Abstract
Viewed through the Social Construction of Technology framework, the effects of AI tools on early childhood cognitive development are not only dependent on the technology itself but also on the technical capabilities and social environments in which they are utilized. Across the analysis presented in this thesis, AI systems are viewed as flexible tools whose developmental impact is shaped through interpretation, regulation, and use.
In this context, children do not engage with AI in isolation. Instead, their interactions are guided by teachers and cultural norms that dictate whether AI is framed as assistance or authority, or when it is restricted entirely. These differing interpretations influence whether AI becomes useful for developing cognitive processes in young minds or as a substitute for independent reasoning. Similarly, developers embed assumptions about knowledge, efficiency, and correctness into these AI systems, which then influence how users perceive and utilize their products.
Educational institutions further stabilize certain meanings of AI by formalizing its role within curricula and classroom practices. Where structured guidance is present, AI tends to function as a helpful tool to facilitate learning and provide instruction. In less structured environments, the same systems can shift toward serving as problem-solvers, hampering students’ learning progress and undermining trust in the education system. Knowledge is no longer exclusive to human educators, and the perceived reliability of AI outputs can reshape how children evaluate information and expertise. This redistribution reflects differences in institutional trust, technological competence, and cultural expectations surrounding learning.
From a SCOT perspective, the role of AI in learning remains contested and continues to evolve through competing social definitions of what education, intelligence, and cognitive development should look like in an increasingly automated society. This synthesis therefore reinforces the central argument that the cognitive effects of AI on young learners cannot be explained through technological capability alone. Rather, these outcomes are the result of interactions between technology and existing social structures, making educational policy, cultural values, and system design equally important in shaping long-term educational institutions for children.
