AI-Based Education: Transforming Learning for Physical Education Students at Universitas Muhammadiyah Luwuk in the Digital Era

Abstract

Objectives: The primary objective of this study is to analyze the role of AI in enhancing learning engagement, personalized feedback, and skill acquisition among Physical Education students. Additionally, the study seeks to identify the key challenges faced in the implementation of AI-based learning, including technological literacy and infrastructure limitations.

Materials and Methods: This research employs a mixed-method approach, combining quantitative and qualitative methodologies. The study involves surveys and structured interviews with 100 students and 10 faculty members at Universitas Muhammadiyah Luwuk. AI-powered learning tools such as motion analysis software, interactive training modules, and virtual simulations were utilized. Data analysis includes descriptive statistics for quantitative findings and thematic analysis for qualitative responses.

Results: Findings indicate that AI significantly enhances student engagement and learning efficiency. Statistical analysis demonstrates a 30% increase in knowledge retention among students using AI-integrated modules compared to traditional teaching methods. Additionally, AI-driven feedback mechanisms improve students' understanding of biomechanics and sports strategies. However, barriers such as insufficient technological infrastructure, lack of AI training for instructors, and limited student access to AI tools hinder full adoption.

Conclusions: This study underscores the transformative potential of AI in sports education. AI-based learning tools provide personalized and data-driven learning experiences, fostering better comprehension and skill development. However, successful implementation requires strategic investments in infrastructure, faculty training, and digital literacy programs. Further research is recommended to explore long-term impacts and best practices for integrating AI into Physical Education curricula.