Abstract:

The integration of Artificial Intelligence in Education (AIED) has transformed pedagogical practices, yet its alignment with established learning theories remains underexplored. This systematic review investigates how learning theories are perceived, enacted, or challenged when mediated through AI technologies in educational contexts. Drawing on an analysis of peer-reviewed articles published between 2021 and 2025, the study synthesizes how behaviorism, cognitivism, constructivism, connectivism, and emerging experiential frameworks have influenced the development and application of AIED.

Findings reveal that while early AIED systems were grounded in behaviorist and cognitivist models, recent advancements increasingly draw on constructivist and connectivist principles, emphasizing personalized, collaborative, and networked learning. However, constructivism dominates the literature, with limited attention to other frameworks such as distributed cognition, embodied learning, or critical pedagogy. Additionally, the review highlights how learning theories inform AI design, application in classrooms, and user perceptions, particularly in relation to technology acceptance and AI literacy.

This research emphasizes the transformative role of AI in reshaping learning theories, while highlighting the importance of AI literacy to instill, critical, ethical and responsible use of AI. The review raises the need for longitudinal research, expanded theoretical diversity, and interdisciplinary collaborations to ensure responsible, pedagogically sound AI adoption in education.

This study contributes to a deeper understanding of how learning theories shape, and are shaped by, the evolution of AIED, offering a foundation for ethically aligned, theory-informed integration of AI in diverse learning environments.

Keywords:

Artificial intelligence, Artificial intelligence in education, Learning theories, Behaviorism, Constructivism, and Connectivism.