Identifying Empirical Needs for AI-Integrated Sustainable Teacher Education: A Convergent Mixed-Methods Study

Husnin  Mubarak; Nurhikmah  H.; Risma  Niswaty

doi:10.63922/ijeter.v4i03.5872

Husnin Mubarak Student of Sciences Education, Makassar State University, Makassar, Indonesia
Nurhikmah H. Student of Sciences Education, Makassar State University, Makassar, Indonesia
Risma Niswaty Student of Sciences Education, Makassar State University, Makassar, Indonesia

DOI: https://doi.org/10.63922/ijeter.v4i03.5872

Keywords: Artificial Intelligence Literacy; Sustainability Literacy; Teacher Education; and Generative Artificial Intelligence.

Abstract

The rapid advancement of Generative Artificial Intelligence (GenAI) offers transformative opportunities for teacher education while raising concerns about ethical use, professionalism, and sustainability. This study identified empirical needs for developing an AI-integrated sustainable teacher education framework using a convergent mixed-methods design within Design and Development Research (DDR). Data from literature and document analysis, focus groups, interviews, and surveys were integrated through methodological triangulation. Five key needs emerged: positioning AI as a human-centered cognitive partner, promoting ethical and evidence-based AI use, integrating AI Literacy and Sustainability Literacy, establishing pedagogical guidance for AI-supported learning, and strengthening teacher agency and responsible decision-making. These findings were translated into evidence-based design requirements, providing a foundation for developing responsible and sustainable AI-integrated teacher education.

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