Introduction

Abstract

The world is facing unprecedented challenges, which its inhabitants and governments are struggling to address.

1.1 The Rise of Complexity and Urgency

The world is facing unprecedented challenges, which its inhabitants and governments are struggling to address. COVID-19 has been a standout example for such challenges since 2020, with huge impacts on the world and on national economies. However, lurking in the background is climate change, the greatest threat to human life on earth. We are already seeing its effects through the increased severity of cyclones, tornadoes, floods, droughts, bushfires, crop failures, dust storms, and so on.

Artificial intelligence and digitalization are additional layers on top of the sustainability goals (SDGs), and they provide new opportunities and challenges for reshaping societies as well as engineering institutions. The Fourth Industrial Revolution, involving an expected increase in the use of new technologies, like the Internet of things (IoT), big data and machine learning, and robotics, will saturate all corners of society from the daily life of citizens to industrial production and global collaboration. New technological opportunities (AI, robotics, the Fourth Industrial Revolution) have changed human interactions, leading to changes in the way students learn, especially with the emergence of digital learning culture.

Emerging trends in engineering education are responding to these challenges. Topics related to systems thinking, design thinking, interdisciplinarity, complexity, and the use of real problems and projects in education are becoming part of engineering education. Many schools have integrated these trends in their curriculum and others are yet to do so.

When the learning situations change overnight, as happened during the COVID-19 crisis, and both teachers and students suddenly are urged into a digital mode, it creates challenges for how to scaffold and support learning. Not only are the complexities of societal problems increasing, AI and big data are more and more commonly applied and become crucial parts of engineering knowledge, learning, and solving complex human challenges.

The complexity of dependencies, which cannot be overlooked, raises attention to more systemic approaches. We need systemic ways of analyzing and modeling these problems so that we can, at least, make a start at addressing them. Systems thinking is a critical skill for future engineers. Systems maps can help to articulate and define the nature of the problem in ways that all stakeholders can relate to and appreciate. A system diagram typically includes the significant components of a system and the interactions between them. The system boundary defines the system of interest, separating it from the larger system in which it is embedded. The definition of the boundary predetermines the solutions available. Redefining the boundary opens new solutions.

High-level modeling tools, such as system dynamics, using stocks and flows, can transform the systems diagram into a quantitative model. The work of Donella Meadows, and others, is a good example (Meadows, 2009). These simple quantitative models can help stakeholders quickly understand the consequence of high-level decision making, e.g., where to allocate funds to reduce poverty. Which is better, spending on health or education? As the understanding of a system deepens, there are more sophisticated tools to be applied at smaller scales. Artificial intelligence, data analytics, and machine learning are all promising, data-driven tools to better understand aspects of system behavior.

Furthermore, the range from the simple to the sophisticated, from overview to the detail, from the philosophical roots of doing to technical insights, clearly questions the ability of any individual to cope with the breadth and depth of these challenges. In other words, the multidimensional nature of engineering calls for increasing capabilities to handle interdisciplinarity. Engineers should not sprend their energy to be interdisciplinary as such, but they should learn how to work in collaborative and interdisciplinary settings, where the interdisciplinarity profiles change with the problem at hand.

1.2 The Vision—Sustainable Development of Sociotechnical Systems

Over the past century, we became aware that most challenges should be viewed within a systems context, and engineering is shifting from technical problem solving to society focused, holistic problem solving. The problem-solving ecosystem requires different curricula, methodologies, and learning processes.

In this book, we examine new educational approaches to address human challenges within multidisciplinary and systems lenses. A broad set of ‘complexity’ traits may better describe current human challenges that are not addressable by positivist analysis. Different learning modalities have emerged and continue to evolve. Many of these modalities are combinations of doing, thinking, and listening, and attempt to engage the working long-term memory. Informal settings, such as maker spaces and active learning areas, encourage more interactions and enable creativity and innovation.

