Volume 10,Issue 8
Research on Teaching Resource Generation for the Theory-Practice Integrated Curriculum in Higher Vocational Education from the Perspective of Human-Machine Collaboration
In recent years, there have been several issues with the development of theory-practice integrated teaching resources in higher vocational education: slow updates, a lack of individualization, and a long cycle. Generative AI offers a new approach to human-machine collaborative development of resources. Based on the case of the “Firewall Technology” course, an all-encompassing chain intelligent resource generation framework has been established in this paper to cover the conversion of knowledge points into project tasks, the generation of theory-practice integrated assignments, the creation of practical training manuals, intelligent generation of test item banks, and support for students’ self-assessment and peer assessment. Using a prompt engineering approach that integrates role empowerment, task decomposition, format constraints, and iterative optimization, we developed a reusable prompt template library. Based on the above practice, the human-machine collaboration model can reduce the initial draft generation time of a single resource from several hours to a few minutes, achieve a quality level of good to excellent according to peer review, and increase the efficiency of personalized exercise generation by more than 80%. The model for human-machine collaboration in resource generation for the theoretical-practical integrated courses at the higher vocational education level put forward in this paper is effective and transferable.
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