lecture 6 teaching computational thinking 2016

68
Teaching Computational Thinking Technologies Education

Upload: jason-zagami

Post on 15-Apr-2017

657 views

Category:

Education


1 download

TRANSCRIPT

Page 1: Lecture 6 Teaching Computational Thinking 2016

Teaching Computational Thinking

Technologies Education

Page 2: Lecture 6 Teaching Computational Thinking 2016

3:45

Page 3: Lecture 6 Teaching Computational Thinking 2016

Big Problem Project Based Learning

Thinking Skills Curriculum Outcomes

Page 4: Lecture 6 Teaching Computational Thinking 2016

Tech

nolo

gies

Lear

ning

Area

Page 5: Lecture 6 Teaching Computational Thinking 2016

Desig

n and

Tech

nolo

gies

Page 6: Lecture 6 Teaching Computational Thinking 2016

Digi

tal T

echn

olog

ies

Page 7: Lecture 6 Teaching Computational Thinking 2016

ICT G

ener

al Ca

pabi

litie

s

Page 8: Lecture 6 Teaching Computational Thinking 2016

Gene

ral C

apab

ilitie

s

Page 9: Lecture 6 Teaching Computational Thinking 2016

Developmental Curriculum

Foundation Year 10

Page 10: Lecture 6 Teaching Computational Thinking 2016

Indicative Timings

F-2 10 Hours

3-4 20 Hours

5-6 30 Hours

7-10 40 Hours

Page 11: Lecture 6 Teaching Computational Thinking 2016

Digital systems: the components of digital

systems: hardware, software and networks and

their use Representation of data:

how data are represented and structured symbolically

Knowledge and UnderstandingDesign and

Technologies Digital

Technologies

Creating Solutions

Technologies and society: the use, development and impact of technologies in

people’s lives Technologies contexts:

technologies and design across a range of

technologies contexts

Page 12: Lecture 6 Teaching Computational Thinking 2016

Investigating and Defining Generating and Designing

Producing and Implementing Evaluating

Collaborating and Managing

Processes and Production SkillsDesign and

Technologies Digital

Technologies

Creating Solutions

Page 13: Lecture 6 Teaching Computational Thinking 2016

Engineering principles and systems

Food and fibre production

Food specialisations

Materials and technologies specialisations De

sign a

nd Te

chno

logi

es

Page 14: Lecture 6 Teaching Computational Thinking 2016

Information systems

Information technology

Software engineering

Computer engineering Digi

tal T

echn

olog

ies

Digi

tal S

yste

ms

R

epre

sent

atio

n of D

ata

Page 15: Lecture 6 Teaching Computational Thinking 2016

Solution Type

• product • environment • service

Page 16: Lecture 6 Teaching Computational Thinking 2016

Futures Thinking

Systems Thinking

Design Thinking

Computational Thinking

Strategic Thinking

Page 17: Lecture 6 Teaching Computational Thinking 2016

Trends, Visioning, Scenarios, Big Idea

B/COT, Circle, Stocks, Flows, Loops

Contexts, Design Challenges, PSE Type

Data, Automation/Programming

Entrepreneurship, Planning, Teamwork

Page 18: Lecture 6 Teaching Computational Thinking 2016

Assessment Criteria

• Interpretive and analytical ability in developing design challenges.

• Interpretive and analytical ability in developing programming challenges.

• Intellectual initiative in research, planning and development of solutions.

• Intellectual initiative in the articulation and presentation.

Page 19: Lecture 6 Teaching Computational Thinking 2016

Two Digital Technologies Contexts

• Data

• Programming / Automation

Page 20: Lecture 6 Teaching Computational Thinking 2016

Two Design Technologies Contexts

• Engineering principles and systems • Food and fibre production • Food specialisations • Materials and technologies

specialisations

Page 21: Lecture 6 Teaching Computational Thinking 2016

Thinking Skills Development

• Teaching Design Thinking; • Teaching Computational Thinking; • Teaching Systems Thinking; • Teaching Strategic Thinking; and • Teaching Futures Thinking.

