Year: 2025
Type: article
Study design: Systematic Review
Abstract: Lifelong learning has become a central axis in the debate on education and innovation, especially in contexts where technological transformations and the integration of artificial intelligence are reshaping the ways individuals acquire, update, and apply knowledge. Despite the growing relevance of this field, research on lifelong learning remains dispersed across different perspectives, highlighting conceptual diversity and methodological fragmentation. This article presents a systematic review aimed at identifying how lifelong learning has been studied in relation to artificial intelligence, focusing on definitions, benefits, and limitations discussed in the literature. The review followed a rigorous methodological process, including a probabilistic sampling strategy, systematic screening and eligibility assessment, and the application of both qualitative and quantitative analyses supported by triangulation to ensure reliability. The findings indicate that research on lifelong learning in relation to artificial intelligence remains fragmented. While many studies emphasize conceptual definitions and highlight potential benefits, relatively few examine limitations, challenges, or empirical evidence of impact. By systematically synthesizing and analyzing the available literature, this review contributes to a more integrated understanding of how AI is shaping lifelong learning, offering both theoretical insights and practical implications for educational practice and policy.
Source: Applied Sciences
DOI: 10.3390/app15179352
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $2,896
Funder: Universidad de La Sabana
OpenAlex ID: W4413655271