Optimization of Distance Learning Systems Using Artificial Intelligence and the Internet of Things in Improving the Quality of Education in the Post-Pandemic Era

Abstract

The COVID-19 pandemic forced a sudden change from face-to-face learning to Distance Learning (PJJ), posing challenges in the quality of learning and student interaction. This study examines the application of Artificial Intelligence (AI) and the Internet of Things (IoT) to optimize the PJJ system in the post-pandemic era. The goal is to evaluate the impact of AI in personalizing learning and IoT in improving student interactivity and collaboration, as well as identify the challenges of implementing this technology. The research uses a mixed-methods approach by combining qualitative and quantitative analysis. Data were obtained from 50 educators, 100 students, and 20 administrators through questionnaires, in-depth interviews, and participatory observations. Correlation tests and logistic regression are used to assess the influence of AI and IoT on learning quality. The results show that 85% of students and 78% of educators agree that AI helps in customizing learning materials. IoT also increases student engagement, with 76% of students feeling more engaged and the likelihood of student engagement increasing 2.35 times greater with IoT. Key challenges include limited technological infrastructure and lack of training for educators. In conclusion, AI and IoT have great potential in improving the quality of education, but support is needed for infrastructure and educator training so that the implementation of these technologies is optimal.