Abstract:

The rapid expansion of transnational higher education presents significant opportunities, but also complex challenges for universities delivering high-quality, research-led programmes across international branch campuses. A central challenge is maintaining academic standards, pedagogical integrity, and a consistent student experience while adapting to diverse cultural, regulatory, and institutional environments.

This paper presents a case study of the design and planned delivery of the MSc Financial Technology with Data Science at the University of Bristol’s new Mumbai Enterprise Campus (MEC), launching in August 2026. Originally developed in the UK within a Faculty of Science and Engineering and recognised by industry for its contribution to FinTech education, the programme is distinguished by its strong emphasis on technical competencies—including data science, AI, statistics, and programming—and their application to real-world financial problems. The curriculum is also closely aligned with industry needs, incorporating authentic datasets and practitioner-informed projects. This stands in contrast to many existing FinTech programmes, which are typically business school-based and more conceptually oriented.

To address the challenges of transnational delivery, a novel pedagogical model has been developed. Teaching at MEC will follow a serial ‘block’ structure, with units delivered intensively in sequence rather than in parallel. This approach is intended to enhance student focus and engagement while enabling a fly-in faculty model, in which UK-based academic staff deliver core teaching alongside locally recruited faculty. This co-teaching model ensures fidelity to Bristol’s academic standards while supporting local staff development through embedded, practice-based training, and creates a structured mechanism for knowledge transfer between campuses.

The paper outlines the strategic, pedagogical, and operational considerations underpinning this model, including curriculum design, staff recruitment and capability building, and alignment with institutional principles for transnational education. It also situates the initiative within broader national and international policy contexts, including India’s National Education Policy (2020), which promotes internationalisation, and the UK’s leadership in AI and data-driven education.

Finally, the paper introduces a planned longitudinal study comparing student experience and academic outcomes between the block delivery model at MEC and the traditional parallel model used in Bristol. This study will provide empirical insight into the impact of delivery format on engagement, learning, and performance in a technical postgraduate context.

This case offers a scalable and transferable model for delivering high-quality, industry-aligned STEM education across international campuses, with implications for pedagogy, quality assurance, and the future of global higher education strategy.

Keywords:

Transnational education, international branch campus, STEM education, financial technology, data science education, AI education, innovative teaching methods, block teaching, industry-aligned curriculum.