Analysing Conceptual Content of International Informatics Curricula for Secondary Education Erik Barendsen Tim Steenvoorden ISSEP, October 13, 2016
Domein B: Basisbegrippen en vaardigheden Subdomein B1: Gegevensrepresentatie in een computer 5. De kandidaat kan gangbare digitale coderingen van gegevens beschrijven en toepassen. Subdomein B2: Hardware 6. De kandidaat kan de functies van een computer benoemen, aangeven welke hardware en bijbehorende gangbare randapparatuur deze functies uitvoeren en de wisselwerking tussen deze functies beschrijven. Ontwikkelen De kandidaat kan, voor een gegeven doelstelling, programmacomponenten ontwikkelen in een imperatieve programmeertaal; daarbij programmeertaalconstructies gebruiken die abstractie ondersteunen; programmacomponenten zodanig structureren dat ze door anderen gemakkelijk te begrijpen en te evalueren zijn. Inspecteren en aanpassen De kandidaat kan structuur en werking van gegeven programmacomponenten uitleggen; zulke programmacomponenten aanpassen op basis van evaluatie of veranderde eisen. Subdomein B3: Software 7. De kandidaat beheerst eenvoudige datatypen, programmastructuren en programmeertechnieken. Computational Thinking: (CT) The student will be able to: Savoirs Capacités Observations Algorithmes simples - rechercher un élément dans un tableau trié par une méthode dichotomique ; - trier un tableau par sélection ; - ajouter deux entiers exprimés en binaire. 4.1 Algorithms A pupil should understand what an algorithm is, and what algorithms can be used for. KEY STAGE 1 Algorithms are sets of instructions for achieving goals, made up of pre-defined steps *the how to part of a recipe for a cake+. Algorithms can be represented in simple formats [storyboards and narrative text]. They can describe everyday activities and can be followed by humans and by computers. Computers need more precise instructions than humans do. Steps can be repeated and some steps can be made up of smaller steps. Comprendre un algorithme et expliquer ce qu'il fait. Modifier un algorithme existant pour obtenir un résultat différent. Concevoir un algorithme. Programmer un algorithme. S'interroger sur l'efficacité d'un algorithme. On présente simultanément les notions d'algorithme et de programme, puis on les distingue. L'objectif est une compréhension de ces algorithmes et la capacité à les mettre en œuvre. Les situations produisant une erreur (division par zéro, dépassement de capacité) sont mises en évidence. 1. Use the basic steps in algorithmic problemsolving to design solutions (e.g., problem statement and exploration, examination of sample instances, design, implementing a solution, testing, evaluation). 2. Describe the process of parallelization as it relates to problem solving. 3. Define an algorithm as a sequence of instructions that can be processed by a computer. 4. Evaluate ways that different algorithms may be used to solve the same problem. 5. Act out searching and sorting algorithms. 6. Describe and analyze a sequence of instructions being followed (e.g., describe a character s behavior in a video game as driven by rules and algorithms). 7. Represent data in a variety of ways including text, sounds, pictures, and numbers.
