How to Effectively Introduce Coding and Computational Thinking into Your Classroom
The inclusion of coding and computational thinking (CT) skills across all levels of education is gaining momentum worldwide. Here at home, the Ministry of Education recently announced a focus on coding and CT skills in our Ontario schools. What follows are recommendations related to how large jurisdictions can adequately prepare our teachers to introduce and foster the development of coding and CT skills in our students.
These recommendations draw on my experience teaching high school computer science and facilitating professional learning for both practicing and pre-service teachers. They are also based on observations from my work in research projects focused on coding and CT across grade levels.
Recently, I have had the privilege to work with school board leadership teams who are experts in running effective professional development. Together we designed professional development focused on identifying, introducing and fostering coding and CT skills. We found that, as with anything in education, it’s best if professional learning is flexible and adjusted to suit the needs of the educators and their students.
Include students in Computational Thinking and Coding professional learning days.
I’ve seen tremendous benefits with including student leaders in professional learning days. Not only do teachers get to see the student perspective and their response to often what is an entirely new concept, there are now many more helping hands as coding and CT is integrated into classes. In my experience, junior and intermediate student leaders have successfully led activities for primary students as well as assisted with activities for their own peers.
Check out the following video to see Jeff, an educator in Algoma District School Board, discuss the benefits of including student leaders in professional learning initiatives.
Ensure the facilitator has a clear understanding of what Computational Thinking is as well as how to integrate Coding effectively.
Consider the work by Kotsopoulos and Lee (2014), in which they indicate that the teacher’s ability to notice and name mathematics in children’s play is important for the teacher to subsequently nurture mathematical thinking in their students. In a recent research project led by Dr. Kotsopoulos on CT, we spent the first few workshop sessions helping educators to name and then nurture CT, drawing on similar assertions from mathematics (Kotsopoulos, Nelson, Floyd and Makosz, submitted for publication).
I often hear advice given to teachers related to coding along the lines of “just dive right in” with your students. Coding and CT are new concepts for many of us and most teachers will need guidance and support if we are expecting them to incorporate these ideas effectively. As with any new educational tool, it’s important that teachers have the opportunity to try out coding activities so that they are not only able to anticipate student misconceptions and possible issues, but so they feel confident in the activities they select to integrate into their lessons. Teachers know their students best and will likely need to adjust suggested tasks to suit the needs of their teaching style and students.
Many excellent examples and videos for integrating Coding and CT effectively with math can be found here.
Focus on the Adaptive Expert mindset and include opportunities for participants to investigate evidence-based research.
Adopting an adaptive expert mindset involves educators drawing “on what is known from research,” and transferring and applying it to their own situation (Le Fevre, Timperley and Ell, 2015). It can also be considered immersing educators in “new ways of thinking about teaching and learning” (Le Fevre, Timperley and Ell, 2015). Coding and CT can certainly be considered a novel way of thinking for many educators and their students.
Ideally, the facilitator will provide research related to coding and CT and allow the participants the opportunity to think critically about the findings and recommendations. It is important that educators can look at the research from their own perspective and select what is relevant and helpful for their own students and teaching practice. The educators’ insights should be valued when identifying next steps in the learning.
For more supporting evidence, see this What Works article by Dr. George Gadanidis.
It is important that educators can look at the research from their own perspective and select what is relevant and helpful for their own students and teaching practice.
Deliver multiple days of professional learning (and include time for consolidation and reflection.)
We know from research that learners need to be given an opportunity to consolidate new ideas and to reflect on these in order for deeper connections to be made. I find limiting professional learning about coding and CT to one day doesn’t provide that level of sustainability and long-term uptake of the associated new pedagogical approaches that most school boards are looking for. Teachers feel more confident when they have time to incorporate coding and CT and then come back for follow-up days of learning. Not only does this allow for reflection, but it also increases the number of connections teachers are able to make to their current practice.
Adopt a model that includes time to try, learn and extend.
Ensure the facilitator provides the teachers with tools and methods to incorporate coding and CT and allows participants enough time to try out these activities. We’ve noted in Computational Thinking in Mathematics Teacher Education (Gadanidis, Cendros, Floyd and Namukasa, in press) that pre-service teachers’ confidence and attitude toward CT increased when introduced to fun hands-on coding and CT activities in class. Once the educators gain experience in coding and CT tools and tasks, they can then begin to imagine and plan out how they can adapt the tasks for their own students.
Finally, if you are looking for a model to focus on as you deliver professional learning, you may want to check out this Pedagogical Framework for Computational Thinking (Kotsopoulos, Floyd, Khan, Namukasa, Somanath, Weber and Yiu, 2017).
Figure 1 Four Pedagogical Experiences of CT, Kotsopoulos et al, 2017.
I find it beneficial to start with an unplugged activity followed by an explanation of what CT is, share examples and provide a chance to try out a variety of activities. Ideally, the activities should provide a low floor, high ceiling to afford integration across multiple grade levels. When the connections across grade levels are made explicit, students are better able to build on what they have been learning. Teachers appreciate this opportunity to test out activities and begin to imagine and plan how they can adapt the activity for their own students.
Lisa Anne Floyd is the Director of Research and Inquiry at Fair Chance Learning and a Computational Thinking in Math/Science instructor at Western University’s Faculty of Education. She recently completed her Masters in Professional Education in the field of Mathematics and has many years of experience teaching computer science, math and science in the Thames Valley District School Board in London, Ontario. Lisa enjoys speaking and sharing her passion for coding and computational thinking through professional learning initiatives with school districts across Canada.
Curzon, P. (2015, July 1). Paul Curzon on teaching Computer Science “Unplugged”. Retrieved November 5, 2017, from https://www.youtube.com/watch?v=brC4LgYefiA
Gadanidis, G., Cendros, R., Floyd, L. & Namukasa, I. (in press). Computational Thinking in Mathematics Teacher Education. Contemporary Issues in Technology and Teacher Education.
Kotsopoulos, D., Floyd, L., Khan, S., Namukasa, I., Somanath, S., Weber, J., Yiu, C. (2017). A Pedagogical Framework for Computational Thinking. Digital Experience in Mathematics Education
Kotsopoulos,D., Nelson, V., Floyd, L. Makosz, S. (submitted for publication review). Noticing and Naming Computational Thinking during Play.
Kotsopoulos, D., & Lee, J. (2014). Let’s talk about math: The LittleCounters® approach to building early math skills. Baltimore, MD: Brookes Publishing Co., Inc.
Fevre, D. Le, Timperley, H., & Ell, F. (2015). Curriculum and Pedagogy : The Learning and the Development of Adaptive Expertise, 309–324.
Ministry of Education. (2016). Ontario Helping Students Learn to Code. Retrieved November 5, 2017 from https://news.ontario.ca/edu/en/2016/12/ontario-helping-students-learn-to-code.html