Abstract:

The advent of Artificial Intelligence across global contexts has had, and will continue to have, profound impact on elementary and teacher education as we drive to prepare our learners and educators to learn and teach in a complex, digital driven world. The skills, knowledge, and perspectives required to be a contributing global citizen continue to evolve as the economy, environment, and humanity more broadly, address the complex problems facing societies across the world. Digital fluency has become a basic requirement for active learning and teaching across levels from Early Childhood, through Elementary and Secondary school, to Postsecondary education. A foundation for thinking in a digital age is computational thinking. Computational thinking is a set of processes through which people arrive at solutions to problems using principles based in computer science, specifically through coding. However, computer coding became less imperative as interfaces moved from direct coding to point and click menus and user-friendly platforms. There is concern that learners and curriculum may be losing the computational thinking skills required to think critically with digital fluency. It is critical that we understand how computational thinking and problem solving are connected and measured in order to ensure learners continue to develop the necessary skills for problem solving in a digital age. This presentation will review the skills, practices, and attitudes across problem-solving and computational thinking and suggest how they interact with Artificial Intelligence in elementary education.

An understanding of how learners use computational thinking in problem solving was developed in a mixed methods study of problem solving and computational thinking across developmental levels with grade 4 and grade 8 students in two elementary schools in Canada. Students completed a computerized CT Assessment (Roman-Gonzalez et al., 2017) measuring Computational Thinking and did trials of the Tower of Hanoi with a “think aloud” protocol. CT scores and Problem Solving scores (Tower of Hanoi trials) will be correlated and compared across grade levels. Transcripts of think alouds during the Tower of Hanoi trials were analyzed for themes that include the skills, knowledge, and perspectives of computational thinking and problem solving. Results will be used to identify differences across grades in terms of problem solving and computational thinking. Qualitative responses will expand the understanding of children’s computational thinking.

Recognizing that Artificial Intelligence (AI) has begun to infiltrate elementary teaching and learning, as both learners and teachers grapple with awareness, application, and evaluation of tools, practices and platforms that utilize AI, the results of the study will be connected to AI literacy as an extension of computational thinking. The key concepts and skills of each construct and how they interact will be presented as part of an ethical, comprehensive framework for implementing AI instruction across disciplines.

Keywords:

Elementary education, teacher education, problem solving, Artificial Intelligence, computational thinking, learning.