-
CiteScore
-
Impact Factor
Volume 1, Issue 3, Frontiers in Educational Innovation and Research
Volume 1, Issue 3, 2025
Submit Manuscript Edit a Special Issue
Article QR Code
Article QR Code
Scan the QR code for reading
Popular articles
Frontiers in Educational Innovation and Research, Volume 1, Issue 3, 2025: 81-91

Open Access | Research Article | 25 December 2025
Exploration of the Reform of Comprehensive Practice Course in Advanced Programming Driven by Large Models
1 School of Information Science and Technology, Beijing University of Technology, Beijing 100124, China
* Corresponding Author: Nan Guo, [email protected]
Received: 31 October 2025, Accepted: 13 November 2025, Published: 25 December 2025  
Abstract
The rapid advancement of AI and large language models has placed newer and higher demands on comprehensive programming practice courses in higher education. Significant shifts in students' learning styles, knowledge acquisition channels, and innovative capabilities have rendered traditional curriculum content and teaching methods inadequate for meeting the talent development requirements of the new era. This paper thoroughly examines the profound impact of the widespread adoption of AI technologies on the curriculum system and proposes a systematic reform framework centered on "AI empowerment, competency orientation, and student-centered approaches." By integrating AI tools into the course, it aims to enhance the efficiency and innovation of students' programming practice, strengthen their ability to use intelligent tools rationally and critically, emphasize interdisciplinary integration and engineering ethics, and ultimately foster students' capacity to solve complex engineering problems systematically.

Graphical Abstract
Exploration of the Reform of Comprehensive Practice Course in Advanced Programming Driven by Large Models

Keywords
artificial intelligence
large language models
curriculum reform
competency-oriented

Data Availability Statement
Data will be made available on request.

Funding
This work was supported by the National Natural Science Foundation of China under Grant 62303027.

Conflicts of Interest
The authors declare no conflicts of interest.

Ethical Approval and Consent to Participate
Not applicable.

References
  1. Peláez-Sánchez, I. C., Velarde-Camaqui, D., & Glasserman-Morales, L. D. (2024, June). The impact of large language models on higher education: exploring the connection between AI and Education 4.0. In Frontiers in Education (Vol. 9, p. 1392091). Frontiers Media SA.
    [CrossRef]   [Google Scholar]
  2. Vemula, S. (2024, October). Enriching Python Programming Education With Generative AI: Leveraging Large Language Models for Personalized Support and Interactive Learning. In 2024 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE.
    [CrossRef]   [Google Scholar]
  3. Laato, S., Morschheuser, B., Hamari, J., & Björne, J. (2023, July). AI-assisted learning with ChatGPT and large language models: Implications for higher education. In 2023 IEEE International Conference on Advanced Learning Technologies (ICALT) (pp. 226-230). IEEE.
    [CrossRef]   [Google Scholar]
  4. Scholl, A., & Kiesler, N. (2024, October). How Novice Programmers Use and Experience ChatGPT when Solving Programming Exercises in an Introductory Course. In 2024 IEEE Frontiers in Education Conference (FIE) (pp. 1-9). IEEE.
    [CrossRef]   [Google Scholar]
  5. Kizilcec, R. F., Huber, E., Papanastasiou, E. C., Cram, A., Makridis, C. A., Smolansky, A., ... & Raduescu, C. (2024). Perceived impact of generative AI on assessments: Comparing educator and student perspectives in Australia, Cyprus, and the United States. Computers and Education: Artificial Intelligence, 7, 100269.
    [CrossRef]   [Google Scholar]
  6. Anderson, N., McGowan, A., Galway, L., Hanna, P., Collins, M., & Cutting, D. (2023, November). Implementing generative AI and large language models in education. In 2023 7th International Symposium on Innovative Approaches in Smart Technologies (ISAS) (pp. 1-6). IEEE.
    [CrossRef]   [Google Scholar]
  7. Boguslawski, S., Deer, R., & Dawson, M. G. (2025). Programming education and learner motivation in the age of generative AI: student and educator perspectives. Information and Learning Sciences, 126(1/2), 91-109.
    [CrossRef]   [Google Scholar]
  8. Allison, J., Hwang, G. J., Mayer, R. E., Pellas, N., Karnalim, O., de Freitas, S., ... & Sanusi, I. (2025). From generative AI to extended reality: Multidisciplinary perspectives on the challenges, opportunities, and future of educational computing. Journal of Educational Computing Research, 63(6), 1327-1363.
    [CrossRef]   [Google Scholar]
  9. Denny, P., Leinonen, J., Prather, J., Luxton-Reilly, A., Amarouche, T., Becker, B. A., & Reeves, B. N. (2024, March). Prompt Problems: A new programming exercise for the generative AI era. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 (pp. 296-302).
    [CrossRef]   [Google Scholar]
  10. Wilkinson, G. G. (2024). Enhancing Generic Skills Development in Higher Education in the Era of Large Language Model Artificial Intelligence. Journal of Higher Education Theory & Practice, 24(3).
    [CrossRef]   [Google Scholar]
  11. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27.
    [CrossRef]   [Google Scholar]
  12. Velázquez-García, L., Cedillo-Hernández, A., Colón-Vallejo, A., Del Pilar Longar-Blanco, M., & Cedillo-Hernández, M. (2025). AI-Based Applications Enhancing Computer Science Teaching in Higher Education. Journal of Information Systems Engineering and Management, 10(2), 14-32.
    [Google Scholar]
  13. Alanazi, M., Soh, B., Samra, H., & Li, A. (2025). The Influence of Artificial Intelligence Tools on Learning Outcomes in Computer Programming: A Systematic Review and Meta-Analysis. Computers (2073-431X), 14(5).
    [CrossRef]   [Google Scholar]
  14. Arya, V., Saraf, A., Chichkanov, N., Papa, A., & Romano, M. (2025). AI-enhanced competency transfer hubs: a conceptual framework for university-industry engagement and knowledge sharing. The Journal of Technology Transfer, 1-31.
    [CrossRef]   [Google Scholar]
  15. Atchley, P., Pannell, H., Wofford, K., Hopkins, M., & Atchley, R. A. (2024). Human and AI collaboration in the higher education environment: opportunities and concerns. Cognitive research: principles and implications, 9(1), 20.
    [CrossRef]   [Google Scholar]

