In recent years, computational thinking (CT) and coding have received increased attention in K-12 education. In response to the global movement toward information-based and technology-driven economies, “industry, government, academia, and non-profit sectors” of society have called for the introduction of CT/coding into school curricula (Gadanidis, Cendros, Floyd, & Namukasa, 2017, p. 473). Many educational jurisdictions worldwide have answered this call. Buteau, Gadanidis, Lovric, and Muller (2017) note that Australia, England, Estonia, France, New Zealand, Sweden, British Columbia, and Nova Scotia have all added aspects of CT/coding to their school curricula.
Indeed, there are many good reasons to add CT/coding to compulsory education. Doing so would help prepare today’s students for tomorrow’s reality as computational thinking and coding skills are predicted to be highly desired in the job market of the near future (Bower & Falkner, 2015; Israel, Wherfel, Pearson, Shehab, & Tapia, 2015; Yadav, Hong, & Stephenson, 2016). Also, the integration of CT/coding with mathematics instruction has been shown to increase student understanding and achievement (Calao, Moreno-León, Correa, & Robles, 2015; Gadanidis, Brodie, Minniti, & Silver, 2017; Gadanidis, Clements, & Yiu, 2018).
However, the benefits of CT/coding are only available to students whose teachers have acquired the skills and knowledge necessary to integrate it effectively with classroom instruction. In Ontario, few teachers fit this description. Most teacher candidates enter faculties of education with little or no understanding of CT/coding (Gadanidis, Cendros, et al., 2017). Given that the province’s teacher education programs have only recently addressed CT/coding, it follows that most practicing educators have never received any formal training in these areas. While it is true that some educators have sought and attained significant CT/coding knowledge and skills, these individuals have been categorized as “atypical innovators” amongst a population badly in need of professional development (Namukasa et al., n.d., p. 10). The lack of a province-wide, Ministry-driven initiative to bring CT/coding to the classroom in a purposeful and effective manner leaves Ontario’s educators with little direction. This absence, coupled with the widespread lack of educator training, leads to a situation in which many educators’ attempts to integrate CT/coding into their practices result in little student learning. Bower and Falkner (2015) describe what commonly happens in classrooms under these circumstances:
Indeed, there are many good reasons to add CT/coding to compulsory education. Doing so would help prepare today’s students for tomorrow’s reality as computational thinking and coding skills are predicted to be highly desired in the job market of the near future (Bower & Falkner, 2015; Israel, Wherfel, Pearson, Shehab, & Tapia, 2015; Yadav, Hong, & Stephenson, 2016). Also, the integration of CT/coding with mathematics instruction has been shown to increase student understanding and achievement (Calao, Moreno-León, Correa, & Robles, 2015; Gadanidis, Brodie, Minniti, & Silver, 2017; Gadanidis, Clements, & Yiu, 2018).
However, the benefits of CT/coding are only available to students whose teachers have acquired the skills and knowledge necessary to integrate it effectively with classroom instruction. In Ontario, few teachers fit this description. Most teacher candidates enter faculties of education with little or no understanding of CT/coding (Gadanidis, Cendros, et al., 2017). Given that the province’s teacher education programs have only recently addressed CT/coding, it follows that most practicing educators have never received any formal training in these areas. While it is true that some educators have sought and attained significant CT/coding knowledge and skills, these individuals have been categorized as “atypical innovators” amongst a population badly in need of professional development (Namukasa et al., n.d., p. 10). The lack of a province-wide, Ministry-driven initiative to bring CT/coding to the classroom in a purposeful and effective manner leaves Ontario’s educators with little direction. This absence, coupled with the widespread lack of educator training, leads to a situation in which many educators’ attempts to integrate CT/coding into their practices result in little student learning. Bower and Falkner (2015) describe what commonly happens in classrooms under these circumstances:
The ideas described above have led to the development of the following inquiry question:
How can computational thinking and coding be integrated effectively into Ontario’s intermediate mathematics curriculum
to increase student engagement and achievement in mathematics?
to increase student engagement and achievement in mathematics?
Barr and Stephenson (2011) state that two sets of resources are required to stimulate systemic change toward effective and lasting incorporation of CT/coding into education. These are summarized in the table below:
Taking Barr and Stephenson’s recommendations as a framework, I have created two sets of resources, both of which are linked below. Together they perform most of the functions described above; the only exception is that definitions for computational thinking, coding, and programming exist here in the larger website and are not repeated in the pages subordinate to this one. These resources have been made equally available to both educational policy makers and teachers as it is important that members of both groups develop clear understandings of all aspects of CT/coding integration with mathematics.
References
Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12. ACM Inroads, 2(1), 48-54.
