Toolkit: Complex Systems Toolkit.

Author: Onyekachi Nwafor (KatexPower).

Topic: Complex systems modelling in renewable energy transition.

Title: Island energy transition.

Resource type: Teaching – Case study.

Relevant disciplines: Electrical engineering; Systems engineering; Environmental engineering; Computer science; Energy.

Keywords: Available soon.

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.

 

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, Configuration Management, Requirements Definition, Communication, Verification, and Validation 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:  Advanced.

 

Learning and teaching notes:

Overview: 

This multi-part case study guides students through the complex systems challenges of Prince Edward Island, Canada’s ambitious 100% renewable energy transition by 2030. Students will experience how technical, social, and economic factors interact through emergence, feedback loops, and multi-scale dynamics that traditional engineering analysis alone cannot capture. 

Learners have the opportunity to: 

Teachers have the opportunity to: 

 

Learning and teaching resources:

 

Overview: Energy transition as a complex systems challenge:

Prince Edward Island (PEI), Canada’s smallest province, aims to achieve 100% renewable electricity by 2030. Its small grid, dependence on imported power, and growing renewable infrastructure make it a natural laboratory for systems thinking in energy transitions. 

This case invites students to explore how technical, social, and policy decisions interact to shape renewable integration outcomes. Using complexity-science tools, they will uncover how local actions produce emergent system behaviour, and why traditional linear models often fail to predict real-world dynamics. 

 

The complex challenge:
Traditional engineering approaches often treat energy systems as predictable and linear, optimising components like generation, transmission, or storage in isolation. However, energy transitions are complex socio-technical systems, characterised by feedback loops, interdependencies, and emergent behaviours. 

In PEI’s case, replacing stable baseload imports with variable wind and solar generation creates cascading effects on grid stability, pricing, storage demand, and social acceptance. The island’s bounded geography magnifies these interactions, making it an ideal context to observe emergence and system-level behaviour arising from local interactions. 

PEI’s energy system presents a fascinating case study of complex systems, where interactions between wind generation, energy storage, demand patterns, and grid infrastructure create emergent behaviours that cannot be predicted from individual components alone. Currently, PEI generates approximately 25% of its electricity from on-island wind farms, with the remainder imported via submarine cables from New Brunswick.  

 

Part one: Understanding system complexity 

The integration paradox:

PEI currently imports about 75% of its electricity via two 180 MW submarine cables, while 25% is produced locally through onshore wind farms (204 MW). Plans for offshore wind, community solar, and hydrogen projects have triggered debates around stability, affordability, and social acceptance. 

Taking on the role of an engineer at TechnoGrid Consulting, students are tasked to advise Maritime Electric, the island’s utility, on modelling strategies to guide $2.5 billion in renewable investments. 

Competing goals:

Discussion prompt: 

In systems terms, where do you see tensions between policy, technology, and society? How might feedback loops amplify or mitigate these tensions? 

 

Part two: Mapping system complexity – What counts as ‘the system’?:

While Maritime Electric’s engineering team insists the project scope should stay strictly technical, limited to grid hardware, generation, and storage, policy advisors argue that social behaviour, market pricing, and community engagement are part of the system’s real dynamics.

Expanding boundaries makes the model richer but harder to manage; narrowing them simplifies computation but risks missing the very factors that determine success. 

Activity 1: Boundary definition: 

Map the PEI energy system by identifying: 

Discuss how including or excluding elements (e.g., electric-vehicle uptake, community cooperatives, carbon policy) changes the model’s focus and meaning. 

Learning insight: 

Complex systems cannot be fully understood in isolation; boundaries are analytical choices that shape both perception and leverage. Every inclusion or exclusion reflects an assumption about what matters and that assumption determines which complexities emerge, and which stay hidden. 

 

Part three: Modelling the system: Multiple lenses of complexity:

(a) Agent-Based Modelling (ABM) with NetLogo: 

Students construct simplified models of households, businesses, and grid operators: 

Emergent patterns such as adoption S-curves or network clustering illustrate how simple local rules generate complex collective dynamics. 

(b) System Dynamics (SD) with Vensim: 

Students then develop causal loop diagrams capturing key feedbacks: 

This provides a macroscopic view of feedback, delay, and leverage points. 

