HCAIApr 10, 2024

Untangling Critical Interaction with AI in Students Written Assessment

arXiv:2404.06955v136 citationsh-index: 24CHI Extended Abstracts
Originality Synthesis-oriented
AI Analysis

It addresses the need for learners to develop effective human-AI partnerships in writing, though it is incremental as a first step toward conceptualization.

The paper tackles the problem of students lacking critical thinking and AI literacy skills when interacting with AI in writing assessments, finding a general lack of deep interaction during the writing process.

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.

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