Frontiers in Educational Innovation and Research
ISSN: 3068-5664 (Online)
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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}
}
Copyright © 2025 by the Author(s). Published by Institute of Central Computation and Knowledge. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. 
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