Cite This Article
APA Style
Guo, N., Han, B., & Qiao, J. (2025). Exploration of the Reform of Comprehensive Practice Course in Advanced Programming Driven by Large Models. Frontiers in Educational Innovation and Research, 1(3), 81–91. https://doi.org/10.62762/FEIR.2025.722615
Export Citation
RIS Format
Compatible with EndNote, Zotero, Mendeley, and other reference managers
RIS format data for reference managers
TY  - JOUR
AU  - Guo, Nan
AU  - Han, Bing
AU  - Qiao, Junfei
PY  - 2025
DA  - 2025/12/25
TI  - Exploration of the Reform of Comprehensive Practice Course in Advanced Programming Driven by Large Models
JO  - Frontiers in Educational Innovation and Research
T2  - Frontiers in Educational Innovation and Research
JF  - Frontiers in Educational Innovation and Research
VL  - 1
IS  - 3
SP  - 81
EP  - 91
DO  - 10.62762/FEIR.2025.722615
UR  - https://www.icck.org/article/abs/FEIR.2025.722615
KW  - artificial intelligence
KW  - large language models
KW  - curriculum reform
KW  - competency-oriented
AB  - The rapid advancement of AI and large language models has placed newer and higher demands on comprehensive programming practice courses in higher education. Significant shifts in students' learning styles, knowledge acquisition channels, and innovative capabilities have rendered traditional curriculum content and teaching methods inadequate for meeting the talent development requirements of the new era. This paper thoroughly examines the profound impact of the widespread adoption of AI technologies on the curriculum system and proposes a systematic reform framework centered on "AI empowerment, competency orientation, and student-centered approaches." By integrating AI tools into the course, it aims to enhance the efficiency and innovation of students' programming practice, strengthen their ability to use intelligent tools rationally and critically, emphasize interdisciplinary integration and engineering ethics, and ultimately foster students' capacity to solve complex engineering problems systematically.
SN  - 3068-5664
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 
BibTeX Format
Compatible with LaTeX, BibTeX, and other reference managers
BibTeX format data for LaTeX and reference managers
@article{Guo2025Exploratio,
  author = {Nan Guo and Bing Han and Junfei Qiao},
  title = {Exploration of the Reform of Comprehensive Practice Course in Advanced Programming Driven by Large Models},
  journal = {Frontiers in Educational Innovation and Research},
  year = {2025},
  volume = {1},
  number = {3},
  pages = {81-91},
  doi = {10.62762/FEIR.2025.722615},
  url = {https://www.icck.org/article/abs/FEIR.2025.722615},
  abstract = {The rapid advancement of AI and large language models has placed newer and higher demands on comprehensive programming practice courses in higher education. Significant shifts in students' learning styles, knowledge acquisition channels, and innovative capabilities have rendered traditional curriculum content and teaching methods inadequate for meeting the talent development requirements of the new era. This paper thoroughly examines the profound impact of the widespread adoption of AI technologies on the curriculum system and proposes a systematic reform framework centered on "AI empowerment, competency orientation, and student-centered approaches." By integrating AI tools into the course, it aims to enhance the efficiency and innovation of students' programming practice, strengthen their ability to use intelligent tools rationally and critically, emphasize interdisciplinary integration and engineering ethics, and ultimately foster students' capacity to solve complex engineering problems systematically.},
  keywords = {artificial intelligence, large language models, curriculum reform, competency-oriented},
  issn = {3068-5664},
  publisher = {Institute of Central Computation and Knowledge}
}

Article Metrics
Citations:

Crossref

0

Scopus

0

Web of Science

0
Article Access Statistics:
Views: 57
PDF Downloads: 20

Publisher's Note
ICCK stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and Permissions
CC BY 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.
Frontiers in Educational Innovation and Research

Frontiers in Educational Innovation and Research

ISSN: 3068-5664 (Online)

Email: [email protected]

Portico

Portico

All published articles are preserved here permanently:
https://www.portico.org/publishers/icck/