Interactionalism: Re-Designing Higher Learning for the Large Language Agent Era

2025-01-01

AI Summary

The rise of large language models (LLMs) poses novel challenges for higher education, necessitating a reconceptualization of pedagogy centered on cultivating learners’ metacognitive and meta-affective competencies—collectively termed “interactional literacy.” Method: This project introduces the novel construct of “interactional intelligence” as a core GenAI-era competency; develops a human–LLM agent co-orchestration learning design paradigm grounded in educational design science, human–AI collaboration theory, and metacognitive training; and derives actionable course design principles and instructional activity templates. Contribution: Moving beyond traditional individual-cognition-centric frameworks, empirical findings demonstrate significant improvements in learners’ core interactional competencies—including high-quality prompting, task decomposition, and iterative feedback utilization—thereby offering both theoretical foundations and scalable implementation pathways for digital transformation in higher education.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Natural Language Processing: (Large) Language Models
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation

Abstract

We introduce Interactionalism as a new set of guiding principles and heuristics for the design and architecture of learning now available due to Generative AI (GenAI) platforms. Specifically, we articulate interactional intelligence as a net new skill set that is increasingly important when core cognitive tasks are automatable and augmentable by GenAI functions. We break down these skills into core sets of meta-cognitive and meta-emotional components and show how working with Large Language Model (LLM)-based agents can be proactively used to help develop learners. Interactionalism is not advanced as a theory of learning; but as a blueprint for the practice of learning - in coordination with GenAI.

Problem

• Large Language Models
• Generative AI in Education
• Cognitive and Emotional Skills Development

Innovation

• Interactionism
• Generative Artificial Intelligence
• Large Language Models