Bower, M., & Falkner, K. (2015). Computational thinking, the notional machine, pre-service teachers, and research opportunities. In D. D'Souza, & K. Falkner (Eds.), Proceedings of the 17th Australasian Computing Education Conference (ACE 2015) (Vol. 160, pp. 37-46). Sydney: Australian Computer Society.
Buteau, C., Gadanidis, G., Lovric, M., & Muller, E. (2017). Computational thinking and mathematics curriculum. In S. Oesterle, D. Allan, & J. Holm (Eds.), Proceedings of the Canadian Mathematics Education Study Group (CMESG) 2017, Kingston (119-135). Kingston: CMESG.
Calao, L. A., Moreno-León, J., Correa, H. E., & Robles, G. (2015). Developing mathematical thinking with scratch. Design for Teaching and Learning in a Networked World Lecture Notes in Computer Science, 17-27.
Gadanidis, G., Brodie, I., Minniti, L., & Silver, B. (2017, April). Computer coding in the K-8 mathematics curriculum? Retrieved April 06, 2018, from http://www.edu.gov.on.ca/eng/literacynumeracy/inspire/research/computer_coding_k8_mathemathics_system.html
Gadanidis, G., Cendros, R., Floyd, L., & Namukasa, I. (2017). Computational thinking in mathematics teacher education. Contemporary Issues in Technology and Teacher Education, 17(4), 458-477.
Gadanidis, G., Clements, E., & Yiu, C. (2018). Group theory, computational thinking, and young mathematicians. Mathematical Thinking and Learning: An International Journal, 20(1), 32-53.
Israel, M., Wherfel, Q. M., Pearson, J., Shehab, S., & Tapia, T. (2015). Empowering K-12 students with disabilities to learn computational thinking and computer programming. TEACHING Exceptional Children, 48(1), 45-53.
Namukasa, I., K., Kotsopoulos, D., Floyd, L., Weber, J., Kafai, Y., Khan, S., Yiu, C., Morrison, L., & Somanath, S. (n.d.). From computational thinking to computational participation: Towards achieving excellence through coding in elementary schools. Retrieved from http://researchideas.ca/coding/docs/CT-participation.pdf
Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends: Linking Research and Practice to Improve Learning, 60(6), 565-568.
Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12. ACM Inroads, 2(1), 48-54.
Bower, M., & Falkner, K. (2015). Computational thinking, the notional machine, pre-service teachers, and research opportunities. In D. D'Souza, & K. Falkner (Eds.), Proceedings of the 17th Australasian Computing Education Conference (ACE 2015) (Vol. 160, pp. 37-46). Sydney: Australian Computer Society.
Buteau, C., Gadanidis, G., Lovric, M., & Muller, E. (2017). Computational thinking and mathematics curriculum. In S. Oesterle, D. Allan, & J. Holm (Eds.), Proceedings of the Canadian Mathematics Education Study Group (CMESG) 2017, Kingston (119-135). Kingston: CMESG.
Calao, L. A., Moreno-León, J., Correa, H. E., & Robles, G. (2015). Developing mathematical thinking with scratch. Design for Teaching and Learning in a Networked World Lecture Notes in Computer Science, 17-27.
Gadanidis, G., Brodie, I., Minniti, L., & Silver, B. (2017, April). Computer coding in the K-8 mathematics curriculum? Retrieved April 06, 2018, from http://www.edu.gov.on.ca/eng/literacynumeracy/inspire/research/computer_coding_k8_mathemathics_system.html
Gadanidis, G., Cendros, R., Floyd, L., & Namukasa, I. (2017). Computational thinking in mathematics teacher education. Contemporary Issues in Technology and Teacher Education, 17(4), 458-477.
Gadanidis, G., Clements, E., & Yiu, C. (2018). Group theory, computational thinking, and young mathematicians. Mathematical Thinking and Learning: An International Journal, 20(1), 32-53.
Israel, M., Wherfel, Q. M., Pearson, J., Shehab, S., & Tapia, T. (2015). Empowering K-12 students with disabilities to learn computational thinking and computer programming. TEACHING Exceptional Children, 48(1), 45-53.
Namukasa, I., K., Kotsopoulos, D., Floyd, L., Weber, J., Kafai, Y., Khan, S., Yiu, C., Morrison, L., & Somanath, S. (n.d.). From computational thinking to computational participation: Towards achieving excellence through coding in elementary schools. Retrieved from http://researchideas.ca/coding/docs/CT-participation.pdf
Yadav, A., Hong, H., & Stephenson, C. (2016). Computational thinking for all: Pedagogical approaches to embedding 21st century problem solving in K-12 classrooms. TechTrends: Linking Research and Practice to Improve Learning, 60(6), 565-568.