Dr. Manoj Ravi, with the support of colleagues and students, reflects on the outcomes of a hackathon between students from the University of Leeds and NTU Singapore which explored solutions to sustainability challenges as well as fostering interdisciplinary and intercultural collaboration.
Experiential learning is vital for preparing engineers to tackle sustainability challenges that cannot be solved in isolation. By enabling engineering students to work in intercultural and interdisciplinary settings, we foster systems thinking skills, where working alongside peers from diverse disciplines help further understand the interconnections between the social, environmental, and economic dimensions of sustainability. Such collaboration reflects the reality that sustainable solutions must also bridge cultural perspectives across countries and local communities, emphasising the collaborative mindset and skills required to design solutions that are globally relevant, equitable and impactful.
How was it done?
Drawing inspiration from this idea, the University of Leeds (UoL) and Nanyang Technological University Singapore (NTU Singapore) organised a year-long student sustainability hackathon. We brought together 10 student teams, each with four members — two from UoL and two from NTU Singapore. The students were first- and second-year undergraduates, working in interdisciplinary groups that combined chemical engineering, bioengineering, and environmental sciences. They were asked to address open-ended problem statements focused on two critical themes for the context of Singapore and Leeds: sustainable transportation and retrofitting. Each problem statement was mapped onto the UN Sustainable Development Goals, ensuring the work aligns with global sustainability priorities while giving students experience in addressing real-world challenges.
The student-led solutions to these global challenges were developed in two phases. Phase 1 was the ideation or conceptualisation stage where students used system and design thinking approaches to brainstorm potential solutions through a mix of asynchronous (individual reflection and analytical thinking) and synchronous activities (online meetings, group brainstorming and planning). Each group then presented their ideas as elevator pitches to receive feedback from staff at both universities. In the second phase, students moved onto validating their idea and prototyping. The objective of this phase was for students to move from ‘an idea on paper’ to produce something more tangible by demonstrating feasibility in multiple dimensions including technical feasibility, economic viability and regulatory alignment. This challenged students to confront issues that might not have been envisioned during the ideation phase often requiring multiple iterations. Each group had flexibility in terms of how they wanted to present their final hackathon output. The solutions proposed included smart, low-cost retrofitting strategies such as LED lighting, daylight harvesting and motion sensors, alongside more experimental approaches involving recycled materials, including food waste-derived phase change materials and repurposed plastic panels. In all these cases, teams considered the applicability of their solutions from a socio-cultural lens reconciling differences in subsidy structures, urban densities, infrastructure constraints and public behaviour across the two countries. This necessitated students to think of sustainable solutions that bridge cultural perspectives across countries and local communities.
Student reflections
“My biggest learnings through the hackathon have been the extent to which the feasibility of an environmental solution being implemented is dependent on various local and national regulations, as well as how the economic sustainability (and hence scalability) of these solutions can differ in different locations depending on the focus of regional environmental subsidies. I should benefit from these learnings in the future in terms of being more acutely aware of how to design a change to a chemical plant, for example, in a legal and economically sustainable way.” – UoL Chemical Engineering Student
“I signed up for this hackathon because I wanted to push myself beyond my comfort zone and explore how far my creativity could take me in an open-ended environment. I have always enjoyed brainstorming ideas and thinking of alternative ways to solve problems, and this hackathon felt like a good opportunity to challenge myself to innovate in areas I was less familiar with. Reflecting on the experience, my biggest learning was understanding how important it is to balance creativity with feasibility. I learned that good ideas need to be refined, prioritised, and supported by clear reasoning in order to be impactful. Working closely with my team also taught me how to adapt quickly, manage differing viewpoints, and stay focused on the core problem despite constraints. These learnings will benefit me in the future by helping me approach complex problems more confidently, collaborate effectively across disciplines, and develop solutions that are not only innovative but also realistic and meaningful projects.” – NTU Singapore Chemical and Bioengineering student
“My thinking changed in two ways. First, brainstorming became more disciplined. Instead of chasing the most exciting idea, we compared options and asked early questions: what problem does this solve, what assumptions are we making, what would fail first, and what evidence would be needed to support it. This helped reduce ambition into something more realistic. Second, I became more focused on feasibility. Over time, I shifted from “this sounds strong/interesting” to “what is the first thing that proves this can work?”, and “what would fail first?” That meant focusing on clear steps, constraints, and what would be required for real approval and real use.” – UoL Geology student
Staff reflections
As staff involved in the design and delivery of this hackathon, we believe this international collaboration creates new pathways for collaborative curriculum development and empowering students to engage deeply with the complexity of global climate challenges. One of our key reflections from this hackathon is that challenge-based learning offers a truly unique environment for students to develop sustainability competencies. It allows for an authentic and holistic consideration of sustainability whereby core disciplinary knowledge is grounded in socio-cultural, economic, policy and environmental considerations.
We also observe that resilience and commitment are crucial for students to successfully engage in this exercise. Working across largely different time zones with fellow students who bring in different perspectives and skills requires a strong degree of commitment and being resilient in the face of challenges. Students who engaged in the hackathon also commented on how they had to pivot on ideas and make assumptions when faced with inadequate information or uncertainties in data. These are all vital skills for future engineers to thrive in an increasingly volatile, uncertain, complex and ambiguous (VUCA) world.
In future iterations, we aspire to focus on strengthening industry engagement and developing more structured mechanisms for evaluating student learning by embedding the activity within the programme or a module of study. More broadly, this work invites educators to consider how collaborative online international learning (COIL) might be adapted within their own institutional settings to better prepare students for the complexities of global engineering practice.
Authors
Dr Manoj Ravi, School of Chemical and Process Engineering, University of Leeds
Dr Vasiliki Kioupi, School of Earth and Environment, University of Leeds
Ericka Lionny, School of Chemistry, Chemical and Bioengineering, NTU Singapore
Samuel Edwards, School of Chemical and Process Engineering, University of Leeds
Abdulbari S Binafif, School of Earth and Environment, University of Leeds
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Downloads: A PDF of this resource will be available soon.
Who is this article for?: Thisarticle should be read by educators at all levels in higher education who are seeking an overall perspective on teaching approaches for integrating complex systems in engineering education.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking and Critical Thinking INCOSE competencies.
AHEP mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems).
Premise:
Engineering education is undergoing a fundamental transformation. The convergence of technological, social, and environmental challenges demands that future engineers move beyond procedural problem-solving toward complex thinking – a mindset capable of navigating uncertainty, interdependence, and dynamic change. This shift has been accelerated by advances in Artificial Intelligence (AI), which have redefined both the nature of engineering practice and the competencies students must develop to thrive in it.
