Dr David Bozward

Tag: innovation in education

  • Embedding Entrepreneurship Across Every Degree: A Practical Model

    Universities have spent the last two decades talking about entrepreneurship. They have launched incubators, created enterprise hubs, introduced optional modules, and invited guest speakers from industry. Yet, despite this activity, entrepreneurship remains marginal to the core student experience. It is something extra—an add-on for the interested few—rather than a foundational capability for the many.

    This is a structural failure.

    In an economy defined by uncertainty, technological disruption, and shifting labour markets, entrepreneurial capability is no longer optional. It is central to employability, innovation, and economic resilience. The question, therefore, is not whether universities should teach entrepreneurship—but how they embed it meaningfully across every degree.

    This blog sets out a practical model for doing exactly that.

    The Problem: Entrepreneurship as an Add-On

    Most institutions approach entrepreneurship in one of three ways:

    1. Standalone modules (often optional)
    2. Enterprise centres or incubators
    3. Extra-curricular competitions and events

    While valuable, these approaches suffer from three critical limitations:

    • Low reach: Only a small percentage of students engage
    • Late intervention: Often introduced in final year, when habits are already formed
    • Weak integration: Disconnected from disciplinary learning

    The result is predictable. Entrepreneurship becomes associated with business schools and start-up culture, rather than a broader way of thinking and acting.

    This is a fundamental misunderstanding.

    Entrepreneurship is not just about starting businesses. It is about creating value under conditions of uncertainty. That applies as much to a nurse redesigning patient care pathways as it does to a founder launching a tech venture.

    Reframing Entrepreneurship: From Activity to Capability

    To embed entrepreneurship effectively, universities must shift from teaching entrepreneurship as an activity to developing entrepreneurship as a capability.

    This capability includes:

    • Opportunity recognition
    • Resource mobilisation
    • Value creation
    • Risk navigation
    • Adaptation and learning

    These are not discipline-specific skills. They are transferable, developmental, and essential across all professions.

    This reframing aligns closely with your broader work on entrepreneurial capital and value creation. Students are not simply learning to “start businesses”; they are learning to deploy different forms of capital—human, social, intellectual, and beyond—to create value in diverse contexts.

    A Practical Model: Embedding Entrepreneurship Across the Curriculum

    A meaningful approach requires a system-level design. The model below integrates three dimensions:

    1. Curriculum Integration (Where it is taught)

    2. Developmental Staging (When it is taught)

    3. Experiential Application (How it is taught)

    Together, these create a coherent, scalable framework.

    1. Curriculum Integration: The “Thin Layer” Model

    Rather than isolating entrepreneurship in single modules, the most effective approach is to embed a “thin layer” of entrepreneurial thinking across all modules.

    This does not require rewriting entire programmes. Instead, it involves introducing targeted interventions within existing teaching.

    Example by discipline:

    • Engineering: Design projects include commercial feasibility and user validation
    • Healthcare: Case studies include service innovation and system improvement
    • Arts: Creative work includes audience development and monetisation strategies
    • Social Sciences: Policy analysis includes implementation and impact creation

    The key is consistency. Every student encounters entrepreneurial thinking repeatedly, in different contexts, across their degree.

    This approach solves the reach problem. Entrepreneurship is no longer optional—it is embedded.

    2. Developmental Staging: A Longitudinal Model

    Embedding entrepreneurship requires more than repetition. It requires progression.

    Here, your 9 Stages of the Entrepreneurial Lifecycle provide a powerful foundation. These stages can be translated into a student development journey.

    Year 1: Discovery

    Students learn to identify opportunities and understand problems.

    • Activities: Problem identification, curiosity exercises, industry exploration
    • Outcome: Awareness of opportunity spaces

    Year 2: Modelling

    Students develop ideas into structured concepts.

    • Activities: Business models, design thinking, prototyping
    • Outcome: Ability to shape and test ideas

    Year 3: Application

    Students apply entrepreneurial thinking in real-world contexts.

