Lifelong Learning in the Age of Artificial Intelligence: Theoretical Analysis and Future Trends Lifelong Learning in the Age of Artificial Intelligence: Theoretical Analysis and Future Trends

Abstract

          The impetus for this article arises from the observation of challenges stemming from technological transformations, particularly the advent of Artificial Intelligence (AI), which has significantly impacted traditional learning systems. AI's integration into education has facilitated the emergence of more flexible and personalized learning models. However, this transition is accompanied by several challenges, notably the persistent digital divide in Thailand. Rural areas often lack adequate Information and Communication Technology (ICT) infrastructure, hindering equitable access to digital learning opportunities. Moreover, ethical concerns surrounding AI in education such as data privacy of learners and the transparency of algorithms used in data analysis pose additional complexities. This academic article aims to analyze theoretical frameworks related to lifelong learning within the context of the transition to the AI era. It examines key theories, including adult learning theory, experiential learning theory, connectivism, and human capital theory. The analysis indicates that future trends in lifelong learning will evolve towards more flexible, personalized, and technologically integrated models. These include learning through AI-powered personal assistants, microlearning, and open learning ecosystems that transcend age and geographical boundaries. Nonetheless, this transition faces challenges such as digital inequality, content quality, and ethical issues associated with intelligent technologies. Therefore, the article proposes policy recommendations to establish an open, equitable, and sustainable lifelong learning ecosystem accessible to all population groups.