Page 22: Lecture 6 Teaching Computational Thinking 2016

https://www.qcaa.qld.edu.au/p-10/aciq/p-10-technologies

Page 23: Lecture 6 Teaching Computational Thinking 2016

Digital Technologies Challenges

Algorithmic Sequences (F-2) Sensor driven interface solutions (3-4) Sensor driven robotic solutions (5-6) Database integrated automation solutions (7-8)

Page 24: Lecture 6 Teaching Computational Thinking 2016

Digital Technologies Challenges

Algorithmic Sequences (F-2) Game based programming (Icon Based) (Guessing Game 3-4, Maze Game 5-6) HTML Website Development solutions (7-8)

Page 25: Lecture 6 Teaching Computational Thinking 2016

Digital Technologies Challenges

Algorithmic Sequences (F-2) Sensor driven interface solutions (3-4) Sensor driven robotic solutions (5-6) Database integrated automation solutions (7-8)

Page 26: Lecture 6 Teaching Computational Thinking 2016

Digital Technologies Challenges

Spreadsheet Decision Based Solutions (3-4) Expert System solutions (5-6, 7-8) Spreadsheet data analysis (7-8) Database and GIS driven websites (7-8) Data Driven App solutions (9-10) Cryptography and Object Oriented Database Solutions (9-10)

Page 27: Lecture 6 Teaching Computational Thinking 2016

Design Technologies Challenges

Making Toys, Puppet Show (F-2) Repurposed Clothing, Lunch Item, Pinball Game (3-4) Healthy Drink, Security System, Garden, Wildlife Protection System (5-6) Cultural Fusions, Farming, etc. (7-8)

Page 28: Lecture 6 Teaching Computational Thinking 2016

Expectations for most students

• Present standard activities taken directly from existing examples and contextualised for the Gold Coast;

Page 29: Lecture 6 Teaching Computational Thinking 2016

Expectations for some students

• Demonstrate that students will have opportunities to develop a range of learning outcomes as detailed in the curriculum and you have made a significant new contribution to the project idea;

Page 30: Lecture 6 Teaching Computational Thinking 2016

Expectations for a few students

• Incorporate, in an integrated way, the development of the range of student thinking skills into your design challenges and show real innovation in your project ideas.

Page 31: Lecture 6 Teaching Computational Thinking 2016

Systems Thinking

Computational Thinking

Design Thinking

Futures Thinking

Strategic Thinking Solutions Thinking .

Page 32: Lecture 6 Teaching Computational Thinking 2016

3:16

Page 33: Lecture 6 Teaching Computational Thinking 2016

1:16

Page 34: Lecture 6 Teaching Computational Thinking 2016

Models of integration

Page 35: Lecture 6 Teaching Computational Thinking 2016

Service Connections

Page 36: Lecture 6 Teaching Computational Thinking 2016

Symmetric Correlations

Page 37: Lecture 6 Teaching Computational Thinking 2016

Syntegration

Page 38: Lecture 6 Teaching Computational Thinking 2016

The Investigation stage does not investigate the

problem to better understand it

Common Unit Problems

Page 39: Lecture 6 Teaching Computational Thinking 2016

Project is the teachers, with students following directions to support the creative ideas

of the teacher

Common Unit Problems

Page 40: Lecture 6 Teaching Computational Thinking 2016

There is no opportunity for students to be creative and design their own solutions