For scientists and engineers, understanding complex systems is critical for the ability to apply knowledge and techniques across diverse contexts. This is particularly visible in fields such as bioengineering, which depends on advances in chemistry, physics, computing, and other engineering disciplines. Such integration requires designing subsystems where engineering expertise can be meaningfully applied. Complex systems also involve human interaction, introducing unpredictability, feedback loops, and uncertainty. Modern AI-enabled systems—ranging from autonomous vehicles to smart grids and biomedical devices—cannot be fully understood through a single traditional discipline. These systems are not simply complicated; they are interconnected, dynamic, and often nonlinear (Jakobsson, 2025).
What this means for engineering education and educators:
Across the globe, educators have turned to Problem-Based Learning (PBL) as a central strategy for cultivating systems-oriented thinking. For instance, Tauro et al. (2017) and the case study conducted at Tishk International University demonstrate that integrating PBL within mechatronics education enhances students’ ability to connect theory with practice, encouraging collaboration and creativity in addressing multifaceted engineering problems. Similarly, Watters et al. (2016) show that industry–school partnerships transform classrooms into real-world laboratories, reinforcing the value of experiential learning and knowledge transfer between academia and professional practice. These initiatives reflect a broader movement toward authentic, interdisciplinary engagement, a necessary foundation for understanding and designing complex systems.
However, adopting PBL and interdisciplinary methods is not only a pedagogical improvement but also an epistemological necessity. As Stegeager et al. (2024) emphasise, educators themselves must evolve from instructors to facilitators, cultivating reflective and adaptive learning environments that mirror the complexity of professional engineering contexts. Mynderse et al. further highlight that when students are given responsibility for solving open-ended problems, they report higher satisfaction and deeper conceptual integration. These outcomes suggest that active learning approaches foster the kind of complex, interconnected reasoning required for contemporary engineering practice.
In parallel, the AI-driven classroom is transforming the educational landscape. Emerging evidence shows that generative AI tools support personalised learning and immediate feedback, freeing educators to focus on mentorship and creativity (Jaramillo, 2024). Yet this technological advancement also underscores the limits of automation. Machines can model and predict, but they cannot interpret ethical implications, reconcile trade-offs, or integrate human and ecological perspectives. This is where complex thinking becomes indispensable: it enables learners to understand AI not merely as a computational tool but as a component within broader sociotechnical systems.
The need for complex systems understanding is especially acute in fields such as bioengineering and mechatronics, where technologies intersect with living systems and social contexts. The defining feature of complex systems is the interaction among multiple components that produce emergent, often unpredictable behaviour. For engineering students, grasping these principles means developing the ability to think beyond linear causality and to engage with feedback loops, uncertainty, and adaptive design.
The imperative to transform engineering education:
In traditional engineering education, students get topics presented in discrete classes. They get trained in thermodynamics and fluid mechanics and they often forget what they have learned by the time they are at the control systems course where there is an opportunity to bring together skills from prior knowledge. This modularised model is already losing its effectiveness in preparing the students for encountering real-world problems. As the adage says, “In theory, theory and practice are the same; in practice, they are not”. Understanding the role of noise, measurement errors, simplifying assumptions and computational errors play an essential role. To this end, it is crucial to centre complex system design and embrace interdisciplinarity to develop a competency that supports life-long, adaptive learning.
As an example, Aalborg University in Denmark stands as a global exemplary of systems-oriented engineering education. Its PBL model is not an add-on; it is the spine of the entire curriculum. Every semester, students tackle a new problem – often tied to societal needs such as urban planning, environmental sustainability, or healthcare. Students must identify relevant knowledge areas, work collaboratively across disciplines, and reflect on both process and outcome. Faculty report that this structure promotes holistic thinking, resilience, and a sense of professional identity early on the students’ journeys (Kolmos et al. 2008).
On the undergraduate level, capstones are a common part of engineering education which happens at the late stages of the student’s studies. At Rowan University (New Jersey, USA), Engineering Clinics provide a different but equally powerful model. Students work across all four years on interdisciplinary teams, contributing to faculty research or industry-sponsored projects. These clinics are embedded in the curriculum and require students to engage deeply with current research problems, often involving complex technical and human systems. A junior clinic project, for example, might involve the optimisation of a renewable energy system integrating mechanical, electrical, and computer engineering principles. Therefore, students learn to navigate ambiguity, collaborate with experts, and see the relevance of their disciplinary knowledge in a broader context by confronting the messy nature of real data.
These are two of many examples where systems thinking is cultivated. Students gain exposure to open-ended problems and practice seeking connection across domains as they encounter the limits of their knowledge. In this fast-moving era, crossing disciplines empowers students for lifelong adaptation, allowing them to incorporate their experiences into any new technological developments. It also encourages treating learning as a collaborative social process, rather than a solo race to secure the first job.
Educators must do more than just deliver content; they also need to act as facilitators and learn alongside their students. By redesigning the curriculum around design-oriented problems that mirror real-world changes, higher education will better prepare future engineers to face upcoming systemic global challenges.
Looking ahead:
As artificial intelligence and automation continue to reshape industry, engineering education must also evolve. Integrating complex systems into teaching offers students the opportunity to engage directly with the data-driven ecosystem they will encounter in practice. The goal is not only to produce technically skilled engineers, but also thoughtful stewards of technology who can navigate its broader social and ethical dimensions.
One ongoing challenge is that independent projects often vary in quality and can be difficult to assess. Without intentional design, students may default to trial-and-error approaches instead of drawing on knowledge from prior courses. At the same time, the pressure to cover extensive technical material can make it difficult to provide the broader systems context essential for modern engineering. Yet when learning is reinforced across the curriculum, students are better prepared for future careers that demand systems-based thinking.
Experiential, self-directed projects play a crucial role in this preparation. They allow students to choose their own path while working closely with advisors and industry partners. Whether developing a product, designing a system, or engaging with professionals, students gain a perspective that feels different from traditional coursework. This process offers them a glimpse of what it means to think and act like real engineers, fostering both confidence and adaptability as they transition from the classroom to the workplace.
References:
Jakobsson, Eric et al. (1999) ‘Complex systems: Why and what?’, New England Complex Systems Institute. Available at: https://necsi.edu/complex-systems-why-and-what (Accessed: 16 July 2025).
Stegeager, N., Traulsen, S., Carvalho Guerra, A., Telléus, P., Du, X. (2024) ‘Do good intentions lead to expected outcomes? Professional learning amongst early career academics in a problem-based program’, Education Sciences, 14(2), p. 205. Available at: https://doi.org/10.3390/educsci14020205.
Tauro, F., Cha, Y., Rahim, F., Rasul, M.S., Osman, K., Halim, L., Dennisur, D., Esner, B., Porfiri, M. (2017) ‘Integrating mechatronics in project-based learning of Malaysian high school students and teachers’, International Journal of Mechanical Engineering Education. Available at: https://journals.sagepub.com/doi/full/10.1177/0306419017708636 (Accessed: 1 August 2025).
