Fostering Deep Belonging Through Culturally-Responsive AI Mentorship Agents: An Identity-Affirming Framework for Educational Support

Zan Li; Yida Zhu

doi:10.70393/6a6374616d.333334

Authors

Zan Li Beijing University
Yida Zhu Rutgers Business School

DOI:

https://doi.org/10.70393/6a6374616d.333334

ARK:

https://n2t.net/ark:/40704/JCTAM.v2n6a06

Disciplines:

Artificial Intelligence and Intelligence

Subjects:

Machine Learning

References:

45

Keywords:

Culturally-Responsive AI, Educational Mentorship Agents, Deep Belonging Framework, Identity-Affirming Technology

Abstract

Culturally-responsive AI mentorship agents represent a substantial change in educational technology, addressing critical gaps between personalized learning systems and students' psychological needs for belonging. This research presents a comprehensive framework integrating multi-agent architectures with identity-affirming interaction mechanisms to cultivate deep belonging across diverse student populations. Through a mixed-methods empirical study involving 120 participants from three distinct cultural groups over six months, we demonstrate that culturally-adaptive AI mentors achieve 34.7% higher belonging scores compared to culturally-neutral systems. The framework employs dynamic cultural profiling, identity-safe feedback strategies, and personalized belonging interventions adapted from established psychological research. Statistical analysis reveals significant mediation effects where cultural responsiveness influences academic outcomes through enhanced belonging (β = 0.412, p < 0.001). Implementation across educational contexts shows differential effectiveness patterns, with underrepresented groups experiencing 42.3% greater benefit from culturally-responsive features. This work establishes theoretical foundations and practical guidelines for deploying AI mentorship systems that strengthen rather than diminish human connection in digital learning environments.

Author Biographies

Zan Li, Beijing University

Communication, Beijing University, Beijing, China.

Yida Zhu, Rutgers Business School

Financial Analysis, Rutgers Business School, NJ, USA.

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