A Qualitative Study of Innovative Experiences in Collaborative Learning in Artificial Intelligence Courses

Abstract

This research examines the positive impacts and challenges of collaborative learning in artificial intelligence (AI) courses and provides solutions for improving the learning process. The study employed a semi-structured qualitative interview method to collect data. Initially, 98 preliminary codes were extracted from the interview analysis. After review by the research team members and professors, and subsequent code screening, the codes were reduced to 30 final codes categorized into three themes: positive impacts of collaborative learning, existing challenges, and proposed solutions. The results indicated that collaborative learning has significant positive effects on both students and instructors. These effects include the improvement of collaboration and teamwork skills, increased motivation and active participation, deepened understanding of complex concepts, and the development of communication skills. However, challenges such as coordination and task division issues, differences in knowledge levels and abilities, and time constraints were also identified. To address these challenges, solutions such as defining clear roles and responsibilities, utilizing group facilitators, and allocating more time for group activities were proposed. This study, focusing on collaborative learning in AI courses, explores the existing challenges and provides solutions to enhance this approach. The findings can help improve the quality of education in the field of AI and other related areas, offering practical strategies to enhance collaborative learning.