Enhancing Student Learning Autonomously: Exploring the Global Impact of Artificial Intelligence - Djoko Sutrisno; Inawati, Iin; Hermanto, Hermanto (Universitas Ahmad Dahlan, 2023)
This study investigates the global impact of Artificial Intelligence (AI) on enhancing student learning autonomously through a mixed-method approach. By combining both qualitative and quantitative data collection and analysis methods, this research provides a comprehensive understanding of the role of AI in autonomous learning as perceived by teachers. The study involves 25 teachers from SD Muhammadiyah Kebumen as participants, representing a diverse educational context. The qualitative analysis delves into the rich tapestry of educators' experiences and perspectives, shedding light on the multifaceted nature of their interactions with AI in the classroom. This qualitative component allows for an in-depth exploration of how teachers perceive and engage with AI in their teaching practices. Additionally, the quantitative analysis quantifies teachers' perceptions and offers statistical evidence of the impact of AI on student learning outcomes. Through surveys and data-driven analysis, the study assesses the extent to which AI influences student learning autonomously. The triangulation of these findings validates and complements each other, reinforcing the positive perception of AI's role in education. However, the research also highlights the need for addressing ethical concerns surrounding AI implementation and the importance of providing comprehensive support mechanisms for teachers navigating the integration of AI in the classroom. These findings contribute to the ongoing discourse on AI in education, offering insights into its potential benefits and challenges while emphasizing the importance of teacher training and ethical considerations in leveraging AI for autonomous student learning.