The session was funded by the National Science Foundation (NSF) and was part of four-year initiative to boost computational thinking knowledge and teaching in K-12 schools in Massachusetts. A website was created by the grant team which includes all the needed information to start implementation of the many interdisciplinary science, math, and computational thinking curriculum units.
There were many specific points made during the day that I found particularly helpful. First, I really enjoyed learning about the language related to computational thinking. I often read and hear the vocabulary, but haven't had a chance to dig into the meaning of words such as abstraction, algorithm, modeling, simulation, debugging, function, loop, and procedure. These will be words that I use more often as I teach math and science in the days to come, and words for which I'll create mini-posters for the classroom in order to encourage their use by the students and me as we learn together.
We participated in a few unplugged coding activities that gave us hands-on experience with the systematic thinking, debugging, and process used to code a set of instructions to complete a task, simulate an experience, and collect data. Then we looked at ways that we can manipulate and analyze the data to form meaningful and helpful analyses. As I engaged in these activities, I was reminded of students' recent conference leadership. As they led their conferences by sharing reflections, they often pointed to the many hands-on activities we've done as the most powerful and meaningful learning activities. The unplugged coding experiences we engaged in today would certainly add to students' good learning so I plan to repeat simulations such as Project Wild's "Oh Dear" and CUPs with students.
With regard to technology, the workshop leaders recommended hands-on learning followed by online simulations and/or data analysis. I can imagine asking children to collect data more often with regard to the learning we're doing or problems we are experiencing, and then using Google sheets to organize, manipulate, and analyze the data. At the start of the year, I can use this as students play a simple dice game to practice addition and multiplication facts. Children can input the data into a shared sheet related to the frequency of the sums and products that appear and then we can organize, manipulate, and analyze that data. It was recommended that the grade two unit on the website provides an early model for this kind of activity.
As a group we discussed the creation and use of models too, and the fact that it's important to discuss relative size with students. Often a model is impossible to make to scale such as a solar system model, and it's important to help students understand that when you make models like that are difficult to replicate. I experienced this phenomenon as I tried to replicate base 10 models for the students. The Museum of Science solar system model was referenced during this discussion and it may be a model that we want to share with families and students this year or next year when we visit the Boston Museum of Science again.
We discussed the skills that students will need in the future. I mentioned the Deloitte study that @davidculberhouse introduced me to and the presenters shared powerful insights about this topic with an emphasis on social intelligence, complex critical thinking, and problem solving. A John Oliver piece was mentioned in this regard.
There are many grade-level units on the website which I look forward to embedding into our curriculum and sharing with colleagues in the days to come. Specifically I will embed Number Fluency and Fractions Unit beginning this week and the Plants Make Their Own Food unit as part of our STEAM grade-level plant packets unit. DESE has made this easier by providing a stipend for materials. The units were designed to fit into the current state scope and sequence of grade-level standards.
Computational thinking was defined as a problem solving process that requires people to think in new ways to enable effective use of computing to solve problems and create solutions. The "big buckets" that the day and follow-up study include are modeling, data and analysis, algorithmic thinking and abstraction. The goal of computational thinking is not to make everyone a programmer, but instead to acknowledge that everyone interacts with tech all day, many times a day, and it's in our best interest to learn how to use these intelligent assistants in meaningful, productive, and enriching ways.
The day left me with lots to think about in the days ahead. Specifically I'll implement the two units I mention above, share other units with colleagues, attend a related June 11th DESE STEM workshop, and continue to immerse myself in this study as I work with colleagues to grow an engaging, empowering multidisciplinary math, science, and computational thinking curriculum.
I welcome your thoughts and ideas as I embark on this new journey. And, thanks to Anne DeMallie and Kevin Waterman for leading such a wonderful and insightful day.
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