Principles for Teaching, Leading, and Participatory Learning with a New Participant: AI

Abstract

This paper discusses principles and practices that can optimize artificial intelligence (AI) in teaching and learning from the perspectives of leading organizational change and by reimaging learning activities with AI as a collaborative partner. Based on the Kowch's participatory teaching and learning (PTL) principles for networked organizations, the authors analyze the integration of new talent patterns emerging in more agile interdisciplinary education systems connected through information and technologies, and propose principles for collaboration through machines as AI participants and principles for designing new education systems where the teams with AI can thrive. Taking a different angle from the traditional linear education system design tasks and education institution redesigns, the proposed principles assume more time for education and training leaders to take stronger leadership roles in the creation of better teams with AI augmentation. We offer principles for designing education institutions that are capable of adapting with these innovations and we also offer principles for designing these next generation learning environments. Finally by "zooming in" on instruction and AI, we use Activity theory to imagine better inclusions of social and cultural components with AI as an important, emerging, and unscripted new partner.