COMPUTATIONAL THINKING LEARNING 1974181

CT and 21st Century Problem Solving

Computational Thinking

Definition

“CT involves solving problems , designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science.” (Wing, 2006).

Vision

A fundamental skill used by everyone by the middle of the 21st century (Wing,2006).

CT Facets

Decomposition

Breakdown problems into smaller and more manageable parts, then focusing on solving each part of problem.

Abstraction

Pulling out the important details and identifying principles that apply to other problems/situations

Algorithm Design

A sequence of steps for solving a problem

Important

Use to describe solutions to problems.

Computer programs execute algorithms to perform specific tasks.

Debugging

Identify and fix the error.

Generalization

The ability to move from specific to broader applicability

Iteration

Repeat design processes to refine solutions, until the ideal result is achieved.

Product of CT

Algorithmic Thinking

The ability to think in a detailed way by placing the proceedings in sequence to produce a solution

Critical Thinking

The ability to analyse and make assessment oriented judgments that lead to decision making

Problem Solving

The ability to sustain in investigative processes by generating solutions

Cooperativity

The ability to help each other in learning with different methods in accordance with a common purpose

Creativity

The ability to develop genuine ideas with the combination of existing ideas and new ideas through critical thinking and problem solving

CT Plugged vs Unplugged

Unplugged - foundational in learning CT

The purpose of unplugged experiences are to introduce preliminary and overlapping concepts related to CT (either conceptually or technologically), during the experience.

Unplugged experiences should be designed to be student-directed, kinesthetic, easily implemented, game-based, and with embedded challenges.

With unplugged experiences, students are able to witness and experience the process required to complete a task, allowing them to put CT into a relatable context

Plugged

CT involves concepts and practices primarily from computer science which are shared across other disciplines such as science, mathematics, social science, biology, language arts and engineering

SCRATCH

Sequences

Loops

Parallelism

Events

Conditionals

Operators

Data

CT Practices and Perspectives

CT Practices

Focus on the process of thinking and learning, moving beyond what you are learning to how you are learning.

4 practices

Incremental and Iterative

Designing a project is a sequential process of first identifying a concept for a project, then developing a plan for the design, and then implementing the design in code

Testing and Debugging

‘Scratchers’ use various testing and debugging practices, which were developed through trial and error, transfer from other activities, or support from knowledgeable others.

Reusing and Remixing

Helping young designers to find ideas and code to build upon, enabling them to potentially create things much more complex than they could have created on their own.

Abstracting and Modularizing

Building something large by putting together collections of smaller parts

Employ modularization and abstraction by separating out the different behaviors or actions

CT Perspectives

Expressing

Use for design and self-expression.

Computation as a medium and thinks

Connecting

Creativity and learning are deeply social practices

The value of creating with others, and the value of creating for others

Appreciated that others were engaging with and appreciating their creations

Questioning

Do not feel this disconnect between the technologies

Can (use computation to) ask questions to make sense of (computational things in) the world.

CT in K-12 Education

Definition of CT for K-12 Education CT is a problem-solving process that includes (but is not limited to) the following characteristics:

Formulating problems in a way that enables us to use a computer and other tools to help solve them

Logically organizing and analyzing data

Representing data through abstractions, such as models and simulations

Automating solutions through algorithmic thinking (a series of ordered steps)

Identifying, analyzing, and implementing possible solutions with the goal of achieving the most efficient and effective combination of steps and resources

Generalizing and transferring this problem-solving process to a wide variety of problems.

Benefits of CT

Moves students beyond technology literacy

Creates problem solvers instead of software users

Emphasizes creating knowledge and designing processes that can be automated

Encourages creativity and problem solving

Enhances many of the problem-solving techniques you already know and teach

Heuristics

Heuristics guide problem solvers by helping them simplify choices regarding the numerous immensely complex and imperfectly understood factors that act simultaneously to shape problems.

Benefits of Heuristics

Heuristics can help produce results that are comparable to problem-solving strategies

Heuristics enhance efficiency regardless of whether the problem is well structured or ill structured

Limitations of Heuristics

Heuristics do not guarantee correct solutions to problems

One type of misapplication commonly occurs when problem solvers use heuristics in situations where logic and probability theory would have been more effective

Ideas for teaching CT

Use computational thinking terms for everyday tasks

Encourage students to critically examine and use information

Allow students to abstract and provide opportunities for students to transfer their learning to other situations

Do CT-building activities in class

NUR SYAMIRA BINTI AZMI 197418