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

arXiv: https://arxiv.org/abs/2501.00867 · HTML: https://mlsanity.com/paper/2501.00867/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Educational agents and math problem solving, one of 16 directions in LLM agents and tool use.
- Builds on 0 of its 2 references that are in the map.
- First posted on arXiv 1 Jan 2025.

## Placed in

- LLM agents and tool use / [Educational agents and math problem solving](https://mlsanity.com/agents/educational-agents-and-math-problem-solving/)

## Built on by (most cited first, 1 of 1)

- [From Individual Prompts to Collective Intelligence: Mainstreaming Generative AI in the Classroom](https://mlsanity.com/paper/2601.06171/) (2026)

## Abstract (arXiv)

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.