Complexity cannot be addressed by individuals or by people from a single discipline. When collaborative approaches are required to address complexity, interactive learning environments, such as problem and project-based studio pedagogies, provide appropriate physical environments that enable problem solving and engage both intrinsic and extrinsic motivations.

More innovative approaches appeared recently. For example, borrowing from the Arts, learning at the studio is ‘supervised’ by critics, who are proxies for the public and other stakeholders, and they provide the broadest context.

Learning in a problem-based setting, and a project-based environment, employs real-life problems as starting points. They integrate context dependency from the challenges experienced in real-life practice with an overall transformative scope of societies.

Several other forums for learning modalities include acting as a method for engaging the emotions and creating collaborations, as a literary campaign, creating sociability and appreciation. In Chap. 2, we present examples of how systems thinking, and inquiry-based learning approaches are appropriate in considerably different institutional contexts.

A world threatened by global problems needs engineers with global perspectives to tackle complexity and to address everyday problems in the broadest perspective. Education has no single model, as it is embedded in societal context. The educational mindset conceptualized in this book provides a frame of reference to the reshaping of engineering education. The examples of how this framing can emancipate itself in different institutional settings illustrate learning as a social experience. The methods exemplified in this book demonstrate how this can be done in formal classrooms, in informal ones, and in person, as well as remotely.

These diverse ecosystems point the way towards curriculum redesign issues that must be addressed. The goal of the book is to bring a focus on reshaping educational mindsets, methods, and directions for better education that may serve the coming decade. We all want to create a better future for ourselves and for the next generations, and there is a general agreement that education and social connections are critical to create a better life on Earth. Education is a key for better understanding the world, which brings more harmony and prosperity.

1.3 Challenges and Mindset for Reshaping Engineering Education

Twenty-first-century challenges are multidimensional and cannot be addressed through one specific perspective. Understanding different aspects of complexity requires not only a diversity of people but it also requires a diversity of mindsets. Due to the increasing multidimensionality of engineering, technological systems are expanding in complexity, and embedded trade-offs in design are increasing.

As such, no single perspective is ever enough in engineering, but as the platform for contextual learning is becoming increasingly complex and dynamic, the more should the focus be on shifting and combining different perspectives. Furthermore, with the increasing complexity and pace of development, the societal risk of using reductionist approaches to engineering is as emergent as ever.

In this book, we argue that a proactive and critical use of newly calibrated mindsets on technological development are needed in alignment with the grand challenges of our time, with a deeply founded respect for contextual differences. We take, as our starting point, the following overall challenges:

• A sociocultural-environmental challenge to address and embrace the diversity of people in complex systems, including ethics. The sustainability challenge must be included to address the increasing urgency to manage complex and interactive resource flows and ensure quality of life for future generations.

• A digital challenge to transform the learning and the development of the disciplines. The digital age must be reflected in the young engineers’ competency development.

• An employability challenge to address the learning outcomes for educating candidates who could relate to the ever-changing work and market conditions and are able to combine professional identity with citizenship as agents of societal change.

We argue that some of the core mindsets needed in engineering education to address these challenges are:

• 1. A future mindset, including systems and design, to systematically address the increasing complexity and unpredictability of sociotechnical systems as well as the digitalization challenge, and to assess the future impact of engineering work. This is discussed in Part I of the book (Chaps. 2, 3 and 4).

• 2. An interdisciplinary-learning mindset to facilitate active and reflective learning, individual and collaborative learning as well as contextual and transformative learning to develop the needed generic competencies required in a complex world. This is discussed further in Part II of the book (Chaps. 5, 6, 7 and 8).

• 3. A disciplinary and digitalization mindset to align engineering education to the emerging nature of engineering disciplines and the digital platforms as well as AI for new knowledge.

These challenges and mindsets are aggregated in Fig. 1.1, in an engineering education context, which puts the learner at the center of the system. The model has been inspired by (a) interacting competencies promulgated by international accreditation bodies, such as ABET and Engineers Australia, (b) interactions between disciplinary knowledge, design, and (c) interpersonal and professional skills, but we expand the views beyond these.

