Abstract:

Generative AI (GenAI) has numerous applications, including within learning and training processes, where it generates new content — such as text, images, music, and videos — based on learning patterns derived from datasets. New content can be generated by algorithms and machine learning models that mimic human creativity, as well as personalized responses tailored to users.

Self-Directed Learning (SDL) is a form of learning in which the learner develops a concept/project, implements it, and evaluates its effectiveness. Learners identify their learning needs and goals, find suitable learning resources, and engage in self-directed learning processes.

It is known that in traditional approaches, the teacher/trainer organizes learning, but within SDL, learners play a significant role and are the driving force behind their own learning. SDL can have collaborative or group session forms within adult education and training, promoting the development of lifelong learning skills.

The use of GenAI within SDL processes has not received enough research until now, but existing results encourage the effective adoption of GenAI to support these.

It is important to understand how Gen AI-driven tools, SDL, and training approaches can foster lifelong learning. There is not much research about the advantages of the use of GenAI to support the development of lifelong learning skills of self-directed learners. Also, the limitations and dangers of using GenAI in this context have to be analyzed. GenAI is a new technology, and the processes used by GenAI-based systems to give answers are not well-known. So human experts, employers, employees, developers, and trainers must closely supervise and test its outputs. It is necessary to protect GenAI users against bad decisions. GenAI models alone cannot offer clear and understandable explanations of their decision-making processes, so such explanations should be given.

In this paper, first, connections between SDL and lifelong learning are discussed. The shift to using GenAI as a potential enhancement for SDL, having a strong impact on lifelong motivation, is explained in this presentation. Also, some limitations of this technology in this context are given.

It is a necessity to define Competence Frameworks for trainers and learners to integrate GenAI systematically and effectively into their SDL and lifelong practices. Inclusive GenAI design and use for SDL and lifelong learning should be done. Some ideas in this context are given in this presentation. This is based on a systematic literature review approach to create the first conceptual ideas, as well as discussions with employees and trainers from some European countries about examples, to better understand the bright and dark sides of using GenAI tools, particularly by employee training.

Keywords:

GenAI, Lifelong Learning, SDL, Competence Frameworks.