# Untangling Critical Interaction with AI in Students Written Assessment

arXiv: https://arxiv.org/abs/2404.06955 · HTML: https://mlsanity.com/paper/2404.06955/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 18 references that are in the map.
- First posted on arXiv 10 Apr 2024.

## Builds on (most cited first, 2 of 2)

- [CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities](https://mlsanity.com/paper/2201.06796/) (2022)
- [How does AI chat change search behaviors?](https://mlsanity.com/paper/2307.03826/) (2023)

## Built on by (most cited first, 7 of 7)

- [Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process](https://mlsanity.com/paper/2504.12488/) (2025)
- [AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review](https://mlsanity.com/paper/2503.00079/) (2025)
- [The Imitation Game for Educational AI](https://mlsanity.com/paper/2502.15127/) (2025)
- [Effects of Varying LLM Access on Essay Writing Behavior](https://mlsanity.com/paper/2606.00250/) (2026)
- [AI-Assisted Writing in Education: Ecosystem Risks and Mitigations](https://mlsanity.com/paper/2404.10281/) (2024)
- [Writing With Machines and Peers: Designing for Critical Engagement with Generative AI](https://mlsanity.com/paper/2511.15750/) (2025)
- [Co-Writing with AI: An Empirical Study of Diverse Academic Writing Workflows](https://mlsanity.com/paper/2604.25389/) (2026)

## Abstract (arXiv)

Artificial Intelligence (AI) has become a ubiquitous part of society, but a key challenge exists in ensuring that humans are equipped with the required critical thinking and AI literacy skills to interact with machines effectively by understanding their capabilities and limitations. These skills are particularly important for learners to develop in the age of generative AI where AI tools can demonstrate complex knowledge and ability previously thought to be uniquely human. To activate effective human-AI partnerships in writing, this paper provides a first step toward conceptualizing the notion of critical learner interaction with AI. Using both theoretical models and empirical data, our preliminary findings suggest a general lack of Deep interaction with AI during the writing process. We believe that the outcomes can lead to better task and tool design in the future for learners to develop deep, critical thinking when interacting with AI.