Fig. 1.1

Conceptual framework for mindsets

The future mindset has two dimensions. The first is self-centered—how do I develop myself as an engineer to achieve my career goals? This is commonly referred to as lifelong learning. The second dimension is a future mindset of professional practice, which embraces impact assessment—what are the consequences of my work? This includes an understanding of the lifecycle of engineering products. How will this product be operated, maintained, decommissioned, recycled, etc.? How does the operational energy over its lifetime compare to the embodied energy in its construction or manufacture? And has this been optimized?

Furthermore, a lifelong learning perspective is needed in an ever-changing world. As we approach challenges as systems and argue for systems analysis, there is a need for even more flexibility. Elements and components can be combined in numerous ways, and through design competencies, relations among the engineering specifics, disciplinary knowledge, and the overall system dynamics need to be articulated within a sociocultural understanding.

The above-mentioned new mindsets provide the tools to integrate systems and complexity in engineering education in various ways—both for the content of the curriculum and the learning methodologies. Thus, the engineering curricula and pedagogy can promote an integrated understanding of complex problem identification and problem solving and enable engineering students to address not only technical requirements but also consider the overall challenges including sustainable and contextual constraints and potentials.

Figure 1.1 furthermore presents the relations between the disciplines, the design processes, and the student engineer, framed in a sociocultural-environmental context. The key aspects of each dimension include core mindsets as elaborated in the following. We, by no means, argue that this is a universal perspective on engineering education, but it is the perspective that we will use in this book to move beyond current requirements from accreditation and establish a new ground for reshaping engineering education.

In addition, these mindsets must be brought into action, and the main purpose with this book is to offer a framework for doing exactly that to exemplify actions in different institutional contexts. As the book relates to reshaping engineering education, a considerable emphasis has been put on the learning mindset in relation to the two other mindsets.

In the following, we will briefly introduce the challenges which have brought this reshaping process into action.

1.4 The Sociocultural-Environmental Challenge

A shift to solving complex human issues is the future of engineering. With that, people’s culture and their interactions must be part of the problem definition, solution, and evaluation. The way people interact, shape, and reshape the cultural settings for technological developments are part of the problem-solving paradigm. In other words, we must consider not only how culture materializes itself, but also how culture is lived. Stressing the need for a sociocultural-environmental mindset on the reshaping of engineering education, to make synergy out of diversity, is needed to address complex and wicked problems. Key components of this sociotechnical mindset are ethical practice and sustainability.

Technology is developed for a purpose, and it is applied very differently in different cultural contexts. Different cultures have different framework conditions, and differences occur in terms of access to financial resources, demographics, market dynamics, political contexts, levels of literacy, among other factors. It is therefore challenging to transfer technology developments across cultural contexts, and this means that we also must include the way people interact, shape, and reshape the cultural settings for technological developments. In other words, we must consider how culture is institutionalized and materialized and embedded in discourses and practices. Thereby a sociocultural-environmental mindset on the reshaping of engineering education is needed to make synergy out of the diversity needed to address complex problems.

However, many of the complex problems that engineers are facing, are grounded in an unsustainable interaction between nature and human behavior, which ties the sociocultural context to the environmental context. The impacts from climate change underline the urgency of the sustainability challenges, but the concern for sustainable development is far from new.

In the 1980s, the report of the World Commission on Environment and Development pointed towards a threatened future and called for coordinated efforts for sustainable development (World Commission on Environment and Development, 1987). Governments and environmental agencies, throughout the world, initiated strategies in alignment with this future trajectory. Cleaner technologies were developed to limit the environmental impacts in the short run, and management systems and standards were developed to provide cleaner production, cleaner products, and cleaner ecosystems that all together could decouple economic growth from environmental impacts. The ambition embedded in the call for a circular economy captures the essence of such decoupling by extending the lifecycle of products and rejecting a linear take-make-consume-trash model.

