AI-Teacher Teaching Task Spectrum in Action

Abstract

The AI-Teacher Teaching Tasks Spectrum (AITTTS) was conceived as a way to understand the relationship between human teachers and the ever-evolving AI technologies in education. This study demonstrates how the AITTTS framework can be operationalised into a tangible intervention, showcasing the design models and practical applications of the AITTTS in real-world educational settings. By categorising teaching tasks into a spectrum, the AITTTS delineates the roles that AI and human teachers can play, providing a structured and nuanced understanding of their collaboration. As a result of the practical application of the AITTTS, a design model was birthed in this study. It highlights various aspects of holistic student outcomes such as positive electronic nonverbal communication (eNVC) cues, adaptive learning paths, and interactive learning responses as elements by which AI should be designed. By providing a structured approach for educators to incorporate AI tools and interventions in their learning environments, this research lays the groundwork for further exploration of the synergistic relationship between AI and human teachers in modern education. This framework can serve as a guide for educators to develop and implement AI-enhanced teaching strategies, fostering a more dynamic and responsive educational landscape.