SlideShare ist ein Scribd-Unternehmen logo
1 von 10
ALGORITHMS & PROGRAMMING
FOR KS3
LEARNING OBJECTIVES
ALGORITHMS
• What is an algorithm?
• Designing an algorithm
• Why use flowcharts or
pseudocode?
PROGRAMMING BASICS
• Program Structure
• Sequencing
• Selection
• Iteration
• Variables
STARTER
SIMON SAYS
WHAT IS AN ALGORITHM?
• An algorithm is a set of step-by-step
instructions to complete a task or solve a
problem.
• Algorithms are NOT computer programs! They help us plan and design the
computer program code that will do the task.
• Flow charts or pseudocode are useful for
developing and visualising algorithms.
REAL-WORLD ALGORITHMS
TASK ALGORITHM EXAMPLE
Building flat-pack
furniture
Affix part A to part B using the
supplied Allan key.
Making a dress Cut along the grain of the fabric.
Use of Television Press ‘Guide’ to access program
listings.
Assembly
Instructions
Sewing
Pattern
TV
Operating
Manual
SIMPLE ALGORITHM
GETTING WASHED & DRESSED STEP 1 – GET UP
1. Get out of bed.
2. Eat breakfast.
STEP 2 – WASH
1. Go to bathroom.
2. Wash face.
STEP 3 - GET DRESSED
1. Remove pyjamas.
2. Put clothes on.
1. What are the INPUTS required to
achieve the OUTPUTS required?
2. What STEPS are needed and in
which SEQUENCE?
3. Are any DECISIONS needed?
4. Is there any REPETITION in the
process?
DO: Write an algorithm for brushing your teeth!
DESIGNING
ALGORITHMS
• Computers need exact instructions
on how and when to perform a task.
• We create a program that performs
exact instructions in the algorithm.
• An algorithm written using a
flowchart or pseudocode can help
us to write effective computer
programming code.
• They help to structure and
SEQUENCE (order) the instructions.
FLOWCHART & PSEUDOCODE EXAMPLE
WHAT IS PROGRAMMING?
A Program is CODE written in a
LANGUAGE that computers
understand.
• SEQUENCE is important so that a computer does
the task in the right order.
• SELECTION is the decision to make or question to
answer. E.g. IF, THEN, ELSE. The path through a
program changes depending on the answers.
• ITERATION is looping through (repeating) a path
until we reach our goal using FOR and WHILE
statements. Iterative programming reduces the
steps required by a program.
Code contains
STATEMENTS
(single instructions)
that tell the computer what to do.
EXAMPLE
Declaring variables to store our
information for use later on.
DO: Identify the variables for the ‘brushing your teeth.’
Using iteration to loop through the steps
whilst the ‘awake’ condition remains true.
Using conditional selection to determine
the path the program will take.
REFLECTION (PLENARY)
WHAT DID YOU LEARN?
What are your key takeaways from the lesson today?
CONFIDENCE LEVEL?
1. Understood ALL of it, very confident.
2. Understood MOST of it, fairly confident.
3. Understood SOME of it and need some support. FURTHER LEARNING…
NEXT LESSON: Datatypes, Variables, Constants and Operators.

Weitere ähnliche Inhalte

Was ist angesagt?

Meetup_Consumer_Credit_Default_Vers_2_All
Meetup_Consumer_Credit_Default_Vers_2_AllMeetup_Consumer_Credit_Default_Vers_2_All
Meetup_Consumer_Credit_Default_Vers_2_All
Bernard Ong
 

Was ist angesagt? (20)

Introduction to cyclical learning rates for training neural nets
Introduction to cyclical learning rates for training neural netsIntroduction to cyclical learning rates for training neural nets
Introduction to cyclical learning rates for training neural nets
 
Learning
LearningLearning
Learning
 
Embed, Encode, Attend, Predict – applying the 4 step NLP recipe for text clas...
Embed, Encode, Attend, Predict – applying the 4 step NLP recipe for text clas...Embed, Encode, Attend, Predict – applying the 4 step NLP recipe for text clas...
Embed, Encode, Attend, Predict – applying the 4 step NLP recipe for text clas...
 
