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COMPUTATIONAL THINKING, Constructivism and social theory - Coggle Diagram
COMPUTATIONAL THINKING
Computational thinking / Peter J. Denning and Matti Tedre (2019) (BOOK)
DEFINITION :
Computational thinking is the mental skills and practices for designing computations that get computers to do jobs for us, and explaining and interpreting the world as a complex of information processes
TEACHING CT FOR ALL
In the 1990s, computer education was mainly offered in universities, with few options in K–12 schools.
Courses focused on basic computer skills and some programming.
-After 2000, there was a shift. People realized how much computers were part of daily life, leading to a consensus among educators and policymakers that understanding digital technology, including algorithms, was crucial for success in the 21st century.
-This shift prompted the integration of computer education into K–12 schooling, as it became clear that knowing how technology works is essential for navigating the modern world.
CT EDUCATION
Struggle for Inclusion
: Introducing computing education to K–12 schools faced significant challenges due to limited teacher experience and minimal political support. Early attempts in the 1980s focused on basic computer literacy but lacked depth in computational thinking (CT).
Computational Thinking Movement
: A movement advocating for computational thinking gained momentum around 2006, emphasizing the importance of understanding algorithms and problem-solving. This energized educators and school boards to integrate computer courses into all K–12 schools.
Fluency vs. Literacy
: In the late 1990s, a push for "fluency with information technology" emerged, promoting a deeper understanding of computing's language and practices. However, this movement did not result in widespread change in K–12 education.
Jeannette Wing's Proposal
: In 2006, Jeannette Wing proposed computational thinking as a crucial skill for everyone, leading to significant investment and initiatives by organizations like the US National Science Foundation (NSF) to integrate CT into K–12 education.
Mainstream Integration
: Despite initial reluctance, the CT movement successfully influenced school boards to adopt computational thinking curricula, leading to widespread inclusion of CT in K–12 education.
Progression of Education Waves
: The evolution of computing education is seen as a series of waves, starting with mathematical problem-solving in the 1950s, evolving through literacy and fluency approaches, and culminating in modern CT designed for K–12 students.
CT AS THINKING TOOLS
Early Beginnings (Late 1940s - 1950s)
: Academic education for computing started in the late 1940s, focusing on numerical methods for large-scale machines. By the 1950s, the mass production of stored-program computers led to a surge in demand for programmers.
Diverse Educational Landscape
: In the 1950s, around 150 US universities offered computing training, but there was no standardized curriculum. Programs varied based on local needs, faculty interests, and business requirements.
Computing as a Thinking Tool
: Early computing educators, like Alan Perlis and George Forsythe, envisioned computing as a tool for problem-solving across various fields, not just computer science. They believed in "algorithmizing," referring to mental skills for developing computational solutions.
Ambitious Visions
: Visionaries like Marvin Minsky argued that computing would surpass mathematics in educational importance, while Donald Knuth highlighted how teaching computers fostered precision and deeper understanding. There was optimism that computing skills could revolutionize problem-solving in all areas.
Premature Optimism
: Despite early enthusiasm, the belief that computing skills would seamlessly transfer to general problem-solving turned out to be premature. Challenges and limitations emerged, as discussed further.
4 pillars of computational thinking skills
1.DECOMPOSITION (LERAIAN)
PATTERN RECOGNITION(PENGECAMAN CORAK)
3.ABSTRACTION (PENISKALAAN)
ALGORITHM (ALGORITMA/PENGITLAKAN)
Computational thinking is helpful not just for jobs in science and technology, but for any career. It helps with managing time and planning tasks, and teaches us how to share work when projects are too big. By making us think like computers, it improves our ability to analyze and solve problems logically. Since it's a way of thinking rather than a specific skill, anyone can use it. As technology becomes more common in all jobs, knowing how to work with it is really important.
Theories used to study computational thinking
https://www.researchgate.net/publication/349074436_A_Systematic_Review_of_Learning_Theory_on_Computational_Thinking
Constructionism theory
Situated learning theory
Active learning theory
item response theory
constructivism and constructionism theory
Scaffolding
theory
Brennen & Resnick framework
(a) Computational thinking CONCEPTS that correspond to programming blocks,including Sequences, Loops, Parallelism, Events, Conditionals, Operators, Data
(b)Computational thinking PRACTISES or construction processes, including Being incremental and iterative, Testing and debugging, Reusing and remixing, Abstraction and modularity and
(c) Computational Thinking PERSPECTIVE that reveal a shift in perspective when learning Computational Thinking, including Expressing, Connecting,Questioning
Constructivism and social theory
