According
to Wing (2006) Computational thinking (CT) is a basic skill that involves
problem formulation, problem solving, and scientific reasoning. Computational
thinking involves ideas like abstraction, data representation, and logically
organizing data, which are also prevalent in other kinds of thinking, such as
scientific thinking, engineering thinking, systems thinking, design thinking,
model-based thinking, and the like. Preceded by terms like algorithmizing,
procedural thinking, algorithmic thinking, and computational literacy.
Computational thinking can be used to algorithmically solve complicated
problems of scale, and is often used to realize large improvements in
efficiency. The characteristics of computational thinking are: Able to provide
troubleshooting using a computer or other device. Able to organize and analyze
data. Able to perform data representation through abstraction with a model or
simulation. Able to automate solutions through algorithmic thinking. Able to
identify, analyze and implement solutions with various combinations of steps /
methods and resources that are efficient and effective. Able to generalize
solutions to a variety of different problems.
STEM
Learning, at its core, simply means educating students in four specific disciplines,
namely, Science, Technology, Engineering, and Mathematics (collectively
shortened as STEM). STEM combines all four in an interdisciplinary and applied
approach, so as to better equip students to have a career and considering
real-world applications. STEM learning aims to improve skills students by
presenting a cohesive learning platform that is largely based on real-world
applications. STEM classrooms typically focus on project-based learning.
Students get to apply the various domains of STEM in a context that helps them
realize a connection between the classroom and the world around them.
From
the understanding of the two terms above, we can imagine that Computational
Thingking is part of STEM, there are many domains that are the scope of
Computational Thingking as well as STEM. Computational Thingking is used in the
STEM learning process, and in achieving STEM learning objectives a
Computational Thingking process is needed, so that it can not only be applied
but applying CT in STEM learning can be said to be a must.
There are several reasons why we integrate Computational Thingking in STEM learning, which are as follows:
- Computational Thinking involves problem formulation, problem solving, and scientific reasoning, these are needed in STEM Learning, without it all STEM Learning processes are difficult to achieve.
- Building a reciprocal
relationship for learning mathematics and science with CT
- Establishing a
sustainable learning environment that can engage all students.
- Bringing efforts in
developing CT in disciplinary education in line with the increasingly
computational nature of scientific and mathematical practices.
How to Apply Computational Thinking (CT) in STEM Learning?
- Integrate or apply Computational Thinking in the STEM learning curriculum by to organize and analyze data, to perform data representation through abstraction with a model or simulation, to automate solutions through algorithmic thinking, to identify, analyze and implement solutions with various combinations of steps / methods and resources that are efficient and effective and than to generalize solutions to a variety of different problems.
- Utilizing various
computer applications or games that aim to train CT-based thinking patterns in
STEM learning.
- Integration of
problem-solving-centered thinking and algorithms in educational curricula.
- Entering computer
programming material on lessons at school
- Teacher training is
critical to the successful application of CT in STEM
- Digital technology is
included as part of the technology area in the national curriculum
- Teach material about algorithms, data representation, digital applications, digital devices and infrastructure, people and computers and programming.
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