Watters, J., Pillay, H. and Flynn, M. (2016) ‘Industry-school partnerships: A strategy to enhance education and training opportunities. Australia’, Queensland University of Technology. Available at: https://eprints.qut.edu.au/98390/ (Accessed: 30 July 2025).
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking, Requirements Definition, Communication, Design For, and Critical Thinking INCOSE Competencies.
AHEP4 mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems), and Integrated / Systems Approach (essential to the solution of broadly-defined problems). In addition, this resource addresses the themes of Sustainability and Communication.
Educational level: Beginner; intermediate.
Acknowledgement:
The case study underpinning this teaching activity was developed by Prof. Kristen MacAskill (University of Cambridge). The Module was first developed and implemented in teaching by TEDI- London, led by a team of learning technologists, Ellie Bates, Laurence Chater, Pratishtha Poudel, and academic member, Rhythima Shinde. This work was carried out in collaboration with the Royal Academy of Engineering through its Engineering X programme — a global partnership that supports safer, more sustainable engineering education and practice worldwide. With critical support from Professor Kristen MacAskill and involvement of Ana Andrade and Hazel Ingham, Aisha Seif Salim. This was a collective effort involving many individuals across TEDI-London and RAEng (advisors and reviewers), and while we cannot name everyone here, we are deeply grateful for all the contributions that made this module possible.
Learning and teaching notes:
This case study introduces a structured, systems-thinking–based teaching resource. It provides educators with tools and frameworks—such as the Cynefin framework and stakeholder mapping—to analyse and interpret complex socio-technical challenges. By exploring the case of the Queensland, Australia floods, it demonstrates how engineering decisions evolve within interconnected technical and social systems, helping students link theory with practice.
The Cynefin framework (Nachbagauer, 2021; Snowden, 2002), helps decision-makers distinguish between different types of problem contexts—simple, complicated, complex, chaotic, and disordered. In an engineering context, this framework guides learners to recognise when traditional linear methods work (for simple or complicated problems) and when adaptive, experimental approaches are required (for complex or chaotic systems).
Within this teaching activity, Cynefin is used to help students understand how resilience strategies evolve when facing uncertainty, incomplete information, and changing stakeholder dynamics. By mapping case study events to the Cynefin domains, learners gain a structured way to navigate uncertainty and identify appropriate modes of action.
This case study activity assumes basic familiarity with systems concepts and builds on this foundation with deeper application to real-world socio-technical challenges.
Summary of context:
The activity focuses on a case study of 2010–2011 floods in Queensland, Australia, which caused extensive damage to urban infrastructure. The Queensland Reconstruction Authority (QRA) initially directed resources to short-term asset repairs but subsequently shifted towards long-term resilience planning, hazard management, and community-centred approaches.
The case resonates with global engineering challenges, such as flood, fire, and storm resilience, and can be easily adapted to local contexts. This case therefore connects systems thinking theory directly to engineering and governance decisions, illustrating how frameworks like Cynefin can support engineers in navigating uncertainty across technical and institutional domains.
Learning objectives:
Aligned with AHEP4 (Engineering Council, 2020) – Outcomes 6, 10, and 16 on systems approaches, sustainability, and risk – this activity emphasises systems thinking, stakeholder engagement, problem definition, and decision-making under uncertainty.
This teaching activity introduces learners to the principles and practice of systems thinking by embedding a real-world case study into engineering education (Godfrey et al., 2014; Monat et al.,2022). The objectives are to:
Enable students to recognise interconnections, interdependencies, and evolving behaviours of stakeholders within socio-technical systems.
Support learners in applying systems frameworks —particularly the Cynefin framework and stakeholder mapping—to analyse complexity, uncertainty, and decision-making in climate resilience and disaster mitigation contexts.
Apply systems thinking tools and frameworks to real-world challenges, such as climate resilience and disaster mitigation.
Strengthen confidence in addressing uncertainty and complexity in engineering problem-solving.
Collaborate effectively across diverse teams, appreciating multiple stakeholder perspectives.
Reflect critically on trade-offs and decision-making in engineering practice.
Equip students to transfer systems insights from case-based scenarios to broader projects in their curriculum and future professional practice.
Teachers have the opportunity to:
Introduce students to complex systems concepts through engaging, real-world case studies.
Facilitate interactive, blended learning using narrative-driven tools, explainer animations, and role-play exercises.
Assess learners’ baseline and improved understanding of systems thinking through pre- and post-module surveys.
Guide students in navigating multiple systems frameworks while managing cognitive load.
Encourage interdisciplinary collaboration and stakeholder-focused analysis within classroom or project-based settings.
Adapt and scale the teaching activity for different educational levels, contexts, and case study themes (e.g., floods, wildfires, extreme heat).
This dedicated platform hosts the interactive modules designed for this teaching activity. Students progress through three modules — Context, Analysis and Insights, and Discussion and Transferable Learning. Each module includes animations, narrative-driven content, scenario prompts, and interactive tasks. The platform ensures flexibility: it can be used in fully online, hybrid, or face-to-face settings. All necessary digital assets (readings, maps, videos, and quizzes) are embedded, so learners have a “one-stop” environment.
The core teaching narrative is anchored in this Engineering X case study. It documents the evolution of the Queensland Reconstruction Authority (QRA) from a short-term flood recovery body to a long-term resilience institution. This resource provides students with authentic socio-technical detail — including stakeholder conflicts, institutional learning, and systemic barriers — which they then interrogate using systems thinking frameworks.
This resource provides a suggested delivery schedule for facilitators. It maps when live sessions, asynchronous tasks, and group discussions should occur, ensuring students remain engaged over the course. It also indicates where key reflective points and assessments (both formative and summative) can be integrated.
5. Pre- and post-module assessment form: (Appendix C)
This tool evaluates students’ systems thinking learning outcomes. It includes:
Baseline survey: assesses initial understanding of systems thinking, approaches to complex problems, and confidence in collaboration.
Scenario-based survey: applies systems thinking questions to a specific context (e.g. extreme monsoon rains and flooding in the case of Sakura Cove – as per the group assignment in module 1).
Post-module survey: measures changes in understanding, confidence, and skills, while also capturing qualitative reflections on learning.
The form provides both quantitative data (Likert scales) and qualitative insights (open-ended reflections), enabling robust evaluation of teaching impact.
Assessment:
Formative: Pre- and post-module surveys assess changes in learners’ self-reported understanding of systems thinking (Appendix A). Facilitators may adapt reflective prompts and scenario-based activities as part of coursework.
