A Multidimensional Conceptual Framework of Generative AI As a Co-Instructor: Measurement Formulation for Personalized and Sustainable Higher Education

Abstract

Generative artificial intelligence (GenAI) is transforming higher education by evolving from a content automation tool into a collaborative instructional partner. However, its conceptualization as a co-instructor remains fragmented and lacks a validated measurement structure. This study develops a multidimensional conceptual framework and measurement formulation that positions GenAI as a structured pedagogical collaborator supporting personalization, sustainability, and ethical integrity. Using a theory-building approach grounded in interdisciplinary literature, the study defines key constructs, specifies relationships, and proposes indicators for future structural equation modeling. The framework identifies three instructional domains co-planning, co-instruction, and co-assessment mediated by pedagogical implementation effectiveness and moderated by ethical governance readiness. An eight-construct model and 37-item instrument are proposed for empirical validation. The study contributes conceptual clarity by advancing a systematic, ethically grounded approach to human–AI collaboration in higher education and recommends institutionally guided, teacher-in-the-loop implementation strategies.