Toolkit: Complex Systems Toolkit.

Author: James C Atuonwu, PhD, MIET, FHEA (NMITE).

Topic: Simulating pinch analysis and multi-stakeholder trade-offs.

Title: Modelling complexity in industrial decarbonisation.

Resource type: Teaching activity.

Relevant disciplines: Energy engineering; Chemical engineering; Process systems engineering; Mechanical engineering; Industrial engineering.

Keywords: Climate change; Modelling; Decarbonisation; Energy production; Heat integration; Optimisation; Stakeholders; Trade offs.

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. It is based upon the author’s 2025 article “A Simulation Tool for Pinch Analysis and Heat Exchanger/Heat Pump Integration in Industrial Processes: Development and Application in Challenge-based Learning”. Education for Chemical Engineers 52, 141–150. 

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, Systems Modelling and Analysis 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). In addition, this resource addresses the themes of Science, mathematics and engineering principles; Problem analysis; and Design. 

Educational level: Intermediate.

Educational aim: To equip learners with the ability to model, analyse, and optimise pathways for industrial decarbonisation through a complex-systems lens – integrating technical, economic, and policy dimensions – while linking factory-level design decisions to wider value-chain dynamics, multi-stakeholder trade-offs, and long-term sustainability impacts. 
 

 

Learning and teaching notes: 

This teaching activity explores heat integration for the decarbonisation of industrial processes through the lens of complex systems thinking, combining simulation, systems-level modelling, and reflective scenario analysis. It is especially useful in modules related to energy systems, process systems, or sustainability.  

Learners analyse a manufacturing site’s energy system using a custom-built simulation tool to explore the energy, cost and carbon-emission trade-offs of different heat-integration strategies. They also reflect on system feedback, stakeholder interests and real-world resilience using causal loop diagrams and role-played decision frameworks.  

This activity frames industrial heat integration as a complex adaptive system, with interdependent subsystems such as process material streams, utilities, technology investments and deployments, capital costs, emissions, and operating constraints. 

Learners run the simulation tool to generate outputs to explore different systems integration strategies: pinch-based heat recovery by heat exchangers, with and without heat pump-based waste heat upgrade. Screenshots of the tool graphical user interface are attached as separate files:

The learning is delivered in part, through active engagement with the simulation tool. Learners interpret the composite and grand composite curves and process tables, to explore how system-level outcomes change across various scenarios. Learners explore, using their generated simulation outputs, how subsystems (e.g. hot and cold process streams, utilities) interact nonlinearly and with feedback effects (e.g., heat recovery impacts), shaping global system behaviour and revealing leverage points and emergent effects in economics, emissions and feasibility. 

Using these outputs as a baseline, and exploring other systems modelling options, learners evaluate trade-offs between heat recovery, capital expenditure (CAPEX), operating costs (OPEX), and carbon emissions, helping them develop systems-level thinking under constraints. 

The activity embeds scenario analysis, including causal loop diagrams, what-if disruption modelling, and stakeholder role-play, using multi-criteria decision analysis (MCDA) to develop strategic analysis and systems mapping skills. Interdisciplinary reasoning is encouraged across thermodynamics, economics, optimisation, engineering ethics, and climate policy, culminating in reflective thinking on system boundary definitions, trade-offs, sustainability transitions and resilience in industrial systems.  

Learners have the opportunity to: 

Teachers have the opportunity to: 

 

Downloads: 

 

Learning and teaching resources:

 

About the simulation tool (access and alternatives):

This activity uses a Streamlit-based simulation tool, supported with process data (Appendix A, Table 1, or an educator’s equivalent). The tool is freely available for educational use and can be accessed online through a secure link provided by the author on request (james.atuonwu@nmite.ac.uk or james.atuonwu@gmail.com). No installation or special setup is required; users can access it directly in a web browser. The activity can also be replicated using open-source or online pinch analysis tools such as OpenPinch, PyPinch PinCH, TLK-Energy Pinch Analysis Online. SankeyMATIC can be used for visualising energy balances and Sankey diagrams. 

Pinch Analysis, a systematic method for identifying heat recovery opportunities by analysing process energy flows, forms the backbone of the simulation. A brief explainer and further reading are provided in the resources section. Learners are assumed to have prior or guided exposure to its core principles. A key tunable parameter in Pinch Analysis, ΔTmin, represents the minimum temperature difference allowed between hot and cold process streams. It determines the required heat exchanger area, associated capital cost, controllability, and overall system performance. The teaching activity helps students explore these relationships dynamically through guided variation of ΔTmin in simulation, reflection, and trade-off analysis, as outlined below. 

 

Introducing and prioritising ΔTmin trade-offs:

ΔTmin is introduced early in the activity as a critical decision variable that balances heat recovery potential against capital cost, controllability, and safety. Students are guided to vary ΔTmin within the simulation tool to observe how small parameter shifts affect utility demands, exchanger area, and overall system efficiency. This provides immediate visual feedback through the composite and grand composite curves, helping them connect technical choices to system performance. 

Educators facilitate short debriefs using the discussion prompts in Part 1 and simulation-based sensitivity analysis in Part 2. Students compare low and high ΔTmin scenarios, reasoning about implications for process economics, operability, and energy resilience. 

This experiential sequence allows learners to prioritise competing factors (technical, economic, and operational), while recognising that small changes can create non-linear, system-wide effects. It reinforces complex systems principles such as feedback loops and leverage points that govern industrial energy behaviour. 

 

Data for decisions:

The simulator’s sidebar includes some default values for energy prices (e.g. gas and electricity tariffs) and emission factors (e.g. grid carbon intensity), which users can edit to reflect their own local or regional conditions. For those replicating the activity with other software tools, equivalent calculations of total energy costs, carbon emissions and all savings due to heat recovery investments can be performed manually using locally relevant tariffs and emission factors. 

The Part 1–3 tasks, prompts, and assessment suggestions below remain fully valid regardless of the chosen platform, ensuring flexibility and accessibility across different teaching contexts. 

 

Educator support and implementation notes:

The activity is designed to be delivered across 3 sessions (6–7.5 hours total), with flexibility to adapt based on depth of exploration, simulation familiarity, or group size. Each part can be run as a standalone module or integrated sequentially in a capstone-style format. 