Summative (optional): Students can integrate insights into ongoing design projects (e.g. climate resilience in urban redevelopment), with assessment based on problem analysis, stakeholder engagement, and solution development.
Narrative of the case:
Learners are introduced to the case via a fictional guide, “Bernice,” who frames the scenario and supports navigation through the material. Students work through three stages that progressively apply the Cynefin framework and other systems tools to understand how resilience emerges through evolving governance and engineering responses:
1. Context module:
Initial Mandate: Students explore how the QRA was first tasked with rapid technical recovery—fixing roads after flood damage.
Narrative Depth: They study the Queensland floods of 2010–11 not just as a physical shock, but as a systemic stress test on multiple layers: infrastructure, governance, and community systems.
2. Analysis & insights module:
Framework Application: Learners apply systems frameworks (e.g., Cynefin, stakeholder maps) to see how QRA’s remit expanded over time—from asset restoration to hazard anticipation and community resilience.
Knowledge Types: Students distinguish between explicit knowledge (e.g., rebuild standards, hydrology data) and tacit knowledge (e.g., local inter-agency trust, relational coordination).
Governance Layers: Activities explore how resilience depends on multi-level governance, local-state-federal coordination, and overcoming systemic barriers like funding cycles or short-lived institutional mandates.
3. Discussion & transfer learning module:
Reflective Debate: Students weigh whether engineering alone can deliver resilience, or whether social relationships and institutions are equally critical.
Barrier Identification: They debate typical constraints—political, funding, institutional—and propose ways systems thinking can mitigate them.
Transfer Lab: Learners apply the evolved QRA model to other scenarios—e.g., urban heat adaptation or wildfires—considering both technical measures and governance dynamics.
Interactive learning design:
The teaching activity integrates multiple interactive elements to immerse students in systems thinking:
Role-play simulations: Learners take on the role of Queensland Reconstruction Authority (QRA) decision-makers, negotiating trade-offs between immediate engineering fixes and long-term institutional resilience. This requires balancing technical priorities with building trust, relationships, and governance capacity.
Scenario challenges: Students are presented with governance disruptions (e.g. funding cuts, loss of stakeholder trust, leadership turnover). They must reframe solutions using systems approaches, moving from reactive technical patchworks towards adaptive, capacity-building strategies.
Interactive digital tools: The online platform provides hotspot maps for exploring interdependencies, drag-and-drop activities for categorising frameworks, explainer animations, and AI-driven chatbot negotiations with sceptical stakeholders. These exercises develop critical and applied problem-solving skills.
Collaborative reflection: Group discussions and peer-to-peer feedback allow learners to surface diverse perspectives, debate trade-offs, and integrate insights into ongoing project briefs.
Why this approach adds value:
Although rooted in social-technical interactions, the activity explicitly connects systems thinking to core engineering design competencies—problem framing, stakeholder analysis, and iterative solution development under uncertainty
Holistic understanding of resilience: Students experience resilience as more than just technical recovery. They engage with a dynamic system that includes knowledge creation, governance evolution, and social relationships.
Adaptive systems thinking in action: The evolving narrative demonstrates how system boundaries shift over time, and how sustainable outcomes require not only engineering but institutional and cultural change.
Direct relevance to real-world engineering: The case mirrors global infrastructure challenges where effective disaster response and resilience planning depend on the interplay between technical solutions, governance capacity, and community engagement.
Guided questions and activities:
Facilitators can use these prompts to stimulate inquiry and structured reflection:
Who are the key stakeholders in the QRA flood response, and where do their priorities align or conflict?
How do feedback loops and interdependencies influence resilience planning?
What trade-offs exist between rapid repair and long-term resilience?
How can systems frameworks such as the Cynefin model or stakeholder mapping guide decision-making under uncertainty?
In role-play: how would you convince a sceptical funder (AI chatbot) to invest in resilience measures?
How could lessons from flood mitigation be applied to other contexts such as wildfire or urban heat resilience?
Opportunities for extension:
In addition to the Queensland floods and Sakura Cove examples, educators may draw parallels with urban heat planning in London, wildfire adaptation in Australia, or storm resilience in the Netherlands. These comparative cases allow learners to generalise systems insights beyond one event or geography.
The activity is designed to be scalable and adaptable:
Broader case study base: Educators can expand beyond flood resilience to include wildfire, storm, or extreme heat events.
Integration with larger modules: The activity can be embedded into project-based learning modules (e.g. urban redevelopment, transport network resilience).
Advanced complexity: For higher-level learners, facilitators can introduce additional frameworks (e.g. agent-based modelling, system dynamics) to deepen analysis.
This flexibility allows educators to tailor the activity to their students’ level of expertise, institutional context, and disciplinary focus.
References:
Design Council. (2021). Beyond Net Zero: A systemic design approach. Design Council.
Godfrey, P., Crick, R. D., & Huang, S. (2014). Systems thinking, systems design and learning power in engineering education. International Journal of Engineering Education.
Monat, J., Gannon, T., & Amissah, M. (2022). The case for systems thinking in undergraduate engineering education. International Journal of Engineering Pedagogy, 12(3), 50–88.
Nachbagauer, A. (2021). Managing complexity in projects: Extending the Cynefin framework. Project Leadership and Society, 2, 100017.
Snowden, D. (2002). Complex acts of knowing: paradox and descriptive self‐awareness. Journal of knowledge management, 6(2), 100-111.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Keywords: Problem solving; Feedback loops; Decision-making; VUCA; Optimisation; Public health and safety; Risk; Sustainability; Ethics; Responsible design; Life cycle; Societal impact; Enterprise and innovation.
Who is this article for?: Thisarticle should be read by educators at all levels in higher education who are seeking an overall perspective on teaching approaches for integrating complex systems in engineering education.
Related INCOSE Competencies: Toolkit resources are designed to be applicable to any engineering discipline, but educators might find it useful to understand their alignment to competencies outlined by the International Council on Systems Engineering (INCOSE). The INCOSE Competency Framework provides a set of 37 competencies for Systems Engineering within a tailorable framework that provides guidance for practitioners and stakeholders to identify knowledge, skills, abilities and behaviours crucial to Systems Engineering effectiveness. A free spreadsheet version of the framework can be downloaded.
This resource relates to the Systems Thinking andCritical Thinking INCOSE competencies.
AHEP mapping: This resource addresses several of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): Analytical Tools and Techniques (critical to the ability to model and solve problems),and Integrated / Systems Approach (essential to the solution of broadly-defined problems).