Semantical Cognitive Scheduling
Semantical Cognitive SchedulingSemantical Cognitive Scheduling
Semantical Cognitive Scheduling
 
Lecture 5 machine learning updated
Lecture 5   machine learning updatedLecture 5   machine learning updated
Lecture 5 machine learning updated
 
Machine learning with scikitlearn
Machine learning with scikitlearnMachine learning with scikitlearn
Machine learning with scikitlearn
 
Branch And Bound and Beam Search Feature Selection Algorithms
Branch And Bound and Beam Search Feature Selection AlgorithmsBranch And Bound and Beam Search Feature Selection Algorithms
Branch And Bound and Beam Search Feature Selection Algorithms
 
Kaggle Higgs Boson Machine Learning Challenge
Kaggle Higgs Boson Machine Learning ChallengeKaggle Higgs Boson Machine Learning Challenge
Kaggle Higgs Boson Machine Learning Challenge
 
Convolutional Neural Networks: Part 1
Convolutional Neural Networks: Part 1Convolutional Neural Networks: Part 1
Convolutional Neural Networks: Part 1
 
Nimrita deep learning
Nimrita deep learningNimrita deep learning
Nimrita deep learning
 
Meetup_Consumer_Credit_Default_Vers_2_All
Meetup_Consumer_Credit_Default_Vers_2_AllMeetup_Consumer_Credit_Default_Vers_2_All
Meetup_Consumer_Credit_Default_Vers_2_All
 
Logistic Regression
Logistic RegressionLogistic Regression
Logistic Regression
 
Feature selection
Feature selectionFeature selection
Feature selection
 
Deep learning summary
Deep learning summaryDeep learning summary
Deep learning summary
 
Deep learning concepts
Deep learning conceptsDeep learning concepts
Deep learning concepts
 
Algorithm and Data Structures - Basic of IT Problem Solving
Algorithm and Data Structures - Basic of IT Problem SolvingAlgorithm and Data Structures - Basic of IT Problem Solving
Algorithm and Data Structures - Basic of IT Problem Solving
 
Design & Analysis of Algorithms Lecture Notes
Design & Analysis of Algorithms Lecture NotesDesign & Analysis of Algorithms Lecture Notes
Design & Analysis of Algorithms Lecture Notes
 
Analytics Boot Camp - Slides
Analytics Boot Camp - SlidesAnalytics Boot Camp - Slides
Analytics Boot Camp - Slides
 
Deep Dive into Hyperparameter Tuning
Deep Dive into Hyperparameter TuningDeep Dive into Hyperparameter Tuning
Deep Dive into Hyperparameter Tuning
 
Deep MIML Network
Deep MIML NetworkDeep MIML Network
Deep MIML Network
 

Ähnlich wie Algorithms and Programming

L1. Basic Programming Concepts.pdf
L1. Basic Programming Concepts.pdfL1. Basic Programming Concepts.pdf
L1. Basic Programming Concepts.pdf
MMRF2
 
classVII_Coding_Teacher_Presentation.pptx
classVII_Coding_Teacher_Presentation.pptxclassVII_Coding_Teacher_Presentation.pptx
classVII_Coding_Teacher_Presentation.pptx
ssusere336f4
 
Computational thinking
Computational thinkingComputational thinking
Computational thinking
r123457
 

Ähnlich wie Algorithms and Programming (20)

DAA Unit 1.pdf
DAA Unit 1.pdfDAA Unit 1.pdf
DAA Unit 1.pdf
 
Logical Structures
Logical StructuresLogical Structures
Logical Structures
 
02 Algorithms and flowcharts - computers.pptx
02 Algorithms and flowcharts - computers.pptx02 Algorithms and flowcharts - computers.pptx
02 Algorithms and flowcharts - computers.pptx
 
Algorithms and flow charts
Algorithms and flow chartsAlgorithms and flow charts
Algorithms and flow charts
 
L1. Basic Programming Concepts.pdf
L1. Basic Programming Concepts.pdfL1. Basic Programming Concepts.pdf
L1. Basic Programming Concepts.pdf
 
Algorithmic problem sloving
Algorithmic problem slovingAlgorithmic problem sloving
Algorithmic problem sloving
 
Debbuging
DebbugingDebbuging
Debbuging
 
Chapter 09 design and analysis of algorithms
Chapter 09  design and analysis of algorithmsChapter 09  design and analysis of algorithms
Chapter 09 design and analysis of algorithms
 