 

Part 1: System mapping: (Time: 2 to 2.5 hours) – Ideal for a classroom session with blended instruction and group collaboration:

This stage introduces students to the foundational step of any heat integration analysis: system mapping. The aim is to identify and represent energy-carrying streams in a process plant, laying the groundwork for further system analysis. Educators may use the Process Flow Diagram of Fig. 1, Appendix A (from a real industrial setting: a food processing plant) or another Process Diagram, real or fictional. Students shall extract and identify thermal energy streams (hot/cold) within the system boundary and map energy balances before engaging with software to produce required simulation outputs. 

 

Key activities and concepts include: 

 

Discussion prompts: 

 

Student deliverables: 

 

Part 2: Running and interpreting process system simulation results (Time: 2 to 2.5 hours) – Suitable for lab or flipped delivery; only standard computer access is needed to run the tool (optional instructor demo can extend depth):

Students use the simulation tool to generate their own results. The process scenario of Fig. 1, Appendix A, with the associated stream data (Table 1) can be used as a baseline.
 

Tool-generated outputs:

 

Learning tasks:

1. Scenario sweeps
Run different scenarios (e.g., different ΔTmin levels, tariffs, emission factors, and Top-N HP selections).
Prompts: How do QREC, QHU/QCU, HX area, and CAPEX/OPEX/CO₂ shift across scenarios? Which lever moves the needle most? 

2. Group contrast (cases A vs B: see time-phased operations A & B in Appendix A)
Assign groups different cases; each reports system behaviours and trade-offs.
Prompts: Where do you see CAPEX vs. energy-recovery tension? Which case is more HP-friendly and why? 

3. Curve reading
Use the Composite & Grand Composite Curves to identify pinch points and bottlenecks; link features on the curves to the tabulated results.
Prompts: Where is the pinch? How does ΔTmin change the heat-recovery target and utility demands? 

4. Downstream implications
Trace how curve-level insights show up in HX sizing/costs and HP options.
Prompts: When does adding HP reduce utilities vs. just shifting costs? Where do stream temperatures/CP constrain integration? 

5. Systems lens: feedback and leverage
Map short causal chains from the results (e.g., tariffs → HP use → electricity cost → OPEX; grid-carbon → HP emissions → net CO₂).
Prompts: Which levers (ΔTmin, tariffs, EFs, Top-N) create reinforcing or balancing effects? 

 

Outcome:

Students will be able to generate and interpret industrial simulation outputs, linking technical findings to economic and emissions consequences through a systems-thinking lens. They begin by tracing simple cause–effect chains from the simulation data and progressively translate these into causal loop diagrams (CLDs) that visualise reinforcing and balancing feedback. Through this, learners develop the ability to explain how system structure drives performance both within the plant and across its broader industrial and policy environment. 

Optional extension: Educators may provide 2–3 predefined subsystem options (e.g., low-CAPEX HX network, high-COP HP integration, hybrid retrofit) for comparison. Students can use a decision matrix to justify their chosen configuration against CAPEX, OPEX, emissions, and controllability trade-offs. 

 

Part 3: Systems thinking through scenario analysis (Time: 2 to 2.5 hours) – Benefits from larger-group facilitation, a whiteboard or Miro board (optional), and open discussion. It is rich in systems pedagogy:

Having completed simulation-based pinch analysis and heat recovery planning, learners now shift focus to strategic implementation challenges faced in real-world industrial settings. In this part, students apply systems thinking to explore the broader implications of their heat integration simulation output scenarios, moving beyond process optimisation to consider real-world dynamics, trade-offs, and stakeholder interactions. The goal is to encourage students to interrogate the interconnectedness of decisions, feedback loops, and unintended consequences in process energy systems including but not limited to operational complexity, resilience to disruptions, and alignment with long-term sustainability goals. 

Activity: Stakeholder role play / Multi-Criteria Decision Analysis 
Students take on stakeholder roles and debate which design variant or operating strategy should be prioritised. They then conduct a Multi-Criteria Decision Analysis (MCDA), evaluating each option based on criteria such as CAPEX, OPEX savings, emissions reductions, risk, and operational ease. 

Stakeholders include:

The team must present a strategic analysis showing how the heat recovery system behaves as a complex adaptive system, and how its implementation can be optimised to balance technical, financial, environmental, and human considerations. 

 

Optional STOP for questions and activities:

Before constructing causal loop diagrams (CLDs), learners revisit key results from their simulation — such as ΔTmin, tariffs, emission factors, and system costs — and trace how these parameters interact to influence overall system performance. Educators guide this transition, helping students abstract quantitative outputs (e.g., changes in QREC, OPEX, or CO₂) into qualitative feedback relationships that reveal cause-and-effect chains. This scaffolding helps bridge the gap between process simulation and systems-thinking representation, supporting discovery of reinforcing and balancing feedback structures. 

 

Instructor guidance:
Each student or small subgroup first constructs a causal loop diagram (CLD) from the viewpoint of their assigned stakeholder (e.g., operations, finance, environment). They then reconvene to integrate these perspectives into a single, shared system map, revealing conflicting goals, reinforcing and balancing feedback, and common leverage points. This two-step approach mirrors real-world decision dynamics and strengthens collective systems understanding. Support materials such as a CLD starter template and a stakeholder impact matrix may be provided to assist instructors in scaffolding systems-thinking activities.

 

Discussion prompts:

 

Instructor debrief (engineering context with simulation linkage):
After students share their CLDs, the educator facilitates a short discussion linking their identified reinforcing and balancing loops to common dynamic patterns observable in the simulation results. For instance: 

This reflection connects quantitative model outputs (e.g. QREC, OPEX, CAPEX, emissions) to qualitative system behaviours, helping learners recognise leverage points and understand how design choices interact across technical, economic, and social dimensions of decarbonisation. 

Activity: Explore “What if?” scenarios 

Working in groups, students choose one scenario to explore using a systems lens:

Each group evaluates the resilience and flexibility of the proposed integration design. They consider:

Educators may add advanced scenarios (e.g. carbon tax introduction, supplier failure, or project delay) to challenge students’ resilience modelling and stakeholder negotiation skills.

