Abstract:

The field of artificial intelligence (AI) has witnessed significant expansion in recent years, leading to a surge in demand for AI professionals and the successful emergence of AI courses. Nevertheless, due to the intricate nature of AI, one of the main obstacles is guaranteeing effective acquisition of knowledge and skills within these courses. This abstract aims to explore the potential of meaningful learning as an approach to enhance acquisition in AI courses.

Artificial intelligence (AI) courses can be challenging for learners because they often cover complex theoretical concepts and technical skills. These concepts and skills can be difficult to understand and master, which can lead to feelings of overwhelm. Many students struggle to understand and retain the information, resulting in suboptimal acquisition. Traditional instructional methods in AI courses often emphasize rote memorization and passive learning, which may not be sufficient for developing deep understanding and practical application of AI principles. This raises the question of whether adopting meaningful learning strategies can address this issue and enhance knowledge acquisition in AI courses.

This study investigates the impact of meaningful learning on the acquisition of knowledge in AI courses. The objective is to identify how meaningful learning strategies, such as problem-based learning, project-based learning, and real-world applications, contribute to deeper understanding and improved retention of AI concepts and skills.

Meaningful learning is a learner-centered approach to education that emphasizes active engagement and the construction of knowledge. Learners are encouraged to relate new information to their existing knowledge and experiences, and to apply AI principles in hands-on, problem-solving activities. This engagement facilitates the development of a robust conceptual framework and promotes critical thinking, collaboration, and creativity.

Early research suggests that meaningful learning strategies can help students acquire knowledge in AI courses. Problem-based and project-based learning can improve comprehension, retention, and transferability of AI concepts. Applying AI principles to real-world scenarios makes learning more relevant and meaningful. Additionally, students who actively participate in discussions, peer interactions, and reflective activities tend to achieve higher levels of mastery in AI courses.

In conclusion, meaningful learning strategies can significantly improve the acquisition of knowledge in AI courses. These strategies promote active engagement, critical thinking, and practical application, which provide learners with a solid foundation for success in the field of AI. Further research and integration of these strategies into AI curricula can create more effective and engaging educational experiences, which will foster the development of skilled and competent AI professionals.

Keywords:

Learner centered approach, learning strategies, problem based learning, project based learning.