Abstract
The past decade has witnessed great progress in the Internet of Things (IoT), which can provide integrated platforms for data with various formats and to serve different parts of human society. Although IoT-supported education management systems have achieved some successful applications, most existing systems cannot perform intelligent information processing, such as autonomous planning and optimal scheduling. To remedy this gap, this work proposes a novel IoT-supported intelligent education management system that is implemented via collaboration of knowledge and data. First, the macroscopic architecture is designed according to field knowledge of education management, and a clustering-based data analysis algorithm is utilized to visualize real-time classroom characteristics. Then, statistics of learning status are generated, and personalized following plans are accordingly suggested to different specific users. Finally, the functions of the designed smart education management system are tested via computer simulation operations. The obtained results show that the proposal can work well under a real-time data stream and is expected to serve as a typical education management application in smart cities. Through verification, it is found that the integration of general education and professional courses is the ideal starting point for the design of the elements of an optimal course structure for engineering practice majors. In particular, we should strengthen the reform of the following course types: introduction to design, general education, concentrated practice, comprehensive design and peak courses.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.