Math and Computational Thinking
Kaput explains that Algebra supports computational thinking because it supports abstraction (symbols to represent relationships between quantities, representing patterns of relationships with generalized equations). This "ideation" is similar to abstraction as it is described in the Wing papers we read last week.
This paper also helped me see ToonTalk from a computational thinking lens (which I don't think was evident in the Simpson, Noss and Hoyles paper. The authors describe using ToonTalk as a way to "decompose" problems in a game for problem solving and debugging.
Kaput describes a problem of programming languages being created for elites, rather than for everyone. Like Wing, Kaput advocates for computational thinking for everyone. It seems like graphic languages, like Scratch or ToonTalk, could begin to address this problem, but it's not quite the same as symbolic representations of math like algebra, because experts likely won't shift to the new representation of using scratch. Instead, it might be more helpful to think about how we can help kids transfer knowledge from scratch to conventional languages.
Wientrop et al. created a more observable and actionable list of computational thinking practices. However, I'm not sure that they all align with Wing. For example, Wientrop et al. list programming as a computational thinking practice. Part of Wing's argument was that you don't need to be able to program or to use a computer to engage in computational thinking.
Assessing Computational Thinking
I thought the Grover, Pea and Cooper FACT assessment could be really interesting in the context of computational thinking in science (or math or lit) classes. Would students using programming for science develop similar computational thinking skill to those who participated in the FACT curriculum? Would their skills be more transferable? As Fai noted last week, different activities have different affordances for supporting computational thinking with programs like scratch. I think modeling would support understanding and use of loops and variables, but it would be interesting to directly assess students' CS skills rather than only their science knowledge/practices at the end of a project.
Kaput explains that Algebra supports computational thinking because it supports abstraction (symbols to represent relationships between quantities, representing patterns of relationships with generalized equations). This "ideation" is similar to abstraction as it is described in the Wing papers we read last week.
This paper also helped me see ToonTalk from a computational thinking lens (which I don't think was evident in the Simpson, Noss and Hoyles paper. The authors describe using ToonTalk as a way to "decompose" problems in a game for problem solving and debugging.
Kaput describes a problem of programming languages being created for elites, rather than for everyone. Like Wing, Kaput advocates for computational thinking for everyone. It seems like graphic languages, like Scratch or ToonTalk, could begin to address this problem, but it's not quite the same as symbolic representations of math like algebra, because experts likely won't shift to the new representation of using scratch. Instead, it might be more helpful to think about how we can help kids transfer knowledge from scratch to conventional languages.
Wientrop et al. created a more observable and actionable list of computational thinking practices. However, I'm not sure that they all align with Wing. For example, Wientrop et al. list programming as a computational thinking practice. Part of Wing's argument was that you don't need to be able to program or to use a computer to engage in computational thinking.
Assessing Computational Thinking
I thought the Grover, Pea and Cooper FACT assessment could be really interesting in the context of computational thinking in science (or math or lit) classes. Would students using programming for science develop similar computational thinking skill to those who participated in the FACT curriculum? Would their skills be more transferable? As Fai noted last week, different activities have different affordances for supporting computational thinking with programs like scratch. I think modeling would support understanding and use of loops and variables, but it would be interesting to directly assess students' CS skills rather than only their science knowledge/practices at the end of a project.
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