 

Stakeholder impact reflection:

To extend systems reasoning beyond the technical domain, students assess how their chosen design scenarios (e.g., low vs. high ΔTmin, with or without heat pump integration) affect each stakeholder group. For instance: 

Each team member rates perceived benefits, risks, or compromises under each design case, and the results are summarised in a stakeholder impact matrix or discussion table. This exercise links quantitative system metrics (energy recovery, emissions, cost) to qualitative stakeholder outcomes, reinforcing the “multi-layered feedback” perspective central to complex systems analysis. 

 

Learning Outcomes (Part 3): 

By the end of this part, students will be able to:

 

Instructor Note – Guiding CLD and archetype exploration:

Moving from numerical heat-exchange and cost data to CLD archetypes can be conceptually challenging. Instructors are encouraged to model this process by identifying at least one reinforcing loop (e.g. “energy savings → lower OPEX → more investment in recovery → further savings”) and one balancing loop (e.g. “higher capital cost → reduced investment → lower heat recovery”). Relating these loops to common system archetypes such as “Limits to Growth” or “Balancing with Delay” helps students connect engineering data to broader system dynamics and locate potential leverage points. The activity concludes with students synthesising their findings from simulation, systems mapping, and stakeholder analysis into a coherent reflection on complex system behaviour and sustainable design trade-offs. 

 

Assessment guidance: 

This assessment builds directly on the simulation and systems-thinking activities completed by students. Learners generate and interpret their own simulation outputs (or equivalent open-source pinch analysis results), using these to justify engineering and strategic decisions under uncertainty. 

Assessment focuses on students’ ability to integrate quantitative analysis (energy, cost, carbon) with qualitative reasoning (feedbacks, trade-offs, stakeholder dynamics), demonstrating holistic systems understanding. 

 

Deliverables (portfolio; individual or group):

1. Reading and interpretation of simulation outputs

Use the outputs you generate (composite & grand composite curves: HX match/area/cost tables; HP pairing/ranking; summary sheets of QHU, QCU, QREC, COP, CAPEX, OPEX, CO₂, paybacks) for a different industrial process (from the one used in the main learning activity) to: 

2. Systems mapping and scenario reasoning 

3. Decision memo (max 2 pages) 

Students should include a short reflective note addressing assumptions, feedback insights, and how their stakeholder perspective shaped their recommendation. 

 

Appendix A: Example process scenario for teaching activity:

The following process scenario explains the industrial context behind the main teaching activity simulations. A large-scale food processing plant operates a milk product manufacturing line. The process, part of which is shown in Fig. 1, involves the following: 

In real operations, the evaporation subprocess occurs at different times from the cooking/separation, oven and pre-finishing operations. This means that their hot and cold process streams are not simultaneously available for direct heat exchange. For a realistic industrial pinch analysis, the process is thus split into two time slices: 

Separate pinch analyses are performed for each slice, using the yellow-highlighted sections of Table 1 as stream data for time slice A, and the green-highlighted sections as stream data for time slice B. Any heat recovery between slices would require thermal storage (e.g., a hot-water tank) to bridge the time gap. 

Fig.1. Simplified process flowsheet of food manufacturing facility.

 

Note on storage and system boundaries:

Because the two sub-processes occur at different times, direct process-to-process heat exchange between their streams is not possible without thermal storage. If storage is introduced: 

 

Table 1. Process stream data corresponding to flowsheet of Fig. 1. Yellow-highlighted sections represent processes available at time slice A, while green-highlighted sections are processes available at time slice B.

 

Appendix B: Suggested marking rubric (Editable):

Adopter note: The rubric below is a suggested template. Instructors may adjust criteria language, weightings and band thresholds to align with local policies and learning outcomes. No marks depend on running software. 

1) Interpretation of Simulation Outputs — 25% 

2) Systems Thinking & Scenario Analysis — 30% 

3) Stakeholder & Implementation Insight — 20% 

4) Decision Quality & Justification — 15% 

5) Communication & Presentation — 10% 

 

References:

 

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.  

Toolkit: Complex Systems Toolkit.

Author: Nafiseh M. Aftah, PhD Candidate (University of Kansas).

Topic: Why integrate complex systems in engineering education? 

Title: Complex systems in a transformational era.

Resource type: Knowledge article.

Relevant disciplines: Any.

Keywords: Interdisciplinarity; Problem-solving; Problem-based learning; Active learning; Professional development; Collaboration; Real world; Artificial Intelligence; Trade offs.

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. 

Downloads: A PDF of this resource will be available soon.

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 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:

 

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.  

Toolkit: Complex Systems Toolkit.

Author: Dr. Stuart Grey, SFHEA (University of Glasgow).

Topic: Student created interactive simulation for complex sociotechnical systems.

Title: LLM-driven interactive simulation for complex sociotechnical systems.

Resource type: Teaching activity.

Relevant disciplines: Any.

Keywords: Artificial Intelligence; Large Language Model; Sociotechnical systems; Ethics; Modelling or simulation; Emergence.

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. It is based upon the author’s article “Enhancing Ethical Reasoning in Engineering Education through Student-Created Interactive Ethical Scenarios Using Generative AI,” 2025 IEEE Global Engineering Education Conference (EDUCON), London, United Kingdom, 2025, pp. 1-5, doi: 10.1109/EDUCON62633.2025.11016531. 

Downloads: 

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, Life Cycle, Configuration Management, Requirements Definition, Verification, and Validation 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). In addition, this resource addresses AHEP themes of Ethics and Communication. 

Education level: Intermediate.

 

Learners have the opportunity to: 

Teachers have the opportunity to: 

 

Overview:

This resource enables engineering students to create, run, and debug a text‑based, interactive simulation of a complex sociotechnical system using a Large Language Model (LLM). It is intentionally flexible and may be delivered as a multi‑session studio activity (including assessment) or used solely as a compact assessment.

  

Purpose and use:

In both modes, students design a robust text prompt, test it with a user, document changes, and submit auditable artefacts that evidence learning. The key activity is interrogating their own thinking on how complex systems should be modelled by making judgements as to how their game does and does not capture the system dynamics. 