(c) Network Analysis with Python (NetworkX):

Students model actor interdependencies: how households, utilities, industries, and regulators interact. Network metrics (centrality, clustering, connectivity) reveal where resilience or vulnerability is concentrated. 

Reflection prompt: 

Which modelling approach offered the most insight into system-level behaviour? What were the trade-offs in complexity and interpretability? 

 

Part four: Scenario exploration: Pathways to 2030:

Students explore three transition scenarios, each with distinct emergent behaviours: 

A. Distributed Solar + Community Storage  300 MW solar, 150 MWh batteries  Decentralised coordination challenges and social clustering effects. 
B. Offshore Wind + Grid Enhancement  400 MW offshore wind, new 300 MW interconnection  Weather-dependent reliability and cross-border dependency. 
C. Hybrid + Hydrogen Production  200 MW offshore wind, 100 MW solar, 50 MW electrolysis  Multi-sector coupling and feedback between hydrogen and electricity markets 

 

Activity 2: Comparative Scenario Analysis 

Run simplified models for each pathway. Track how feedback loops evolve over time and identify points of instability or resilience. 

Inquiry questions: 

 

Part five. Dealing with uncertainty: 

Complex systems resist deterministic prediction. Instead, students use Monte Carlo simulations or sensitivity tests to explore uncertainty. 

Activity 3: Communicating uncertainty:

Students prepare short policy memos to government or utility executives: 

Learning outcome: 

Effective system modelers communicate uncertainty transparently and use it to support adaptive decision-making. 

 

References: 

Modelling Software and Tutorials:

 

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: 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: Available soon.

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.  

Background

Complex intelligent systems, systems thinking competency, and understanding complexity are all critical to engineering in the 21st century, and when integrated holistically, complex systems in engineering teaching can align with other initiatives that promote responsible engineering. Learning approaches for integrating complex systems knowledge, skills, and mindsets in engineering supports educators in their own professional development, since many may have not learned about this topic that they are now expected to teach. Accreditation frameworks increasingly refer to complex problems and systems thinking in outcomes for engineering programmes, and yet very few resources exist that support engineering educators to integrate these into their teaching in a comprehensive and effective way or indeed to upskill educators to be able to deliver this teaching.

To address this gap, a Complex Systems Toolkit is being developed by the Engineering Professors’ Council with support from Quanser. Its development is guided by a Working Group comprised of academic, industry, and professional organisation experts.

 

Register your interest

Please register your interest in developing a resource by completing this form by 30th June 2025.

If you have already registered an interest and we are expecting your submission, the deadline to submit first drafts is 15th August. Submit your Complex Systems Toolkit Contribution here. Co-authors should complete this form.

If you would like to become a reviewer for the toolkit, please complete this form.

If you would like to suggest links to pages or online resources that we can add to our database of engineering education resources for complex systems teaching, please email Wendy Attwell: w.attwell@epc.ac.uk

 

The Complex Systems Toolkit Working Group seeks contributors to develop resources for inclusion in the toolkit

These resources will fit into three categories:

Read more about the specific content we are looking for (click on the arrows to expand the sections):

Submit a knowledge article

Submit a knowledge article

The Complex Systems Toolkit Working Group seeks contributors to write knowledge articles on the following subjects:

  1. Why teach / learn about Complex Systems?

This should include reference to:

    • The increasing ubiquity of complex systems
    • The need to understand complexity as a concept
    • The need for systems thinking competency among engineers
    • How complex systems are related to all engineering disciplines
  1. Why integrate Complex Systems into Engineering Education?

This should include reference to:

    • Why engineered systems require certain properties (e.g. resilience)
    • The consequences of system failures
    • Knock-on effects beyond engineering
    • Interaction with other systems (e.g. human and natural)
  1. What are Complex Systems?

This should provide a real-world explanation and include:

    • Examples of engineered systems / Engineering Complexity
    • Examples of socio-technical systems and the wider context

These articles should also connect the why (why must teaching about complex systems be present in engineering education?) to the how (how can this be done efficiently and effectively?). Through these tools, we aim to help upskill UK engineering educators so that they feel capable of and confident in integrating complex systems into their engineering teaching.

The deadline for submitting a knowledge article is 15th August 2025.

