Abstract
<p>This article proposes Sociocritical Computing, a framework for understanding computational learning as the co-development of technical practice, cultural meaning, and critical consciousness. Drawing on a theory synthesis of constructionism and sociocritical literacies, the framework centers computational creation as the site where learners build knowledge through iterative making, debugging, and sharing while also engaging questions of identity, representation, and power. Sociocritical Computing organizes this process through four analytic dimensions: knowledge and identity work, social dialogue, critical consciousness, and transformative sharing. Together, these dimensions show how learners’ interactions with computational artifacts can support both conceptual development and sociopolitical reflection. Three cases from a critical machine learning program designed for children aged 9 to 13 illustrates the framework through cases from a critical machine learning program illustrate how learners used computational tools to examine bias and the social consequences of deep learning AI systems. Across these cases, computational tinkering became a means for developing technical understanding alongside culturally and critically meaningful forms of interpretation and action. The framework contributes an integrated lens for research and design in learning with computational media, with particular relevance for emerging contexts in which young people are increasingly expected to understand, question, and shape technologies in their lives.</p>