Premise:
We live in a complex world. Complexity is a key challenge, captured in leadership terms by the VUCA framework: volatile, uncertain, complex and ambiguous (Lanucha 2024). Engineers have the privilege of creating products and processes for humans to use in this landscape. Each of these likely has numerous parts which interact, as well as interacting with the environment, people, and needing to meet a host of safety, quality, sustainability, ethics, and financial obligations. Traditionally, engineers analyse problems by breaking them down into simple parts. This helps understanding and makes calculations feasible, but it’s easy to lose understanding of the whole system. Any change can easily create a problem elsewhere. From a technical viewpoint, engineers need to understand this interconnectedness in order for their creations to work. In a wider sense, ‘systems thinking’ is a skill central to engineering quality and management techniques, which seek to rationalise the complexity of entire organisations and their ever-changing market pressures.
The case for understanding systems:
Systems is perhaps one of the most misunderstood words in engineering. It is often found combined with mathematical modelling or control – topics often perceived as challenging – and is used in other fields like Computer Science, where tools and models are different. In all cases, the idea revolves around a group of interacting or interrelated elements which form a unified whole. Those elements can be physical or information, hardware or software, or any combination of mechanical, electrical, and other engineering domains. Thinking in terms of systems can therefore be thought of as a holistic approach.
The Engineering Council UK’s AHEP criteria include a systems approach: C/M6 – “Apply an integrated or systems approach to the solution of complex problems.” Several other AHEP criteria also reference complexity and complex problems, which they define as having “no obvious solution and may involve wide-ranging or conflicting technical issues and/or user needs that can be addressed through creativity and the resourceful application of engineering science. The Systems Thinking Alliance (2025) gives a broader definition of complexity as referring to “the condition of systems, objects, phenomena, or concepts that are challenging to understand, explain, or manage due to their intricate and interconnected nature. It involves multiple elements or factors that interact in unpredictable ways, often requiring significant information, time, or coordinated efforts to address.” For these, there is no ‘one-size-fits-all solution’ (Ellis 2025). This is the reality that engineers need to manage by understanding the potential effects on all parts of the system.
In order to analyse, engineers dissect complexity into manageable components, and educators teach these simple components before moving onto more complex systems. For example, students initially learn basic electrical components, simple beams, rigid bodies, etc. before bringing these together in case studies, and then moving onto topics like mechatronic systems. Historically, engineers specialised on graduation, perhaps becoming a stress engineer or fluid dynamicist in dedicated offices and functional teams. A design decision by one team could have unintended consequences for another, as well as additional uncertainty. The advent of cross-functional project and ‘matrix’ organisations mitigated against this, and companies have moved towards attribute teams which can consider the balance of behaviour. Even so, some uncertainty remains in the form of assumptions in calculations, changes in material properties with temperature or stress, or small variations in composition and manufacturing tolerances, which can all accumulate. Any parts which are bought ‘off-the-shelf’ or made by other companies under license must be carefully specified. Relationships can be nonlinear – or even chaotic – and contain feedback loops which can amplify changes (Kastens et al 2009). This all increases the risk of a product’s comfort, performance, and safety being impacted in ways that weren’t anticipated. Any problem that doesn’t come to light until the testing phase – late in the design process – represents costly redesigns and delays. In the unlikely event that a problem isn’t captured during testing either, the outcome could be disastrous.
Systems engineers will bring the product together and establish these complex behaviours through models and testing. Identifying potential problems early in the design phase can save significant money and facilitate better designs. This can be challenging, especially for systems using novel materials or operating in extreme environments, which aren’t accurately captured by standard calculations. Models may be linearised, neglect external forcing, or be derived for an assumed air density or ambient temperature which may not be valid. In recent decades, the engineering industry has moved towards model-based design and virtual prototyping, facilitated by advances in computer tools. These are increasingly sophisticated, but models still need to be built by engineers with an appreciation of complexity and the mechanisms by which a problem could arise. As humans develop new materials and technologies, and explore the limits of what is possible, engineering techniques and calculations need constant revision, and software tools are frequently updated to facilitate this.
That holistic view of problems has benefits outside of designing engineering artefacts. The manufacturing process is itself a complex system with potentially long supply chains. As is the organisation, which is comprised of numerous people operating in a landscape of financial pressures, employment law, politics and culture. Quality guru William Deming’s 14 Points for Management (Deming 2018) can be viewed as a systems approach to handling this complexity, by breaking down barriers between departments and instigating continuous improvement. Once a product is produced, it exists in a wider world and continues to interact with it. From a sustainability viewpoint, this can be the user and surrounding community, the environmental impact over a product’s lifecycle, and the financial markets which dictate whether a product is viable. It can also be the social, political, and legal landscapes: these can place direct constraints in the forms of laws governing safety and emissions (such as the UK’s legally binding target of net zero by 2050), or through embargos, tariffs, and subsidies. Each country has its own regulations, which can necessitate multiple variations of a product: a good example is cars, which need to be produced in both left- and right-hand drive, satisfy varying safety and emissions regulations, and cater for differing personal and cultural preferences for size, noise, usage and driving styles. Even when not legislated, a company might choose to support fair trade, lead the way in sustainable practices, or refuse to do business with suppliers or regimes they find objectionable – potentially making this a key part of their brand.
An engineer’s ability to appreciate and understand the wider social and business landscape is a reason why finance and management consultancy companies can often be seen recruiting engineers at student careers fairs. The Sainsbury Management Fellowship (SMF) scheme notably develops UK engineers as industry leaders, and fellows have made a major contribution to the UK’s economic prosperity (RAEng 2025).
Conclusions:
Complex systems are the “real world” that engineers attempt to understand and design for. They are complicated, interconnected, changing, and uncertain. The well-known part of engineering is analysis: breaking systems into understandable parts. There needs to be a parallel operation where those parts are assembled or integrated into a whole, and that whole interacts with everything around it. This is where unforeseen problems can occur. Systems models and a holistic systems thinking approach can mitigate this risk. A systems approach and ability to manage complexity is a key skill for engineers, and positions them well for other fields like management.
Kastens, K., Manduca, C., Cervato, C., & Frodeman, R., Goodwin, C., Liben, L., Mogk, D., Spangler, T., Stillings, N., Titus, S. (2009). How Geoscientists Think and Learn. Eos, Transactions American Geophysical Union. 90. 10.1029/2009EO310001.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Authors: Professor Anne Nortcliffe (Wrexham University); Crystal Nwagboso (Engineering Professors’ Council).
Topic: A practical guide for educators on using the Toolkit to embed inclusive employability in teaching, illustrated with real-life case studies and step-by-step session plans.
Engineeringdisciplines: Any.
