle school Tertiary education – University Computer lessons (ICT) ICT and Informatics for all with elements of algorithmics Informatics for all students, 1h Informatics adv. – elective, 6h Informatics education 3 Before 2008: ICT for all students, 2h Informatics adv. – elective, 6h From 2015-2016: Informatics for all students with elements of programming Informatics introduced in our curriculum in 1985, never has been removed !!! Computer Science education

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Informatics education, as in 2008 ICT and Informatics in the present National Curriculum (2008): Primary education (1-6 grades), all students computer lessons (1 hour/week) – ICT Middle school (Gimnazjum, 7-9 grades), all students informatics with elements of algorithmics and Web 2.0 High School (10-12 grades) informatics (1 hour/week for a year) for all students informatics (3 hours/week for 2 years) – elective matura (final exam) – mainly on solving algorithmic problems, also data base, spreadsheet – the only experimental exam 4 Informatics as a stand-alone subject on all school levels !!!

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Informatics (CS) versus ICT Informatics (Computer Sience) is concerned with designing and creating informatics ‘products’ and ‘tools’, such as: algorithms, programs, application software, systems, methods, theorems, computers, … ICT – applications of CS (computing) – concentrates on how to use and apply informatics and other information technology tools in working with information; can be also creative Now: computer science education (CS education) – education on computer science informatics education – includes CS education, ICT in other subjects, anything in schools related to computers computing – the term not used 5 Maciej M. Sysło

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History: 1965 – … computers in education 1965 … 1985 … Informatics curricula and teaching – computer science – there was no information technology beginning of 90’ moves in education: computer science → information technology i.e.: constructing computer solutions → using ready-made tools i.e.: computer science for some students → information technology for all recent move: informatics for all based on computational thinking 6 Maciej M. Sysło

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Computer science (education) – in crisis? Q: Is computer science in crisis? a dying discipline? A crisis in university computer science (US, in 2008): the number of students enrolled in CS has fallen for several years: in 2007 dropped 49% from 2001/2002 impact on degree „production”: the number of bachelor’s degrees fell 43% between 2003/04 and 2006/07 Similar figures for UK In Poland: declining interests in high school informatics, in „matura” in informatics and in university CS and CS career On the other hand – there is still a demand for experts and specialists in computer use and applications 7 Maciej M. Sysło

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Computer science education in crisis some answers A: students have tested enough ICT in their upbringing and they want something different at a university level the traditional school and university curricula in computing are unattractive to present-day students students (but not only students) do not distinguish between using and studying (computer tools) opposed to a vocational qualification, the mission of university is to develop understanding, rather than skills only The lack of adequate CS education in high schools 8 Maciej M. Sysło

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Ewolucja szkoły ku elastycznemu systemowi kształcenia M.M. Sysło UK: harmful ICT replaced by Comp Sci – 2012 9 Maciej M. Sysło September2014: Computing at School On all stages of K-12

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Informatics education – shifts in approach 60’ – 90’: algorithmic thinking: creating programs, algorithmics, programming – there was no ICT 90’ – ICT era: step back: basic computer literacy – the capability to use today’s technology beginning of 2000: fluency with ICT – the capability to use new technology as it evolves J. Wing, 2006: computational thinking – competencies built on the power and limits of computing: 3R + computational thinking Shift: algorithmic thinking to computational thinking informatics for informatics to informatics for all 10 ICT for all Maciej M. Sysło

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Computational thinking (J. Wing) in informatics for all Includes a range of mental tools for problem solving originated in computer science: reduction and decomposition of complex problems approximation, when exact solution is impossible recursion: inductive thinking representation and modeling of data or phenomena heuristic reasoning (thinking) The influence on other disciplines – in mathematics: the purpose of computing is insight not numbers [R.W.Hemming, 1959] Applies to all other disciplines 11 Maciej M. Sysło

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Computational thinking old notions, extended meaning Extended meaning of two notions: a problem – in a wider context, not necessarily algorithmic – occurs when one has to provide a solution based on what one has learned but is not told how to do it; here – provide a computer solution programming – giving a computer something to do, since computers only run programs; hence, we have the following ‘programs’: spreadsheet, data base, presentation, website, documents, … ; a program – not necessarily an effect of using a programming language Programming should not be confused with coding – we have programming constructions independent of tools, programming methods, methodology 12 Maciej M. Sysło

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A new curriculum Structure: Introduction on the importance of computer science for our society in general and for our school students in particular Then follow the curricula for each level of education. Each curricula consists of three parts: 2 nd part is the same in all curricula. It includes Unified aims which define five knowledge areas in the form of general requirements 1 st part is a description of Purpose of study, formulated adequately to the school level. 3 rd part consists of detailed Attainment targets. The targets grouped according to their aims define the content of each aim adequately to the school level. Thus learning objectives are defined that identify the specific computer science concepts and skills students should learn and achieve in a spiral fashion through the four levels of their education. 13 Maciej M. Sysło