Algorithm defination, design & Implementation
Algorithm defination, design & ImplementationAlgorithm defination, design & Implementation
Algorithm defination, design & Implementation
 
classVII_Coding_Teacher_Presentation.pptx
classVII_Coding_Teacher_Presentation.pptxclassVII_Coding_Teacher_Presentation.pptx
classVII_Coding_Teacher_Presentation.pptx
 
Algrithms and frowcharts.pptx
Algrithms and frowcharts.pptxAlgrithms and frowcharts.pptx
Algrithms and frowcharts.pptx
 
Beekman5 std ppt_13
Beekman5 std ppt_13Beekman5 std ppt_13
Beekman5 std ppt_13
 
Algorithm.pdf
Algorithm.pdfAlgorithm.pdf
Algorithm.pdf
 
C programming for Computing Techniques
C programming for Computing TechniquesC programming for Computing Techniques
C programming for Computing Techniques
 
Algorithm and flowchart
Algorithm and flowchartAlgorithm and flowchart
Algorithm and flowchart
 
Computer and programming language
Computer and programming languageComputer and programming language
Computer and programming language
 
Computational thinking
Computational thinkingComputational thinking
Computational thinking
 
Cse
CseCse
Cse
 
Algorithm Design and Problem Solving [Autosaved].pptx
Algorithm Design and Problem Solving [Autosaved].pptxAlgorithm Design and Problem Solving [Autosaved].pptx
Algorithm Design and Problem Solving [Autosaved].pptx
 
Basic syntax : Algorithm,Flow chart
Basic syntax : Algorithm,Flow chartBasic syntax : Algorithm,Flow chart
Basic syntax : Algorithm,Flow chart
 

Kürzlich hochgeladen

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
QucHHunhnh
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
Chris Hunter
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
negromaestrong
 

Kürzlich hochgeladen (20)

psychiatric nursing HISTORY COLLECTION .docx
psychiatric  nursing HISTORY  COLLECTION  .docxpsychiatric  nursing HISTORY  COLLECTION  .docx
psychiatric nursing HISTORY COLLECTION .docx
 
PROCESS RECORDING FORMAT.docx
PROCESS      RECORDING        FORMAT.docxPROCESS      RECORDING        FORMAT.docx
PROCESS RECORDING FORMAT.docx
 
Micro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdfMicro-Scholarship, What it is, How can it help me.pdf
Micro-Scholarship, What it is, How can it help me.pdf
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Application orientated numerical on hev.ppt
Application orientated numerical on hev.pptApplication orientated numerical on hev.ppt
Application orientated numerical on hev.ppt
 
Unit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptxUnit-IV; Professional Sales Representative (PSR).pptx
Unit-IV; Professional Sales Representative (PSR).pptx
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Key note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdfKey note speaker Neum_Admir Softic_ENG.pdf
Key note speaker Neum_Admir Softic_ENG.pdf
 
microwave assisted reaction. General introduction
microwave assisted reaction. General introductionmicrowave assisted reaction. General introduction
microwave assisted reaction. General introduction
 
General Principles of Intellectual Property: Concepts of Intellectual Proper...
General Principles of Intellectual Property: Concepts of Intellectual  Proper...General Principles of Intellectual Property: Concepts of Intellectual  Proper...
General Principles of Intellectual Property: Concepts of Intellectual Proper...
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
Python Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docxPython Notes for mca i year students osmania university.docx
Python Notes for mca i year students osmania university.docx
 
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptxBasic Civil Engineering first year Notes- Chapter 4 Building.pptx
Basic Civil Engineering first year Notes- Chapter 4 Building.pptx
 
Making and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdfMaking and Justifying Mathematical Decisions.pdf
Making and Justifying Mathematical Decisions.pdf
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
2024-NATIONAL-LEARNING-CAMP-AND-OTHER.pptx
 
Asian American Pacific Islander Month DDSD 2024.pptx
Asian American Pacific Islander Month DDSD 2024.pptxAsian American Pacific Islander Month DDSD 2024.pptx
Asian American Pacific Islander Month DDSD 2024.pptx
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Seal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptxSeal of Good Local Governance (SGLG) 2024Final.pptx
Seal of Good Local Governance (SGLG) 2024Final.pptx
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 