During this development, increasing focus has been given to the social pillars of sustainability and, in 1999, the United Nations Global Compact was initiated. It was recognized that environmental and human impacts had to be considered alongside trade-offs, which made decision making for sustainability even more difficult.

The power of education has also been a part of the sustainability agenda for several decades. In 2005, UNESCO launched the United Nations Decade of Education for Sustainable Development and in the final stages of the decade, in 2012, The Higher Education Sustainability Initiative (HESI) took off (United Nations, 2022). During its first decade, HESI grew to a membership of almost 300 universities worldwide.

Education for Sustainable Development (ESD) furthermore institutionalized itself in the framing of different professions, and in 2002 the first conference on Engineering Education in Sustainable Development was held. What Stephen Sterling had called the BIG question became an important part of rethinking engineering education: How should—and how can—education and learning be rethought and reconfigured to make a significant and central contribution to achieving a more sustainable and just world? (Sterling, 2022).

What also became evident in this new century is that we needed to rethink the way we understand nature. As a reaction to the understanding of nature as something to be exploited for the benefit of the humankind, a preventive approach to nature developed during the last part of the twentieth century. Symptomatic was the famous act of Julia Butterfly Hill who sat in her treehouse for 738 days to prevent the tree from being cut down. There is no doubt that social movements striving for environmental protection have had crucial importance by raising attention to value of nature in itself.

In the twenty-first century, nature however started to communicate more clearly without the help of environmental protectionists—a language spoken in terms of cyclones, tornadoes, floods, droughts, bushfires, crop failures, dust storms, etc. For some, nature might still be an object of exploitation on one hand and a treasure to protect on the other, but most of all, nature has become one of the most important stakeholders to serve for long-term survival.

In 2015, the UN Sustainable Development Goals, the SDGs, provided a comprehensive framework for addressing the complexity of grand challenges which are excellent plans for engineering projects; in a similar way the US National Academy of Engineering provided similar guidelines (United Nations, 2021; US National Academy of Engineering, 2022). The SDGs related to clean water, energy, industry and infrastructure; cities and responsible production are directly targeted in engineering practice. However, engineering underpins every industry, which ultimately contributes to improving poverty, hunger, health, equality, work and economic growth, climate action, life on land and in water, peace, and partnerships.

Furthermore, besides providing a framework to handle the complexity of sustainability itself, the SDGs succeeded in addressing nature conservation and protection as well as the sociocultural context. Engineers of the twenty-first century must think in triple bottom lines (People, Profits, and the Planet) to act as agents for sustainable development and to identify themselves as global citizens and partners.

The engineering education community has responded in different ways to address this question. One response has been to create new branches of engineering with specific focus on sustainability, such as environmental engineering. Beyond such specializations in sustainability science, engineering, and management, efforts have been made to integrate sustainability in engineering programs at large. These approaches revealed challenges that are not easy to overcome. Many programs that have focused on development and teaching of solutions to standard problems had a tunnel vision approach that limited engagements of other areas of engineering disciplines.

Conceptual frameworks and methodologies from sustainability science can frame system thinking toward sustainable societies (e.g., lifecycle-thinking, ecodesign, and circular economy frameworks), but the increasing complexity of the sustainability challenge necessarily calls for collaboration across disciplines, sectors, and cultures. No single discipline, sector, or culture can manage this challenge alone; partnerships are needed to combine knowledge across interdisciplinary borders, and contextual learning is needed to point to the right partnerships to cope with the problem at hand.

In summary, complex problems must be solved in a larger sociocultural and environmental context to sustain nature and human beings and to create conditions for humanity beyond being. We all want to experience quality of life, whatever that means in different cultural settings. No doubt, engineering has had and will have a profound effect on humanity and on the planet. If we are to mitigate climate change, then engineering will need to play a larger part.

