13 Matching Annotations
  1. Mar 2023
    1. Research has found thatenabling students to explore scientific and mathematicalphenomena using computational problem solving practicessuch as programming, algorithm development, and creatingcomputational abstractions can help learners develop deepunderstandings of mathematical and scientific phenomena

      This is how I was think computer science could be useful for every learner -- using computational problem solving. I really do think that computation thinking is especially for helpful for reasoning about the world, so it makes sense that this would be really useful for math and science.

    2. The pedagogical power of compu-tational models comes not just from students using existingmodels, but also from enabling students to design, build,and assess models of their own

      I just think this is cool because I was just doing some readings for data science that focused on how models can be used for basically everything and how all of science really has do with models. I think it's cool that this is one of the main ways this paper suggests using CT in education.

    3. Our aim in this paper is to develop a more nuancedunderstanding of computational thinking specifically as itapplies to the mathematic and scientific disciplines and theneeds of high school teachers

      This is really good -- I do think that one of the downsides of computational thinking is that it can sound impractical and kind of theoretical. It's cool that this research is being done that can show what CT actually looks like.

  2. Feb 2023
    1. also one that emerged from a love for the beauty of mathematics, procedures, and information.

      I just like this a lot -- this is how I would hope to position CS as a teacher.

    2. The resulting relationship — higher education educates students about computer science, and industry hires them — is the one we live with today.

      This so true! There's definitely a pipeline from university to industry (eg. students reaching out to graduates from their institution to get a job at their company, companies looking for graduates from a specific institution -- it's so much about who you know/who you're connected to)

    3. The low-wage pathways for women to jobs as human computers — majoring in mathematics and working in science and industry — disappeared, replaced by new pathways that focused on White men in higher education

      Ouch -- and this is still mostly the case. It's very interesting to think about how these jobs largely started with women studying math, but now most of those in higher education in CS are like those described here. I suppose it actually hasn't been that long since then.

    1. strong, positiverelationships are necessary in order for studentsto be willing to take big risks in the classroom

      This is so true -- I definitely agree here that relationships of trust give students the confidence to try things at all in the classroom. It also just gives them motivation to try at all; it doesn't necessarily have to big a huge risk. Also, strong relationships just make everything more enjoyable.

    2. Do myclassroom routinesand protocols supportdeeper learningfor all students?

      This seems to me like a really key question. All students should be learning in the classroom, so this really just makes sense.

    1. Many curricula (in ancient Greece, philoso-phy and rhetoric; in the nineteenth century, Latin; and in the twentiethcentury, computer programming) were intended to develop more rigorous

      I really like here how philosophy, rhetoric, and Latin are associated with computer programming for teaching critical thinking. This makes a lot of sense to me, but I wouldn't have made those associations on my own.

    2. Computers may have become extensions of ourselves, but to whatextent are we teaching children how to design and manage these exten-sions?

      We aren't really! This seems like an important reason to me to teach computational thinking, and I guess, as this reading goes on, computational participation.

    3. The national total of African American computer science test takersthat same year was twenty-nine (less than 1 percent).

      I had to read this multiple times to make sure I was reading right -- this is so shocking

    1. the tools influenced what stories they made and how thesestories were expressed.

      This is one conclusion that I think can with certainty be drawn from this study -- that the tools we use influence the expression of what is being created. Because in this case with storytelling, a tool is used, the story isn't going to be completely accurate as to perfectly reflect itself. Tools used affect the result always.

    2. computer as a “material” thatcould be manipulated like paint, clay, and paper

      I like this way of referring to a computer, as a material that can be manipulated. I think this is a good way to look at it because a computer is not static (it can be customized and worked with on a unique level), but it isn't something that is just completely created by an individual. There are limits and rules for its use.