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The Truth Behind Computational Thinking:

Jon Hamlin

Greater Victoria School District

E-mail: jonhamlin@gmail.com

Twitter: @jonhamlin

Web: jonhamlin.com

CodeBC.ca/Pro-D

You’re already doing it, guaranteed!

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codebc.ca/pro-d

Shape of the Session

• Introductions
• CodeBC - Overview & Exploration
• Introducing Computational Thinking
• Activity - Connecting CT to Your Classroom
• Questions & Discussion
• Wrap up

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Introductions: Find your partner(s)

1. Organize yourselves in a line from least teaching experience to most.

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• Then fold the line in half e.g. the person with the most experience partners with the person with the least, etc.

Introductions: Find your partner(s)

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Introduce yourselves:

• What / where do you teach?
• What brought you here today?
• What do you hope to get from this session?

Introductions: Who is this guy?

Introductions: Who is this guy?

Introductions: Who is this guy?

Introductions: Who is this guy?

Introductions: Who is this guy?

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Connect existing coding and computational thinking resources to BC’s new curriculum

Created by K-12 BC teachers with our specific needs in mind

The Problem: Where to get started?

The Problem: Where to get started?

Solution: Make Connections

Making Connections

Coding & Computational Thinking Resources

Core Competencies

Cross-Curricular

Skill Levels

Mentorship Map

Ratings System

Online Training

Cost

Platforms

Logins?

CodeBC - Overview

• Connected to the curriculum
• 9 key search filters
• Mentorship map
• Coding events calendar
• Online Training
• Discourse Forum
• Ratings tools

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Time to Explore

CodeBC.ca

Introduction to Computational Thinking

• Breaking big problems down into a small, more manageable problems (decomposition).
• Look for patterns and connections to prior learning (patterns & generalisations)
• Focusing only on the important details, while ignoring irrelevant information (abstraction).
• Design simple steps or rules to solve each of the smaller problems (algorithmic thinking).

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Computational Thinking: Decomposition

Breaking down complex problems into smaller, more manageable parts

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• Reduces complexity
• Study key areas with greater depth
• Manage large projects
• Aids in teamwork & collaboration
• Focuses on connections

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Computational Thinking: Decomposition

Computational Thinking: Decomposition

Computational Thinking: Decomposition

Computational Thinking: Decomposition

Computational Thinking: Decomposition

Cross-Curricular Connections: Decomposition

Computational Thinking: Patterns & Generalisation

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• Once the problem is decomposed,

we examine for patterns

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• Problems are easier to solve when

we can find patterns

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• We can use the same solution

wherever the problem exists

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Computational Thinking: Patterns & Generalisation

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All cats have eyes, tails, and fur.

What about me?

Computational Thinking: Patterns & Generalisation

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Once we describe one cat, we can describe others by following the pattern. (Generalisation)

Computational Thinking: Patterns & Generalisation

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Computational Thinking: Patterns & Generalisation

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Generalisation: Solving new problems based on previous problems we have solved.

Computational Thinking: Patterns & Generalisation

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Finding the area of a rectangle

Computational Thinking: Abstraction

• Filtering (critical thinking)
• What details need attention, what can be ignored
• Reduces complexity

Make something complex easier to grasp by

removing extraneous details

Computational Thinking: Abstraction

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Jason has 7 toy cars but his brother Ryan has 8.

Jason has mostly passenger cars and Ryan has race cars.

How many cars do they own in total?

Computational Thinking: Abstraction

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Jason has 7 toy cars but his brother Ryan has 8.

Jason has mostly passenger cars and Ryan has race cars.

How many cars do they own in total?

Computational Thinking: Abstraction

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Jason has

Jason has mostly

7 + 8 =

Computational Thinking: Abstraction

Computational Thinking: Abstraction

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What is the provincial flower of British Columbia?

Computational Thinking: Abstraction

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provincial flower of BC?

Computational Thinking: Abstraction

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BC flower

Computational Thinking: Abstraction

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Computational Thinking: Algorithmic Thinking

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• A precise step by step guide to achieving a specific outcome.
• Allows solutions to be automated.
• Improves efficiency for future problem solving.

Computational Thinking: Algorithmic Thinking

Computational Thinking: Algorithmic Thinking

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Becomes more helpful

when instructions become

complex.

Computational Thinking: Algorithmic Thinking

Computational Thinking: Algorithmic Thinking

4 Chord

Algorithm

Computational Thinking: Algorithmic Thinking

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Computational Thinking: Algorithmic Thinking

3 6 9 12

15

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Cross-Curricular Connections: Algorithmic Thinking

Computational Thinking: Evaluation

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• Evaluating the effectiveness

of the solution or algorithm.

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• Factoring multiple perspectives within this process.

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Computational Thinking: Evaluation

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Key factors to determine if solution is a success:

• Is it easily understood (fully decomposed)?
• Does it create any unintended consequences?
• Does it fully solve all aspects of the problem?
• Is it efficient?

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Computational Thinking: Evaluation

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Computational Thinking: Evaluation (Debugging)

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Grace Hopper: The First Computer Bug

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Grace Hopper

1906 - 1992

Grace Hopper: The First Computer Bug

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Activity: Connecting CT to YOUR classroom

• Breaking big problems down into a small, more manageable problems (decomposition).
• Look for patterns and connections to prior learning (patterns & generalisations)
• Focusing only on the important details, while ignoring irrelevant information (abstraction).
• Design simple steps or rules to solve each of the smaller problems (algorithmic thinking).

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Questions & Comments

CodeBC: Teachers’ Guide to Computational Thinking

The Truth Behind Computational Thinking

Jon Hamlin

E-mail: jonhamlin@gmail.com

Twitter: @jonhamlin

CodeBC.ca/Pro-D