ThesisPDF Available

Resilience in Engineering Education - Competencies for Designing Resilient Systems

Authors:

Abstract

Global challenges such as climate change lead to increasing volatility, uncertainty, complexity and ambiguity that pose numerous challenges for socio-technical systems. Engineers are jointly responsible for the design of these systems. Thus, engineering students need to be enabled to build and design complex systems that adapt to sudden disturbances, i.e., resilient systems. Doing so requires different, novel ways of thinking and acting that go beyond established problem-solving skills. These novel ways of thinking and acting can be subsumed under resilience thinking, planning and management. The demand for engineering professionals to be competent at designing resilient systems is well-reported. Despite that, there is hardly any research on systems resilience in engineering education. Existing research suggests that engineers are insufficiently trained to design resilient systems because the necessary competencies are not addressed in their education. This thesis addresses this gap by contributing not only to generating an understanding of the relevance of resilience in engineering education, but also to developing a framework to improve engineering education practice. This is done by questioning the current state of the art from a resilience thinking perspective aimed at better preparing engineering students to design resilient systems. Due to the lack of research on resilience in engineering education, the research approach was iteratively and systematically developed, where each study raises the research questions for the following ones. Based on an interpretivist educational research perspective, the research underlying this thesis was approached using different methodologies, which were guided by the respective research questions. In total, seven studies were conducted that build on and complement each other. These have three foci: resilience in engineering education research, resilience-related competencies in engineering education, and practical applications in and implications for teaching. By addressing both scholarliness and usefulness, this thesis presents a holistic approach to resilience in engineering education, combining theory and practice. To this effect, this thesis develops the state of the art by providing a theoretical framework for defining and categorizing the concept of resilience within engineering education research as well as for resilience-related competencies, contributing to both research and practice. Furthermore, this thesis provides and suggests concrete examples for teaching, learning and assessment activities to foster engineering students’ competency development in terms of resilience. Implications for engineering education practice include the design of course concepts which holistically integrate problem- and case-based learning as well as deep reflection and feedback methods. Finally, this thesis highlights both the lack of and the need for a (better) integration of resilience in engineering education research and practice. Subsequently, this thesis concludes that the current practice in engineering education does not adequately prepare students to design resilient systems, as required competencies for this purpose are not sufficiently addressed in their studies. Thus, the results of this thesis indicate both challenges and opportunities in terms of changing the paradigm of engineering education towards a future-oriented education that specifically enhances competencies for designing resilient systems.
Resilience in Engineering Education
Competencies for Designing Resilient Systems
Von der Fakultät für Bauingenieurwesen der Rheinisch-Westfälischen Technischen
Hochschule Aachen zur Erlangung des akademischen Grades einer Doktorin der
Ingenieurwissenschaften genehmigte Dissertation
vorgelegt von
Ann-Kristin Winkens
Berichter: Univ.-Prof. Dr. phil. Carmen Leicht-Scholten
Univ.-Prof. Dr.-Ing. Heribert Nacken
Tag der mündlichen Prüfung: 04.07.2024
Diese Dissertation ist auf den Internetseiten der Universitätsbibliothek online verfügbar.
I
Acknowledgements
“Expect the best, plan for the worst and prepare to be surprised” – This quote by Denis Wait-
ley not only describes the idea of resilience very well, but also the process of my PhD. Above
all, I would like to thank my doctoral supervisor, Professor Carmen Leicht-Scholten, for her
invaluable guidance, support and encouragement throughout the entire journey of completing
this thesis. Throughout this time, she challenged me to aim higher and to develop as a re-
searcher. At the same time, she also fostered my own resilience, and as such shaped both
my academic, and personal growth.
I am also grateful to my second reviewer, Professor Heribert Nacken, for his insightful feed-
back and constructive criticism, and his motivation to engage with my work.
I extend my heartfelt thanks to my colleagues and companions Clara Lemke, Frauke Kordto-
meikel and Julia Berg for their camaraderie, support, and stimulating discussions, which
have enriched my research and teaching experience.
Special appreciation goes to my dear friends Felix Engelhardt and Sarah Hilker for their un-
wavering support, for their critical questions, their encouragement and understanding during
the challenging phases of this academic pursuit. Their friendship has been a constant source
of strength and inspiration.
I am indebted to my father, Andreas Winkens, and my grandfather, Paul Winkens, for their
endless love, encouragement, and belief in my competencies.