Algorithms and Programming

  • 2. LEARNING OBJECTIVES ALGORITHMS • What is an algorithm? • Designing an algorithm • Why use flowcharts or pseudocode? PROGRAMMING BASICS • Program Structure • Sequencing • Selection • Iteration • Variables
  • 4. WHAT IS AN ALGORITHM? • An algorithm is a set of step-by-step instructions to complete a task or solve a problem. • Algorithms are NOT computer programs! They help us plan and design the computer program code that will do the task. • Flow charts or pseudocode are useful for developing and visualising algorithms.
  • 5. REAL-WORLD ALGORITHMS TASK ALGORITHM EXAMPLE Building flat-pack furniture Affix part A to part B using the supplied Allan key. Making a dress Cut along the grain of the fabric. Use of Television Press ‘Guide’ to access program listings. Assembly Instructions Sewing Pattern TV Operating Manual
  • 6. SIMPLE ALGORITHM GETTING WASHED & DRESSED STEP 1 – GET UP 1. Get out of bed. 2. Eat breakfast. STEP 2 – WASH 1. Go to bathroom. 2. Wash face. STEP 3 - GET DRESSED 1. Remove pyjamas. 2. Put clothes on. 1. What are the INPUTS required to achieve the OUTPUTS required? 2. What STEPS are needed and in which SEQUENCE? 3. Are any DECISIONS needed? 4. Is there any REPETITION in the process? DO: Write an algorithm for brushing your teeth!
  • 7. DESIGNING ALGORITHMS • Computers need exact instructions on how and when to perform a task. • We create a program that performs exact instructions in the algorithm. • An algorithm written using a flowchart or pseudocode can help us to write effective computer programming code. • They help to structure and SEQUENCE (order) the instructions. FLOWCHART & PSEUDOCODE EXAMPLE
  • 8. WHAT IS PROGRAMMING? A Program is CODE written in a LANGUAGE that computers understand. • SEQUENCE is important so that a computer does the task in the right order. • SELECTION is the decision to make or question to answer. E.g. IF, THEN, ELSE. The path through a program changes depending on the answers. • ITERATION is looping through (repeating) a path until we reach our goal using FOR and WHILE statements. Iterative programming reduces the steps required by a program. Code contains STATEMENTS (single instructions) that tell the computer what to do.
  • 9. EXAMPLE Declaring variables to store our information for use later on. DO: Identify the variables for the ‘brushing your teeth.’ Using iteration to loop through the steps whilst the ‘awake’ condition remains true. Using conditional selection to determine the path the program will take.
  • 10. REFLECTION (PLENARY) WHAT DID YOU LEARN? What are your key takeaways from the lesson today? CONFIDENCE LEVEL? 1. Understood ALL of it, very confident. 2. Understood MOST of it, fairly confident. 3. Understood SOME of it and need some support. FURTHER LEARNING… NEXT LESSON: Datatypes, Variables, Constants and Operators.

Hinweis der Redaktion

  1. Step-by-step: Like giving directions to a friend. How do we write an algorithm? For a comic, we might draw pictures in a story board. We use flow charts and pseudocode to visualise our algorithm easily. Pseudo means ‘not the real thing’ so pseudocode is the instructions in our own words. Let’s be clear: Algorithms are NOT computer programs!
  2. When we design an algorithm, it forces us to think about the overall goal; the individual steps needed to accomplish that task. We consider the inputs required to achieve the output needed. The algorithm design process can also help us to think about different ways of solving problems. END OF SLIDE: Now write your own simple algorithm for brushing their teeth.
  3. Computers need exact Instructions! Take away the “Is water boiled” question – our while loop (ITERATION) – we could end up with a cold cup of tea! Take away the “put teabag in cup” statement and you have just hot water. Equally, the order (SEQUENCE) is important… is it milk first or last? One to discuss outside of the lesson!
  4. THIS IS WHERE PROGRAMMING COMES IN! SELECTION is important to manage the various paths through a program depending on decision points. Without selection, there would only be 1 path and the program would be ineffective and unrealistic. ITERATION is efficient and requires less processing as it managed the repetitive tasks. It keeps the algorithm simple.
  5. We learned about algorithms, what can helps us to design them, Program structure and basic programming concepts. At the beginning of the next lesson (before moving on), I would ask the students what they can recall from the last lesson. Perhaps ask different students to come out “Be the teacher” and give 1 minute mini teach on the different areas.