However, as nature has started to speak back in rather indisputable terms, the attention to the interdependencies and diversity in the societal and environmental context becomes ever more critical. Engineering, as a profession, therefore, must prepare graduates to work on the grand challenges of the twenty-first century, but in doing so, their ability to collaborate becomes crucial. Complex challenges have many interacting components and cannot be addressed by individuals or by groups of similar backgrounds. Broad collaborations by diverse teams are critical. Furthermore, no single society can afford finding solutions alone nor keep grand challenges outside their borders. Nature cannot be kept within borders.

1.5 The Digital Challenge

Over the past 15 years, digital technologies have expanded and invaded every aspect of our lives. The introduction of smartphones in 2007, enabled an unprecedented level of information exchange, and the ability to connect wirelessly to the Internet attracted younger and older generations. The introduction of social websites connected people and opened new doors for new commerce at unexpected volumes. In a short time, the world experienced the birth and growth of many small companies that became commercial giants by facilitating enquiries, sales, and purchases online, worldwide.

All these changes happened at an unprecedented speed; a digital quake overwhelmed us and made it necessary to navigate through fast and permanent changes to seek criteria for norms and regulations that would embody ethics and civility, enable free will, freedom, and democratic processes. Unfortunately, these goals remain elusive.

What is astonishing is that the digital quake covered every geographical area of the world, almost at the same time. This created unprecedented opportunities for people and countries. Although the utility of the digital technology is vastly available, innovation in digital technologies continues to be in the hands of a few countries that have dominated the digital markets and then gained from its related commerce. This might be viewed as an extension of the early innovation in semiconductors leading to amazing advancements in electronics, information storage technologies, and wireless circuitry.

In addition, software evolved into flexible platforms and enabled communications and constructing information. Although many of these technologies were initiated by US companies, the world at large participated and created supplementary technologies, without which the current advancements could not have happened. For example, a vast number of sensors of different types and purposes are now connected by the Internet of things (IoT) which enable further communications and generation of data that can be used for many social, medical, security, and educational purposes.

Although challenging, digitalization holds a huge potential in the reshaping of engineering education. Employing digital technologies in education continue to be layers within current content and pedagogy. We observe more and more digital learning and blended formats for engineering students. These will create even more possibilities for active learning methodologies and applied blended learning modes. However, learners will have to organize their own learning process virtually, and they will need ideas, imagination, peer-to-peer discussions, and structures for how they can organize, reflect, and improve these processes. Therefore, meta-cognitive skills for progressing learning become an important part of future skill sets.

Digital technologies are not only a matter of communicating and teaching online. Artificial intelligence will dominate the digital technology space. This is creating a need for massive shifts in content of many of the courses as well as in pedagogy.

Many of the current courses added computational aspects and simulations to their content and problem solving, but this is the tip of the iceberg. Machine learning will shift how and what we teach. Unfortunately, the instructors are not ready for this massive shift, and there is a resistance to moving forward with a fully digitized curriculum. How do we enable our students to be true citizen of the digital age? How are they going to learn to work with intelligent machines and learn along with them?

1.6 The Employability Challenge

The employability challenge is not a new one. It is the challenge of bridging the gap between education and the skills needed for productive work. Engineers, who match future societal needs, are in many countries a scarce resource, and matching students’ talents to jobs that are evolving quickly is a complex matter.

Competencies for employability can, according to Yorke (2004), be viewed as ‘a set of achievements – being skills, understandings and personal attributes – that make graduates more likely to gain employment and be successful in their chosen occupation, which benefits themselves, the workforce, the community, and the economy’ (Yorke, 2004, p. 3).

First, such description captures the complexity of moving from the individual micro-level to the societal value of graduates on a macrolevel. Graduates may be educated to address different contextual layers in the design of technological products and services, but to transfer this to a situation where they must put themselves in the center of development is another matter. The interaction between intrinsic and extrinsic motivation becomes important. Students need to reflect on how personal traits, personal interests, and attributes will shape their career track, on the one hand, and external requirements on the other.

