Social humanoid autonomous robots in K–12 schools: a role–evidence–governance framework for distributed instructional capacity

Abstract

Persistent teacher shortages, large classes, and advances in embodied artificial intelligence invite renewed theoretical attention to social humanoid autonomous robots (SHARs) in K–12 schools. This conceptual framework article develops a positive but qualified socio-technical account of SHARs as emerging embodied instructional and schoolwide support agents. Through an integrative, evidence-graded synthesis spanning educational social robotics, intelligent tutoring, mathematics and language education, inclusion, learning theory, AI governance, child rights, and teacher-workforce research, the article proposes a Role–Evidence–Governance (REG) Framework. REG examines the role assigned to a SHAR, the evidentiary warrant for that function, and the governance conditions required for educational defensibility, treating deployment scale as a cross-cutting contextual modifier. A constructed near-future limit-case vignette—a SHAR in a multilingual 10th-grade mathematics classroom—stress-tests the framework; no robot was deployed and no data were collected. Distributed cognition, Activity Theory, and the ICAP framework clarify how SHARs might reorganize participation, feedback, representation, language mediation, and teacher–student–technology relations. The analysis distinguishes directly supported functions, adjacent-technology-supported functions, plausible extensions, and speculative high-risk applications, without claiming current SHARs are ready as unrestricted teachers of record. It identifies bounded research pathways, nondelegable human responsibilities, and governance requirements around privacy, surveillance, bias, over-trust, accountability, labor, and safety.