In Hong Kong, IT talent shortage has been a pressing issue for many CIOs in the recent past. As the Government stepped up its efforts to promote STEM education, what has been done in the community level to foster IT learning? How long before these efforts will bear fruit?
To inspire students' digital creativity, the CoolThink@JC initiative was designed to equip primary students with "computational thinking" skills, whereby students at participating schools experiment with sensors, IoT systems and mobile applications development, among others.
HK$216 million computational thinking education initiative
Branded CoolThink@JC, the computational thinking initiative is a HK$216 million project funded by The Hong Kong Jockey Club Charities Trust to enhance the computational thinking ability of upper primary school children (Primary 4-6) in Hong Kong. Running from November 2016, the four-year CoolThink@JC program is aimed at inspiring young school children to think digitally, who can then innovate to tackle challenges in any field in the future.
"Children at the age of 9 to 11 are at the right age to build the foundation for computational thinking, as they start to develop the ability to conceptualize matters. With computational thinking, children can become creators of technology, instead of just consumers of technology," said Daniel Lai, programme director of CoolThink@JC.
What is computational thinking?
First coined by the American mathematician and computer scientist Seymour Papert in 1980, "computational thinking" is a set of fundamental thinking skills and way for a person to think like a computer scientist.
With computational thinking, when one faces a problem, he or she can understand the problem, decompose it into smaller problems, then create a set of instructions and ultimately a system to solve the problem. "Computational thinking focuses more on the thinking process rather than just coding," Lai explained.
Not just about coding
CoolThink@JC provides a three-stage curriculum that teaches young children the fundamental coding concepts, problem-solving skills, and finally identity and motivation. Some of the key components of computational thinking are: algorithmic thinking, decomposition, abstraction, generalization, testing and debugging.
"These skills are much more valuable than the know-how of using PowerPoint or word processing software. Why should we teach the use of productivity tools in P.4 when it can be pushed back to P.1-3?" Lai queried.