 

Why and how: 

The approach aims to give students hands-on experience in putting systems thinking into practice. Concepts such as stakeholders, feedback loops, delays, uncertainty, and emergent behaviour can be implemented and interrogated without heavy tooling.  

The submission is a text LLM prompt with tracked changes, which allows students to demonstrate system design and debugging, produce transparent process evidence, and scale to large cohorts with minimal infrastructure. 

 

Delivery options at a glance:

Audience Undergraduate Years 2–4 and taught MSc, any engineering discipline 
Modes Studio activity (3–5×2 h + independent study) or Assessment‑only (prompt‑only; 1–2×2 h + 4–6 h)
Teams 3–4 students (solo permitted for assessment‑only) 
Assessment Portfolio (studio) or prompt‑plus‑change‑log (assessment‑only) 
Platforms Institutional Copilot licences successful; encourage exploration of free tools (students record model/version)

 

Materials and software:

 

Delivery modes:

Mode A — Studio activity (3–5 sessions) 

Mode B — Assessment‑only (prompt‑only; 1–2 sessions) 

In both modes, module leaders may supply a predefined scenario(s) to standardise scope and simplify marking. A ready‑to‑use example is provided in Appendix C. 

 

Assessment:

Studio portfolio — rubric (suggested weighting):

Criterion  A  B  C  D–E  % 
Complexity modelling  Clear boundary; rich stakeholders; ≥4 correct loops; delays explicit; coherent KPIs  Mostly sound  Basic map  Superficial  25 
Simulation design and prompt quality  Consistent state logic; visible feedbacks/delays; non‑linearity; negative choices allowed with consequences; clear commands  Mostly coherent  Playable but brittle  Confusing/linear  25 
Debugging evidence  Systematic play‑tests; clear issue → fix → re‑test artefacts  Some iteration  Minimal  None  20 
Insight and reflection  Deep analysis of emergence, trade‑offs, equity, uncertainty, and LLM limits  Good  Descriptive  Vague  20 
Communication and referencing  Clear, concise, correct Harvard referencing  Minor issues  Adequate  Disorganised  10 

 

Assessment‑only (prompt‑only) — compact rubric: 

 

Scenario options: 

Students may propose their own topic or the module leader may supply a predefined scenario. Options suited to UK engineering contexts include: 

 

Appendix A — Prompt template (simulation + debug‑ready): 

Title: Complex Systems Simulator — [Scenario] 

Purpose: Run a turn‑based interactive simulation of a complex sociotechnical system. Track named state variables, apply feedback and delays, and let the player’s decisions drive non‑linear outcomes. 

Setup: 

  1) Offer three roles (distinct authority/constraints). 

  2) Introduce 3–5 NPCs with clear goals and plausible interventions. 

  3) Show a dashboard of [STATE_VARIABLES] each turn with short context. 

State rules: 

Commands: status, talk [npc], inspect [asset], implement [policy], pilot [intervention], advance time, review log. 

Debug commands (for testing): trace on/off (print update logic), why (state which loops/delays drove the change), show variables (print current state table), revert (roll back one turn), reseed (slight exogenous shock). 

Realism and ethics: Allow all plausible actions and report consequences neutrally. If unsafe in the real world, refuse, propose safer alternatives, and continue with plausible systemic effects. 

LLM pitfalls to avoid: Do not invent new variables; ask clarifying questions rather than guessing; keep outputs concise; summarise trajectory every five turns. 

Begin: Greet the player, state the scenario, ask for a role, and wait. 

 

Appendix B — Debugging and play‑test checklist: 

Functional coherence 

Robustness 

User experience and clarity 

Report 

 

Appendix C — Predefined scenario (Urban Heatwave Response, UK city): 

Boundary: One UK local authority area during the July–August heatwave period. Focus on public health, energy demand, and community resilience. 

Roles: (1) Local Authority Resilience Lead; (2) NHS Trust Capacity Manager; (3) Distribution Network Operator (DNO) Duty Engineer. 

Stakeholders: Residents (with a focus on vulnerable groups), care homes, schools, SMEs, DNO, local NHS Trust, emergency services, voluntary/community groups, Met Office (for alerts), and local media. 

State variables (examples): Heat‑health alert level (0–4); Emergency Department occupancy (%); Electricity demand/capacity (% of peak); Indoor temperature exceedance hours (hrs > 27 °C); Public trust (0–100); Budget (£); Equity index (0–100). 

Events/shocks: Red heat alert; substation fault; procurement delay; misinformation spike on social media; transport disruption; community centre cooling failure. 

KPIs and stop conditions: Heat‑related admissions; unserved energy; cost variance; equity gap across wards. Stop if alert level 4 persists >3 days, budget overspends >10%, or trust <25. 

Notes for assessors: Using a standard, predefined scenario simplifies marking and ensures comparable complexity across teams, while still allowing for diverse strategies and outcomes. 

 

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.  

Toolkit: Complex Systems Toolkit.

Author: Mariam Makramalla, PhD, FRSA (New Giza University).

Topic: Integrating complex systems learning outcomes in engineering curricula.

Title: How to scaffold complex systems learning outcomes across a curriculum.

Resource type: Guidance article.

Relevant disciplines: Any.

Keywords: Learning outcomes; Pedagogy; Curriculum; Curriculum map; Critical thinking; Problem-solving; Life cycle; Decision-making . 

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. 

Downloads:

Who is this article for?: This article should be read by educators at all levels of higher education looking to embed and integrate complex systems topics into curriculum, module, and / or programme design.   

 

Premise:  

Teaching and learning engineering carries with it a double layer of complexity. On the one hand, this complexity is connected to the growing interdisciplinary nature of engineering itself. On the other hand, the complexity is connected to the growing diversity of engineering students that are often present in one project team. This multifaceted complexity requires a re-envisioned understanding of the role and purpose of the engineering educator.  

With the growing trend of a global classroom reality, we often find that learners in the classroom are representing different cultures, which in turn are rooted in them unconsciously carrying historical and socio-cultural baggage relating to these cultures. Thus, it becomes crucial to unpack the challenge and potential that such a diverse collective intelligence can offer to an engineering learning experience.  

