ARTIFICIAL INTELLIGENCE IN TEACHER EDUCATION: SWOT ANALYSIS, USE CASES AND IMPACTS ON ASSESSMENTS

Abstract

In contemporary society, teachers function within interconnected networks,  primarily engaging with digital natives, that is, students who are born into and raised  in a technologically-driven environment. Within this social context, it is implausible  for teachers to effectively carry out their profession without the assistance of  technologies which have played crucial roles in shaping this new social landscape,  especially Artificial Intelligence (AI). Anchored to the Unified Theory of Acceptance  and Use of Technology, this paper explored the use cases, strengths, weaknesses,  opportunities and threats (SWOT Analysis) of the integration of AI in teacher  education. It broadly analysed the use-controls and framework for Artificial  Intelligence integration in education while interrogating the impact of AI in  educational assessment. The paper deploys theoretical analysis, narrative synthesis  and literature review to chart the emerging trajectories of AI in teacher education.  The paper showed that AI technologies have both positive and negative effects on  education, and it has become critical to integrate AI in teacher education curriculum,  just as teacher training institutions need to implement appropriate strategies to meet  teachers' and students' pedagogical needs within the AI space. A sample mind mapping of the use cases of the AI in the teacher education was constructed, and the  how AI technologies will change educational assessment was speculated, in what is  called The Inverted Bloom's Taxonomy.