    • Activities: Live projects, placements, consultancy challenges
    • Outcome: Experience of value creation

    Postgraduate / Advanced Study: Scaling & Adaptation

    Students engage with complexity, growth, and system-level thinking.

    • Activities: Strategic projects, innovation management, venture scaling
    • Outcome: Capability to lead and adapt in uncertain environments

    This staged approach ensures that entrepreneurship is not a one-off experience but a developmental journey.

    3. Experiential Application: Learning Through Action

    Entrepreneurship cannot be learned through lectures alone. It must be experienced.

    The most effective programmes integrate structured experiential learning into the curriculum.

    Key methods:

    • Live industry projects
    • Simulations and decision-making environments
    • Work-based learning and placements
    • Student-led ventures and initiatives

    The goal is not necessarily to produce start-ups. It is to create situations where students must act under uncertainty.

    This is where entrepreneurial capability is formed.

    Embedding Through Graduate Outcomes: The Hidden Lever

    One of the most underutilised mechanisms for embedding entrepreneurship is the graduate outcomes framework.

    Most universities already define what they want graduates to become—often through employability frameworks or graduate attributes.

    The problem is that these frameworks are rarely operationalised.

    Entrepreneurship provides a mechanism to do this.

    Example:

    Instead of stating:

    “Graduates will be innovative”

    Translate this into:

    • Identify opportunities in ambiguous contexts
    • Develop and test solutions
    • Mobilise resources to create value

    Now link these to:

    • Assessment tasks
    • Module learning outcomes
    • Co-curricular activities

    This creates alignment between strategy and delivery.

    Assessment: The Missing Piece

    If entrepreneurship is not assessed, it will not be taken seriously.

    However, traditional assessment methods are poorly suited to entrepreneurial learning.

    Instead, universities should adopt authentic assessment approaches, such as:

    • Opportunity analysis reports
    • Prototype development
    • Reflective learning journals
    • Live project outcomes
    • Pitch presentations

    The focus shifts from “right answers” to quality of thinking, action, and learning.

    This aligns with real-world performance.

    The Role of Staff: From Experts to Facilitators

    Embedding entrepreneurship also requires a shift in teaching practice.

    Traditional models position academics as subject experts delivering knowledge. Entrepreneurial education requires them to act as:

    • Facilitators of learning
    • Designers of experiences
    • Connectors to industry

    This does not mean abandoning disciplinary expertise. It means augmenting it with new pedagogical approaches.

    Staff development is therefore critical.

    Key areas of support:

    • Training in experiential learning design
    • Access to industry partners
    • Tools for assessment and feedback
    • Communities of practice

    Without this, embedding efforts will remain superficial.

    Institutional Infrastructure: Making It Work at Scale

    For this model to succeed, it must be supported by institutional systems.

    Key enablers:

    1. Central coordination
    A dedicated function (e.g. Employability & Entrepreneurship team) to design, support, and monitor delivery.

    2. Data and measurement
    Tracking student engagement, skill development, and outcomes.

    3. Digital platforms
    Systems that connect students with opportunities, employers, and projects.

    4. Employer partnerships
    A pipeline of real-world challenges and collaboration opportunities.

    This is where many initiatives fail. Without infrastructure, embedding becomes fragmented and inconsistent.

    Measuring Success: Beyond Start-Ups

    A common mistake is to measure entrepreneurship initiatives by the number of start-ups created.

    This is too narrow.

    A more meaningful approach focuses on entrepreneurial value creation, including:

    • Graduate adaptability
    • Career progression
    • Innovation within organisations
    • Contribution to regional economies

    This aligns with broader policy goals around productivity and growth.

    It also reflects reality. Most graduates will not start businesses immediately—but many will act entrepreneurially within their careers.

    A Model in Practice: What It Looks Like

    When implemented effectively, this model produces a very different student experience.

