This article is part of a three-part series on building interdisciplinary capability for schools, universities, and employers — from the urgent need, to design, to assessment.
Work is getting messier. AI is automating routine tasks. Global markets shift overnight. New industries — gaming, synthetic biology, climate-tech — are scaling before universities can create degree programs for them.
The World Economic Forum’s Future of Jobs report lists analytical thinking and creative problem-solving as the top skills for 2025. But here’s the catch: you can’t build those skills in a single discipline. Real problem-solving means thinking across domains.
The strategic plan of the U.S. National Science Foundation (NSF) states: “Future generations of the U.S. science and engineering workforce will need to collaborate across national boundaries and cultural backgrounds, as well as across disciplines”
Consider two graduates entering the health-tech sector. The first has a biomedical engineering degree — she understands device mechanics but struggles to adapt her designs to unpredictable regulatory and patient-behaviour challenges. The second studied biomedical engineering but also took a “Parametric Design for Medical Devices” course co-taught by an architect and a medical product designer. She uses computational modeling techniques from architecture to redesign a wearable for better fit and patient adherence.
The difference? The second graduate was taught to transfer methods from one discipline into another. And that skill is fast becoming a competitive advantage.
Why Current Education and Training Miss the Mark
From school to corporate L&D, learning is still largely siloed. We separate “design” from “health,” “business” from “sports,” “engineering” from “ethics.” Students and professionals may excel in their vertical, but when faced with a problem that spills across domains — as most do — they hit a wall.
Decades of research back this up. David Perkins and Gavriel Salomon’s studies on transfer of learning show that without deliberate scaffolding, people rarely apply what they’ve learned in one setting to another. Knowing how to run a marketing campaign doesn’t mean you can lead a community for an online game; knowing how to use AI in a general sense doesn’t mean you can optimise a bank’s fraud-detection system.
This gap is expensive. Companies pay twice — once for generic training, then again for on-the-job retraining to make that knowledge usable. Universities graduate capable specialists who still require months of context-specific onboarding before they’re productive.
Interdisciplinary Approaches Pay Off
Well-designed interdisciplinary learning isn’t about throwing unrelated subjects together — it’s about connecting them in ways that demand conceptual transfer.
The International Baccalaureate’s Theory of Knowledge (TOK) course builds explicit skills in linking ideas from different domains. Studies of the IB and MYP frameworks show higher performance in adaptation tasks when learning is scaffolded and assessed for transfer.
In professional education, project-based and problem-based learning consistently deliver stronger real-world outcomes when built around authentic, cross-domain problems. MDRC research found that workplace projects co-designed with industry partners increase both retention and performance.
Borrego & Newswander’s review of interdisciplinary graduate programs shows that when institutional design supports co-teaching, authentic projects, and reflective practice, learners build durable, adaptive capabilities. Without these elements, “interdisciplinary” risks becoming little more than a marketing word.
Context + Design Beats Content + Hope
Whether it’s “AI for Banking,” “Pro Athlete Mindset for Entrepreneurs,” or “Parametric Design for Health-Tech,” the winning formula is the same:
- Anchor in a domain learners care about or work in.
- Introduce tools and frameworks from a different domain with clear application pathways.
- Give them a high-stakes, authentic project that demands integration.
- Facilitate transfer explicitly through reflection and principle extraction.
This is exactly the approach EducAI8 takes — bringing together practitioners, researchers, and academics from multiple fields, then layering in evidence-based learning design and pedagogy. By combining subject-matter expertise with the science of how people actually learn and transfer knowledge, we create programs that are both context-specific and structurally engineered for lasting capability.
Looking Ahead
In the next article, we’ll unpack exactly how to design these programs — from sports-business hybrids to industry-specific innovation capstones — and show how employers, universities, and professional schools can pilot them at low cost and high impact.
For now, the message to decision-makers is simple:
Stop investing only in vertical expertise. Start building horizontal capability. Because the problems the world is facing today don’t come with subject labels and cannot be solved by one dominant way of thinking either.
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