From hanging out to figuring it out: Socializing online as a pathway to computational thinking

2020-05-21

New Media & Society

AI Summary

This study addresses a key challenge in educational platforms: effectively transforming adolescents’ online social interactions into opportunities for computational thinking development. Focusing on over 14,000 comments from the Scratch platform, the research introduces the novel concept of “participatory debugging,” wherein users cultivate computational thinking through collaborative troubleshooting. Employing a mixed-methods approach that integrates inductive analysis, content analysis, and longitudinal qualitative analysis, the study identifies three critical social antecedents that support this practice: sustained community engagement, identifiable problems, and topical permeability. The findings not only demonstrate the prevalence of participatory debugging but also establish a theoretical framework linking interest-driven social interaction to computational thinking learning, offering empirical grounding and design implications for creating socially engaging, learning-oriented platforms.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Economics, Online Markets and Human Computation: Social networks and social learning
• Social Networks and Social Media: Computational social science
• Web Mining and Content Analysis: Community question answering

Abstract

Although socializing is a powerful driver of youth engagement online, platforms struggle to leverage social engagement to promote learning. We seek to understand this dynamic using a multi-stage analysis of over 14,000 comments on Scratch, an online platform designed to support learning about programming. First, we inductively develop the concept of “participatory debugging”—a practice in which users learn through the process of collaborative technical troubleshooting. Second, we use a content analysis to establish how common the practice is on Scratch. Third, we conduct a qualitative analysis of user activity over time and identify three factors that serve as social antecedents of participatory debugging: (1) sustained community, (2) identifiable problems, and (3) what we call “topic porousness” to describe conversations that are able to span multiple topics. We integrate these findings in a framework that highlights a productive tension between the desire to promote learning and the interest-driven sub-communities that drive user engagement in many new media environments.

Problem

• online socializing
• computational thinking
• youth engagement
• learning promotion
• participatory debugging

Innovation

• participatory debugging
• computational thinking
• online learning communities
• topic porousness
• social antecedents