INTRODUCTION TO COMPUTATIONAL THINKING

1. KAY YONG, KHOO BSc.(Malaya); MSc(ITE) (HKU); EdD (HKU)
Portfolio: mels.hk/kykhoo/
A member of the external
Advisory Board for
MSc(ITE) of the University
of Hong Kong
Computational Thinking

2. STEM
How to enable STEM education?
What is STEM –
Transdisciplinary
Approach
Why we need STEM–
The real world problems are interdisciplinary based.
Computational Thinking
How to STEM –
Emerging Educational Needs

3. STEM STEAM
STREAM
Science
Technology
Engineering
Mathematics
Science
Technology
Art
Engineering
Mathematics
Science
Technology
Art
Engineering
Mathematics
Robotic

4. Attitudes about the role of technology in early
childhood tend to be unnecessarily polarized.
On one side are those who
believe we must protect children
from technology because of the
potential dangers of exposing
children to too much screen time
and an unsupervised internet.
On the other side are those who
believe that children will benefit
from using the newest
technology early and often, so
they will grow to be savvier and
smarter than the previous
generation.

5. The key to building a computer science literate
society is teaching our children computation
thinking skills, starting in early childhood.

6. What is computational thinking?
Computers can be used to help us solve problems.
However, before a problem can be tackled, the
problem itself and the ways in which it could be
solved need to be understood.
Computational thinking allows us to do this.
(Cuny, Snyder, & Wing, 2010; Aho, 2011; Lee, 2016

7. Each cornerstone is as
important as the others.
They are like legs on a
table - if one leg is
missing, the table will
probably collapse.
Correctly applying all
four techniques will
help when
programming a
computer.

8. You can’t solve
problems if you can’t let
go something..
So ….learn to
focus on the
important
information only,
ignoring
Abstraction

9. You will have different
outcomes if the sequence of
steps is different..
developing a step-by-
step solution to the
problem, or the rules
to follow to solve the
problem
Algorithmic skills

10. To solve problems, you
need the have the
ability to ...
breaking down a
complex problem
or system into
smaller, more
manageable

11. It is a big data and AI
generation, if you can’t read
the pattern, you can’t tell the
machine to solve for you..
looking for
similarities among and
within problems
Pattern Recognition

12. “Ephemeralization”
You never change things by
fighting the exiting reality. To
change something, build a new
model that makes the existing
model obsolete.
R. Buckminster Fuller

13. To do more and more
with less and less until
eventually it can do
everything with
nothing.