Towards a learning progression of sequencing and algorithm design for five- and six-years-old children engaging with an educational robot

Abstract

ABSTRACTBackground and Context Computational thinking (CT) is a fundamental skill and a new form of literacy that everyone should develop to participate in civic society. Sequencing and algorithmic thinking are at the core of CT. This study looked into how young children enrolled in a kindergarten in Colombia develop CT skills.Objective This paper aims to develop a learning progression of sequencing and algorithm design for early childhood. This goal is complemented by identifying the challenges children face to advance into more sophisticated approaches to problem-solving using algorithmic thinking.Method Fourteen five- and six-year-old students participated in this study. These children participated in unplugged learning activities, and solved two sets challenges with the BeeBot. We used a grounded theory approach to analyze how they solved these algorithmic thinking activities and the challenges they faced in this process.Findings Our results suggest four increasingly sophisticated approaches to solving these activities: step-by-step, simple decomposition, advanced decomposition, and full algorithm design. We also found different challenges students faced when working on these activities. These challenges can relate to critical cognitive skills.Implications These results will enable educators to support student learning about CT. These results also open new questions about the relationship between cognitive skills and CT activities in early childhood.KEYWORDS: Computational thinkingearly childhoodlearning progressionsequencingalgorithmic thinkingvisuospatial skills AcknowledgmentsWe would like to thank Mariana Arboleda, Gabriela de la Rosa, Roxana Quintero, Britny Velasquez, Gisella Jassir, and Angélica Carrasquilla for all the data collection support.Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThe work was supported by the Fulbright Colombia and Center for Global Inquiry and Innovation at theUniversity of Virginia.