Edge Computing and Internet of Things in Ideological and Political Education in Colleges: A New Paradigm of Intelligent Teaching

With the rapid advancement of technology, edge computing (EC) and Internet of Things (IoT) have revolutionized many sectors, including education. This approach is to enhance the efficiency and personalization of learning experiences. In ideological and political education (IPE) in colleges, integrating EC and IoT can offer support for student engagement and learning outcomes. Conventional strategies for evaluating student performance in IPE fail to capture the student learning journey, including behavioral, cognitive, and emotional aspects. This research explores the application of EC and IoT in IPE to create a new paradigm for intelligent teaching. Student attendance, participation, facial expressions, emotional responses and academic performance data were collected using a combination of smart classroom technologies, wearable devices, and cloud-based platforms. It directly integrates edge devices used by students and educators, creating a foundation for real-time, personalized student performance evaluation and enhanced teaching strategies. The collected data were preprocessed using data augmentation techniques to enhance the quality and quantity of collected data, ensuring robust analysis. The research proposed a novel intelligent tunicate swarm optimized gradient boosting machines (ITSO-GBM) method that was utilized to analyze these data points, optimizing performance prediction and dynamic evaluation of each student’s progress. The ITSO-GBM model also facilitates better monitoring of student engagement and participation, leading to improved academic performance and understanding of the IPE content. The proposed method of ITSO-GBM observed accuracy at 92%, precision at 89%, recall at 87% and F1 score at 88%. This new paradigm of intelligent teaching allows for a more comprehensive and responsive educational experience, which not only enhances student learning but also supports the continuous improvement of teaching methodologies.