Artificial Intelligence in Education: Theoretical Frameworks, Applications, and Emerging Challenges

DOI

10.2991/978-2-38476-599-7_5How to use a DOI?

Keywords

Artificial Intelligence; Educational Management; Adaptive Learning; Education 4.0; Generative AI; Digital Transformation; Educational Inclusion

Abstract

The digital transformation of education, accelerated by the COVID-19 pandemic, has led to the extensive integration of artificial intelligence (AI) into teaching and learning processes. This paper examines the role of AI in reshaping education through a systematic literature review complemented by a narrative synthesis. The aim of the study is to identify the main theoretical frameworks, applications, benefits, and challenges associated with the use of AI in education within the context of the Education 4.0 paradigm.

The analysis is grounded in relevant theoretical models, including self-regulated learning (Zimmerman), the TPACK framework, and constructive alignment (Biggs), highlighting how AI-based technologies support personalized learning, adaptive feedback, and the development of metacognitive skills. Applications such as adaptive systems, intelligent tutoring systems, learning analytics, and generative artificial intelligence are examined, emphasizing their impact on the educational experience.

The findings indicate that AI significantly contributes to improving the efficiency of educational processes, enhancing accessibility, and supporting self-regulated learning. However, major challenges are also identified, including ethical risks, algorithmic bias, privacy concerns, and inequalities in access. The paper highlights the need for governance frameworks and educational policies that ensure the responsible and equitable implementation of AI.

The conclusions emphasize the importance of maintaining a balance between technological innovation and the essential role of the teacher in the educational process.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if you modified the licensed material. You do not have permission under this license to share adapted material derived from this chapter or parts of it.

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TY  - CONF
AU  - Maria Flori
AU  - Daniel Hunyadi
AU  - Ralf Fabian
PY  - 2026
DA  - 2026/07/31
TI  - Artificial Intelligence in Education: Theoretical Frameworks, Applications, and Emerging Challenges
BT  - Proceedings of the International Conference on Management and Entrepreneurial Leadership for K-12 Education Excellence (LEADK12 2026)
PB  - Atlantis Press
SP  - 78
EP  - 93
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-599-7_5
DO  - 10.2991/978-2-38476-599-7_5
ID  - Flori2026
ER  -