Learning Computational Thinking Practices Through Agent-Based Modeling in an Informal Setting

Abstract

In this qualitative study, I investigated the form of interaction when learners co-constructed computational thinking practices in an informal setting. This study focuses on the roles of five youth, three adult mentors, and a facilitator during a summer camp and documents how learners interacted to exchange ideas, collaborate, and accommodate other perspectives. Participants used questions that promote deep thinking to engage in computational thinking practices during the interactions. Analysis of data shows that learners developed computational thinking practices including interpreting, modeling connections to the real-world, manipulating parameters, discovering ideas to explore models, prompting, conjecturing, and making predictions when working on agent-based modeling and writing codes in NetLogo. These practices are further grouped together as model interpretation and connection to the real world, parameter manipulation and discovery, prompting and exploring, and making predictions/conjectures and generalizing. This study also finds some community-based practices such as practical wisdom, trying something and adjusting, and the use of network of resources relevant during interaction to develop computational thinking practices.