| With the widespread application of artificial intelligence technology in the manufacturing industry,more and more enterprises need talents with relevant knowledge and skills.The development of middle-level artificial intelligence courses is of great significance to the cultivation of Chinese manufacturing talents.However,the current teaching status of the secondary vocational "artificial intelligence" course has problems such as the traditional teaching mode and the lack of course resources.In order to solve these problems,this study analyzes the existing problems and individual characteristics of learners in the current teaching status of courses,constructs a learner evaluation model from the two dimensions of learning level and learning style type,constructs and implements the online and offline hybrid hierarchical teaching mode of artificial intelligence for middle vocational "artificial intelligence",and finally evaluates the effectiveness of the model with the help of practical application.Specifically,it includes the following parts:1.Analysis of the current situation of teaching of secondary vocational artificial intelligence course.Through student questionnaire surveys,teacher interviews,higher vocational course bridging surveys and enterprise job surveys,this paper studies the existing problems and causes of these problems in the current teaching of secondary vocational artificial intelligence courses,and proposes an online and offline hybrid hierarchical teaching mode to solve the problems existing in the teaching of secondary vocational artificial intelligence courses,and analyzes the feasibility.2.Hybrid layered teaching design of online and offline artificial intelligence for middle vocational artificial intelligence.Firstly,this study analyzes students’ academic situation,teaching content,teaching resources and teaching evaluation.Secondly,based on the individual differentiation characteristics of learners,the learning level of second-order clustering students is carried out for clustering and stratification.At the same time,clustering and stratification are carried out based on students’ learning styles.Based on the above results,a learner evaluation model was constructed.Then,the superstar learning platform,Easy DL-zero threshold AI development platform and Baidu AI open platform are integrated to build an online and offline hybrid hierarchical teaching mode,including three links before,during and after class,and use a combination of process evaluation and summary evaluation for evaluation.3.Applied practice research.In this study,students from Class 1 and Class 2 of the 2021E-commerce Major(Artificial Intelligence Business Application and Service)of Guangzhou A Secondary Vocational School were selected for teaching implementation,and the students were divided into experimental class and control class by comparative experimental method.By comparing and analyzing the results of experimental and control classes,student questionnaire surveys and student interviews,the results of this institute are concluded to verify the effectiveness of the hybrid layered teaching mode of artificial intelligence for middle vocational artificial intelligence proposed by this institute.According to the experimental results,suggestions and improvement directions for further improving the teaching mode are proposed.The results show that the hybrid layered teaching mode of secondary vocational artificial intelligence constructed by this institute has a significant effect on the improvement of students’ academic performance,in addition,the teaching mode can also promote the improvement of students’ learning ability,learning interest,learning motivation and learning enthusiasm to a certain extent,and can also improve students’ participation in the classroom,which can effectively solve the problems of traditional teaching mode and lack of curriculum development resources in the middle vocational artificial intelligence course. |
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