Author(s)

Jiani Cheng ¹

Affiliation(s)

¹ Chongqing College of Mobile Communication, Chongqing, 401520, China

Corresponding Author

Jiani Cheng

ABSTRACT

Against the backdrop of the digital economy and the digital transformation of education, university-wide business courses for non-business majors in application-oriented universities face a mismatch among students’ learning needs, instructional provision, and the application of digital-intelligence technologies. Based on 417 valid questionnaires from non-business students, this study examines learning needs, learning difficulties, and the use of artificial intelligence (AI) tools. The findings show that students primarily seek applicable business knowledge, improved employability, and innovation capabilities; the theory–practice gap is a major learning difficulty; and although AI tools are widely used, they are mainly applied to general tasks such as information retrieval and text generation rather than being fully integrated into business-learning scenarios. Guided by Outcome-Based Education (OBE), the study proposes a three-dimensional, nine-element course-objective framework, a teaching model comprising three stages, seven steps, and one thread throughout, and a four-dimensional AI teaching scaffold. It also establishes a data-driven assessment mechanism combining formative and summative assessment. The framework offers practical ideas for developing business literacy among non-business students in application-oriented universities.

KEYWORDS

Digital Intelligence; Outcome-Based Education; Application-Oriented Universities; University-wide Business Courses; Teaching Reform

CITE THIS PAPER

Jiani Cheng. OBE-Oriented Digital Transformation of University-wide Business Courses in Application-Oriented Universities. Curriculum and Teaching Methodology (2026). Vol. 9, No. 5, 116-122. DOI: http://dx.doi.org/10.23977/curtm.2026.090515.

REFERENCES

[1] Lu, Y., & Tang, X. (2025). Forms and developmental pathways of generative artificial intelligence in empowering classroom teaching. E-Education Research, 46(6), 75–82, 106.
[2] Ouyang, J., Liu, M., Dong, W., et al. (2025). International experiences and implications for promoting the educational application of generative artificial intelligence. Modern Distance Education Research, 37(6), 1–8. 
[3] Ren, T. (2024). Optimizing talent development in marketing based on the OBE concept in the context of the digital economy. Intelligence, (34), 149–152.
[4] Xie, J. (2024). Reflections on the "intelligent marketing communication" course based on the OBE concept. Huashang Review, 6(2), 59–67. 
[5] Miao, T. (2024). Research on the "1+N" new-business talent-development model enabled by digital intelligence. Theoretical Research and Practice of Innovation and Entrepreneurship, 7(24), 10–13. 
[6] Wang, Y., & Wen, R. (2023). Constructing a digital teaching quality assessment system in higher education under the OBE approach. Journal of Bingtuan Education Institute, 33(4), 66–72, 77. 
[7] Simarmata, H. A., & Mayuni, I. (2023). Transition from competency-based to learning freedom: Curriculum reform in the digital age. International Journal of Educational Innovation, 2(2), 30–45.

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