21st century career development is increasingly characterized by recurring participation in work-related skill learning, much of which is mediated by technology. However, integration of this technology into work-related lifelong learning contexts has been relatively atheoretical and non-systematic. Building on interdisciplinary adult learning research and our findings from several studies on an online graduate degree program in a high demand STEM field, we propose a multilevel, person-centric framework of adult learning processes related to: (1) knowledge and skill acquisition, (2) the development and maintenance of motivation and wellbeing over time, and (3) transfer of learning to career-related goals. For each level of the framework, we discuss issues related to the measurement and evaluation of learning. We outline affordances (i.e., functional benefits) of technology (including artificial intelligence) for supporting career-related learning at each level, and present future directions related to major gaps in the field's understanding of these affordances. Throughout the final section, we illustrate the implications of our framework with examples of its use in a research institute focused on AI adult learning technologies. Finally, we present guiding questions for researchers and practitioners interested in technology-mediated career-related learning.
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