Computational Thinking and

Curriculum

Nick Reynolds

Learning With Interactive Devices

EDUC90588 – 2015

Melbourne Graduate School of Education

The Curriculum

• There will be a Digital Technologies curriculum in Victorian Schools in 2015▫ It is mandated

▫ It has Achievement Standards that can be reached on their own or as embedded in other Learning Areas

Difference between ‘Integrated’ and ‘Embedded’?

• This is important in many ways both nationally and internationally

READ THE DOCUMENT!

• Key Concepts (page 23, ACARA)▫ These are the building blocks of the curriculum▫ They tell you why

• Achievement Standards (at end of each year level)▫ They tell you what should be achieved▫ Can be seen as “working towards” as well as “at the

end of”• Content Descriptors (each year level and Scope and

Sequence)▫ They say what is contained▫ They provide specific guidance▫ Provide opportunities to build assessment

Key Concepts (p.23)

• Abstraction, which underpins all content, particularly the content descriptions relating to the concepts of data representation and specification, algorithms and implementation

• Data collection (properties, sources and collection of data), data representation (symbolism and separation) and data interpretation (patterns and contexts)

• Specification (descriptions and techniques), algorithms(following and describing) and implementation(translating and programming)

• Digital systems (hardware, software, and networks and the internet)

• Interactions (people and digital systems, data and processes) and impacts (sustainability and empowerment)

DISCUSSION

Abstraction Data collection

data representation

data interpretation

implementation

algorithms

Specification

Digital systemsInteractions

impacts

What do they mean?

Key Concepts (p.23)

Abstraction, which underpins all content, particularly the content descriptions relating to the concepts of data representation and specification, algorithms and implementation

• Ignoring what is not relevant• Breaking a problem into small, easily workable

components

For example, when students are asked how to make toast for breakfast, they do not mention all steps explicitly, assuming that the listener is an intelligent implementer of the abstract instructions (ACARA)

Key Concepts (p.23)

• Data collection (properties, sources and collection of data)

What is collected, measured, calculated (the basis of digital systems)

• Data representation (symbolism and separation)

How it is shown (represented) in digital systems

• Data interpretation (patterns and contexts)

Making meaning from data

Key Concepts (p.23)

• Specification (descriptions and techniques)

Describing, defining and clarifying the problem: I need to go from A to B

I want golden brown, hot toast for breakfast

• Algorithms (following and describing –reading and writing)

The ‘menu’ or set of instructions to tell you how to go from A to B: Go forward 4 steps, turn left (to avoid table) …Take bread from packet, turn on toaster, put bread in toaster, push slide button down.

Key Concepts (p.23)

• Implementation (translating and programming)

Actually writing the code ‘automating the algorithm’, applying the above steps

LIST: bread, toaster, power, knife, butter …

IF brown … ELSE …

Problem:

Provide instructions for someone to go from this room to the Melbourne Museum.

SpecificationAbstraction

Algorithm Implementation

Automation

Key Concepts (p.23)

• Digital systems (hardware, software, and networks and the internet)

The whole lot!

Often overlooked but there are significant interactions going on between systems every time something is done digitally:

Connecting a camera

Getting hardware to talk to hardware (or software)

Saving to a network drive

Key Concepts (p.23)

• Interactions (people and digital systems, data and processes)

The relationships between computers (hardware and software) and people

• Impacts (sustainability and empowerment)

What happens (or could happen) when people use computers.

Safety, security, development, social connection …

Computational Thinking

• Papert’s notion of technology as “objects to think with” (p. 11)

• Wing (2006) defines computational thinking as “a way that humans, not computers think” (p. 35).

• “mental tools” and “metal tools” (computers)• “the power of our ‘mental’ tools is amplified

through the power of our ‘metal’ tools” (Wing, 2008, p. 3718)

• the ability to think computationally (a human quality) is paramount in achieving outcomes not achievable without those metal tools.

• “a universally applicable attitude and skill set everyone, not just computer scientists, would be willing to learn and use” (Wing, 2006, p. 33).

Computational Thinking• Papert uses the term “think like a computer”

▫ the term does not mean to only or always think like a computer, rather it is “a powerful addition to a person’s stock of mental tools” (Papert, 1993, p. 155).

• When Papert asks himself to think like a computer, he does so knowing that “it does not close of other epistemologies. It simply opens new ways for approaching thinking” (p. 155).

Papert, S. (1993). Mindstorms: Children, computers and powerful ideas (2nd ed.). New York: Basic Books

Wing, J. (2006). Computational Thinking. Communications of the ACM, 49(3), 33-35.

Wing, J. (2008). Computational thinking and thinking about computing. Philosophical Transactions of

the Royal Society A, 366, 3717-3725.

Computational Thinking

In its most basic, but possibly its most universally accepted form, computational thinking requires a mindset or thinking approach that applies an understanding of the way computers work (think, act, function, are programmed) in order to solve complex contemporary problems

Reynolds, N., Swainston, A. & Bendrups, F (2014 in press). Music Technology and Computational Thinking: Young people displaying competence. In T. Brinda, N. Reynolds, R. Romeike & A. Shwill (2014). Proceedings of the KEYCIT2014 Conference, Potsdam, Germany. IFIP, University of Potsdam, Commentarii informaticae didacticae (CID). (pp. 279-284)

Three (general)approaches

• Look at current practice (What am I or my school doing?)

▫ A careful investigation of practice and a re-alignment to allow specific focus on Digi Tech

• Look at new ways of approaching things (What does the curriculum want me/let me do?)

▫ Starting point is the curriculum accompanied by a knowledge of or desire to do something new (coding, programming)

• Rely on specific knowledge and skill in application (What do I already know and how can I make it fit?)

▫ Specific content knowledge enables looking at Digi Tech (or what is already in their program) and expand to suit.

Assessment

What students:

Make

SayDoWrite

Evidence in those things

Multiple opportunities to collect that evidence

The products and processes

In order for … to happen … must have happened

Can we create tasks whose very completion require the student to have gained the required skills and knowledge? If we can, why then do we need to ‘test’ that knowledge?

THANK YOU