The paper analyzes the teaching and learning of computational thinking and data literacy as it impacts pres-service teachers, and provides two research-based instructional design strategies.
United States education has experienced a big push for students to learn coding as part of computer science and more explicitly address computational thinking. Some of this focus stems from the 2013 Next Generation Science Standards, which asserts “In both science and engineering, mathematics and computation are fundamental tools for representing physical variables and their relationships. They are used for a range of tasks such as constructing simulations; statistically analyzing data; and recognizing, expressing, and applying quantitative relationships.” Additionally, the 2016 International Society for Technology in Education standards for students and for educators directly addresses computational thinking and its benefits.
Computational thinking (CT) is often associated with mathematics, which remains a challenging subject for many students, including pre-service teachers. CT also overlaps computer science, which tends to be offered as an elective course in P-16 education. In K-8 settings, specially, teachera often use pre-packaged lessons that are unrelted to existing curriculum. Furthermore, even fewer pre-service teachers were taught STEM problem-solving such that their solutions were derived in ways that a computer could execute them. In short, pre-service students usually do not have foundational knowledge to guide them in integrating computer science and computational thinking into the curriculum that they will eventually teach as instructors themselves.
Pre-service teacher instruction about computational thinking sometimes mirrors K-12 approach: that is, a short-term unit that covers CT principles and applications in core curriculum through lesson planning. Sometimes students evaluate CT materials and CT-related tools, which they might adapt for a specific setting. Other times, computational thinking and computer science are combined in a separate course, which might be required or optional. In such courses, students typically do some coding. In either case, instructors and learners usually find it hard to integrate CT in non-STEM disciplines.
Two research-based strategies hold promise. In an educational technology course, a module on teaching problem-solving with technology defined CT and explained its benefits. Course students examined CT lessons and projects. CT was also linked to the design process, and the students did a learning activity on the engineering design process. Students then blogged about their design process experience and how it might inform teaching how to solve problems using computational thinking. As their signature assignment, the students had to create a WebQuest that focused on computational thinking. In another course, focusing on math methods for K-8 settings, pre-service teachers also learned about CT concepts and collaborated to create CT lessons for K-8 students that linked CT to everyday life.
In some, this session explains computational thinking in light of K-12 education, identifies issues integrating computational thinking into K-12 curriculum, and discusses pre-service teachers’ preparation that can lead to their successful incorporation of CT into the curriculum.