Hello Eric:

I will look further into your CT-S measurement framework to see how our work might use that as part of our impact assessment. We purposely pushed for purposeful measurement and quantitative data analysis in hopes that our general biology courses would include more computation. We learned from work with our biology teachers that the use of Punnet Squares was the most common response when asked about Computation in Biology classes. They just used pre-existing Punnet Squares and did not analyze population data. I wondered if your work might have seen a similar trend in the K-12 Life Sciences?

Thanks for sharing! What you found about Punnet Squares resonates--one thing that emerged as we were developing the framework is just how uncommon computational data practices are in K12 classrooms, despite being pervasive in modern science. Our measure includes items that attend to these kinds of 'data moves' as well as other computational practices common in science practice in the 21st century. Please let us know how we might support your work!

Hi Folks, Thanks for your interest in our work! Here's a link to our technical report for the measure. The report details the conceptualization, development, and validity evidence of the computational thinking for science survey. In this report, we provide an operational definition of CT-S, describe the survey construction process, and provide validity evidence to support inferential claims from the survey about a middle school student’s computational thinking for science ability. 

That's exactly what I needed ...the Technical Report!  Thank you! BTW if you haven't read "Homo Deus"...I highly recommend it!

Fascinating work, to tackle the conceptual and cognitive framing of computational thinking.  I am interested in whether the assessment can be used in informal STEM learning environments, and if it is already, and what you are learning? Also, as we increasingly see opportunity for college students to be engaged in research and projects that will require integration of computational thinking with other STEM areas, what are your thoughts on the developmental trajectory of computational thinking in science?  Do you have research underway on that front?

We have developed an integrated CSTEM class for 9th grade students, and will definitely look into your framework. For anyone else who is interested in our Learning by Making curriculum, please feel free to contact me and to check our website http://lbym.sonoma.edu

Thank you for sharing this intriguing study. Your study recognized that the work that scientists engage in is often so different than what we see occurring in classrooms. Did you collaborate with practicing scientists to get a sense of the computational work they do in their profession? Do students get to interact with scientists.

Also, I noticed in your video (close to minute one) students were posing questions about how they might investigate different phenomena (like using technology to track the sun at the horizon over the course of a year.) These questions seemed particularly sophisticated and insightful. Moreover, they demonstrate an understanding of what tool one would need to have in order to investigate a particular phenomena. Can you share about the process of shaping students competencies with asking these kinds of scientific and investigative questions? Thank you for your work.

Thanks for your comment! For our measurement development work, we drew on recent studies that inquire into the computational work that practicing scientists engage in (for example, Weintrop, et al., 2016) as well as our network of scientists and advisors on this project. Our work with students was primarily in cognitive interviews to understand what different kinds of computational tasks reveal about youth thinking and evaluate alignment between what we think an item is measuring and how youth are interpreting the question. 

In terms of the questions--are you referring to the text in the framework cells (1:24)? They are sophisticated questions, for sure! The questions are meant to evoke the kinds of tasks that would clearly engage CT-S. That is to say, one would be likely to see (e.g., for assessment) CT-S by answering that question. As your comment suggests, there remains a huge challenge to support students with the competencies to ask these kinds of questions as well as answer them--our hope is that the framework and tool developed through this project serves to articulate the aspects of CT that best position youth for success in science learning, and can inform educators and curriculum developers seeking to advance student learning in those areas.

Thanks for sharing, this is a very interesting project.

I understand your measurement work centered on developing an instrument to assess the key outcome of interest here (CT learning). On the other hand, the framework in your video explicitly positions pedagogy as a key factor (perhaps THE key?) influencing this outcome.

I am wondering  whether you also tried to measure instructional practices/pedagogical approach in your project. If you did I would be very interested in learning about how you went about it. If not, what are your thoughts on how we may building a knowledge base (and eventually instruments) to measure instruction related to CT.

Developing measures of classroom processes is an area very close to my interests and I am currently collaborating with Math and Science educators at UCLA/Center X to develop and pilot an observation rubric to measure CT-instruction. Thanks!

Thanks for sharing this work! Also, thanks for sharing the technical report, it is very informative.

Could you tell more about the digital tools students have been used to engage with computational modeling? I wonder if designing these tools is also a part of the project, or if you have found any that suit your need.
By the way, we are designing a block-based programming environment with this same goal, in case you want to check it out (link) :)