 

Step 1: Read the guidance for submitting a knowledge article

Guidance #1: Research Guidance #2: OverviewGuidance #3: PurposeGuidance #4: ContentGuidance #5: References and resourcesGuidance #6: Format

Research:

Knowledge articles are resources that users can access to improve their knowledge or find more information. These are intended to provide theoretical and practical background on complex systems concepts and tools such as modelling or decision-making approaches. While guidance articles focus on “how”, knowledge articles focus on “what”.

Before you begin, you should review knowledge articles that form a part of the EPC’s Sustainability Toolkit, since we hope that contributions to the Complex Systems Toolkit will be fairly consistent in length, style, and tone.

Knowledge articles are meant to be overviews that a reader with no prior knowledge of complex systems could refer to in order to develop a baseline understanding and learn where to look for additional information (they can reference other sources). They should be understandable to students as well: imagine that an educator might excerpt content from the article to provide their students context on a project or learning activity.

They should be approximately 500-1000 words (although they can be more in depth if necessary) and reference relevant online open-source resources.

Overview:

The articles are meant to be able to stand on their own as a piece of knowledge on a topic; they are also meant to work alongside other articles so that taken together they form a sort of complex systems in engineering handbook.

Purpose:

Each article should inform, explain, and provide knowledge on the topics. Put yourself in the perspective of an engineering educator who is new to complex systems.

Content:

The content of the article should be organised and well developed. That is, it should be presented in a logical way and thoroughly explained.

References and resources:

Where additional explanation could be given, it might point to other resources, and where information is presented from another source, it needs to be properly referenced using Harvard referencing.

Format

Knowledge articles should follow this format:

  • Premise;
  • Body of article, divided up into headed sections as necessary;
  • Conclusion (optional);
  • References: use Harvard referencing;
  • Resources (online and open source).

Step 2: Before you submit, review this checklist

  • Does the article both make sense as a single piece of content as well as fit in with the rest of the articles to be developed?
  • Would someone new to complex systems understand the information presented and would it help them?
  • Do you need to expand on any ideas or reorganise them to make them clearer?
  • What additional resources or references have you included?
  • Are open resources or links to other toolkit materials included?
  • Are sources cited using Harvard referencing?
  • Before you submit your contribution, have you registered as a contributor? If not, please register your interest here.

 

Step 3: Submitting your knowledge article

The deadline for submitting a knowledge article is 15th August 2025.

Knowledge articles should be submitted in Word file format (.doc or .docx). Any corresponding images should be submitted in either .jpeg, .jpg or .png format.

To ensure that everyone can use and adapt the Toolkit resources in a way that best fits their teaching or purpose, this work will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Under this licence users are free to share and adapt this material, under terms that they must give appropriate credit and attribution to the original material and indicate if any changes are made.

You may download a PDF version of the guidelines (as outlined in Step 1) here – UPDATED JULY 2025.

Submit your knowledge article here.

 

 

Submit a guidance article

Submit a guidance article

The Complex Systems Toolkit Working Group seeks contributors to write guidance articles on the following subjects:

1. Guide to Explaining Complex Systems to students

This guidance should mirror the tone and style of resources from the Ethics and Sustainability Toolkits which provide a “how to” approach.

2. How Complex Systems relate to AHEP 4.

This should include guidance in understanding language in AHEP 4 around “complex problems” and their connection to Complex Systems.

3. How to scaffold Complex Systems learning outcomes across a curriculum

This should include good practice and examples of learning outcomes or objectives integrated in engineering curricula at different levels, either in general or in a particular engineering degree.

4. How do we assess for skills / competencies in Complex Systems?

This resource could mirror the tone and style of resources from the Ethics and Sustainability Toolkits, and could contain:

These articles should also connect the why (why must teaching about complex systems teaching be present in engineering education?) to the how (how can this be done efficiently and effectively?). Through these tools, we aim to help upskill UK engineering educators so that they feel capable of and confident in integrating complex systems into their engineering teaching.

The deadline for submitting a guidance article is 15th August 2025.

 

Step 1: Read the guidance for submitting a guidance article

Guidance #1: Research Guidance #2: Overview Guidance #3: Purpose Guidance #4: ContentGuidance #5: References and resourcesGuidance #6: Format

Research:

Guidance articles are resources that users can access to learn how to do something. These are intended to provide practical advice on subjects such as how to explain complex systems to students, or how to assess for skills and competencies in complex systems. While knowledge articles focus on “what”, guidance articles should focus on “how.”

