Proceedings Article | 28 June 2023
KEYWORDS: Machine learning, Online learning, Optoelectronics, Intelligence systems, Defense technologies, Quality systems, Mathematical optimization
With the widespread use of mobile internet, cloud computing, big data, and artificial intelligence in the field of education, a new teaching model based on cloud technology has been rapidly developed. This new model follows the curriculum's "construction-implementation-evaluation" process and includes a quaternity intelligent cloud teaching framework consisting of teaching content, teaching tools, teaching management, and teaching evaluation. This framework comprises intelligent cloud teaching materials, cloud-based classes, cloud-based big data management, and an intelligent monitoring system for teaching quality. The data and services of these four modules can be mutually invoked and supported. Intelligent cloud teaching has been studied and implemented in many core courses, such as "Optoelectric Technology," "Applied Optics," "Physical Optics," "Photoelectric Information Comprehensive Experiments," and "Electrodynamics." The implementation of intelligent cloud teaching has shown several advantages. Firstly, it allows students to make full use of fragmented time for autonomous learning, which is particularly beneficial for optoelectronic majors that require knowledge from various fields such as optics, electronics, mechanics, computer science, and materials science. Secondly, it enables teachers to promote formative evaluation and research-oriented teaching reform, and to continuously improve their courses. Thirdly, it facilitates intelligent monitoring of teaching quality, with relevant teaching big data being used to evaluate teaching and learning and support evidence-based teaching research. Lastly, it provides a historical database that can support professional construction and certification, meeting the requirements for output orientation, quality assurance, achievement evaluation, and improvement. In order to further promote the intelligent cloud teaching model, several suggestions have been proposed, including optimizing the construction of evaluation and incentive mechanisms and implementing technologies to improve the intelligent cloud teaching platform.
