New Perspectives in Science Education
Didactica Artificialis: Toward a New Discipline for Teaching and Learning with Artificial Agents
Constantine Andoniou, Abu Dhabi University (United Arab Emirates)
Abstract
Artificial intelligence now saturates educational settings—tutoring, companioning learners, generating content—yet our theoretical tools have not kept pace. Educational technology scholars tend to view AI as an instrument, something that serves human learning. Machine learning researchers, for their part, treat the training of models as an optimization problem, with little interest in what this might mean pedagogically. Neither field has developed the vocabulary needed to make sense of what happens when an artificial agent becomes part of the teaching-learning relationship. This paper puts forward Didactica Artificialis as a field in its own right: an inquiry into teaching and learning whenever at least one participant is artificial. Such a field would need to build its own ontological ground, its own ethical commitments, its own methods, and its own sense of where it came from historically. What we stand to gain is the ability to pose questions that fall outside existing disciplines altogether—questions about whether training a model counts as teaching it, whether something can learn without experiencing, what hidden curricula AI systems might carry, and what changes when a teacher has never struggled or grown.
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Keywords |
artificial intelligence in education, didactics, pedagogy, human-AI interaction, educational theory |
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