Before you begin, you should review guidance articles that form a part of the EPC’s Sustainability Toolkit, since we hope that contributions to the Complex Systems Toolkit will be fairly consistent in length, style, and tone.

Guidance articles aim to help situate our teaching resources in an educational context and to signpost to additional research and resources on complex systems theory and tools.

They should be approximately 500-1000 words (although they can be more in depth if necessary) and reference relevant online open-source resources.

Overview:

The articles are meant to be able to stand on their own as a piece of guidance on a topic; they are also meant to work alongside other articles so that taken together they form a sort of complex systems in engineering handbook.

Purpose:

Each article should inform, explain, and provide knowledge on the topics. Put yourself in the perspective of an engineering educator who is new to complex systems.

Content:

The content of the article should be organised and well developed. That is, it should be presented in a logical way and thoroughly explained.

References and resources:

Where additional explanation could be given, it might point to other resources, and where information is presented from another source, it needs to be properly referenced using Harvard referencing.

Format

Guidance articles should follow this format:

  • Premise;
  • Body of article, divided up into headed sections as necessary;
  • Conclusion (optional);
  • References: use Harvard referencing;
  • Resources (online and open source).

Step 2: Before you submit, review this checklist

  • Does the article both make sense as a single piece of content as well as fit in with the rest of the articles to be developed?
  • Would someone new to complex systems understand the information presented and would it help them?
  • Is the explanation clear, logically structured and technically accurate?
  • Do you need to expand on any ideas or reorganise them to make them clearer?
  • Are sources cited using Harvard referencing?
  • Are open resources or links to other toolkit materials included?
  • What additional resources or references have you included?
  • Before you submit your contribution, have you registered as a contributor? If not, please register your interest here.

 

Step 3: Submitting your guidance article

The deadline for submitting a guidance article is 15th August 2025.

Guidance articles should be submitted in Word file format (.doc or .docx). Any corresponding images should be submitted in either .jpeg, .jpg or .png format.

To ensure that everyone can use and adapt the Toolkit resources in a way that best fits their teaching or purpose, this work will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Under this licence users are free to share and adapt this material, under terms that they must give appropriate credit and attribution to the original material and indicate if any changes are made.

You may download a PDF version of the guidelines (as outlined in Step 1) here – UPDATED JULY 2025.

Submit your guidance article here.

 

Submit a teaching activity

 

Submit a teaching activity/resource

The Complex Systems Toolkit Working Group seeks contributors to create teaching activities based on the following briefs:

1. Case Studies that, through a real-world situation, illustrate different types of complex systems, use cases for the tools that can be used to model / simulate these, techniques that promote development and use of systems architecture, and effects such as trade-offs, emergent properties, impacts, or unintended consequences. Case studies could also reference the implications for risk, security, ethics, sustainability, teamwork, and communication.

Case study topics could include:

    • Air traffic control
    • Smart agriculture
    • Autonomous driving
    • Robotics
    • Smart cities

2. Demonstrator simulations that provide examples of how systems can be modelled.

This could include:

    • Examples of simple, complicated, and complex systems
    • Interactive examples showing how well-intentioned action can lead to failure
    • Interactive examples showing the best approaches to handling complexity

3. Lesson plans, coursework and teaching activities that are useful in integrating learning around complexity, systems thinking, and complex systems.

These resources should promote active learning pedagogies and real-world teaching methods by showing how complex systems teaching can be embedded within technical problems and engineering practice. Through these resources, we aim to help upskill UK engineering educators so that they feel capable of and confident in integrating complex systems into their engineering teaching.

The deadline for submitting a teaching activity is 15th August 2025.

 

Step 1a: Read the guidance for submitting a case study

Guidance #1: Research Guidance #2: Overview Guidance #3: Authenticity Guidance #4: Complexity of issue Guidance #5: Activities and resourcesGuidance #6: Educational level & AssessmentGuidance #7: Format

Research

Teaching activities are resources that users can access to help them know what to integrate and implement. These include use cases/case studies which provide examples of complex systems which can be directly utilised in teaching with the suggested tools, as well as other classroom activities such as coursework, project briefs, lesson plans, demonstration simulations, or other exercises.