As our understanding of the engineering discipline gets more rooted and interconnected with the precarious reality that our world is witnessing today, it becomes essential that the engineering education community would take up a proactive role in actively contributing to the formation of engineering citizenship. In other words, every engineering student should be educated as a citizen that has mastered the engineering cross-cutting fields in such a way that they are free to create and solve problems of the present and the future.  

With this in mind, it becomes very clear that the one-size-fits all model of a single discipline engineering classroom can no longer sustain itself. It does not factor in the richness that a diverse student body can offer, and it dilutes the value and potential of an engineering learner to think clearly or solve problems. It is therefore imperative that engineering educators grasp the complex reality of an integrated engineering discipline and address it in a way that fosters scaffolding of diverse knowledge. Some students might specialise in one core technical discipline. Yet, future projections for most students showcase the need to have a wide level of exposure to broader competency development. Students need to learn to understand the field of engineering at large and to develop system thinking skills that enable them to exist, challenge and have an impact on the system that they are a part of.  

 

How to scaffold learning outcomes in a complex engineering curriculum:

The below table has been designed for embedding Complex Systems Learning Outcomes across an engineering curriculum. It maps against competencies and suggests scaffolding techniques across educational levels. It is also important to note, that efforts need to be made to align to the relevant AHEP requirements or other accreditation standards. Table 1 presents the different strands of the Complex Systems Engineering Curriculum, colour coded in line with the INCOSE Competency Framework outline (INCOSE, 2025). Table 2 presents a practical guide for educators to scaffold Complex Systems learning outcomes across a curriculum. The intention is for the scaffolding framework to compare the trade-offs between different elements of the competency group. For example, system modelling and analysis as an element from the core competency and planning from the management competency. The table suggests activities that would integrate different competencies together in a scaffolded approach.  

Table 1. Competency Areas for Complex Systems (INCOSE, 2025).

Table 1 presents Competency Areas for Complex Systems. As mentioned, the skills range to include a wide variety of competencies, thereby enabling a solid and grounded systems thinking approach for students. As students approach their learning, they go through a series of development stages that gradually build up student level of expertise until they reach the stage of what the INCOSE competency framework refers to as a lead practitioner role. Building on the competencies of the complex system toolkit presented in Table 1, Table 2 presents a potential outline for a scaffolding framework that maps varying threads of the framework in a way that enables scaffolded activities at every developmental stage for learners. Depending on the learning context and educational level, educators can choose which level of attainment is appropriate to their curriculum.  

Table 2. Scaffolding Complex Systems Learning Outcomes across the curriculum 

 

Discussion and next steps:

As we are approaching the fuzzy front end to complexity in engineering pedagogy, as educators we need to be constantly toggling between devising frameworks, being informed by literature, contextualising ideas, validating these in our classrooms and repeating this cycle to continually fine-tune our complex teaching navigational complexity framework. The invitation is open for all educators who would like to connect as we continue to explore different ways of developing responsible engineers who leave a lasting and sustainable mark transforming their stationed realities.  

 

References:

   

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.  

 

Toolkit: Complex Systems Toolkit.

Author: Dr. Rebecca Margetts (Nottingham Trent University).

Topic: The importance of teaching and learning about complex systems.

Title: The real world is a complex system.

Resource type: Knowledge article.

Relevant disciplines: Any.

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.

Licensing: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. 

Downloads: 

Learning and teaching resources:

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 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: 

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.   

 

References:

 

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.

Engineering disciplines: 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.

 

Download the How-To Guide (PDF):

English

Welsh

Authors: Dr. Kieran Higgins(Ulster University); Dr. Alison Calvert (Queen’s University Belfast).

Topic: Integrating Education for Sustainable Development (ESD) into higher education curricula.

Type: Guidance

Relevant disciplines: Any.

Keywords: Curriculum design; Global responsibility; Sustainability; SDGs; Course design; Higher education; Pedagogy;

Sustainability competency: Anticipatory; Integrated problem-solving; Strategic; Systems thinking.

Related SDGs: SDG 4 (Quality education); SDG 13 (Climate action).

Reimagined Degree Map Intervention: Adapt and repurpose learning outcomes; Authentic assessment; Active pedagogies and mindset development.

Who is this article for?:  This article should be read by educators at all levels of higher education looking to embed and integrate ESD into curriculum, module, and / or programme design.

Link to resource: AdvanceHE’s Education for Sustainable Development Curriculum Design Toolkit

 

Learning and Teaching Notes:
Supported by AdvanceHE, this Toolkit provides a structured approach to integrating Education for Sustainable Development (ESD) into higher education curricula. It uses the CRAFTS methodology and empowers educators to enhance their modules and programs with sustainability competencies aligned with UN Sustainable Development Goals.

Key Features:
• Five-Phase Process: Analyse stakeholder needs, map current provision, reflect on opportunities for development, redesign with an ESD focus, and create an action plan for continuous enhancement.
• Practical Tools: Includes templates for stakeholder analysis, module planning, active learning activities, and evaluation.
• Flexible Implementation: Designed for use at both module and programme level.
• Competency-Based: Focuses on developing authentic learning experiences across cognitive, socio-emotional, and behavioural domains.

Benefits
• Identify stakeholder sustainability needs
• Map existing ESD elements in your curriculum
• Reflect on opportunities to enhance ESD integration
• Redesign modules with active learning approaches of ESD
• Create actionable plans for implementation and evaluation

Click here to access the Toolkit.

Read more here.

 

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: Dr. Kieran Higgins (Ulster University); Dr. Alison Calvert (Queen’s University Belfast).

Keywords: Curriculum design; Global responsibility; Sustainability; SDGs; Course design; Higher education; Pedagogy.

Who is this article for?: This article should be read by module coordinators, programme directors, and teaching teams in higher education who want to meaningfully integrate ESD into their curriculum design and delivery.

 

It’s always a struggle to get started on something new in the time- and resource-poor environment that is higher education. Sustainability can become just another box to tick rather than the world-changing priority it should be.

That’s why we have created the Education for Sustainable Development Curriculum Design Toolkit to build sustainability into the curriculum in a way that stimulates the critical reflection it needs to truly embed it within modules.

