TY  - JOUR
AU  - Zhang, Huiyan
AU  - Jin, Xuebo
AU  - Cui, Xiaoyu
PY  - 2025
DA  - 2025/02/26
TI  - Exploration of Course Resources and Modes under Generative Artificial Intelligence
JO  - Frontiers in Educational Innovation and Research
T2  - Frontiers in Educational Innovation and Research
JF  - Frontiers in Educational Innovation and Research
VL  - 1
IS  - 1
SP  - 4
EP  - 9
DO  - 10.62762/FEIR.2024.649562
UR  - https://www.icck.org/article/abs/FEIR.2024.649562
KW  - generative AI
KW  - course resources
KW  - course modes
KW  - automatic control theory
AB  - To find an approach that combines standardization and personalization, the course resources and teaching modes are explored by generative artificial intelligence. By researching and summarizing the problems and solutions in the course teaching process, it is proposed to set up an assessment way based on key nodes. Then, targeted analysis action of students who did not pass the assessment will be assisted with the effective linkage of generative artificial intelligence technology, teacher and students to achieve the expected goals. Research has shown that with the effective linkage, it can provide advanced assistance for multi-level and personalized teaching in terms of broadening horizons, inspiring ideas, and case demonstrations. In addition, the integrated application framework of course resources proposed in the study can provide reference and guidance for the construction of other engineering courses in the future.
SN  - 3068-5664
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Zhang2025Exploratio,
  author = {Huiyan Zhang and Xuebo Jin and Xiaoyu Cui},
  title = {Exploration of Course Resources and Modes under Generative Artificial Intelligence},
  journal = {Frontiers in Educational Innovation and Research},
  year = {2025},
  volume = {1},
  number = {1},
  pages = {4-9},
  doi = {10.62762/FEIR.2024.649562},
  url = {https://www.icck.org/article/abs/FEIR.2024.649562},
  abstract = {To find an approach that combines standardization and personalization, the course resources and teaching modes are explored by generative artificial intelligence. By researching and summarizing the problems and solutions in the course teaching process, it is proposed to set up an assessment way based on key nodes. Then, targeted analysis action of students who did not pass the assessment will be assisted with the effective linkage of generative artificial intelligence technology, teacher and students to achieve the expected goals. Research has shown that with the effective linkage, it can provide advanced assistance for multi-level and personalized teaching in terms of broadening horizons, inspiring ideas, and case demonstrations. In addition, the integrated application framework of course resources proposed in the study can provide reference and guidance for the construction of other engineering courses in the future.},
  keywords = {generative AI, course resources, course modes, automatic control theory},
  issn = {3068-5664},
  publisher = {Institute of Central Computation and Knowledge}
}