Leveraging Symbolic Representations to Understand Young Learners’ Interactions with Computational Thinking Concepts

摘要

Computational thinking (CT) holds significant value in STEM education because it emphasizes cultivating problem-solving skills mediated by computational technologies.This aspect of CT enhances the educational experience for learners and can open promising opportunities for supporting and assessing learning with new technologies.Using a 14-week curriculum designed to integrate CT into fourth-grade mathematics classrooms using a programmable robot, we explore how young learners use symbolic representations to translate across contexts.We investigate the potential of symbolic representations in developing CT skills, including decomposition and abstraction.We present vignettes to show how young learners' use of symbolic representations in CT tasks can contribute to a deeper understanding of how students conceptualize and engage with computational problem-solving.This work advances our understanding of how integrating CT in early-grade classrooms can significantly enrich STEM education thus highlighting the importance of developing CT skills for earlygrade learners. Previous workFoundations of CT can be traced back to Papert's pioneering work with Logo (Papert, 1980).Jeannette Wing popularized the term in her 2006 article, defining CT as the ability to "solve problems, design systems, and understand human behavior by leveraging core concepts from computer science" (Wing, 2006, p.33).Researchers have developed various frameworks to define CT adapted to specific contexts or target age groups.Expressing CT ideas requires students to articulate real-world problems in a manner that a computer or machine can interpret and execute (Wing, 2016).This process demands problem-solving proficiency, clearly articulating intentions and instructions, interaction with the learning environment, and engagement with the computer system (Papert, 1980).