Keywords: Academics; Active Learning; Case Study; Employability and Skills; Curriculum or Course; Engineering Professionals; Inclusive or Responsible Design; Interdisciplinary or Multidisciplinary; Pedagogy; Problem-Based Learning; Project-Based Learning; Students; Teaching and Learning; Workshop; Collaboration; Higher Education; General and Non-Specific or Other Engineering; Equity, Diversity and Inclusion
Who is this how-to guide / case study for? This guide is designed for educators, curriculum developers, and academic support staff seeking to integrate inclusive employability into engineering education. Through real-world case studies and detailed session plans, it provides practical strategies for fostering students’ professional skills, reflective practice, and meaningful engagement with industry, adaptable across diverse engineering disciplines and teaching contexts.
Sustainability competency: Critical thinking; Integrated problem-solving, Collaboration.UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
AHEP mapping: This resource addresses two of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this resource to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.
Related SDGs: SDG 4 (Quality education); SDG 13 (Climate action).
Reimagined Degree Map Intervention: More real-world complexity; Active pedagogies and mindset development.The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Who is this article for? This article should be read by educators at all levels in higher education who are seeking an overall perspective on using PBL for integrating sustainability in engineering education. Engaging with this topic will also help to prepare students with the soft skill sets that employers are looking for.
Premise:
Engineering graduates are increasingly required to implement sustainability-focussed initiatives within industry, alongside enhanced expectations from professional bodies and the UK specification (UK-SPEC) for engineers (Engineering Council, 2024). However, a recent study of UK Higher Education institutions highlighted that only a handful have implemented Education for Sustainable Development (ESD) into their curricula in a systemic manner (Fiselier et al., 2018), which suggests many engineering institutions still need support in this area. This article aims to explain opportunities and challenges for integrating ESD into engineering programmes via project-based learning.
1. An overview of problem-based learning as a tool for teaching sustainability within engineering:
To develop sustainability-literate graduates, the Higher Education Academy (AdvanceHE) and the UK Quality Assurance Agency for Higher Education (QAA) emphasise that students need to:
understand what the concept of environmental stewardship means for their discipline and their professional and personal lives;
think about issues of social justice, ethics, and wellbeing, and how these relate to ecological and economic factors; and
develop a future-facing outlook by learning to think about the consequences of actions, and how systems and societies can be adapted to ensure sustainable futures (QAA & HEA, 2014).
Problem-Based Learning (PBL) provides a suitable teaching method for addressing these educational objectives. It is an influential approach in engineering education that emphasises real-world problem-solving and student-centred investigation. PBL deeply engages engineering students, prompting them to develop higher-level thinking skills while they personally confront and navigate economic, social, and environmental issues. This method fosters holistic systems thinking, interdisciplinary insights, ethical considerations, and an emphasis on the long-term viability of technical solutions (Cavadas and Linhares, 2023), while also inspiring and motivating learners (Loyens, 2015).
While PBL can be delivered through theoretical case study examples, the term is used interchangeably with Project-Based Learning within engineering education. Both problem-based learning and project-based learning share characteristics such as collaboration and group work, the integration of knowledge and practice, and foregrounding problem analysis as the basis of the learning process (De Graaff and Kolmos, 2003). One of the main differences is where the parameters lie: with problem-based learning the parameters are defined at the beginning and students are able to find a range of solutions; with project-based learning the parameters lie at the end and students are expected to reach a specific end solution (Savery, 2006). There is also a difference in the role of the tutor and the information they provide: in problem-based learning the tutor facilitates but gives little information, while in project-based learning they are both a facilitator and a source of knowledge (Savery, 2006). Project based learning may be more accepted within engineering education since it is considered to more closely resemble the reality of the profession (Perrenet, Bouhuijs and Smits, 2000), hence Aalborg’s working definition of PBL as “Problem-Oriented, Project-Organized, Learning” (Dym et al., 2005).
PBL thus facilitates the creation of immersive student-centric environments where group projects enable collaborative learning (Kokotsaki, Menzies and Wiggins, 2016). As Lozano et al. (2017) highlight, the nature of PBL advances critical thinking and problem-solving in engineering contexts, enabling students to critically reflect on sustainability concepts and apply this understanding to real-world challenges. Importantly, it is paramount in engineering education to foster action-oriented competencies and incorporate social contextualisation aspects (Fogg-Rogers et al., 2022), such as ethical nuances, justice, and equality, ensuring a comprehensive grasp of an engineer’s role amidst evolving societal and environmental challenges (Wang et al., 2022).
2. Overcoming challenges within PBL:
While PBL presents an obvious approach for embedding sustainability, there are a series of challenges which engineering educators need to overcome to facilitate transformational learning. This section presents some of the most common challenges encountered, along with pedagogic solutions.
Lack of apparent topic relevance Sustainability topics can sometimes be treated as isolated topics, rather than an integrated aspect of an engineering problem. A perception of sustainability in engineering is that it is not implicit in design, manufacture, and operation; rather it is often perceived as an ‘add-on’ to technical skill development. This applies to both students and teachers: both require support to understand the relevance and complexities of sustainability. When academics delivering sustainability materials may struggle to relate the topic to their own engineering disciplines, students may fail to see how they can impact change. Students must work on real-world projects where they can make a difference locally or globally, and they are more inclined towards sustainability topics that are relevant to their subject discipline with subject experts.
Dealing with an overwhelming amount of information Students can be overwhelmed by the large amounts of multidisciplinary information that needs to be processed when tackling real-world problems. This can also be a challenge for academics delivering teaching, especially if the topic is not related to their speciality. Additional support (and training), along with allocation of teaching workload, are needed to successfully integrate sustainability contexts for both staff and students.
Group work challenges PBL is best conducted by mixing individual study and group work. However, groups can fail if group creation, monitoring, supporting, and assessing processes are inconsistent, or not understood by academic tutors or students. Tutors need to act as group facilitators to ensure successful collaborative learning.
Issues with continual engagement PBL often requires active engagement of students over an extended period (several weeks or months). This can be a challenge, as over time, students’ focus and priorities can change. We suggest that whole programmes need to be designed around PBL components, so that other modules and disciplines provide the scaffolding and knowledge development to the relevant PBL topics.
Delivering PBL online
PBL is best delivered using experiential hands-on learning. For example, at UWE Bristol, this is provided through civic engagement with real-world industry problems and service learning through engagement with industry, schools, and community groups (Fogg-Rogers et al., 2017). This experiential learning was exceptionally challenging to deliver online during the COVID-19 pandemic, and programmes would need to be re-designed for online learning.
3. Recommendations for successful implementation of PBL:
Sustainability topics need to be embedded within engineering education so that each discipline-specific engineering problem is explored within PBL from a technical, economic, ethical, and sustainability perspective. Drawing from UWE Bristol’s journey of ESD implementation using PBL, key recommendations are outlined below.
Managing academic workload In the initial phases of ESD integration at UWE Bristol, a small number of committed academics contributed a lot of time, effort, and dedication to push through and enable ESD acceptance from staff and students. Programme-wide implementation of ESD required wider support at the institutional level, alongside additional support for module leaders and tutors, so they felt capable of delivering ESD with a realistic workload.
