Academic Affairs Office of Minjiang University, Fuzhou 350108, China.
Comput Math Methods Med. 2022 Sep 10;2022:8503239. doi: 10.1155/2022/8503239. eCollection 2022.
In recent years, many colleges and universities have been experimenting and exploring the evaluation of education and teaching system and have achieved certain results. In order to understand the quality of education and teaching system in colleges and universities, to improve the school conditions, and to promote the reform of teaching management, methods and means of evaluating the quality of education and teaching system in general higher education institutions are needed. Modern university education and teaching system should realize the combination of classroom teaching and practice teaching, and education and teaching system adopts the mode of the combination of on-campus practice and off-campus practice, so the design of teaching system is the key to the quality of teaching. Aiming at the current problem that talents cultivated by colleges and universities can hardly meet social demands in terms of engineering practice ability, innovation ability, and international competitiveness, this paper proposes the evaluation and adjustment of college education and teaching system driven by algorithms based on artificial intelligence (AI). By designing the teaching system of talent cultivation, and then establishing a quantitative and controllable quality assurance system for practical teaching, a new mechanism for the design of university education system is further explored. Specifically, the framework of the instructional system is built with the aid of an actor-critic algorithm in reinforcement learning, which assists in the design of the university education system, allowing students to truly understand, master and flex their knowledge, and strengthening the correct understanding of the students' internal learning mechanisms. The practical teaching effect shows that the AI-driven instructional designs are more popular with contemporary students and have higher evaluation scores. The numerical experiment results also show the stability of the instructional design, overcoming the drawbacks of traditional manual subjectivity in the design. AI-driven college education and teaching system is conducive to cultivating students' solid technical theoretical foundation. Therefore, through the AI-driven teaching system to strengthen the training of practical ability, so as to comprehensively improve students' comprehensive quality and innovation ability.
近年来，许多高校一直在尝试和探索教育教学评价体系，并取得了一定的成果。为了了解高校教育教学质量，改善办学条件，促进教学管理改革，需要建立一套评价普通高等教育教学质量的方法和手段。现代大学教育教学体系应实现课堂教学与实践教学的结合，教育教学体系采用校内实践与校外实践相结合的模式，因此教学体系的设计是教学质量的关键。针对高校培养的人才在工程实践能力、创新能力和国际竞争力等方面难以满足社会需求的现状，本文提出了基于人工智能（AI）的算法驱动的高校教育教学系统评价与调整。通过设计人才培养教学体系，建立实践教学的定量可控质量保证体系，进一步探索高校教育体系设计的新机制。具体来说，借助强化学习中的演员-批评者算法构建教学系统框架，辅助高校教育系统设计，使学生真正理解、掌握和灵活运用知识，增强学生对内部学习机制的正确认识。实践教学效果表明，AI 驱动的教学设计更受当代学生欢迎，评价得分更高。数值实验结果也表明了教学设计的稳定性，克服了传统人工设计的主观性缺陷。AI 驱动的高校教育教学体系有利于培养学生扎实的技术理论基础。因此，通过 AI 驱动的教学系统加强实践能力的培养，从而全面提高学生的综合素质和创新能力。
