Teaching and learning with AI: an Integrated AI-Oriented Pedagogical Model

Abstract The emergence of Generative Artificial Intelligence (GenAI) marks a fundamental transformation in education, mirroring wider technological changes across society. This conceptual article positions GenAI not merely as a tool, but as a relational paradigm shift that redefines pedagogy. Drawing on posthumanist and phenomenological perspectives, we explore how AI reshapes educational practice, focusing on shifts in pedagogy, teacher identity and student engagement. Posthumanism challenges anthropocentric assumptions, inviting new collaborations between human and machine. Phenomenology foregrounds the lived experiences of learners and educators in AI-mediated environments, emphasising the affective and relational dimensions of technological integration. By synthesising these perspectives through the interconnected dimensions of Positionality, Relationality and Functionality, we outline the educational implications of GenAI. Teacher positionality shifts from authoritative knowledge-holder to facilitator; relationality reframes AI as a co-creative presence; and functionality opens new modes of assessment, feedback and creative production. These principles inform the development of the ‘Integrated AI-Oriented Pedagogy Model’ for reimagining classroom practice and teacher education. A fictional classroom narrative is offered to illustrate the complexity of GenAI integration, showing the tensions and possibilities educators navigate. This work contributes to emerging scholarship on ethical and effective AI use in education, advocating for approaches that respect human experience while embracing the agency of intelligent technologies.

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Publication Details

Journal
The Australian Educational Researcher
Published
2025-10-09
DOI
https://doi.org/10.1007/s13384-025-00913-6
Citations
6
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
10.16
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article

Teaching and learning with AI: an Integrated AI-Oriented Pedagogical Model

Kelly Carabott, Edwin Creely
6 citations
The Australian Educational Researcher
Online Learning and Analytics
10.16
article

Teaching and learning with AI: an Integrated AI-Oriented Pedagogical Model

Kelly Carabott, Edwin Creely
article en
6 citations

Abstract

Abstract The emergence of Generative Artificial Intelligence (GenAI) marks a fundamental transformation in education, mirroring wider technological changes across society. This conceptual article positions GenAI not merely as a tool, but as a relational paradigm shift that redefines pedagogy. Drawing on posthumanist and phenomenological perspectives, we explore how AI reshapes educational practice, focusing on shifts in pedagogy, teacher identity and student engagement. Posthumanism challenges anthropocentric assumptions, inviting new collaborations between human and machine. Phenomenology foregrounds the lived experiences of learners and educators in AI-mediated environments, emphasising the affective and relational dimensions of technological integration. By synthesising these perspectives through the interconnected dimensions of Positionality, Relationality and Functionality, we outline the educational implications of GenAI. Teacher positionality shifts from authoritative knowledge-holder to facilitator; relationality reframes AI as a co-creative presence; and functionality opens new modes of assessment, feedback and creative production. These principles inform the development of the ‘Integrated AI-Oriented Pedagogy Model’ for reimagining classroom practice and teacher education. A fictional classroom narrative is offered to illustrate the complexity of GenAI integration, showing the tensions and possibilities educators navigate. This work contributes to emerging scholarship on ethical and effective AI use in education, advocating for approaches that respect human experience while embracing the agency of intelligent technologies.

The Australian Educational ResearcherVol. 52(6)
Monash University (AU)
Openalex Percentile: Top 2%
Online Learning and Analytics
10.16
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