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

Authors

DOI:

https://doi.org/10.53761/pc04tp05

Keywords:

Generative Artificial Intelligence (GenAI), curriculum design, constructive alignment, business higher education

Abstract

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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Author Biographies

  • Xue Zhou, University of Leicester

    Professor Xue Zhou is a Professor in AI in Business Education and a Principal Fellow of the Higher Education Academy (PFHEA), recognised for her strategic leadership in advancing curriculum innovation, AI integration, and academic development across higher education.

    Her research focuses on the ethical and effective use of artificial intelligence in education and industry, with particular interests in AI literacy, digital pedagogy, interdisciplinary co-creation, and technology-enhanced learning. She also explores digital transformation and technology adoption in industry, examining how businesses leverage digital tools to drive innovation, operational efficiency, and workforce development.

    Professor Zhou is an Associate Editor of Intelligent Technologies in Education and serves as a guest editor for several academic journals in the fields of digital education, business innovation, and AI. She has led and contributed to a range of funded projects supported by the QAA, British Academy of Management (BAM), ALDinHE, and institutional grants, focusing on AI-enhanced learning, staff development, and student employability.

  • Qianqian Chai, Queen Mary University of London

    Dr Qianqian Chai is a Lecturer in Business Management at Queen Mary University of London, where she teaches across Business, Management, and Marketing. She is a Fellow of the Higher Education Academy and is committed to student-centred pedagogy and interactive learning design. Her research focuses on assessment design, student engagement, and employability, with particular interest in authentic assessment approaches that enhance learning experience and academic integrity. As generative AI becomes more prevalent in education, she explores how the principles of authentic assessment can be strengthened to remain meaningful and effective in this evolving context. Building on this foundation, her current work investigates how AI can be systematically integrated into curriculum and assessment design to support deeper learning and pedagogical innovation. She is particularly interested in developing strategies that align AI-enhanced practices with institutional goals and educational values.

  • Bhuvana Chilukuri, Queen Mary University of London

    Bhuvana Chilukuri is an international undergraduate student studying BSc Business Management at Queen Mary University of London. Her academic interests lie at the intersection of marketing, innovation, and the creative industries, with a growing focus on inclusive design, accessibility, and social impact. She currently works as a Communications & Marketing Co-Creator Intern at Queen Mary, co-developing a sustainability course aligned with the UN Sustainable Development Goals and leading creative campaign development and engagement tracking. In 2024, she was selected as one of eight UK finalists in the Red Bull Basement competition for her AI-powered accessibility app concept, Dcode. She also serves as Co-President of the Queen Mary Consulting Society, contributing to industry-facing events and student engagement initiatives. She worked as a Research Intern on the President and Principal’s Fund for Educational Excellence, contributing to research activities through stakeholder engagement, data analysis, and workshop coordination.

  • Jasmine Jing Yian Quach, Queen Mary University of London

    Jasmine Quach is an undergraduate student pursuing a BSc in Business Management at Queen Mary University of London. Her academic interests include media content creation, marketing, and the role of artificial intelligence in business. She is particularly interested in how AI-driven innovation can support inclusive, ethical, and future-oriented practices across academic and organisational settings, and actively engages with research in these areas.

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Published

2026-03-30

Data Availability Statement

The data that support the findings of this study are not publicly available due to ethical considerations and participant confidentiality.

Issue

Online First

Section

Educational Technology

License

Copyright (c) 2026 Xue Zhou, Qianqian Chai, Bhuvana Chilukuri, Jasmine Jing Yian Quach

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

From Experimentation to Integration: Embedding GenAI in Business Higher Education through the Lens of Constructive Alignment. (2026). Journal of University Teaching and Learning Practice. https://doi.org/10.53761/pc04tp05