We knew there was more to ESD than simply labelling a module handbook with the SDG logos, especially when it was only SDG4 because it happens to mention education. There was a need to become familiar and comfortable with a deeper perspective on the SDGs and their related targets and indicators – without becoming intimidated by them. ESD should prepare students to tackle unforeseen challenges and navigate complex systems, rather than focusing on content alone. As higher education professionals, we recognised the inherent challenges of this.

As a result, we developed our CRAFTS (Co-Designing Reflective Approaches for the Teaching of Sustainability) model of curriculum design, based on an adaptation of Design Thinking, to provide a structured and usable, yet accessible, flexible, and not discipline-specific means of embedding and embodying ESD in the curriculum. We were then approached by AdvanceHE to develop this further into a practical, systematic resource that would empower educators to take genuine ownership of sustainability in their teaching and assessment.

The Toolkit helps tackle these issues in a straightforward way by breaking them down into five stages.

First, it shows how to analyse what stakeholders like students, employers and accrediting bodies want and need from a module when it comes to sustainability.

Then, it guides educators to map exactly what is being taught as the curriculum stands, aligning it to the SDGs and the ESD Competencies. This is a moment of real relief for many people, who discover that much of what they already do aligns perfectly with ESD.

After that, there’s a guided reflection to see where stronger integration might happen or where superficial coverage can be expanded into something more meaningful.

The redesign process helps to embed active learning and authentic assessments and finishes off with an action plan for moving forward and measuring impact for future evaluation.

We find it heartening to watch colleagues pivot from feeling like ESD is an add-on to realising it can enhance what they already do. Instead of worrying that they must become experts in every single SDG, the Toolkit reminds them that authentic engagement with a few well-chosen goals can lead to the deeper kind of learning we all aspire to provide.

This personal, reflective approach has helped academics overcome the sense that sustainability in the curriculum is an overwhelming requirement. They see it as a powerful lens through which students learn to handle uncertainty, become resilient critical thinkers and gain the confidence to tackle real-world problems.

We hope the Toolkit continues to spark conversations and encourage more creative approaches to ESD across disciplines. We don’t believe there’s a one-size-fits-all solution. It has been inspiring to see colleagues reclaim that sense of possibility and excitement, reassured that teaching for a sustainable future can be woven into what they’re already doing – just with an extra layer of intentionality and reflection.

If you’re looking for a way to bring ESD into your own classroom, we hope the Toolkit will be a reliable companion on that journey.

Dr Kieran Higgins (Lecturer in Higher Education Practice, Ulster University) and Dr Alison Calvert (Senior Lecturer in Biological Sciences, Queen’s University Belfast) have collaborated on Education for Sustainable Development projects for over 4 years, drawing on extensive and wide ranging experiences of higher education and sustainability. Their vision is of transformed global higher education curricula that empowers all graduates, regardless of discipline or career path, to become champions of a sustainable future.

 

This post is also available here.

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. 

Case study example: Water wars: managing competing water rights

Activity: Assessment. This example demonstrates how the questions provided in Assessing ethics: Rubric can be used to assess the competencies stipulated at each level.

Authors: Dr. Natalie Wint (UCL); Dr. William Bennett (Swansea University).

Related content:

 

Water wars: managing competing water rights 

This example demonstrates how the questions provided in the accompanying rubric can be used to assess the competencies stipulated at each level. Although we have focused on ‘Water Wars’ here, the suggested assessment questions have been designed in such a way that they can be used in conjunction with the case studies available within the toolkit, or with another case study that has been created (by yourself or elsewhere) to outline an ethical dilemma. 

Year 1 

Personal values: What is your initial position on the issue? Do you see anything wrong with how DSS are using water? Why, or why not?

Professional responsibilities: What ethical principles and codes of conduct are relevant to this situation?

Ethical principles and codes of conduct can be used to guide our actions during an ethical dilemma. How does the guidance provided in this case align/differ with your personal views? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)

What are the moral values involved in this case and why does it constitute an ethical dilemma? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)

What role should an engineer play in influencing the outcome? What are the implications of not being involved? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)

Year 2 

Formulate a moral problem statement which clearly states the problem, its moral nature and who needs to act. (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)

Stakeholder mapping: Who are all the stakeholders in the scenario? What are their positions, perspective and moral values?

Stakeholder  Perspectives/interests  Moral values 
Data Storage Solutions (DSS)  Increasing production in a profitable way; meeting legal requirements; good reputation to maintain/grow customer base.  Accountability; sustainability (primarily economic). 
Farmers’ union  Represent farmers who suffer from economic implications associated with costly irrigation.  Accountability; environmental sustainability; justice. 
Farm  The farm (presumably) benefits from DSS using the land.  Ownership and property; environmental sustainability; justice. 
Local Green Party  Represent views of those concerned about biodiversity. May be interested in opening of green battery plant.  Human welfare; environmental sustainability; justice. 
Local Council  Represent views of all stakeholders and would need to consider economic benefits of DSS (tax and employment), the need of the university and hospital, as well as the needs of local farmers and environmentalists. May be interested in opening of green battery plant.  Human welfare and public health; trust; accountability; environmental sustainability; justice. 
Member of the public  This may depend on their beliefs as an individual, their employment status and their use of services such as the hospital and university. Typically interested in low taxes/responsible spending of public money. May be interested in opening of green battery plant.  Human welfare; trust; accountability; environmental sustainability; justice. 
Stakeholders using DSS data storage  Reliable storage. They may also be interested in being part of an ethical supply chain.  Trust; privacy; accountability; autonomy. 
Non-human stakeholders  Environmental sustainability. 

 

What are some of the possible courses of action in the situation. What responsibilities do you have to the various stakeholders involved? What are some of the advantages and disadvantages associated with each? (Reworded from case study.)

What are the relevant facts in this scenario and what other information would you like to help inform your ethical decision making? (This is a question we had created in addition to those provided within the case study to meet the requirements stipulated in the accompanying rubric.)

 

 

Year 2/Year 3  

(At Year 2, students could provide options; at Year 3 they would evaluate and form a judgement.) 