    A student might:

    • Identify a real-world problem in Year 1
    • Develop a solution concept in Year 2
    • Test and apply it in a live environment in Year 3
    • Refine or scale it post-graduation

    Along the way, they develop:

    • Confidence in uncertainty
    • Ability to create value
    • Practical experience of delivery

    This is not theoretical entrepreneurship. It is lived experience.

    Common Pitfalls to Avoid

    Embedding entrepreneurship is challenging. Common mistakes include:

    1. Over-reliance on optional modules
    This limits reach and impact

    2. Lack of progression
    One-off experiences do not build capability

    3. Poor staff engagement
    Without buy-in, embedding fails

    4. Weak assessment design
    If it is not assessed, it is not prioritised

    5. Fragmented delivery
    Without coordination, efforts remain isolated

    Avoiding these requires a system-level approach.

    Strategic Implications for Universities

    Embedding entrepreneurship across every degree is not just a pedagogical decision. It is a strategic one.

    It positions the university as:

    • A driver of innovation
    • A contributor to economic development
    • A provider of future-ready graduates

    In a competitive higher education landscape, this matters.

    It also aligns directly with regulatory and policy pressures around:

    • Graduate outcomes
    • Employability
    • Regional impact

    Universities that get this right will differentiate themselves meaningfully.

    Final Thought: From Marginal to Foundational

    The challenge is not a lack of activity. It is a lack of integration.

    Entrepreneurship will remain marginal until it is treated as foundational—a core part of what it means to be a graduate.

    The model outlined here is not theoretical. It is practical, scalable, and aligned with how students actually learn and develop.

    The opportunity now is execution.

    Because the institutions that succeed will not be those that offer entrepreneurship.

    They will be those that embed it into the fabric of every degree, every module, and every student journey.

  • Why Universities Are Measuring Employability Completely Wrong

    Employability has become one of the defining metrics of higher education. It sits at the centre of league tables, regulatory frameworks, and institutional strategy. Yet, despite the attention it receives, most universities are measuring it in ways that fundamentally misunderstand what employability actually is—and how it is created.

    This is not a minor technical issue. It is a structural flaw. And it is quietly shaping the behaviour of institutions, the design of curricula, and the experiences of students in ways that ultimately undermine the very outcomes universities claim to prioritise.

    The Problem: Measuring Outcomes, Ignoring Systems

    Most universities measure employability through a narrow set of outcome indicators:

    • Graduate employment rates (often within 6–15 months)
    • Salary levels
    • Progression into “highly skilled” roles
    • Further study rates

    These metrics are attractive because they are simple, comparable, and quantifiable. They allow regulators and rankings to create clean hierarchies. But they also create a dangerous illusion: that employability is an endpoint rather than a process.

    In reality, employability is not something that happens after graduation. It is something that is developed—often unevenly—over time.

    By focusing only on outcomes, universities overlook the underlying systems that produce those outcomes. This leads to three critical distortions:

    1. Short-termism – prioritising immediate employment over long-term career capability
    2. Attribution errors – assuming university input is the primary driver of outcomes
    3. Metric gaming – designing interventions to improve scores rather than substance

    The result is a measurement system that is precise, but not accurate.

    Employability Is Not Employment

    The first conceptual error is simple but profound: employability is not the same as employment.

    A graduate securing a job within six months tells us very little about their underlying capability. It tells us even less about their long-term trajectory.

    Employment outcomes are shaped by multiple external variables:

    • Local and national labour market conditions
    • Socio-economic background and networks
    • Prior work experience
    • Industry demand cycles
    • Geographic mobility

    A student with strong social capital and access to networks may secure employment quickly, even with relatively underdeveloped skills. Conversely, a highly capable student without those advantages may take longer to secure a role.

    If we measure employability purely through employment outcomes, we are effectively measuring advantage, not capability.

    This distinction matters. Because universities are not primarily responsible for labour markets—but they are responsible for capability development.