Before you begin, you should review case studies that form a part of the EPC’s Sustainability Toolkit or Ethics Toolkit, since we hope that contributions to the Complex Systems Toolkit will be fairly consistent in length, style, and tone. While complex systems cases may not have the same learning outcomes, the format and approach should be similar. Remember that the audience for these case studies is educators seeking to embed complex systems concepts within their engineering teaching.

Case studies present real-world scenarios that can be used in teaching about complex systems in engineering. They provide students with opportunities to explore complex systems tools, and trade-offs, in authentic contexts, and reflect on decisions made about them.

They are usually based on a real example, although fictionalised cases are acceptable when they are grounded in realistic detail. Case studies should enable students to identify or interpret key features of complex systems (feedback loops, interdependence or emergent behaviour) and apply relevant tools or frameworks to make sense of the situation.

Case studies will vary in length depending on scope and resource, but many are around 1500-2000 words. They should reference relevant online open-source resources.

Please see the current research on good practice in writing case studies, which you may find helpful as you write, as well as our article about a recipe for writing a case study. This ‘recipe’ can guide you as you write to include or develop other aspects of the case. Both articles are from our Engineering Ethics Toolkit, but the guidance given can be adapted for complex systems cases.

Overview

The case study should be presented as a narrative about a complex systems issue in engineering.

Narrative strength: the case should be clearly structured with a compelling and coherent story. System complexity: it should explore interdependencies, multiple stakeholders and/or competing goals. Tool integration: systems tools should be mentioned or incorporated (e.g. soft systems methodology, SysML, Agent-based modelling etc).  Activities and Resources: there should be questions, prompts or teaching activities to guide discussion or classroom use.

Authenticity

Case studies are most effective when they feel like they are realistic, with characters that you can identify or empathise with, and with situations that do not feel fake or staged. Giving characters names and backgrounds, including emotional responses, and referencing real-life experiences help to increase authenticity.

Complexity of issue

Many cases are either overly complicated so that they become overwhelming, or so straightforward that they can be “solved” quickly. A good strategy is to try to develop multiple dimensions of a case, but not too many that it becomes unwieldy. Additionally, complexity can be added through different parts of the case so that instructors can choose a simpler or more complicated version depending on what they need in their educational context.

Activities and resources

You should provide a variety of suggestions for discussion points and activities to engage learners, as well as a list of reliable, authoritative open-source online resources, to both help educators prepare and to enhance students’ learning. Where information is presented from another source, it needs to be properly referenced using Harvard referencing.

Educational level and Assessment

Educational level: When writing your case study, you should consider which level it is aimed at. A Beginner-level case is aimed at learners who have not had much experience in engaging with a complex problem, and usually focuses on only one or two dimensions of a challenge. An Advanced-level case is aimed at learners who have had previous practice in engaging with complex systems, and often addresses multiple challenges. An Intermediate case is somewhere in between.

Assessment: If possible, suggest assessment opportunities for activities within the case, such as marking rubrics or example answers. 

Format

The case study should follow the following format:

  • Teaching notes (with learning objectives, time needed, materials): This is an overview of the case and its dilemma, and how it relates to AHEP4 and INCOSE competencies.
  • Learning and teaching resources: A list of reliable, authoritative, open-source online resources that relate to the case and its dilemma. These can be from a variety of sources, such as academic institutions, journals, news websites, business, and so on. We suggest a minimum of five sources that help to provide context to the case and its dilemmas. You may want to suggest an author flag up certain resources as suggested pre-reading for certain parts of the case, if you feel that this will enrich the learning experience.
  • Summary of system or context.
  • Narrative of the case (presenting the complexity).
  • Questions and activities. This is where you provide suggestions for discussions and activities related to the case and the dilemma.
  • Further discussion or challenge (optional). Some case studies are sufficiently complex at one dilemma, but if the case requires it you can provide further parts (up to a maximum of three).
  • References: use Harvard referencing.
  • Resources (ideally online and open source).
  • If possible, suggest assessment opportunities for activities within the case, such as marking rubrics or example answers.
  • Keywords: On the submission form you will be prompted to provide keywords, including educational aims, issues and situations highlighted in the case. 

