Computational Thinking and Programming Concepts

Computational Thinking, Problem Solving, and Programming Computational Thinking

• Decomposing

• Pattern Recognition

• Abstraction

• Algorithms

Unit Overview

• 4.1 General Principles

  • Thinking Procedurally

  • Thinking Logically

  • Thinking Ahead

  • Thinking Concurrently

  • Thinking Abstractly

• 4.2 Connecting Computational Thinking and Program Design

  • Standard Searches and Sorts

  • Collections

  • Pseudocode

  • Flowcharts

  • Efficiency

• 4.3 Introduction to Programming

  • Fundamentals: Add, compare, retrieve, and store data.

  • Compound: e.g., "find the largest"

  • Features: Fixed vocabulary, grammar, syntax

  • Higher Level Languages: Needed as the complexity of systems increases, abstraction is required.

  • Translation: High to low (compiler, interpreter, virtual machine)

  • Key Concepts: Variables, constants, operators, collections, loops, branching, subprograms

Thinking Procedurally

• Definition: Turning the solution to a problem into a reproducible set of steps.

• Each step can be divided into sub-procedures with their own steps.

• Purpose: Employ a divide-and-conquer strategy by breaking down overwhelming problems into manageable sections.

• Consideration: The sequencing of steps is crucial for effective workflow.

Order of Procedures

• Identify the order of procedures in problem solving.

• Example Sequence: 2, 4, 6, 8, 10, 12, 14

• Query: What comes next?

Evaluating Activity Order

• Sequence Example: "My Day"

• Activities: asleep, wake up, get dressed, wash face, brush teeth, brush hair

• Evaluate effectiveness of the order to achieve desired outcomes.

Role of Sub-Procedures

• Structure:

  • Code before inputs

  • Step 1 → Subprocedure → Rest of Program → Returned Answer → Step 2 → Return

Thinking Logically

• Definition: Making decisions and formalizing conditions for these decisions.

• Three Steps:

  • Identify when decision-making is required.

  • Specify the decision to be made.

  • Determine conditions for the decision.

Decision-Making Requirements

• True/False Questions:

  • e.g., speed > 55?

  • e.g., speed < 40?

• Outputs:

  • "Too fast!"

  • "Too slow!"

  • "You're OK!"

Decision Requirements for Specific Solutions

• Pseudocode Structure:

  • CASE → THEN ELSE → END

  • Conditional logic via IF statements

Conditions with Decisions

• True/False Conditions illustration with decision blocks.

Conditions in Pseudocode

• Symbols and Definitions:

  • Operators for comparisons, logical conditions (AND, OR, NOT)

  • Examples of usage in conditions.

Decisions and Conditions Relationships

• Flow of Program:

  • Test expressions correlate with true/false decision blocks.

Conditional Relationships in Systems

• if-else Structure:

  • Demonstrated with programming constructs in Java for conditional flows.

Further Conditional Structures

• Java Programming Example:

  • User age checks for conditional outputs.

Flowcharts

• Usage:

  • Intuitive interpretation of symbols is crucial.

  • Guidelines include consistent flow direction and appropriate spacing between symbols.

Inputs and Outputs Identification

• Distinction between inputs (e.g., values), processes, and outputs within a system flow.

Pre-Planning in Problem Solving

• Real-life examples of pre-planning:

  • Pre-ordering, Preheating, School Locker use

  • Data caching references.

Importance of Preconditions

• Define preconditions (conditions before operations) and postconditions (conditions after operations).

• Example of downloading a file with conditions outlined.

Preconditions and Postconditions Outline

• Description of constraints in use cases.

• Example: PlaceOrder use case with actors and conditions detailed.

Exceptions in Problem Solutions

• Discussing exceptions to consider, demonstrated through numerical operations (e.g., square root).

Basic Rule: Think Ahead!

• Guidelines for exception handling and runtime behaviors illustrated.

Thinking Concurrently

• Definition: Handling multiple tasks simultaneously.

• Relevant examples such as GANTT charts for project management.

Identifying Concurrent Parts of a Solution

• Distinction between sequential and concurrent processes explained.

Concurrent Processing Described

• Characteristics:

  • Utilizing multiple processors for execution of instructions.

  • Complexity considerations discussed in context of performance enhancements.