    The Missing Layer: Capability Development

    At its core, employability is about the development of capabilities that allow individuals to:

    • Enter the labour market
    • Navigate uncertainty
    • Create and capture value
    • Adapt over time

    These capabilities are multi-dimensional. They include:

    • Human capital (skills, knowledge, competencies)
    • Social capital (networks, relationships, signalling)
    • Cultural capital (confidence, norms, behaviours)
    • Experiential capital (practical application, real-world exposure)

    Most employability metrics fail to capture these dimensions in any meaningful way.

    Instead, they rely on proxy indicators—such as employment status—that sit several steps removed from the actual developmental process.

    This creates a measurement gap: universities are judged on outcomes they only partially control, while the capabilities they do influence remain largely invisible.

    The Pipeline Fallacy

    Universities often treat employability as a linear pipeline:

    Education → Graduation → Employment

    This model is intuitive—but wrong.

    In reality, employability is a complex, iterative process that begins long before university and continues long after graduation.

    Students do not enter university as blank slates. They bring with them:

    • Prior educational experiences
    • Family expectations
    • Networks and connections
    • Confidence (or lack of it)
    • Exposure to the world of work

    Similarly, graduation is not a fixed endpoint. Careers are no longer linear. They involve transitions, pivots, and periods of uncertainty.

    By imposing a linear model onto a non-linear reality, universities create systems that are poorly aligned with how careers actually develop.

    The Timing Problem: Measuring Too Late

    One of the most significant flaws in current employability metrics is timing.

    Most measurements occur after graduation—often 6 to 15 months later. By this point:

    • The student has left the institution
    • Multiple external factors have influenced outcomes
    • The opportunity for intervention has passed

    This is equivalent to evaluating a learning process only after the exam, without ever assessing progress during the course.

    If universities are serious about employability, measurement must shift upstream.

    We need to ask:

    • What capabilities are students developing during their studies?
    • How are these capabilities evolving over time?
    • Where are the gaps—and how can they be addressed early?

    Without this, employability becomes a retrospective exercise rather than a developmental one.

    The Behavioural Consequences of Bad Metrics

    Metrics do not just measure behaviour—they shape it.

    When universities are judged primarily on graduate outcomes, they respond rationally:

    • Focusing resources on final-year students
    • Prioritising “quick wins” in employment outcomes
    • Targeting students who are easiest to place
    • Investing in reporting systems rather than developmental systems

    This creates a skewed distribution of support, where those who need the most help often receive the least.

    It also encourages surface-level interventions:

    • CV workshops without real experience
    • Mock interviews without industry context
    • Job boards without network development

    These activities are not inherently bad—but they are insufficient on their own. They treat employability as a set of discrete tasks rather than a deeply embedded process.

    The Employability Illusion

    Many universities can point to impressive employability statistics. High employment rates. Strong salary outcomes. Positive graduate surveys.

    But these metrics often mask underlying issues:

    • Students lacking confidence in real-world environments
    • Graduates struggling to progress beyond entry-level roles
    • Limited entrepreneurial capability
    • Weak industry integration within curricula

    This creates what might be called the employability illusion: the appearance of success without the underlying substance.

    The danger is that institutions begin to believe their own metrics—while students experience a very different reality.

    Reframing Employability: A Systems Perspective

    To fix this problem, we need to move from an outcome-based model to a systems-based model.

    Employability should be understood as the interaction of multiple systems:

    1. Curriculum systems – how learning is designed and delivered
    2. Experience systems – access to placements, projects, and real-world exposure
    3. Support systems – careers services, mentoring, coaching
    4. Network systems – employer engagement, alumni connections
    5. Student systems – motivation, agency, identity

    Measurement must reflect this complexity.

    Instead of asking, “Did the student get a job?” we should be asking:

    • What capabilities has the student developed?
    • What experiences have they accumulated?
    • What networks have they built?
    • How confident are they in navigating uncertainty?

    These are harder questions—but they are the right ones.