Structured delivery of ESD Structuring delivery over time and throughout different modules enables students to work through large amounts of information. Providing summative feedback/assessments during key phases of the PBL exercise can also help students stay on track and manage their workload. At UWE Bristol, group presentations with pass/fail grading are introduced mid-project, so students can present information gathered about the context, before beginning problem-solving.
Managing group work challenges PBL is best conducted by mixing individual study and group work. Ensuring assessment briefs have implicit sustainability requirements is vital to embedding ESD concepts, so that students can see the need for engagement. This is further enhanced by stating the relevance to workplace contexts and UK-SPEC requirements. Tutors need to facilitate group dynamics and engagement, along with providing support structures for students who, for whatever reason, are unable to engage with group work.
Creating an enabling environment for ESD integration The integration of sustainable development throughout the curricula at UWE Bristol has been supported at the institutional level, and this has been critical for the wide scale rollout. An institution-wide Knowledge Exchange for Sustainability Education (KESE) network was created to support staff by providing a platform for knowledge sharing. Within the department, Staff Away days were used to run sustainability workshops to discuss ESD and topics of interest to students. An initial mapping exercise was conducted to highlight where sustainability was already taught within the curriculum and to identify the discipline relevant contexts (Lamere et al., 2022). Further training and industrially relevant contexts were provided to convince some staff that sustainability needed to be included in the curriculum, along with evidence that it was already of great relevance in the wider engineering workplace. This led to the development of an integrated framework of key learning requirements which embedded professional attributes and knowledge of the UK-SPEC.
Student motivation and continual engagement
For sustainability education to be effective, the content coverage should be aligned, or better still, integrated, with the topics that form part of students’ disciplinary studies. To maintain continual engagement during the PBL delivery and beyond, clear linkages need to be provided between learning and future career-related practice-based sustainability activities. Partnerships have been developed with regional stakeholders and industry, to provide more context for real-world problems and to enable local service learning and community action (Fogg-Rogers, Fowles-Sweet, 2018). Industry speakers have also been invited to contribute to lectures, touching on a wide range of sustainability and ethical issues. ESD teaching is also firmly linked to the individual’s own professional development, using the UK-SPEC competency requirements, and linked to end-point assessments. This allows students to see the potential impact on their own professionalism and career development.
These recommendations can enable engineering educators to integrate sustainability topics within the curriculum using PBL to enhance student learning and engagement.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Sustainability competency: Systems-thinking; Collaboration; Integrated problem-solving.UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
AHEP mapping: This resource addresses two of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this resource to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.
Related SDGs: SDG 2 (Zero hunger); SDG 3 (Good health and well-being); SDG 4 (Quality education); SDG 12 (Responsible consumption and production); SDG 13 (Climate action).
Reimagined Degree Map Intervention: Active pedagogies and mindset development; Authentic assessment; More real-world complexity.The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Who is this article for? This article should be read by Chemical Engineering educators in higher education who are seeking to integrate sustainability in their project modules. Engaging with this topic will also help to prepare students with the soft skill sets that employers are looking for.
Premise:
The design project (DP) is considered to be the major focus of the CE curriculum, where students work in groups to design a complete chemical process – feeds, products process routes, energy requirements, financial aspects and emissions. It is considered challenging for various reasons including the following: the requirement to recall and combine knowledge covered previously in taught classes (some of which may have been forgotten), dealing with a huge corpus of data (unavailability, uncertainty, some being in conflict and some being superfluous) and all the design decisions that need to be made from many options. This is a major contrast with standard taught modules where all the data required is normally provided in advance. Just making decisions is not enough – they need to be timely and justified otherwise the project may be rushed and may not complete by the deadline. This is why the DP is valued by employers. Furthermore, if Education for Sustainable Development (ESD) is embedded in the design project, it is more likely that students will take forward sustainability into the workplace. Figure 1 illustrates Chemical processes and the design project.
1.Subject (CE) and DP pictorial representations:
Part (a) is a generic representation of a chemical process and shows the input-output nature of chemical processes. A chemical process takes a feed and converts it to useful products (the process shown has two equipment units and four streams). Part (b) is a representation of the design project, where the specification (or brief) is provided to groups at the start (DSpec) and the final submission (or solution) is the information in part (a). Part (c) shows that specifications can be product-based (the top two) or feed-based (the bottom two). The dashed lines indicate specifications where the flowrate and composition of the feed/product is subject to design choice – a typical factor that will extend the design procedure and require more decision-making.
2. Inclusion of sustainability in the project topic and communication with students:
This is fairly straightforward in CE design projects, because of the circular economy and the associated waste minimisation. So, from Figure 1, a feed-based (rather than product-based) specification can be employed. Topics that have been used at Strathclyde in recent years have been the utilisation of coffee grounds, food waste and (in 2024) green and garden waste. It is helpful that such topics can be linked to many of the UN SDGs. Furthermore, waste products are often complex with many components, and one of the characteristics of chemical engineering is the various separation techniques. These two factors should be communicated to students to improve engagement.
3. Inclusion of sustainability as an ESD activity to be carried out by groups:
One of the complicating factors about the UN SDGs is that there are so many, meaning that there is the possibility of a chemical process having both positive and negative impacts on different SDGs. This means that groups really need to consider all of the SDGs. This might be conveniently demonstrated as per Table 1. Certainly, it would be hoped that there are more ticks in column 2 than in column 3. Column 4 corresponds to minimal change, and column 5 where there is not enough information to determine any impact.
Table 1: Sustainability rating form for design project submissions
As an example, consider a design project which is based on better utilisation of green waste. Let us say that this results in less greenhouse gas emissions, as well as there being less need to plant and harvest plants. This will result in positive outcomes for SDG12 and SDG13. There are also positive effects because more land can be used for crops, and there will be higher plant coverage during the year. It could be argued then that there are minor positive effects om SDG2 and SDG3. The subsequent SDG profile in Table 1 shows two major impacts and two minor impacts – this might be typical for DPs.
4. Assessment of sustainability in the design project:
Table 2 shows the typical sections in a DP submission. For convenience these are shown as having equal 20-mark contributions. One way of determining marks is to divide these sections into a number of dimensions, for example: use of the literature, technical knowledge, creativity/innovation and style/layout. Sustainability could then be included as a fifth dimension. It is then a case of determining the sustainability dimension for each of the marking sections. It could be argued that sustainability is particularly important at the start of the project (when feeds and amounts are being decided) and at the end (when the final process is being assessed). This explains the larger weightings in Table 2. Coherence refers to how well the submission reads in terms of order and consistency and is thus independent of sustainability. The weightings are subject to debate, but they do at least give the potential for consistent (and traceable) grading between different assessors.
