From Classroom Care to Digital Support: Ecological Foundations for Teacher-Responsibility, AI-Integration and Student Well-Being Framework

Abstract

This theoretical article develops a lean conceptual framework describing how the teacher responsibility can promote student mental health in higher education by the mediating factor of AI integration in learning. The model is based on the Ecological Systems Theory (PPCT), which places teacher responsibility as a proximal classroom factor that organizes facilitating processes, such as clear guidance, formative feedback, and scaffolding, and responsibly deployed AI tools (adaptive practice, intelligent tutoring, conversational agents) offer timely and personalized support, which decreases cognitive load and enhances autonomy and competence. We formulate testable hypotheses that state that (a) there exists a direct positive correlation between teacher responsibility and student mental well-being and (b) there is an indirect impact through the adoption of AI. The paper describes suggested operational definitions and reflective scales (adapted teacher responsibility, Warwick-Edinburgh Mental Well-Being Scale (WEMWBS), and AI-integration scales), provides a procedure/statistical solution to method bias, and provides a roadmap to empirical validation (using a cross-sectional survey and mediation analysis). In theory, the work incorporates both human and technological support into an ecological framework, beyond siloed approaches to education and ed-tech. In practice, the work supports educators and institutions in co-designing responsibility-informed teaching with the use of ethically governed AI used to create inclusive and supportive learning environments to meet emerging student mental-health issues. The framework is designed to guide evidence-based policy and course design in fast-digitizing systems, with China being a topical setting to be tested in the future.