    A Better Model: Measuring Development, Not Just Outcomes

    A more effective employability measurement framework would include three layers:

    1. Input Measures (What Universities Provide)

    • Integration of employability into curriculum
    • Access to industry projects and placements
    • Quality of employer engagement
    • Availability of mentoring and coaching

    2. Process Measures (What Students Do)

    • Participation in work-based learning
    • Engagement with careers services
    • Development of portfolios and projects
    • Network-building activities

    3. Capability Measures (What Students Become)

    • Problem-solving ability
    • Communication and collaboration
    • Adaptability and resilience
    • Entrepreneurial thinking

    Outcome measures (employment, salary) should still exist—but as one part of a broader system.

    This shifts the focus from what happened to how it happened.

    Embedding Employability, Not Bolting It On

    One of the most persistent challenges is that employability is often treated as an add-on rather than a core function.

    Careers services operate in parallel to academic departments. Workshops are optional. Engagement is uneven.

    This model does not work.

    Employability must be embedded into the curriculum itself:

    • Assessment linked to real-world problems
    • Industry projects integrated into modules
    • Reflection on skills and development built into learning
    • Continuous exposure to professional contexts

    This requires a fundamental shift in how universities design education.

    It also requires academic staff to see employability not as an external requirement—but as part of their core role.

    The Role of Data: From Reporting to Insight

    Universities are not short of data. The problem is how it is used.

    Most employability data is designed for reporting—to regulators, rankings, and stakeholders. It is retrospective and static.

    What is needed is developmental data:

    • Real-time insights into student engagement
    • Tracking of capability development over time
    • Identification of at-risk students early
    • Feedback loops that inform intervention

    This is where systems such as integrated dashboards, longitudinal tracking, and learning analytics become critical.

    But the purpose must be clear: not to produce better reports, but to enable better decisions.

    The Equity Dimension

    Current employability metrics also obscure issues of equity.

    Students from disadvantaged backgrounds often face structural barriers:

    • Limited access to networks
    • Financial constraints limiting unpaid opportunities
    • Lower confidence in professional environments
    • Fewer role models

    If universities are judged purely on outcomes, there is little incentive to address these deeper issues.

    A capability-based model, by contrast, allows institutions to:

    • Identify gaps early
    • Target support where it is needed most
    • Measure progress in a more nuanced way

    This is not just a measurement issue—it is a question of fairness.

    Entrepreneurship: The Missing Piece

    Another major omission in employability measurement is entrepreneurship.

    Most frameworks assume that success means entering employment. But for many students, particularly in a changing economy, value creation may take different forms:

    • Starting a business
    • Freelancing or portfolio careers
    • Creating social enterprises
    • Innovating within organisations

    Entrepreneurial capability is increasingly central to employability. It includes:

    • Opportunity recognition
    • Resource mobilisation
    • Risk management
    • Value creation

    Yet it is rarely measured explicitly.

    This reflects a deeper issue: universities are still operating with an industrial-era model of employment, while the economy is moving towards a more fluid, entrepreneurial reality.

    Towards a More Honest System

    Fixing employability measurement does not require abandoning metrics. It requires making them more honest.

    An honest system would:

    • Acknowledge the limits of outcome data
    • Measure capability development explicitly
    • Track student engagement over time
    • Reflect the diversity of career pathways
    • Prioritise long-term outcomes over short-term wins

    It would also require regulators and rankings to evolve—moving beyond simplistic indicators towards more nuanced frameworks.

    Conclusion: From Metrics to Meaning

    The current approach to employability measurement is not failing because it lacks data. It is failing because it is measuring the wrong things.

    By focusing on outcomes rather than systems, employment rather than capability, and short-term metrics rather than long-term development, universities have created a model that is easy to report—but difficult to defend.

    If we are serious about preparing students for a complex, uncertain, and rapidly changing world, we need to rethink what employability means—and how it is measured.

    This is not just a technical adjustment. It is a strategic shift.

    Because in the end, employability is not about whether a graduate gets a job.

    It is about whether they can build a career, create value, and adapt over time.

    And that is something no single metric can capture—but a well-designed system can support.