Generative AI (GenAI) is believed to support generational learning. However, there is no single study that examines the use of GenAI for self-directed learning (SDL), active learning (AL), and critical thinking (CT) of different cohorts of adult learners. Specifically, in the field of adult education, there are limited studies on the effect of GenAI on teaching and learning. This study employs a cross-sectional quantitative design to examine the relationships between SDL, AL, and CT in the context of adult learners' use of GenAI tools like ChatGPT. It considers how demographic variables moderate these relationships. The study was underpinned by the SDL theory by Tough in 1971. An analysis of 281 survey responses of adult learners grouped by generation from five (5) adult higher education institutions in Ghana was performed using descriptive statistics, ANOVA (analysis of variance), and SEM (structural equation modeling). The study's findings indicate that GenAI is perceived as having a significant positive effect on the SDL, AL, and CT of adult learners. A significant positive interrelationship was observed between SDL, AL, and CT. Demographic factors involving gender, year born (generational group), education level, and mode of learning had a perceived significant positive effect on SDL, AL, and CT. Notably, no statistical mean differences were found in the use of GenAI for SDL, AL, and CT across generational groups. The findings advocate for the effective adoption of GenAI to foster lifelong learning among adult learners. Developers of learning technologies and higher education leaders should ensure an inclusive GenAI design. © 2025 The Author(s)
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