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A new curriculum – Unified Aims at each Level 1. Understanding and analysis of problems based on logical and abstract thinking, algorithmic thinking, algorithms and representations of information. 2. Programing and problem solving by using computers and other digital devices – designing and programming algorithms; organizing, searching and sharing information; utilizing computer applications; 3. Using computers, digital devices, and computer networks – principles of functioning of computers, digital devices, and computer networks; performing calculations and executing programs; 4. Developing social competences – communication and cooperation, in particular in virtual environments; project based learning; taking various roles in group projects. 5. Observing law and security principles and regulations – respecting privacy of personal information, intellectual property, data security, netiquette, and social norms; positive and negative impact of technology on culture, social live and security. 14 Maciej M. Sysło ICT

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A new curriculum – general comments remember: computer science ≠ programming concepts before tools, before programming there are plenty of ways to introduce/teach computer science … without computers – computer science unplugged – Bebras tasks motivate and engage students by personalization Programming programming is a tool, not a goal which programming language? – there are 3000 any, which can be used to introduce and illustrate concepts introduce new constructs when needed a program is a message for a computer and other people different languages different programming methods visual and textual languages and programming – when change visual for textual? remember: almost all application can be „programmed”: editors, data bases, webpages, … - the role of ICT 15 Maciej M. Sysło

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Introducing CS concepts – to kids (1-3, 4-6) 16 Maciej M. Sysło We use all three forms of activities: visual learning auditory learning kinesthetic learning We work in environments consisting of two stages: cooperative games and puzzles that use concrete meaningful objects computational thinking about the objects and concepts Personally, I combine my hobbies with my duties at children’s universities: collecting computing instruments and graph theory as my „research hobby” We extend, when appropriate, unplugged CS by adding … a computer The Hour of Code – introduction to (visual) programming

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Collection of mechanical instruments for computing 17 Maciej M. Sysło

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School mechanical calculators 18 Maciej M. Sysło

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School mechanical calculators 1920 Quipu, South America Soroban, Japan World vice-Champion in mental calculations 19 Maciej M. Sysło

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Children playing with machines 6 years old student !!! Slide rules – 400 anniversary of inventing logarithm by John Napier 20 Maciej M. Sysło

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Playing with machines – the Educated Monkey For 5 x 5 How to: multiply two numbers divide two numbers factor a number With another table, can be used for additions Concepts: maths basic operations, the use of a calculating instrument, algorithms Children: where we can buy these instruments !!! 1916 21 Maciej M. Sysło

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1617 Made in 2007 Napier’s rods – 400 anniversary of inventing logarithm, in 2014 22 John Napier 1550-1617 Maciej M. Sysło

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25 x 25 125 + 50 625 2 5 2525 4 1 1 2 5 0 0 0 + 2056 Traditional multiplication: Using Napier’s rods 23 First calculator Concepts: the algorithm for multiplying two number using Napier’s rods and then with pencil and paper Maciej M. Sysło

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Schickard’s calculator, 1624 From a letter of Schickard to Kepler Found in late 50’ XX C Replica of Schickard’s calculator, 2005 W. Schickard used round rods 24

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25 Maciej M. Sysło Recursion, recursive thinking – CS Unplugged Ershov, 1988: eat porridge; if the plate is empty then STOP else eat a spoonful of porridge; eat porridge Syslo, 2009: dance; if the music is not played then STOP else make a step; dance

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The Hanoi Towers 26 first, kids play and try to find „an algorithm” and calculate the number of moves for different numbers of rings results: formulate algorithms and make a table with the number of moves then they play with (against) a computer program finally, they verify initial findings Maciej M. Sysło

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Another puzzle 27 Find if a knight can visit all the board squares, each exactly once, and finish in the starting square. Only a few children can play chess but they easily learn how a knight moves and try to find if such a tour exists. Difficult task Maciej M. Sysło

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28 Another puzzle Solution (suggested): number the squares make a graph model of the night moves find if a knight can visit all the points, each exactly once, and finish in the starting point: 12, 4, 10, 11, 5, 7, 1, 9, 3, 2, 8, 6, 12 This version of the puzzle appears to be much easier Concepts: graph models algorithm Hamiltonian graphs Maciej M. Sysło

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29 Greedy algorithm – Dijksta’s Algorithm Shortest path – Beaver task Maciej M. Sysło

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30 Kids are working with real situation – motivates them: Find your house and your school on the Google map Find your way to/from school Find shortest paths (distance and time) to/from school by different transportation means: on foot, by bicycle, by car Which is the shortest path (time/distance) to school? Shortest path Maciej M. Sysło

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Typical approach, a greedy type: the nearest neighbor method. It doesn’t work ! However it works when you go from Diamond to Einstein !!! Remember: Dijkstra’s algorithm which a greedy method is optimal 31 Shortest path – PISA task Concepts: graph models algorithm greedy approach shortest paths Dijkstra’s algorithm Maciej M. Sysło From Einstein to Diamond it takes 31 min – which way?

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32 Teacher preparation – a teacher is the most important technology standards, evaluation and support in the classroom in-service training at universities – based on standards Web service – materials, MOOCs Our goal: a computer science teacher should be prepared as a I st degree computer science graduate (3 years of study) Comments to the curricula of other subjects how to use computational thinking in solving problems coming from other areas PBL and flipped learning – off school activities of students – extra hours of school learning Computer science oriented tasks in school tests Supporting activities Maciej M. Sysło

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Thank you for your attention and don’t forget to:

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