Common Unit Problems

Page 41: Lecture 6 Teaching Computational Thinking 2016

There is no demonstration of the iterative nature of the

design cycle, using what was learnt from evaluation to

inform further investigation, generation and production

Common Unit Problems

Page 42: Lecture 6 Teaching Computational Thinking 2016

It is an ICT unit that supports the learning of another

learning area

Common Unit Problems

Page 43: Lecture 6 Teaching Computational Thinking 2016

Evaluation is little more than reflection, with no criteria or

possibility of failure

Common Unit Problems

Page 44: Lecture 6 Teaching Computational Thinking 2016

Creativity

Page 45: Lecture 6 Teaching Computational Thinking 2016

Creativity

Creativity is the process of having original ideas that have value

Page 46: Lecture 6 Teaching Computational Thinking 2016

6:00

Page 47: Lecture 6 Teaching Computational Thinking 2016

Creativity is the process of producing something that is both original and worthwhile. Wallas (1926) presented one of the first models of the creative process where creative insights and illuminations may be explained by a process

consisting of 5 stages:

Creativity

Page 48: Lecture 6 Teaching Computational Thinking 2016

preparation preparatory work on a problem that focuses the

individual's mind on the problem and explores the problem's dimensions

Creativity

Page 49: Lecture 6 Teaching Computational Thinking 2016

incubation where the problem is internalised into the unconscious

mind and nothing appears externally to be happening

Creativity

Page 50: Lecture 6 Teaching Computational Thinking 2016

intimation the creative person gets a "feeling"

that a solution is on its way

Creativity

Page 51: Lecture 6 Teaching Computational Thinking 2016

illumination or insight where the creative idea bursts forth from its preconscious

processing into conscious awareness

Creativity

Page 52: Lecture 6 Teaching Computational Thinking 2016

verification where the idea is consciously verified, elaborated, and

then applied

Creativity

Page 53: Lecture 6 Teaching Computational Thinking 2016

1:22

Page 54: Lecture 6 Teaching Computational Thinking 2016

The best way to have a good idea is to have lots of ideas Linus Pauling

Creativity

Page 55: Lecture 6 Teaching Computational Thinking 2016

2:53

Page 56: Lecture 6 Teaching Computational Thinking 2016

There are three groups of creativity techniques:

Aleatoricism introduces chance into the creative process;

Improvisation encourages spontaneity and free thought;

and

problem solving has a wide range of tools and methodologies that can support creativity.

Creativity Techniques

Page 57: Lecture 6 Teaching Computational Thinking 2016

1:24

Page 58: Lecture 6 Teaching Computational Thinking 2016

Problem solving creativity techniques include:

TRIZ; Brainstorming and Brainwriting;

Six Thinking Hats; Think outside the box;

SWOT analysis; USIT;

Five Ws; Thought experiments; and

Dilemmas.

Creativity Techniques

Page 59: Lecture 6 Teaching Computational Thinking 2016

4:18

Page 60: Lecture 6 Teaching Computational Thinking 2016

It is better to have enough ideas for some of them to be wrong, than to be always right by having no ideas at all.

Edward de Bono

Creativity

Page 61: Lecture 6 Teaching Computational Thinking 2016

More general approaches for inspiring creativity include:

Linking (word association); Black Box (inputs and outputs);

Parallels (past solutions); Variation (focus on a single tool);

Additive Examples (combinations).

Creativity Techniques

Page 62: Lecture 6 Teaching Computational Thinking 2016

0:57

Page 63: Lecture 6 Teaching Computational Thinking 2016

Innovation is the development of new solutions, products, services, and ways of doing.

Innovation is not just improvement but doing something different rather than doing the same thing better.

Through Technologies education, students develop the ability to be innovative, using their thinking processes and creativity to develop novel innovations to solve problems

and develop opportunities.

Innovation

Page 64: Lecture 6 Teaching Computational Thinking 2016

1:14

Page 65: Lecture 6 Teaching Computational Thinking 2016

Failure

Page 66: Lecture 6 Teaching Computational Thinking 2016

3:26

Page 67: Lecture 6 Teaching Computational Thinking 2016

0:27

Page 68: Lecture 6 Teaching Computational Thinking 2016

Griffith University

Dr Jason Zagami

www.zagami.info