Evaluating Concurrent Processing Decisions

• Evaluation criteria for decision making in concurrent processing context: Time, cost, feasibility.

Thinking Abstractly

• Explanation:

  • Creating meaningful models or representations of real-world concepts focusing on crucial aspects only.

• Examples provided: Maps, planners, schools as abstractions.

Definition of Abstraction

• Process: Taking away characteristics to focus on essential qualities.

• Purpose: Manage system complexity in computer science.

The Tube Map

• Example of abstraction in conveying essential information without overwhelming detail.

Need for Abstraction in Computational Solutions

• Reasons: Focus on essential problem aspects to tackle complexity efficiently.

Real vs Abstraction Comparison

• A comparison illustrating abstract versus detailed presentations.

Connecting Computational Thinking and Program Design (HL & SL)

• Overview of program design elements.

Flowchart Symbols

• Importance of standardized symbols in flowchart creation to avoid confusion.

Analyzing Algorithms via Flowcharts

• Overview of flowchart types and meanings of associated symbols, along with analysis methodologies.

Types of Flowcharts

• Illustrative example of a flowchart demonstrating decision-making, inputs, and order structure.

IB Flowchart Example

• Example of sequential and conditional operations neatly laid out in both flowchart and pseudocode forms.

Flowchart Looping Examples

• Depicting while-loop and from/to-loop conditions through flowcharts.

Analyzing Pseudocode Algorithms

• Purpose: Usage in describing algorithms clearly in a readable format for beginners.

Pseudocode Conventions

• Established conventions for variable naming, assignment, and output processes in pseudocode.

Trace Tables

• Utilization of trace tables for performing dry-runs of programs to observe variable changes.

Trace Table Example and Functions

• Step-by-step examples demonstrating the workings of trace tables in programming context.

Calculating with Trace Tables

• Assumed user inputs and trace operations with pseudocode logic presented to illustrate functional flows.

One Dimensional Arrays

• Definition: Array characteristics; holding multiple data elements of the same type, zero-based indexing.

1D Arrays Example

• Pseudocode and Java examples demonstrating input and output handling for one-dimensional arrays.

Outputting Arrays

• Java code demonstrating the output of array elements.

Averaging Array Values

• Pseudocode to find averages of non-zero numbers within an array through simple calculations.

Algorithm for Frequency Range Calculation

• Activity to construct algorithms in pseudocode relevant to frequency calculations from real data sets.

Linear Arrays Description

• Characteristics of standard algorithms applied to linear arrays.

Declaring 2D Arrays

• Syntax and examples for declaring, referencing, and creating two-dimensional arrays.

2D Arrays Example

• Inputs, outputs in both pseudocode and Java context demonstrated through practical code examples.

Implementation of 2D Arrays

• Explanation of how 2D arrays function conceptually.

Size of 2D Arrays

• Queries on 2D array size and dimension properties along with their types.

String Arrays Concept

• Details on string arrays and properties of immutable string values.

Parallel Arrays Explanation

• Concept of parallel arrays; correlations amongst them for organizing data across multiple attributes.

Parallel Arrays Code Example

• Java example highlighting the use of parallel arrays in real data assignments and outputs.

Array of Objects Overview

• Explaining array of objects and their properties with examples of usage in programming.

Example of Array of Objects

• Practical examples showcasing the usage of object arrays with JavaScript syntax.

Sequential Search Algorithm

• Definition: Description of a linear or sequential search algorithm's functionality and use-cases.

Sequential Search Pseudocode

• Implementation of the sequential search detailed in pseudocode format.

Java Implementation of Sequential Search

• Java Code: User inputs and logical structures to handle sequential searches through array processing.

Binary Search Explanation

• Definition: Characteristics and functional flow of binary search in sorted arrays.

Binary Search Steps

• Flowchart depicting search processes, illustrating midpoint comparisons for binary search.

Binary Search Pseudocode

• Detailed pseudocode structure for implementing binary search logic.

Java Implementation of Binary Search

• Code samples demonstrating the binary search algorithm's transition into practical programming syntax.

Binary vs Sequential Search Animation

• Side-by-side comparisons illustrating both search algorithms visually and in terms of step efficiency.

Comparison of Search Algorithms

• Key differences between linear search and binary search performance metrics outlined.

Sorting Algorithms Overview

• Importance of sorting algorithms for efficient data management and retrieval.

