The rapid development of artificial intelligence(AI)is accelerating the digital transformation of higher education.Today,“AI+Education”has become a key feature of Education Informatization 2.0 Action Plan in China.T...The rapid development of artificial intelligence(AI)is accelerating the digital transformation of higher education.Today,“AI+Education”has become a key feature of Education Informatization 2.0 Action Plan in China.This study presents practical experiences in applying AI to programming courses.First,the global trends in AI-powered teaching and learning are analyzed.Key challenges in programming education that can be addressed by AI are then identified.Focusing on common teaching problems,an introductory programming course is used to demonstrate the construction of a course engine powered by large language models.This engine enables the creation of intelligent courses,driving innovation in teaching scenes,and transforming both teaching and learning methods.The exploration then extends to the design of AI-enhanced teaching and learning environments,featuring AI teaching assistants and AI learning companions.These tools provide scalable,differentiated,and personalized support for teachers.They also enable one-on-one,adaptive,and customized learning experiences for students.An integrated learning support system is proposed,which combines courses,training,competitions,testing,evaluation,and certification.The goal is to build a smart teaching ecosystem with knowledge services,personalized learning,and instructional support,as well as to realize the entire teaching process of“course–training–competition–testing–evaluation”empowered by AI for all elements and all time periods.Furthermore,the intelligent&interactive virtual massive open online courses(IMOOCs)for C programming is developed.A new hybrid teaching model based on IMOOC,which integrates virtual and real elements and promotes crossdomain collaboration,has also been explored.Potential risks of overreliance on AI tools are discussed,together with strategies to address them.Finally,future trends and challenges in“AI+Higher Education”are examined.The study argues that AI will unlock new possibilities for reshaping how higher education is delivered and experienced.展开更多
Knowledge graphs,as an important supporting technology for digital and intelligent education,are driving the teaching model of vocational education to shift from being driven by experience to being driven by data.This...Knowledge graphs,as an important supporting technology for digital and intelligent education,are driving the teaching model of vocational education to shift from being driven by experience to being driven by data.This paper focuses on knowledge graphs and conducts research on the innovation and practice of higher vocational teaching models.Relying on the"Xuexitong"platform,a knowledge map for the"Performance Management"course was constructed.Based on this,an integrated teaching model of"teaching-learning-assessment-application"supported by the knowledge map was designed,achieving the complete connection of the entire process from pre-class self-study,task-driven in class,to data feedback after class.The results indicate that this model can effectively enhance the structuring of course resources and the personalization of the learning process,facilitate the collaborative transformation of the roles of teachers and students,and achieve precise alignment between course content and job competency standards.This research provides a feasible practical approach and theoretical reference for higher vocational colleges to promote digital and intelligent teaching reforms and deepen industry-education integration.展开更多
The teaching of reading in the EFL class in China is supposed to be the most important course forEnglish learners in colleges and universities because it is expected to fulfil two tasks:the develop-ment of reading ski...The teaching of reading in the EFL class in China is supposed to be the most important course forEnglish learners in colleges and universities because it is expected to fulfil two tasks:the develop-ment of reading skills and the development of language skills.The former set of skills is assigned tothe course called Extensive Reading,which is top-down oriented,and,like the top-down model be-fore 1980’s,its emphasis on the language competence such as syntax and vocabulary often leads to"wild guessing"and misunderstanding.Another reading course,Intensive Reading,is supposed to beresponsible for the latter set of skills.This bottom-up manner of reading often results in word-to-word reading and also causes miscomprehension.The Holistic Model of Reading,as developed on thebasis of interactive models with particular concern over the Chinese learning environment,attemptsto combine the two courses into one and the result,as our studies show,turns out to be promising.展开更多
基金supported by Key Project of Higher Education Teaching Reform Research in Heilongjiang Province,China(Undergraduate Education)(Grant No.SJGZB2024028).
文摘The rapid development of artificial intelligence(AI)is accelerating the digital transformation of higher education.Today,“AI+Education”has become a key feature of Education Informatization 2.0 Action Plan in China.This study presents practical experiences in applying AI to programming courses.First,the global trends in AI-powered teaching and learning are analyzed.Key challenges in programming education that can be addressed by AI are then identified.Focusing on common teaching problems,an introductory programming course is used to demonstrate the construction of a course engine powered by large language models.This engine enables the creation of intelligent courses,driving innovation in teaching scenes,and transforming both teaching and learning methods.The exploration then extends to the design of AI-enhanced teaching and learning environments,featuring AI teaching assistants and AI learning companions.These tools provide scalable,differentiated,and personalized support for teachers.They also enable one-on-one,adaptive,and customized learning experiences for students.An integrated learning support system is proposed,which combines courses,training,competitions,testing,evaluation,and certification.The goal is to build a smart teaching ecosystem with knowledge services,personalized learning,and instructional support,as well as to realize the entire teaching process of“course–training–competition–testing–evaluation”empowered by AI for all elements and all time periods.Furthermore,the intelligent&interactive virtual massive open online courses(IMOOCs)for C programming is developed.A new hybrid teaching model based on IMOOC,which integrates virtual and real elements and promotes crossdomain collaboration,has also been explored.Potential risks of overreliance on AI tools are discussed,together with strategies to address them.Finally,future trends and challenges in“AI+Higher Education”are examined.The study argues that AI will unlock new possibilities for reshaping how higher education is delivered and experienced.
基金Supported by the Chongqing Municipal Education Science Planning Project.Research on the Path of Digital Intelligence Empowering the Deep Integration of Industry and Education in Higher Vocational Colleges(No.K24YG3260033)Supported by Education and Teaching Reform Research Project of Chongqing Institute of Engineering(No.JY2024210)Supported by the Chongqing Academy of commerce(No.2025XJZX01)。
文摘Knowledge graphs,as an important supporting technology for digital and intelligent education,are driving the teaching model of vocational education to shift from being driven by experience to being driven by data.This paper focuses on knowledge graphs and conducts research on the innovation and practice of higher vocational teaching models.Relying on the"Xuexitong"platform,a knowledge map for the"Performance Management"course was constructed.Based on this,an integrated teaching model of"teaching-learning-assessment-application"supported by the knowledge map was designed,achieving the complete connection of the entire process from pre-class self-study,task-driven in class,to data feedback after class.The results indicate that this model can effectively enhance the structuring of course resources and the personalization of the learning process,facilitate the collaborative transformation of the roles of teachers and students,and achieve precise alignment between course content and job competency standards.This research provides a feasible practical approach and theoretical reference for higher vocational colleges to promote digital and intelligent teaching reforms and deepen industry-education integration.
文摘The teaching of reading in the EFL class in China is supposed to be the most important course forEnglish learners in colleges and universities because it is expected to fulfil two tasks:the develop-ment of reading skills and the development of language skills.The former set of skills is assigned tothe course called Extensive Reading,which is top-down oriented,and,like the top-down model be-fore 1980’s,its emphasis on the language competence such as syntax and vocabulary often leads to"wild guessing"and misunderstanding.Another reading course,Intensive Reading,is supposed to beresponsible for the latter set of skills.This bottom-up manner of reading often results in word-to-word reading and also causes miscomprehension.The Holistic Model of Reading,as developed on thebasis of interactive models with particular concern over the Chinese learning environment,attemptsto combine the two courses into one and the result,as our studies show,turns out to be promising.
