Human–Machine Collaboration in Gen AI-Hybrid Teaching: Emotion Analysis

Author : Amelia Ijiri, Lynsey Mori

Abstract : Human–machine collaborative decision-making in education requires a deliberate balance between algorithmic intelligence and human professional judgment. While artificial intelligence (AI) systems excel at processing large-scale, time-series, emotional and behavioral data, educational decision making remains fundamentally value-laden, relational, and context-dependent. This study positions teachers as central agents within human–machine hybrid teams, arguing that emotional analytics can support teachers’ ethical judgment, emotional attunement, and responsibility for classroom climate and emotional regulation. Data provides teachers with evidence-based insights into classroom emotional “temperature,” enabling informed micro-adjustments to pedagogy, pacing, and peer-support strategies while maintaining teacher agency over instructional decisions. This data functions as a starting point for dialogue including prompting teacher-initiated check-ins, peer-buddy interventions, and norm setting around emotional transparency. The division of labor reinforces complementary strengths: AI supports detection and aggregation, while educators preserve accountability for values, trust, and care. Within emerging human-machine co-teaching environments, generative AI systems can support pattern recognition across large volumes of affective communication data, while humans retain responsibility for interpretation, ethical response, and relational repair Positioned within a broader framework of culturally responsive and relational AI integration, this study highlights the risks of algorithmic overreach and epistemic reductionism, advocating instead for teacher-centered hybrid systems that prioritize professional agency, relational sensitivity, and contextual judgment

Keywords : Generative artificial intelligence, human-machine collaboration, social emotional learning

Conference Name : International Conference on Education Technology and Big Data (ICETBDA-26)

Conference Place : Bristol, UK

Conference Date : 13th Jun 2026