AI & transformative learning: balancing technology with humanity in education

Evangelia Fragouli

AI & transformative learning: balancing technology with humanity in education

Evangelia Fragouli

Faculty of Business and Social Sciences (FBSS)

Research output: Contribution to conference › Paper › peer-review

Abstract

This research examines how AI-driven adaptive learning systems interact with
transformative pedagogy in higher education. Using Mezirow's transformation
theory, Freire's critical consciousness, and Kolb's experiential learning as
frameworks, we identified tensions between AI's data-driven approach and the
deeply human, reflective nature of transformative learning.
While AI enhances personalization and engagement, it struggles with emotional intelligence and recognizing identity shifts crucial to transformation.

Our findings suggest hybrid approaches that maintain human mentorship alongside technological innovation are essential for ethical and effective educational experiences.

Original language	English
Publication status	Published - 17 Jun 2025
Event	Festival of Learning 2025: Transformative Higher Education Pedagogies - Kingston University, Kingston upon Thames, United Kingdom Duration: 17 Jun 2025 → 17 Jun 2025

Conference

Conference	Festival of Learning 2025
Country/Territory	United Kingdom
City	Kingston upon Thames
Period	17/06/25 → 17/06/25

Keywords

artificial intelligence technologies
transformative learning
data-driven approach
transformative learning methodologies
AI driven adaptive learning systems

Cite this

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title = "AI \& transformative learning: balancing technology with humanity in education",

abstract = "This research examines how AI-driven adaptive learning systems interact with transformative pedagogy in higher education. Using Mezirow's transformation theory, Freire's critical consciousness, and Kolb's experiential learning as frameworks, we identified tensions between AI's data-driven approach and the deeply human, reflective nature of transformative learning. While AI enhances personalization and engagement, it struggles with emotional intelligence and recognizing identity shifts crucial to transformation. Our findings suggest hybrid approaches that maintain human mentorship alongside technological innovation are essential for ethical and effective educational experiences. ",

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AU - Fragouli, Evangelia

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N2 - This research examines how AI-driven adaptive learning systems interact with transformative pedagogy in higher education. Using Mezirow's transformation theory, Freire's critical consciousness, and Kolb's experiential learning as frameworks, we identified tensions between AI's data-driven approach and the deeply human, reflective nature of transformative learning. While AI enhances personalization and engagement, it struggles with emotional intelligence and recognizing identity shifts crucial to transformation. Our findings suggest hybrid approaches that maintain human mentorship alongside technological innovation are essential for ethical and effective educational experiences.

AB - This research examines how AI-driven adaptive learning systems interact with transformative pedagogy in higher education. Using Mezirow's transformation theory, Freire's critical consciousness, and Kolb's experiential learning as frameworks, we identified tensions between AI's data-driven approach and the deeply human, reflective nature of transformative learning. While AI enhances personalization and engagement, it struggles with emotional intelligence and recognizing identity shifts crucial to transformation. Our findings suggest hybrid approaches that maintain human mentorship alongside technological innovation are essential for ethical and effective educational experiences.

KW - artificial intelligence technologies

KW - transformative learning

KW - data-driven approach

KW - transformative learning methodologies

KW - AI driven adaptive learning systems

M3 - Paper

Y2 - 17 June 2025 through 17 June 2025

ER -

AI & transformative learning: balancing technology with humanity in education

Abstract

Conference

Keywords

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Cite this