Make use of ethical frameworks and/or professional codes to evaluate the options for DSS both short term and long term. How do the uncertainty and assumptions involved in this case impact decision making?

Option  Consequences  Intention  Action 
Keep using water  May lead to expansion and profit of DSS and thus tax revenue/employment and supply. 

Reputational damage of DSS may increase. Individual employee piece of mind may be at risk. 

Farmers still don’t have water and biodiversity still suffers which may have further impact long term. 

 Intention behind action not consistent with that expected by an engineer, other than with respect to legality  Action follows legal norms but not social norms such as good will and concern for others. 
Keep using the water but limit further work  May limit expansion and profit of DSS and thus tax revenue/employment and supply. 

Farmers still don’t have water and biodiversity still suffers and may have further impact long term. This could still result in reputation damage. 

 Intention behind action partially consistent with that expected by an engineer.  Action follows legal norms but only partially follow social norms such as good will and concern for others. 
Make use of other sources of water  Data storage continues. 

Potential for reputation to increase. 

Potential increase in cost of water resulting in less profit potentially less tax revenue/employment. 

Farmers have water and biodiversity may improve.

Alternative water sources may be associated with the same issues or worse. 

 Intention behind action seems consistent with that expected by an engineer. However, this is dependent upon 

whether they chose to source sustainable water with less impact on biodiversity etc. 

 This may be dependent on the degree to which DSS proactively source sustainable water. 
Reduce work levels or shut down  Impact on profit and thus tax revenue/employment and supply chain. Farmers have water and biodiversity may improve. 

May cause operational issues for those whose data is stored. 

 Seems consistent with those expected of engineer. Raises questions more generally about viability and feasibility of data storage.  Action doesn’t follow social norms of responsibility to employees and shareholders. 
Investigate other cooling methods which don’t require as much water/don’t take on extra work until another method identified. 
 May benefit whole sector. 

May cause interim loss of service. 

 

 This follows expectations of the engineering profession in terms of evidence-based decision making and consideration for impact of engineering in society.  It follows social norms in terms of responsible decision making. 

 

Downloads:

Assessing ethics: Guidance

Assessing ethics: Rubric

Assessing ethics: Case study assessment example: Water Wars

 

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

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: Dr. Natalie Wint (UCL); Dr. William Bennett (Swansea University).

Keywords: Assessment; Accreditation, AHEP, Competencies; Curriculum design; Pedagogy.

Who is this article for?: This article should be read by educators at all levels in higher education who wish to integrate ethics into the engineering and design curriculum or module design.

Related content:

 

Guidance

Premise:

As engineering educators, it is uncommon that we were taught or assessed on ethical thinking within our own degree programmes. Although we may be able to think of plenty of ethical scenarios from our own experience, we may not necessarily be able to identify the best way to assess the ability of a student to engage in ethical thinking in a systematic and robust manner, something which is critical for both the evaluation of learning and teaching (as explained further here).

Furthermore, the complex, ill-structured nature of ethical dilemmas, which often involve a variety of diverse stakeholders, perspectives and cultural norms, necessitates an ability to navigate tensions and compromise. This results in situations in which multiple possible courses of action can be identified, meaning that there is not one single ‘good’ or ‘correct’ answer to ethical questions posed.

It is also necessary to evidence that students are able to meet the criteria outlined by accreditation bodies. Within the UK context, it is the Engineering Council (EC) that is responsible for providing the principal framework which guides engineering course content and sets accreditation threshold standards of competence through AHEP, the Accreditation of Higher Education Programs, as part of The UK Standard for Professional Engineering Competence (UKSPEC).

The knowledge, skills and attributes expected of engineering graduates constantly shifts, and since the advent of AHEP in 2004 there has been increased focus on strengthening design, and consideration for economic, ethical, environmental, legal, and social factors.

In-keeping with a need to assess engineering ethics in a robust manner, this article provides step-by-step considerations for designing assessment and is primarily intended to be used in conjunction with an existing ethics case study, such as those available through the EPC’s Engineering Ethics Toolkit (we later make use of the existing ‘Water Wars’ case study to exemplify the points made).

The guidance and accompanying rubric have been designed in a way that encourages students to grapple with the numerous tensions involved in ethical decision making, and the focus is thus on assessment of the decision-making process as opposed to the ‘answer’ given, the decision made or the outcome of the scenario.

 

Assessment purpose:

The first consideration is the year group you are assessing, and the competencies they have already acquired (for example in the case of Level 5 and Level 6 students). You may want to consider the (partial) learning outcome (LO) as defined by AHEP4 LO8 (Table 1). Whilst this shouldn’t act to limit what you choose to assess, it is a good place to start in terms of the level of ability your students should be demonstrating.

Note that the Engineering Council (EC) claim “This fourth edition of AHEP has reduced the total number of learning outcomes in order to focus attention on core areas, eliminate duplication and demonstrate progression between academic levels of study”. They are thus interested in the differences between level. You are recommended to make this explicit in module specification and associated assessment description. Key differentiations are shown in Table 1. For example, at Level 5 you may be more interested in students’ abilities to identify an ethical situation, whereas at Level 6 you may want them to be able to reason through options or make a judgement.

Table 1: AHEP4 Learning Outcomes

Year 1
(Level 4)		 Year 2
(Level 5)		 Year 3
(Level 6)		 M Level
(Level 7)
LO8 Apply ethical principles and recognise the need for engineers to exercise their responsibilities in an ethical manner and in line with professional codes of conduct. Identify ethical concerns and make reasoned ethical choices informed by professional codes of conduct. Identify and analyse ethical concerns and make reasoned ethical choices informed by professional codes of conduct. Identify and analyse ethical concerns and make reasoned ethical choices informed by professional codes of conduct (MEng).
Interpretation Awareness of issues, obligations, and responsibilities; sensitising students to ethical issues. Ability to resolve practical problems; identify ethical issues and to examine opposing arguments. Ability to resolve practical problems; identify ethical issues and examine and evaluate/critique opposing arguments. Ability to resolve practical problems; identify ethical issues and examine and evaluate/critique opposing arguments.