Table 2: Design project assessment now including ESD
Feijoo, G., Moreira, M.T. (2020) “Fostering environmental awareness towards responsible food consumption and reduced food waste in chemical engineering students”, Education for Chemical Engineers 33, pp. 27–35
IChemE (2021), “Accreditation of chemical engineering programmes: a guide for education providers and assessors”
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
Sustainability competency: Collaboration; Integrated problem-solving.UNESCO has developed eight key competencies for sustainability that are aimed at learners of all ages worldwide. Many versions of these exist, as are linked here*. In the UK, these have been adapted within higher education by AdvanceHE and the QAA with appropriate learning outcomes. The full list of competencies and learning outcome alignment can be found in the Education for Sustainable Development Guidance*. *Click the pink ''Sustainability competency'' text to learn more.
AHEP mapping: This resource addresses two of the themes from the UK’s Accreditation of Higher Education Programmes fourth edition (AHEP4): The Engineer and Society (acknowledging that engineering activity can have a significant societal impact) and Engineering Practice (the practical application of engineering concepts, tools and professional skills). To map this resource to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.
Related SDGs: All 17; see specific examples below for SDG 2 (Zero Hunger); SDG 13 (Climate Action).
Reimagined Degree Map Intervention: Adapt and repurpose learning outcomes; Active pedagogies and mindset development; Authentic assessment.The Reimagined Degree Map is a guide to help engineering departments navigate the decisions that are urgently required to ensure degrees prepare students for 21st century challenges. Click the pink ''Reimagined Degree Map Intervention'' text to learn more.
Who is this article for? This article should be read by educators at all levels in Higher Education who wish to embed sustainable development goals into computing projects.
Education for Sustainable Development (ESD) is defined by UNESCO (2021) as: “the process of equipping students with the knowledge and understanding, skills and attributes needed to work and live in a way that safeguards environmental, social and economic wellbeing, in the present and for future generations.” All disciplines have something to offer ESD, and all can contribute to a sustainable future. This guide presents how to embed the Sustainable Development Goals (SDGs) into undergraduate computing projects, using problem-based learning and teamwork as the main pedagogical tools (Mishra & Mishra, 2020).
Embedding Sustainable Development Goals (SDGs) into computing group projects:
Typically, the aim of the undergraduate Computing Group Project is to:
start preparing students for a professional career in the computing industry.
familiarise the students with working in software development teams.
give them the experience of delivering a non-trivial software system.
This type of project provides students with an opportunity to integrate various skills, including design, software development, project management, and effective communication.
In this project setting, the students can be asked to select a project theme based on the SDGs. The module team then can support student learning in three key ways:
1. Lectures, labs, and regular formative assessments can build on lab activities to walk the project groups through a sustainability journey that starts from a project pitch, continues with design, implementation, and project progress reporting, and ends with delivering a final demo.
2. Blending large classroom teaching with small group teaching, where each group is assigned a tutor, to ensure timely support and feedback on formative assessments.
3. A summative assessment based on a well-structured project portfolio template, guiding students to present and reflect on their individual contribution to the group effort. This portfolio may form the only graded element of their work, giving the students the opportunity to learn from their mistakes in formative assessments and present their best work at the end of the module.
Mapping the learning outcomes to the eight UNESCO key competencies for sustainability (Advance HE, 2021), the students will have the opportunity to experience the following:
Group work: The students plan, manage, and track a substantial group activity, understanding and applying the principles of professional and ethical behaviour in a group context. They “recognise that a collective effort is not just a simple sum of each individual’s effort but is likely to be more complex and have multiple drivers that may be personal, political or communal” (Advance HE, 2021, p. 24).
Open-ended problem: The groups take an open-ended problem, collect, and analyse relevant information and define the requirements. They will “identify the tensions between the 17 SDGs and recognise their interconnections” (Advance HE, 2021, p. 24) and work towards “creating their visions for the future” (Advance HE, 2021, p. 25).
Non-trivial software development: The students will independently and systematically design, develop, and evaluate a piece of software that is data-driven and has non-trivial functionality. This way, they will “develop and implement innovative actions that further sustainable development at the local level and beyond” (Advance HE, 2021, p. 27).
Alternative solutions: They will analyse complex systems and compare and evaluate alternative problem solutions according to given criteria, including from a technical perspective.
Communication: They will effectively present ideas and solutions, recognising the importance of “verbal and non-verbal communication skills and their role in group cohesion” (Advance HE, 2021, p. 28).
More specifically, sustainable development can be embedded following a lecture-lab-formative assessment-summative assessment path:
1. Introduction lecture: Introduce the SDGs and give real-life examples of software that contribute to SDGs (examples include: for SDG 2 – Zero Hunger, the World Food Programme’s Hunger Map; SDG 13 – Climate Action, Climate Mind ). The students then can be instructed to do their own research on SDGs.
2. Apply design thinking to project ideation: In a lecture, students are introduced to design thinking and the double-diamond of design to use a diverge-converge strategy to first “design the right thing” and second “design things right.” In a practical session, with teaching team support, the students can meet their groups for a brainstorming activity. It is essential to inform students about setting ground rules for discussion, ensuring all voices are heard. Encourage students to apply design thinking to decide which SDG-based problem they would like to work on to develop a software solution. Here, giving students an example of this process based on a selected SDG will be useful.
3. Formative assessment – project pitch deliverable: The next step is to channel students’ output of the design thinking practical to a formative assessment. Students can mould their discussion into a project pitch for their tutors. Their presentation should explain how their project works towards one or more of the 17 SDGs.
4. Summative assessment – a dedicated section in project portfolio: Finally, dedicating a section in a project portfolio template on ideation ensures students reflect further on the SDGs. In the portfolio, students can be asked to reflect on how individual ideas were discussed and feedback from different group members was captured. They should also reflect on how they ensured the chosen problem fits one or more SDGs, describe the selection process of the final software solution, and what alternative solutions for the chosen SDG they have discussed, elaborating on the reasons for the final choice.
Conclusion:
Computing projects provide an excellent opportunity to align teaching, learning, and assessment activities to meet key Sustainable Development competencies and learning outcomes. The projects can provide transformational experiences for students to hear alternative viewpoints, reflect on experiences, and address real-world challenges.
Lewrick, M., Link, P., Leifer, L.J. & Langensand, N. (2018). The design thinking playbook: mindful digital transformation of teams, products, services, businesses, and ecosystems. New Jersey: John Wiley & Sons, Inc, Hoboken.
Any views, thoughts, and opinions expressed herein are solely that of the author(s) and do not necessarily reflect the views, opinions, policies, or position of the Engineering Professors’ Council or the Toolkit sponsors and supporters.
