Artificial Intelligence and the Future of Asynchronous Online Teacher Education

Abstract

Artificial intelligence (AI) is forcing higher education, and online teacher preparation in particular, to confront difficult questions about integrity, equity, and the very purpose of professional preparation. Online programs have long been valued for their flexibility and accessibility; however, the rise of generative AI (Gen AI) challenges assumptions about what it means to learn, to demonstrate competence, and to become a teacher. This paper examined how AI disrupts online teacher education, raising urgent concerns while offering pedagogical possibilities. The most pressing risks involve the temptation for students to let AI complete their work, the inaccuracy of detection systems that can create unfair accusations, and the persistence of inequities for those with limited access to digital tools. These challenges represent the core of instruction, questioning how educators can design tasks that promote authentic engagement and ensure learning outcomes are met. If left unaddressed, such weaknesses could undermine the credibility of online teacher education at a time when it has already faced skepticism. At the same time, AI offers powerful new avenues for teaching and learning. It can provide adaptive feedback, tailor learning to individual needs, support continuous access to resources, and create rich simulations for practicing essential teaching skills. Approaches such as field -based assignments and pedagogy such as project-based learning, are conducive to AI integration while preserving human-centered, real-life learning experiences that prepare candidates for effective teaching. This paper concludes that the future of online teacher education depends on finding a balance between innovation and accountability, using AI to enrich learning and expand opportunities while ensuring authentic, ethical, and human-centered pedagogy remains central, so programs prepare competent teachers rather than becoming degree mills.