Computing in Secondary Education Workshop:15-19September2014,Leiden,theNetherlands
Documents
Documents France (2012)
Documents France (2012) CAS (2012)
Documents France (2012) CAS (2012) CSTA (2011)
Documents France (2012) CAS (2012) CSTA (2011) the Netherlands (2007)
Documents France (2012) CAS (2012) CSTA (2011) the Netherlands (2007) the Netherlands (2016)
Method Step 1 Coding concepts in curriculum documents Step 2 Categorising concepts Step 3 Quantitative analysis Step 4 Zooming in: in-depth analysis
Step 1 Coding concepts in curricula documents (Standardised) concept codes image file function instruction server social media string web browser
Mathematics Data Algorithms Graphics Rest Architecture Usability Modelling Networking Engineering Society Intelligence Security Programming ACM/IEEE (2013)
Step 2 Categorising concepts Knowledge categories Algorithms Data Networking Society
Step 2 Categorising concepts (Standardised) concept codes image file function instruction server social media string web browser Knowledge categories Algorithms Data Networking Society
Step 3 Quantitative analysis (1) CSTA CAS France 1. Algorithms (44) 2. Engineering (40) 3. Architecture (37) 4. Society (30) 5. Networking (27) 1. Algorithms (44) 2. Networking (40) 3. Architecture (38) 4. Data (33) 5. Programming (19) 1. Data (28) 2. Programming (15) 3. Architecture (14) Networking (14) 4. Algorithms (13) NL 2007 NL 2016 (core) NL 2016 (comlete) 1. Architecture (13) 2. Data (12) 3. Engineering (10) 4. Networking (4) Rest (4) 1. Programming (18) 2. Engineering (17) 3. Data (11) 4. Society (10) 5. Architecture (9) 1. Programming (22) 2. Architecture (19) Society (19) 3. Data (18) Engineering (18)
Step 3 Quantitative analysis (1) CSTA CAS France 1. Algorithms (44) 2. Engineering (40) 3. Architecture (37) 4. Society (30) 5. Networking (27) 1. Algorithms (44) 2. Networking (40) 3. Architecture (38) 4. Data (33) 5. Programming (19) 1. Data (28) 2. Programming (15) 3. Architecture (14) Networking (14) 4. Algorithms (13) NL 2007 NL 2016 (core) NL 2016 (comlete) 1. Architecture (13) 2. Data (12) 3. Engineering (10) 4. Networking (4) Rest (4) 1. Programming (18) 2. Engineering (17) 3. Data (11) 4. Society (10) 5. Architecture (9) 1. Programming (22) 2. Architecture (19) Society (19) 3. Data (18) Engineering (18)
Step 3 Quantitative analysis (1) CSTA CAS France 1. Algorithms (44) 2. Engineering (40) 3. Architecture (37) 4. Society (30) 5. Networking (27) 1. Algorithms (44) 2. Networking (40) 3. Architecture (38) 4. Data (33) 5. Programming (19) 1. Data (28) 2. Programming (15) 3. Architecture (14) Networking (14) 4. Algorithms (13) NL 2007 NL 2016 (core) NL 2016 (comlete) 1. Architecture (13) 2. Data (12) 3. Engineering (10) 4. Networking (4) Rest (4) 1. Programming (18) 2. Engineering (17) 3. Data (11) 4. Society (10) 5. Architecture (9) 1. Programming (22) 2. Architecture (19) Society (19) 3. Data (18) Engineering (18)
Step 3 Quantitative analysis (2) 25% 24% CSTA CAS France Netherlands 2007 Netherlands 2016 (core) Netherlands 2016 (complete) 22% 19% 20% 22% 19% 20% 22% 8% 16% 13% 10% 13% 13% 11% 11% 10% 13% 7% 6% 15% 12% 7% 8% 14% 8% 10% 9% 9% 13% 6% 13% 2% 4% 11% 1% 0% Data Architecture Networking Algorithms Engineering Programming 12% 11% 4% 0% 10% 9% 8% 7% 7% 6% 4% 5% 4% 4% 4% 4% 4% 3% 2% 2% 2% 2% 2% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% Society Mathematics Modeling Security Rest Usability Intelligence 2%
Step 4 Zooming in: Data CSTA CAS France Netherlands 2007 Netherlands 2016 (core) Netherlands 2016 (complete) 16% 25% 22% 13% 10% 8% Data
Step 4 Zooming in: Algorithms CSTA CAS France Netherlands 2007 Netherlands 2016 (core) Netherlands 2016 (complete) CAS 15% 22% 12% 7% 8% 0% Algorithms
Step 4 Zooming in: Engineering CSTA CAS France Netherlands 2007 Netherlands 2016 (core) Netherlands 2016 (complete) 19% 20% 14% 8% 10% 4% Engineering
Step 4 Zooming in: Society France CAS CSTA CSTA CAS France Netherlands 2007 Netherlands 2016 (core) Netherlands 2016 (complete) algorithms information algorithms data computational thinking languages programs programming & practice machines computers communication computers & devices 11% 12% 11% collaboration society & ethical issues 1% 4% 0% Society
Step 4 Zooming in: Rest CSTA CAS France Netherlands 2007 Netherlands 2016 (core) Netherlands 2016 (complete) 7% 0% 0% 1% 0% 0% Rest
Wrap up Documents Differences in emphasis Method Quickly code and characterise Large intercoder agreement Helped to develop new Dutch curriculum Easily extensible with new documents