Reflexivity about professional identity-making, thereby becomes an important competency for graduates in a lifelong learning perspective. It is about making sense of a new work-context and relating it to personal motivations. Graduates must be able to think critically about the context and be creative to do more than react to requirements; they should also be able to create changes in the new work environment. This is expected from an academically trained workforce. Some universities have responded to the employability challenge by requiring students to make a competency profile or a career plan of their own, but that is not enough.

Secondly, it can be noted that the descriptions presented above imply a rather individual focus on employability, as the single graduate is intended to meet these sets of requirements. For sure, individuals must be enabled to stand on their own when graduating as they cannot bring either professors or fellow students with them on their first day in a new job. However, professional requirements are seldom fully met by individuals alone, but collaboratively. This might be in peer-to-peer collaboration, in teams or by interacting in larger technological as well as national systems of innovation.

Thereby, each student must also reflect on how they position themselves within these social settings, critically consider the preconceptions they bring into a group, reflect on the relation between individual and collective values, and contribute to a healthy work environment. The accessibility and interplay of resources, the strategies reinforced by management as well as the administrative support might also interfere at the organizational level.

In that sense, the university must act as a playground for future professional work, for example by letting students work on real-life problems. It might be hard to solve complex problems in education—but the relation to the real-world problems should be part of students’ learning processes to prepare them for their later careers. The transformation from the educational setting to the professional setting can be further reinforced by making room for students to have a part-time job related to their subject of study or supporting internships. The conditions for doing might however be considerable different in different national contexts. In research universities, working in research labs opens possibilities for understanding work on open-ended problems.

Third, the definition of employability includes complexity due to a high degree of diversity in stakeholder interests in both the workforces and communities. Therefore, students might find themselves in very different types of engagements dependent on how they are intertwined in the quadruple-helix ecosystem which involves the university, industry, government, and civil society. Work in business, academia, government, and non-governmental workforces will evidently include different practices, institutions, and discourses. As technological systems as well as the challenges of engineering are becoming more complex, graduates are expected to be able to cope with more interactions and partnerships in the quadruple-helix.

As the streams in the quadruple-helix get more closely intertwined, and the partnerships more mutually dependent, the boundaries become more blurred. What then becomes important is that graduates have a clear professional identity, and at the same time can connect in meaningful ways across boundaries. It also means that graduates should be able to decode organizational cultures and structures within their own discipline, department, section, or community. They must make sense of and reinvent different patterns of boundary crossing between organizational and interorganizational units to create synergy out of diversity.

The major boundary to cross for graduates, from education to work, not only calls for skills to cross different disciplinary borders, but also to cross borders between the academic and non-academic domains. How educational stakeholders shape ‘what matters’ from an academic point of view might not correspond to what other stakeholders would outline as a matter of importance (Kolmos & Holgaard, 2018). Thereby, interactions and communications among university faculty and future employers of graduates are crucial.

To sum up, employability challenges engineering education institutions to develop a set of professional attributes suited to the future of work and citizenship. This must include interdisciplinarity and a range of generic competencies. Following this complexity, conceptualizations of employability competencies overall call for boundary-crossing competencies in many difference shades. Learning about creating innovations and entrepreneurial skills is also critical. Some universities have courses and open spaces for innovations and startups.

1.7 Structure of the Book

The educational mindsets conceptualized in this book provide a frame of reference to the reshaping of engineering education. Some examples of how this framing can be applied are provided.

The book is structured in three parts, where the first two parts elaborate on the presented mindsets including the future-system-design mindset (Part 1—Chaps. 2, 3, and 4) and the interdisciplinary-learning mindset (Part 2—Chaps. 5, 6, 7, and 8). Part 3 exemplifies how these mindsets can act as a framing of educational activities as had been practiced in three different institutions, Harvard University, the University of Technology Sydney (UTS), and Aalborg University (AAU), Denmark (Chaps. 9, 10, and 11). Finally, Part 4, Chap. 12, summarizes the lessons learned and the lessons yet to be learned.