Step 2a: Before you submit, review this checklist:

  • Does it follow the correct format?
  • Narrative strength: is the case clearly structured with a compelling and coherent story?
  • System complexity: does it explore interdependencies, multiple stakeholders and/or competing goals?
  • Tool integration: are systems tools mentioned or incorporated (e.g. soft systems methodology, SysML, Agent-based modelling etc)
  • Activities and Resources: Are there questions, prompts or teaching activities to guide discussion or classroom use?
  • Are open resources or links to other toolkit materials included?
  • Are sources cited using Harvard referencing?
  • What additional references have you included?
  • Before you submit your contribution, have you registered as a contributor? If not, please register your interest here.

 

Step 1b: Read the guidance for submitting a different teaching activity

Guidance #1: Purpose & outcomesGuidance #2: Research Guidance #3: Purpose Guidance #4: Presentation & clarityGuidance #5: Resources & guidanceGuidance #6: Format

Purpose & outcomes

Teaching Tools are intended to support educators’ ability to apply and embed complex systems concepts within their engineering teaching.

Educators need to quickly and easily find help with:

    • Adapting and integrating existing complex systems resources to their disciplinary context;
    • Implementing new and different pedagogies that support complex systems learning.
    • Structuring lessons, modules, and programmes so that complex systems skills and outcomes are central themes.

Thus, these teaching tools will provide crucial guidance for those who may be teaching complex systems-related material for the first time, or who are looking for new and different ways to integrate complex systems concepts into their teaching.

They may take the form of learning activities, project briefs, modelling or simulation activities, technical content related to complex systems, worksheets, slides, or other similar teaching materials.

Before you begin to write, you should familiarise yourself with content that has been created to complement case studies in our Ethics Toolkit and teaching tools in our Sustainability Toolkit since we want these resources to be produced in a similar style and format.

Research

Purpose

Imagine that you are an engineering educator who is new to teaching complex systems concepts. You turn to this teaching tool to help you apply and embed these in your module.

    • Does this resource help introduce or develop concepts related to complex systems or systems thinking so that learners can engage with these topics in the context of engineering?
    • If not, what is needed to make this possible?

Presentation and Clarity

Depending on the resource, you may choose to provide worksheets, slides, problem sets, or narrative prompts.

    • Is the resource explained in such a way that someone new to teaching complex systems could understand how to use it?
    • Is the material clearly introduced and described?

Resources and Guidance

Depending on the topic, educators may need additional resources or guidance to support their use of the material. For instance, background information may be required or a technical topic explained.

    • Have you provided sufficient material so that educators can easily employ the resource?
    • Do references use Harvard referencing?

Format

The teaching tool should follow this format:

  • Overview
    • Short description of what the resource is and what it aims to do.
    • States how it is related to complex systems or systems thinking, referring to external content such as INCOSE Competencies and AHEP 4.
    • Provides an overview of the activity, suggesting how it might be implemented and in what contexts, how long it might take, and any other relevant delivery information.
  • Details any specific materials or software required for the activity, as well as any modelling or simulation tools to be used.
  • Lists any learning and teaching resources recommended in order to undertake the activity, including suggested pre-reading or other references.
  • Explains the activity in as much detail as is required (this will vary depending on the type of material the resource addresses.)
  • If relevant, provides assessment guidance–marking rubrics, sample answers, etc.

 

Step 2b: Before you submit, review this checklist:

  • Does this resource help introduce or develop concepts related to complex systems or systems thinking so that learners can engage with these topics in the context of engineering?
  • Is the resource explained in such a way that someone new to teaching complex systems could understand how to use it?
  • Is the material clearly introduced and described?
  • Have you provided sufficient material so that educators can easily employ the resource?
  • Do references use Harvard referencing?
  • Does it follow the correct format?

Step 3: Submitting your teaching activity

The deadline for submitting a teaching activity is 15th August 2025.

To ensure that everyone can use and adapt the Toolkit resources in a way that best fits their teaching or purpose, this work will be licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Under this licence users are free to share and adapt this material, under terms that they must give appropriate credit and attribution to the original material and indicate if any changes are made.

Teaching activities should be submitted in Word file format (.doc or .docx). Any corresponding images should be submitted in either .jpeg, .jpg or .png format.

You may download a PDF version of the guidelines (as outlined in Step 1) here – UPDATED JULY 2025.

Submit your teaching activity here.

 

 

Deadlines

Please register your interest in developing a resource by completing this form by 30th June.

If you have already registered an interest and we are expecting your submission, the deadline to submit first drafts is 15th August.

Submit your Complex Systems Toolkit Contribution here. Co-authors should complete this form.

If you wish to develop materials to contribute beyond this, we will be opening the next cycle in spring 2026.

If you would like to become a reviewer for the toolkit (initially between July and October 2025), please complete this form.

If you would like to suggest links to pages or online resources that we can add to our database of engineering education resources for complex systems teaching, please email Wendy Attwell: w.attwell@epc.ac.uk

 

Additional information

In undertaking this work, contributors will become part of the growing community of educators who are helping to ensure that tomorrow’s engineering professionals have the complex systems skills, knowledge, and attributes that they need to provide a better future for us all. Contributors will be fully credited for their work on any relevant Toolkit materials, and will be acknowledged as authors should the resources be published in any form. Developing these resources will provide the chance to work with a dynamic, diverse and passionate group of people leading the way in expanding engineering teaching resources, and may help in professional development, such as preparing for promotion or fellowship. If contributors are not compensated by their employers for time spent on this type of activity, a small honorarium may be available to encourage participation.

As part of the toolkit project, we are also developing tools for collaborating with our Working Group in-house. Stay tuned for further details.

 

Learn more about the Complex Systems Toolkit

Those interested in contributing to the Complex Systems Toolkit should fill out this form and we will be in touch.

Hear from our Working Group Co-Chairs on why you should get involved.

Learn more about the Complex Systems Toolkit, here.

Learn more about the members of the Complex Systems Toolkit Working Group, here.

 

 

This post is also available here.

Author: Onyekachi Nwafor (CEO, KatexPower). 

Topic: Waste management. 

Tool type: Teaching. 

Relevant disciplines: Environmental; Civil; Systems engineering. 

Keywords: Sustainability; Environmental justice; Water and sanitation; Community engagement; Urban planning; Waste management; Nigeria; Sweden; AHEP; Higher education. 

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

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 6 (Clean Water and Sanitation); SDG 11 (Sustainable Cities and Communities); SDG 13 (Climate Action).  

Reimagined Degree Map Intervention: More real-world complexity; Active pedagogies and mindset development; Cross-disciplinarity.

Educational level: Beginner. 

 

Learning and teaching notes: 

This case study juxtaposes the waste management strategies of two cities: Stockholm, Sweden, renowned for its advanced recycling and waste-to-energy initiatives, and Lagos, Nigeria, a megacity grappling with rapid urbanisation and growing waste challenges. The contrast and comparison aim to illuminate the diverse complexities, unique solutions, and ethical considerations underlying their respective journeys towards sustainable waste management. 

This case is presented in parts. If desired, a teacher can use Part one in isolation, but Parts two and three develop and complicate the concepts presented in Part one to provide for additional learning. The case study allows teachers the option to stop at multiple points for questions and/or activities, as desired.   

 

Learners have the opportunity to: 

Teachers have the opportunity to: 

 

Learning and teaching resources: 

Websites: 

Government publications: 

Journal articles: 

 

Part one: 

You are a renowned environmental engineer and urban planner, specialising in sustainable waste management systems. The Commissioner of Environment for Lagos invites you to analyse the city’s waste challenges and develop a comprehensive, adaptable roadmap towards a sustainable waste management future. Your mandate involves: 

 

Optional STOP for questions and activities: 

 

Part two: 

As you delve deeper, you recognise the multifaceted challenges Lagos faces. While Stockholm boasts advanced technologies and high recycling rates, its solutions may not directly translate to Lagos’s context. Limited infrastructure, informal waste sectors, and diverse cultural practices must be carefully considered. Your role evolves from simply analysing technicalities and policies to devising a holistic strategy. This strategy must not only champion environmental sustainability but also champion social equity, respecting the unique socio-economic and cultural nuances of each urban setting. You must design a system that: 

 

Optional STOP for questions and activities: 

 

Adaptability for diverse contexts: 

 

Discussion prompts: 

 

Part three: 

While implementing your strategy, you encounter enthusiasm from some sectors but also resistance from others, particularly informal waste workers and industries whose livelihoods may be impacted. Balancing immediate socio-economic concerns with long-term environmental benefits becomes crucial. 

 

Optional STOP for questions and activities: 

 

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. 

To view a plain text version of this resource, click here to download the PDF.

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