Abstract Models in Computational Thinking (OCR A-Level Computer Science): Flashcards
Practise the cards
15 cards from this deck
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Practise the cards
15 cards from this deck
Abstract model definition
Abstract model definition
Simplified representation focusing on key components, not details
Purpose of abstract models in computational thinking
Purpose of abstract models in computational thinking
Break down complex problems to make them easier to analyse & solve
1st step in devising an abstract model
1st step in devising an abstract model
Identify key entities (main components)
2nd step in devising an abstract model
2nd step in devising an abstract model
Determine relationships between entities
3rd step in devising an abstract model
3rd step in devising an abstract model
Focus on essentials - include only necessary details
Benefit: How abstract models improve problem solving
Benefit: How abstract models improve problem solving
Break complex problems into simpler, solvable parts
Benefit: Reusability of abstract models
Benefit: Reusability of abstract models
Can be adapted for similar problems in different contexts
Benefit: Efficiency of abstract models
Benefit: Efficiency of abstract models
Reduces cognitive load by simplifying complex systems
School timetable system entities
School timetable system entities
Teacher, Student, Classroom, Subject
Traffic light control system entities
Traffic light control system entities
Traffic Light, Timer, Vehicle Sensor, Pedestrian Button
Online shopping system entities
Online shopping system entities
Product, Customer, Order, Payment
Weather forecasting system entities
Weather forecasting system entities
Weather Station, Sensor Data, Forecast Model
Common mistake: Overcomplicating abstract models
Common mistake: Overcomplicating abstract models
Including too many details defeats purpose of abstraction
Common mistake: Oversimplifying abstract models
Common mistake: Oversimplifying abstract models
Omitting essential components makes model ineffective
Balance needed in effective abstract models
Balance needed in effective abstract models
Simplicity & completeness - core aspects, no irrelevant details
