Utilizing Generative AI to Develop Programming Skill Through Self-Directed and Interactive Learning

In an era where technology plays a significant role in the lives of people of all ages, adapting to rapidly advancing technology is essential. Lifelong learning, which integrates formal, non-formal, and informal education, helps learners develop skills and abilities independently. Programming skills serve as an example of lifelong learning, requiring the development of technical skills such as programming, planning, and testing, as well as communication, teamwork, and systematic thinking. This research focuses on utilizing Generative Artificial Intelligence (Generative AI) to enhance programming skills through self-directed learning combined with interactive learning. The study was conducted with 21 students enrolled in the Higher Vocational Certificate (Diploma) program in Mechatronics and Robotics. The study applied the MAR model, which consists of three stages: The motivation stage, is designed to encourage learners to engage in activities that link prior knowledge or experiences with new knowledge, thereby fostering self-directed learning motivation, such as designing personalized learning activities based on individual interests; the Activity stage, which provides opportunities for learners to use Generative AI technology for self-directed learning according to their goals and plans, enabling them to understand concepts, apply knowledge in various situations, and track their learning progress; and the Reflection and Progress stage, focusing on reviewing, analyzing, and reflecting on learning outcomes, as well as exchanging ideas and skills with peers and receiving constructive feedback. These stages were designed based on theoretical foundations and a literature review. Furthermore, the research emphasized ethical considerations in AI use, such as data privacy and societal impacts, to promote high-quality, beneficial lifelong learning. The findings showed that before the learning process, the learner had no background in programming and had never used AI technology. However, after participating in the learning activities, students became more open to learning and responded positively to the self-designed activities, which aligned with their interests and skills related to their field of study. These findings suggest that this learning process, when implemented effectively, can be applied to lifelong learning for individuals of all genders and ages.