Leveraging the Synergy of IPv6, Generative AI, and Web Engineering to Create a Big Data-driven Education Platform
DOI:
https://doi.org/10.13052/jwe1540-9589.2321Keywords:
Web Engineering, IPv6, Generative AI, Education Informatization, big data platformAbstract
The rapid advancement of network technology in China has significantly accelerated the implementation of information technology in higher education. Through the utilization of computer technology, multimedia technology, big data technology, artificial intelligence technology, and network communication technology, the integration of these technologies in university teaching has become widespread. This paper presents an analysis and discussion on the utilization of the latest IPv6 network transmission protocol technology to enhance the application of data collection in university education, with a specific focus on gathering information related to university faculties. By leveraging web engineering and multimedia technology as fundamental components, the network facilitates the sharing of educational resources among students, thereby enabling the reform of management approaches, fostering educational progress in China, and establishing a comprehensive big data-driven education platform specifically tailored to colleges and universities. Additionally, the incorporation of big data visualization and analysis tools allows for easy retrieval of existing university educational information, facilitates the creation of data charts, and expedites the utilization of data for its inherent value. Finally, the proposed approach employs generative AI to collect and analyze feedback from students and educators, followed by the application of web engineering techniques to continuously enhance the online education platform based on this feedback.
Downloads
References
Zhang Yue, Hu Wei. Cultivation of students’ tactical awareness in high school volleyball teaching [J]. Sports Vision, 2021(22):38–39.
Zhao Liang. The construction of volleyball course content in college under multimedia video practice teaching mode [J]. Liberal arts enthusiasts (education teaching), 2020(04):10+12.
Wu LQ. Thinking about the use of multimedia technology in university volleyball teaching [J]. DOI: 10.16655/j.cnki.2095-2813.2020.05.082.
Li Mei. The application of multimedia technology in college volleyball teaching [J]. Digital World, 2020(03):160–161.
Du N. Research on the construction of digital resources for volleyball network teaching[J]. Contemporary Sports Science and Technology, 2019, 9(35):246+248.
Nguyen, H., et al. “Web-based object detection and sound feedback system for visually impaired people.” 2020 International Conference on Multimedia Analysis and Pattern Recognition (MAPR) 2020.
Henukh, A., et al. “Multimedia development with web-based connected massive open online course (cmoocs) in basic physics material.” Journal of Physics Conference Series 1569(2020):022027.
Paraskevaidis, P., and E. Fokides. “Using 360 Videos for Teaching Volleyball Skills to Primary School Students.” Open Journal for Information Technology 3.1(2020):21–38.
Batez, M. “Effects of Teaching Program Based on Teaching Games for Understanding Model on Volleyball Skills and Enjoyment in Secondary School Students.” Sustainability 13.2(2021):606.
Shao J, Jiang H, Zhang C, et al. Medium Access Controller Design for Wireless Body Area Network[A]. Proceedings of ICCSIT 2011[C]. Beijing, China: Institute of Microelectronics Tsinghua University, 2021. 48–52.
Gupta P, McKeown N. Packet classification using hierarchical @ intelligent cuttings[J]. IEEE Micro, 2021, 20(1):34–41.
Tomasz Mrugalski, Jozef Wozniak. Analysis of IPv6 handovers in IEEE 802.16 environment[J]. Telecommunication Systems, 2019, 452.
Abdullah M A, Othman N E. Review of IPv6 transition mechanism implementation on campus network[J]. International Journal on Communications Antenna and Propagation, 2021, 5(5):269–278.
Wu P, Cui Y, Wu J, et al. Transition from IPv4 to IPv6: A state-of-the-art survey[J]. IEEE Communications Surveys & Tutorials, 2021, 15(3):1407–1424.
Tylman W. Native Support for Modbus RTU Protocol in Snort Intrusion Detection System[J]. 2020, 224:479–487.
Cui Y, Chen Y, Liu J, et al. State management in IPv4 to IPv6 transition[J]. IEEE Network, 2019, 29(6):48–53.
Luckie M, Hyun Y, Huffaker B, et al. Traceroute Probe Method and Forward IP Path Inference[C]// Internet Measurement Conference. ACM, 2022:311–324.
Steenstra J, Taylor K S, Chen L, et al. Location based service (LBS) system and method for creating a social network: U.S. Patent 9,402,156[P]. 2018-7-26.
Song C, Havlin S, Makes H A. Self similarity of complex networks[J]. Nature, 2019, 433(7023):392–395.
Hector Garcia-Molina and Daniel Barbara. How to assign votes in a distributed system. Journal of the ACM, 32(4):841–860, 2022.
Mehedi Bakht and Robin Kravets. Searchlight: asynchronous neighbor discovery using systematic probing. ACM SIGMOBILE Mobile Computing and Communications Review, 14(4):31–33, 2020.
