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From Experimentation to Integration: Embedding GenAI in Business Higher Education through the Lens of Constructive Alignment

Xue ZHOU et al.

Journal of University Teaching and Learning Practice2026https://doi.org/10.53761/pc04tp05article
ABDC C
Weight
0.50

What the paper says

As Generative Artificial Intelligence (GenAI) tools such as ChatGPT rapidly enter higher education, business educators face increasing pressure to integrate these technologies meaningfully into curricula. While emerging literature discusses AI integration in higher education broadly, limited empirical research has examined its practical application and pedagogical impact within business school contexts. This study addresses this gap by analysing 17 cases of GenAI adoption at one of Russel Group universities in UK during its first year of implementation. Adopting a qualitative case study approach, the research examines current practices of AI integration into the business curriculum, along with associated benefits, challenges, and influencing factors across cases. The findings reveal a clear trade-off between depth of integration and educational impact: curriculum-integrated modules reported enhanced student engagement, performance, and employability, while fragmented approaches were more susceptible to issues such as ethical concerns, overreliance, and inequality. The study extends Biggs’ theory of constructive alignment by demonstrating how GenAI can be embedded into existing pedagogical strategies without requiring full curriculum redesign. It offers both theoretical insights and practical guidance for aligning GenAI with strategic learning outcomes, supporting more coherent and sustainable adoption in business higher education.

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https://doi.org/https://doi.org/10.53761/pc04tp05

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@article{xue2026,
  title        = {{From Experimentation to Integration: Embedding GenAI in Business Higher Education through the Lens of Constructive Alignment}},
  author       = {Xue ZHOU et al.},
  journal      = {Journal of University Teaching and Learning Practice},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.53761/pc04tp05},
}

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From Experimentation to Integration: Embedding GenAI in Business Higher Education through the Lens of Constructive Alignment

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.