Selection Sort Description

• Overview of selection sort's operational efficiency and its process-based logic.

Bubble Sort Description

• Characteristics of bubble sort, including its simplicity and performance critique.

Bubble Sort Efficiency

• Explications on bubble sort's operational structure with hints on performance during iterations.

Bubble Sort Pseudocode

• Structured pseudocode for bubble sort process detailing its nested loops and conditions.

Bubble Sort Java Implementation

• Java code for the bubble sort process showing creation, sorting, and output features.

Selection Sort Characteristics

• Explanation of selection sort's unique processing advantages alongside its limitations.

Selection Sort Process

• Detailed steps showcasing selection sort's operational logic and comparisons within its loop.

Selection Sort Pseudocode

• Pseudocode covering operational sequencing and structure of the selection sort procedure.

Selection Sort Java Code

• Example showing the use of selection sort terminology within Java syntax for practical implementation.

Bubble vs Selection Sort Comparison

• Contrast between both algorithms' performance and situational efficiency highlighted.

Discussing Algorithms for Specific Problems

• Key takeaway comparing the efficiencies of binary search versus sequential search in relation to conditions of data storage.

Analysis of Sequential Search

• Notes on Efficiency: Explanation touching on simple structure versus performance for sequential search methods.

Analysis of Binary Search

• Explicit Characteristics: Explanation focusing on the binary search's core procedure and necessary conditions.

Collections Overview

• Discussion on what collections are and their role in holding multiple data types.

Manipulating Collections

• Definition of collection properties and the operations available for managing items within collections.

Comparison between Collections and Arrays

• Key distinctions outlined between static arrays and dynamic collection structures.

Collection Methods Summary

• Overview of common methods available within collections and their functional impacts in programming.

Collection Access Example

• Example loop demonstrating iteration through collection elements within programming logic.

Introduction to Programming

• Overview of basics surrounding programming languages such as .js, HTML, PHP.

Fundamental Operations of a Computer

• Discussion of core CPU instructions essential for executing commands, namely ADD, COMPARE, RETRIEVE, STORE.

Fundamental vs Complex Operations

• Illustrations contrasting simple instructions with complex operations in programming contexts.

Compound / Complex Operations Example

• Pseudocode illustrating finding maximal values among multiple inputs as an example of complex operations.

Essential Features of Programming Languages

• Definition emphasizing semantics, syntax, and vocabulary of programming languages, with examples.

Essential Features Summary

• List of essential features found in computer languages including vocabulary, syntax, types, and structures.

Need for Higher Level Languages

• Explanation of the evolution of programming needs and why high-level languages are essential for efficiency and manageability.

Translation from High-level to Machine Code

• Depiction of the translation process step-by-step from high-level commands to executable machine code.

Interpreter vs Compiler

• Comparison of the two roles of translators in programming and the relative advantages of each in execution.

Key Terminology Definitions

• Definitions for common terminology in programming translation across high-level languages.

Java Processing Steps

• Overview of Java program development from writing source files to executing through the JVM.

Java Virtual Machine Overview

• Explanation of JVM's functionality in enabling Java cross-compatibility across various hardware settings.

Variable Definitions

• Characteristics and functionalities of variables in programmatic scenarios, with usage examples.

Constant Definitions

• Explanation contrasting constants vis-a-vis variables, elucidating their functional properties.

Operator Definitions

• Overview of operators in computer programming; including arithmetic and logical operators and their applications.

Expanded Operator Definitions

• Detailed list of operators alongside their defined functionality within algorithms.

Sequential and Conditional Operations Examples

• Flowchart expressions demonstrating sequential and condition operations within programming.

Object Definitions in OOP

• Explanation of objects as instances of classes holding data and methods relevant to manipulating that data.

Definitions Recap

• Summarization of key programming concepts including variables, constants, operators, and objects.

Assignment Operator Definition

• Description of assignment operator and practical usage examples.

Unary Operator Definitions

• Specifications on unary operators and their functions demonstrated through examples and context.

Variables and Operators in Algorithms

• Case study on algorithms illustrating how variables and operators function together in logic statements.

Using Constants in Java Programs

• Example of Java program utilizing constants in calculations and their importance in equations.

Local and Global Variable Scope

• Discussion on variable scope detailing local vs global visibility within algorithms as a fundamental programming concept.