 

The final row in Table 1 provides our interpretation of the LO, making use of language similar to that within the EPC’s Ethics Learning Landscape. We believe this is more accessible and more easily operationalised.

The following steps outline the process involved in designing your assessment. Throughout we make reference to an existing EPC case study (Water Wars) to exemplify the points made.

1.) The first consideration is how much time you have and how much of the case study you want to use. Many of the case studies have multiple stages and could be spread over several sessions depending on time constraints.

2.) Linked to this is deciding whether you want to assess any other LOs within the assessment. For example, many of the case studies have technical elements. Furthermore, when using reports, presentations, or debates as methods of assessment you may also want to assess communication skills. Whatever you decide you should be careful to design the assessment in such a way that assesses LO8 in a robust manner, whereby the student could not pass the element without demonstrating they have met the individual LO to the required level (this is a key requirement to meet AHEP4). For example, in an assessment piece where ethics is worth 50% of the grade, a student could still pass the element as a whole (with 40%) by achieving high scores in the other grading criteria without the need to demonstrate their ability to meet LO8.

3.) Once you are aware how much of a case study you have time for and have decided which LOs (other than LO8) you are assessing, you should start to determine which questions are aligned with the level of study you are considering and/or the ability of the students (for example you may query whether students at Level 5 have already developed the skills and competencies suggested for Level 4). At each level you can make use of the accompanying rubric to help you consider how the relevant attributes might be demonstrated by students. As an example, please refer to the accompanying document where we provide our thoughts about how we would assess Water Wars at Levels 4-6.

4.) Once you have selected questions you could look to add any complementary activities or tasks (that do not necessarily have to be assessed) to help the students broaden their understanding of the problem and ability to think through their response. For example, in the Water Wars case study, there are multiple activities (for example Part 1, Q3 and Part 2, Q3, Q4, Q6, Q7) aimed at helping students understand different perspectives which may help them to answer further ethical questions. There are also technical questions (for example Part 1, Q5) which help students understand the integrated nature of technical and social aspects and contextualise scenarios.

5.) Once you have selected your questions you will need to make a marking rubric which includes details of the weightings given for each component of the assessment. (This is where you will need to be careful in selecting whether other LOs are assessed e.g., communication, and whether a student can pass the assessment/module without hitting LO8). You can then make use of the guidance provided in terms of expectations at a threshold and advanced level, to write criteria for what is expected at each grade demarcation.

Although we have focused on ‘Water Wars’ here, the suggested assessment questions within the accompanying rubric have been designed in such a way that they can be used in conjunction with the case studies available within the toolkit, or with another case study that has been created (by yourself or elsewhere) to outline an ethical dilemma.

 

Other considerations:

As acknowledged elsewhere within the toolkit (see here), there are “practical limits on assessment” (Davis and Feinerman, 2012) of ethics, including demands on time, pressure from other instructors or administrators, and difficulty in connecting assessment of ethics with assessment of technical content. These are some other considerations you may wish to make when planning assessment.

• Number of students and/or marking burden: With large student numbers you may be more inclined to choose a group assessment method (which may also be beneficial in allowing students to share perspectives and engage in debate), or a format which is relatively quick to mark/allows automated marking (e.g. a quiz). In the case of group work it is important to find a way in which to ensure that all students within each group meet the LO in a robust manner. Whilst assessment formats such as quizzes may be useful for assessing basic knowledge, they are limited in their ability to ensure that students have developed the higher-level competencies needed to meet the LO at output level.

• Academic integrity: As with any LO there is a need to ensure academic integrity. This may be particularly difficult for large cohorts and group work. You may wish to have a range of case studies or ensure assessment takes place in a controlled environment (e.g. an essay/report under exam conditions). This is particularly important at output level where you may wish to provide individual assessment under exam conditions (although competencies may be developed in groups in class).

• Logistics/resourcing: Many of the competencies associated with ethics are heavily linked to communication and argumentation, and answers tend to be highly individual in nature. Role play, debates, and presentations may therefore be considered the most suitable method of assessment. However, their use is often limited by staffing, room, and time constraints. Many of these methods could, instead, be used within class time to help students develop competencies prior to formal assessment. You may also choose to assess ethics in another assessment which is more heavily resourced (for example design projects or third year projects).

• Staged assessment: The ethical reasoning process benefits from different perspectives. It may therefore be desirable to stage assessment in such a way that individuals form their own answer (e.g. a moral problem statement), before sharing within a group. In this way a group problem statement, which benefits from multiple perspectives and considerations, can be formed. Similarly, individuals may take the role of an individual stakeholder in an ethical dilemma before coming together as a group.

• Use of exams: Whilst we see an increasing movement away from exams, we feel that a (closed book) exam is a suitable method of assessment of ethics based LOs in the situation that:

o There is a need to ensure academic integrity, and that each student meets the LO at output level.

o The exam is assessing competencies (e.g. ethical argumentation) as opposed to knowledge.

o All the relevant information needed is provided and there is limited content for students to learn in advance (aside from argumentation, justification, decision making skills etc developed in class).

Their use may therefore be limited to Level 6.

 

Rubric

This document provides the partial AHEPLO8 at each level. The competences involved in meeting this LO have then been identified, along with what students would need to demonstrate to evidence meeting a threshold level, or advanced level. Example questions are given to show how students may demonstrate their competence at each level. For each question there is an explanation of how the question supports achievement of LO at that level. The rubrics should be used alongside the accompanying guidance document which offers practical suggestions and advice.

Year 1: This year focuses on developing awareness of issues, obligations, and responsibilities, and sensitising students to ethical issues.

Year 2: This year focuses on developing the ability to identify ethical issues and to examine opposing arguments, all of which is needed to examine, analyse, and evaluate ethical dilemmas in Year 3.

Year 3: This year focuses on ensuring that students can satisfy LO8 at an output level in a robust manner.

 

References:

Davis, M. and A. Feinerman. (2012). ‘Assessing graduate student progress in engineering ethics’, Science and Engineering Ethics, 18(2), pp. 351-367.

 

Downloads:

Assessing ethics: Guidance

Assessing ethics: Rubric

Assessing ethics: Case study assessment example: Water Wars

 

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

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.

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