A New Computer Science Curriculum for All School Levels in Poland

Maciej M. SysłoUniversity of Wrocław, University of Toruń,

syslo@mat.umk.pl, http://mmsyslo.pl/

Contents

2Maciej 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

The School System in Poland (2008)

1st stageintegrated

Pre-school year

7 -

96

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 allwith elements of algorithmics

Informatics for all students, 1hInformatics adv. – elective, 6h

Informatics education

3

Before 2008:ICT for all students, 2hInformatics adv. – elective, 6h

From 2015-2016:

Informatics for all students with elements of programming

Informatic

s intro

duced in our c

urriculum in

1985, never h

as been re

moved !!!

Computer Science education

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

Informatic

s as a

stand-alone su

bject on all s

chool levels !

!!

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

5Maciej M. Sysło

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

6Maciej M. Sysło

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

7Maciej M. Sysło

Computer science education in crisissome 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

8Maciej M. Sysło

Ewolucja szkoły ku elastycznemu systemowi kształcenia M.M. Sysło

UK: harmful ICT replaced by Comp Sci – 2012

9Maciej M. Sysło

September2014: Computing at SchoolOn all stages of K-12

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

ICTfor all

Maciej M. Sysło

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

11Maciej M. Sysło

Computational thinkingold 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

12Maciej M. Sysło

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: 2nd part is the same in all curricula. It includes Unified aims which

define five knowledge areas in the form of general requirements 1st part is a description of Purpose of study, formulated adequately

to the school level. 3rd 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.

13Maciej M. Sysło

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.

14Maciej M. Sysło

ICT

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

15Maciej M. Sysło

Introducing CS concepts – to kids (1-3, 4-6)

16Maciej 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

Collection of mechanical instruments for computing

17Maciej M. Sysło

School mechanical calculators

18Maciej M. Sysło

School mechanical calculators

1920

Quipu, South America

Soroban, Japan

World vice-Champion in mental calculations

19Maciej M. Sysło

Children playing with machines 6 years old student !!!

Slide rules – 400 anniversary of inventing logarithm by John Napier 20Maciej M. Sysło

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

21Maciej M. Sysło

1617

Made in 2007

Napier’s rods – 400 anniversary of inventing logarithm, in 2014

22

John Napier1550-1617

Maciej M. Sysło

25

x 25

125

+ 50

625

2 5

2

5

4

1

1

2

5

0

0

0

+

20 56

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

Schickard’s calculator, 1624

From a letter of Schickard to KeplerFound in late 50’ XX C

Replica of Schickard’s calculator, 2005

W. Schickard used round rods

24

25Maciej 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

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

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

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

29

Greedy algorithm – Dijksta’s Algorithm

Shortest path – Beaver task

Maciej M. Sysło

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

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?

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 Ist 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

Thank you for your attention

and don’t forget to: