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.  

Authors: Ahmet Omurtag (Nottingham Trent University); Andrei Dragomir (National University of Singapore / University of Houston).

Topic: Data security of smart technologies.

Engineering disciplines: Electronics; Data; Biomedical engineering.

Ethical issues: Autonomy; Dignity; Privacy; Confidentiality.

Professional situations: Communication; Honesty; Transparency; Informed consent; Misuse of data.

Educational level: Advanced.

Educational aim: Practising Ethical Analysis: engaging in a process by which ethical issues are defined, affected parties and consequences are identified, so that relevant moral principles can be applied to a situation in order to determine possible courses of action.

 

Learning and teaching notes:

This case involves Aziza, a biomedical engineer working for Neuraltrix, a hypothetical company that develops Brain-computer interfaces (BCI) for specialised applications. Aziza has always been curious about the brain and enthusiastic about using cutting-edge technologies to help people in their daily lives. Her team has designed a BCI that can measure brain activity non-invasively and, by applying machine learning algorithms, assess the job-related proficiency and expertise level of a person. She is leading the deployment of the new system in hospitals and medical schools, to be used in evaluating candidates being considered for consultant positions. In doing so, and to respond to requests to extend and use the BCI-based system in unforeseen ways, she finds herself compelled to weigh various ethical, legal and professional responsibilities.

This case study addresses two of AHEP 4’s themes: 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 case study to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.

The dilemma in this case is presented in three parts. If desired, a teacher can use the Summary and Part one in isolation, but Parts two and three develop and complicate the concepts presented in the Summary and Part one to provide for additional learning. The case 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:

Legal regulations:

Professional organisations:

Philanthropic organisations:

Journal articles:

Educational institutions:

 

Summary:

Brain-computer interfaces (BCIs) detect brain activity and utilise advanced signal analysis to identify features in the data that may be relevant to specific applications. These features might provide information about people’s thoughts and intentions or about their psychological traits or potential disorders, and may be interpreted for various purposes such as for medical diagnosis, for providing real-time feedback, or for interacting with external devices such as a computer. Some current non-invasive BCIs employ unobtrusive electroencephalography headsets or even optical (near-infrared) sensors to detect brain function and can be safe and convenient to use.

Evidence shows that the brains of people with specialised expertise have identifiable functional characteristics. Biomedical technology may translate this knowledge soon into BCIs that can be used for objectively assessing professional skills. Researchers already know that neural signals support features linked to levels of expertise, which may enable the assessment of job applicants or candidates for promotion or certification.

BCI technology would potentially benefit people by improving the match between people and their jobs, and allowing better and more nuanced career support. However, the BCI has access to additional information that may be sensitive or even troubling. For example, it could reveal a person’s health status (such as epilepsy or stroke), or it may suggest psychological traits ranging from unconscious racial bias to psychopathy. Someone sensitive about their privacy may be reluctant to consent to wearing a BCI.

In everyday life, we show what is on our minds through language and behaviour, which are normally under our control, and provide a buffer of privacy. BCIs with direct access to the brain and increasing capability to decode its activity may breach this buffer. Information collected by BCIs could be of interest not only to employers who will decide whether to hire and invest in a new employee, but also to health insurers, advertising agencies, or governments.

 

Optional STOP for questions and activities:

1. Activity: Risks of brain activity decoding – Identify the physical, ethical, and social difficulties that could result from the use of devices that have the ability to directly access the brain and decipher some of its psychological content such as thoughts, beliefs, and emotions.

2. Activity: Regulatory oversight – Investigate which organisations and regulatory bodies currently monitor and are responsible for the safe and ethical use of BCIs.

3. Activity: Technical integration – Investigate how BCIs work to translate brain activity into interpretable data.

 

Dilemma – Part one:

After the company, Neuraltrix, deployed their BCI and it had been in use for a year in several hospitals, its lead developer Aziza became part of the customer support team. While remaining proud and supportive of the technology, she had misgivings about some of its unexpected ramifications. She received the following requests from people and institutions for system modifications or for data sharing:

1. A hospital asked Neuraltrix for a technical modification that would allow the HR department to send data to their clinical neurophysiologists for “further analysis,” claiming that this might benefit people by potentially revealing a medical abnormality that might otherwise be missed.

2. An Artificial Intelligence research group partnering with Neuraltrix requested access to the data to improve their signal analysis algorithms.

3. A private health insurance company requested Neuraltrix provide access to the scan of someone who had applied for insurance coverage; they stated that they have a right to examine the scan just as life insurance agencies are allowed to perform health checks on potential customers.

4. An advertising agency asked Neuraltrix for access to their data to use them to fine-tune their customer behavioural prediction algorithms.

5. A government agency demanded access to the data to investigate a suspected case of “radicalisation”.

6. A prosecutor asked for access to the scan of a specific person because she had recently been the defendant in an assault case, where the prosecutor is gathering evidence of potential aggressive tendencies.

7. A defence attorney requested data because they were gathering potentially exonerating evidence, to prove that the defendant’s autonomy had been compromised by their brain states, following a line of argument known as “My brain made me do it.”

 

Optional STOP for questions and activities: 

1. Activity: Identify legal issues – Students could research what laws or regulations apply to each case and consider various ways in which Neuraltrix could lawfully meet some of the above requests while rejecting others, and how their responses should be communicated within the company and to the requestor.

2. Activity: Identify ethical issues – Students could reflect on what might be the immediate ethical concerns related to sharing the data as requested.

3. Activity: Discussion or Reflection – Possible prompts:

 

Dilemma – Part two:

The Neuraltrix BCI has an interface which allows users to provide informed consent before being scanned. The biomedical engineer developing the system was informed about a customer complaint which stated that the user had felt pressured to provide consent as the scan was part of a job interview. The complaint also stated that the user had not been aware of the extent of information gleaned from their brains, and that they would not have provided consent had been made aware of it.

 

Optional STOP for questions and activities: 

1. Activity: Technical analysis – Students might try to determine if it is possible to design the BCI consent system and/or consent process to eliminate the difficulties cited in the complaint. Could the device be designed to automatically detect sensitive psychological content or allow the subject to stop the scan or retroactively erase the recording?

2. Activity: Determine the broader societal impact and the wider ethical context – Students should consider what issues are raised by the widespread availability of brain scans. This could be done in small groups or a larger classroom discussion.

Possible prompts:

 

Dilemma – Part three:

Neuraltrix BCI is about to launch its updated version, which features all data processing and storage moved to the cloud to facilitate interactive and mobile applications. This upgrade attracted investors and a major deal is about to be signed. The board is requesting a fast deployment from the management team and Aziza faces pressure from her managers to run final security checks and go live with the cloud version. During these checks, Aziza discovers a critical security issue which can be exploited once the BCI runs in the cloud, risking breaches in the database and algorithm. Managers believe this can be fixed after launch and request the engineer to start deployment and identify subsequent solutions to fix the security issue.

 

Optional STOP for questions and activities: 

1. Activity: Students should consider if it is advisable for Aziza to follow requests from managers and the Neuraltrix BCI board and discuss possible consequences, or halt the new version deployment which may put at risk the new investment deal and possibly the future of the company.

2. Activity: Apply an analysis based on “Duty-Ethics” and “Rights Ethics.” This could be done in small groups (who would argue for management position and engineer position, respectively) or a larger classroom discussion. A tabulation approach with detailed pros and cons is recommended.

3. Activity: Apply a similar analysis as above based on the principles of “Act-Utilitarianism” and “Rule-Utilitarianism.”

Possible prompts:

 

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: Cortney Holles (Colorado School of Mines); Ekaterina Rzyankina (University of Cape Town).

Topic: Critical digital literacy.

Engineering disciplines: Computer Science; Information Systems; Biomedical engineering.

Ethical issues: Cultural context; Social responsibility; Privacy.

Professional situations: Public health and safety; Working in area of competence; Informed consent.

Educational level: Intermediate.

Educational aim: Engaging in ethical judgement: reaching moral decisions and providing the rationale for those decisions.

 

Learning and teaching notes:

The case involves an engineering student whose personal choices may affect her future professional experience. It highlights both micro- and macro-ethical issues, dealing with the ways that individual actions and decisions can scale to create systemic challenges.

An ethical and responsible engineer should know how to work with and use digital information responsibly. Not all materials available online are free to use or disperse. To be digitally literate, a person must know how to access, evaluate, utilise, manage, analyse, create, and interact using digital resources (Martin, 2008). It is important to guide engineering students in understanding the media landscape and the influence of misleading information on our learning, our political choices, and our careers. A large part of critical digital literacy is evaluating information found on the web. For students working on a research project or an experiment, accessing accurate information is imperative. This case study offers several approaches to engaging students in the critique and improvement of their critical digital literacy skills. The foundations of this lesson can be applied in multiple settings and can be expanded to cover several class periods or simplified to be inserted into a single class.

This case study addresses two of AHEP 4’s themes: 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 case study to AHEP outcomes specific to a programme under these themes, access AHEP 4 here and navigate to pages 30-31 and 35-37.

The dilemma in this case is presented in two parts. If desired, a teacher can use the Summary and Part one in isolation, but Part two develops and complicates the concepts presented in the Summary and Part one to provide for additional learning. The case 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:

News articles:

Educational institutions:

Legal regulations:

Non-profit organisations:

Business:

 

Summary:

Katherine is a biomedical engineering student in her 3rd year in 2022, and will have a placement in a community hospital during her last term at university. She plans to pursue a career in public health after seeing what her country went through during the Covid-19 pandemic. She wants to contribute to the systems that can prevent and track public health risks from growing too large to manage, as happened with Covid-19. She is motivated by improving systems of research and treatment for emerging diseases and knows that communication between a variety of stakeholders is of the utmost importance.

 

Optional STOP for questions and activities:

1. Discussion: What can you determine about Katherine’s values and motivation for her studies and her choice of career?

2. Discussion: How do you connect with her mission to improve diagnostic and treatment systems for public health threats?

3. Discussion: Who should be responsible for the messaging and processes for public health decisions? How are engineers connected to this system?

4. Activity: Research the Covid-19 vaccine rollout in the United Kingdom versus other countries – how did power, privilege, and politics influence the response?

5. Activity: Research current public health concerns and how they are being communicated to the public. In what ways might engineers affect how and what is communicated?

 

Dilemma – Part one:

As Katherine approaches the winter holiday season, she makes plans to visit her grandmother across the country. She hasn’t seen her since before the Covid-19 pandemic and is excited to be around her extended family for the holidays once again. However, she receives an email from her cousin informing everyone that he and his family are not vaccinated against Covid-19 because the whole vaccination operation was forced upon citizens and they refused to participate. Katherine is immediately worried for her grandmother – at 85 years old, she is at a higher risk than most – and for her brother, who suffers from Addison’s disease, an autoimmune disorder. Additionally, if Katherine comes into contact with Covid-19 while celebrating the holidays with her family, she could suffer repercussions at both her university and the hospital where she will work for her placement.

 

Optional STOP for questions and activities:

1. Discussion: How can Katherine communicate with her cousin about her concerns for her brother and grandmother? How might she use her expertise as a biomedical engineer in this conversation?

2. Discussion: What kind of information will be most convincing to support her decision? What sources would provide the evidence she is looking for, and which ones would provide counter arguments?

3. Discussion: What impacts might the decision have on Katherine’s position as a student or in the hospital?

4. Discussion: Do engineers, scientists, and medical professionals have more of an obligation to promote and adhere to public health guidance? Why or why not?

5. Activity: Talk to people in your life about their experience of navigating the Covid-19 vaccine. Did they choose to get it as soon as it was available? Did they avoid getting the vaccine for particular reasons? Were there impacts on their personal relationships or work because of their choices about the vaccine?

6. Activity: Research some of the impacts on individuals with health concerns and comorbidities in regard to Covid-19 and other viruses or public health concerns. How do these experiences match with or differ from your own?

7. Activity: Investigate the different ways that engineers were involved in vaccination development and response.    

 

Dilemma – Part two:

Katherine went back to university after a lengthy break for the holidays and immediately registered for an account on Facebook as a brand-new user. She was in such a hurry to have her profile up that she did not take the time to configure any privacy settings. She stayed up late reading an article about Covid-19  that had been posted on the website of one of the online newspapers. Before she posted this report on her own Facebook page, she did not verify the accuracy of the information or the source of the information.

 

Optional STOP for questions and activities:

1. Discussion: What kind of impact might this social media activity have on Katherine’s position as a student or in the company/organisation/hospital she is working for as an intern? What should Katherine be worried or concerned about after posting information?

2. Discussion: Do social media companies collect or ask for any other non-essential information from you? Why does the website claim that they are collecting or asking for your information? Does the website share/sell/trade the information that they collect from you? With whom does the website share your collected information? How long does the website keep your collected information? Does the website delete your information, or simply de-personalise it?

3. Discussion: Regarding question 2, how are engineers involved with products, processes, or services that enable those choices and actions?

4. Discussion: What is real and fake news? How do you know? What do you look for to know if it is real or fake news (share guidelines)? Do you expect it to be easy to spot fake news? Why should we care if people distribute and believe fake news?

Students are particularly susceptible to being duped by propaganda, misleading information, and fake news due to the significant role that information and communication technology which is problematic to verify plays in their everyday life. Students devote a significant portion of their time to participating in various forms of online activity, including watching television, playing online games, chatting, blogging, listening to music, posting photos of themselves on social networking sites, and searching for other individuals with whom they can engage in online conversation. Students owe a significant portion of what they know about the world and how they perceive reality to the content that they read online. While many people share reliable and positive information online, others may engage in negative impact information sharing:

5. Discussion: What are some other examples of how engineering might fall prey to negative impact information sharing?

6. Discussion: How might engineers help address the problem of fake news and negative impact information sharing?

 

References:

Martin, A. (2008). ‘Digital Literacy and the “Digital Society”’, in Lankshear C. and Knobel M. (eds.), Digital Literacies: Concepts, Policies, and Practices. New York: Peter Lang,  (pp. 151-176).

 

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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