Collaborative Thinking: A Pedagogical Approach to AI-Integrated Learning

Abstract Book of the 11th International Conference on Research in Education

Year: 2026

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Collaborative Thinking: A Pedagogical Approach to AI-Integrated Learning

Christopher Sullivan

ABSTRACT:

Artificial intelligence tools have rapidly entered classrooms, often framed as threats to academic integrity or as replacements for student thinking. This practitioner-based article argues that the educational impact of artificial intelligence depends largely on how it is framed pedagogically. Rather than treating AI as a shortcut or a substitute for student effort, this paper proposes a framework for teaching students to interact with AI systems as collaborative thought partners in inquiry-driven learning.
The article introduces two related frameworks: the Instruction-Context-Goal (ICG) prompt structure and the Ask-Interact-Revise (AIR) model for AI-supported learning. In this approach, students initiate the intellectual work while artificial intelligence functions as a mechanism for clarification, critique, and extension of thinking. Students are taught to construct structured prompts, interact with AI systems, critically evaluate responses, and revise their thinking accordingly. Classroom vignettes drawn from secondary mathematics instruction demonstrate how AI can support differentiation, multilingual access, visualization of complex concepts, and iterative feedback on student work. The paper argues that these practices support metacognitive reflection and develop forms of AI literacy necessary for a world in which humans increasingly collaborate with intelligent systems.

Keywords: Artificial Intelligence, AI Literacy, Collaborative Thinking, Prompting, Differentiation, Metacognition, Secondary Education