I would also like to acknowledge Benjamin Scharte for the insightful discussions on the nor-
mativity of resilience, and the entire SEFI community for their contributions to my academic
journey.
Finally, I would like to thank all those who have directly or indirectly supported me in the
completion of this thesis. Their encouragement, advice and inspiration have been invaluable.
Thank you.
Ann-Kristin Winkens
II
Abstract
Global challenges such as climate change lead to increasing volatility, uncertainty, complexity
and ambiguity that pose numerous challenges for socio-technical systems. Engineers are
jointly responsible for the design of these systems. Thus, engineering students need to be
enabled to build and design complex systems that adapt to sudden disturbances, i.e., resilient
systems. Doing so requires different, novel ways of thinking and acting that go beyond estab-
lished problem-solving skills. These novel ways of thinking and acting can be subsumed under
resilience thinking, planning and management.
The demand for engineering professionals to be competent at designing resilient systems is
well-reported. Despite that, there is hardly any research on systems resilience in engineering
education. Existing research suggests that engineers are insufficiently trained to design
resilient systems because the necessary competencies are not addressed in their education.
This thesis addresses this gap by contributing not only to generating an understanding of the
relevance of resilience in engineering education, but also to developing a framework to improve
engineering education practice. This is done by questioning the current state of the art from a
resilience thinking perspective aimed at better preparing engineering students to design resil-
ient systems. Due to the lack of research on resilience in engineering education, the research
approach was iteratively and systematically developed, where each study raises the research
questions for the following ones. Based on an interpretivist educational research perspective,
the research underlying this thesis was approached using different methodologies, which were
guided by the respective research questions. In total, seven studies were conducted that build
on and complement each other. These have three foci: resilience in engineering education
research, resilience-related competencies in engineering education, and practical applications
in and implications for teaching.
By addressing both scholarliness and usefulness, this thesis presents a holistic approach to
resilience in engineering education, combining theory and practice. To this effect, this thesis
develops the state of the art by providing a theoretical framework for defining and categorizing
the concept of resilience within engineering education research as well as for resilience-related
competencies, contributing to both research and practice. Furthermore, this thesis provides
and suggests concrete examples for teaching, learning and assessment activities to foster
engineering students’ competency development in terms of resilience. Implications for engi-
neering education practice include the design of course concepts which holistically integrate
problem- and case-based learning as well as deep reflection and feedback methods.
Finally, this thesis highlights both the lack of and the need for a (better) integration of resilience
in engineering education research and practice. Subsequently, this thesis concludes that the
current practice in engineering education does not adequately prepare students to design re-
silient systems, as required competencies for this purpose are not sufficiently addressed in
their studies. Thus, the results of this thesis indicate both challenges and opportunities in terms
of changing the paradigm of engineering education towards a future-oriented education that
specifically enhances competencies for designing resilient systems.
III
Zusammenfassung
Globale Herausforderungen wie der Klimawandel führen zu zunehmender Volatilität, Unsicher-
heit, Komplexität und Ambiguität, die zahlreiche Herausforderungen für soziotechnische Sys-
teme mit sich bringen. Ingenieur*innen sind für die Gestaltung dieser Systeme mitverantwort-
lich. Entsprechend müssen sie im Rahmen ihrer Ausbildung dafür sensibilisiert und dazu be-
fähigt werden, komplexe Systeme zu gestalten und zu entwickeln, die sich an plötzliche Stö-
rungen anpassen können, das bedeutet resiliente Systeme. Das Gestalten resilienter Systeme
erfordert alternative und neuartige Denk- und Handlungsweisen, die über bekannte und
etablierte Problemlösungsansätze hinausgehen. Diese neuen Denk- und Handlungsweisen
können unter „Resilience Thinking“ sowie resilienzorientierter Planung und Management zu-
sammengefasst werden.
Der Bedarf an Ingenieur*innen, die dazu fähig sind, resiliente Systeme zu gestalten, ist hinrei-
chend bekannt. Trotz dessen gibt es kaum Forschung zu systemischer Resilienz in der Inge-
nieurausbildung. Im Gegenteil suggeriert der Stand der Forschung zur Ingenieurausbildung,
dass Ingenieur*innen unzureichend ausgebildet sind, um resiliente Systeme zu entwerfen, da
die erforderlichen Kompetenzen in ihrer Ausbildung nicht adressiert bzw. vermittelt werden.
Die vorliegende Dissertation nimmt sich dieser Forschungslücke an, indem sie nicht nur zu
einem Verständnis der Relevanz von Resilienz in der Ingenieurausbildung beiträgt, sondern
auch einen Rahmen zur Verbesserung der Praxis der Ingenieurausbildung entwickelt. Dabei
wird aus einer „Resilience Thinking“-Perspektive der Status-quo hinterfragt, um Studierende
der Ingenieurwissenschaften besser auf die Gestaltung resilienter Systeme vorzubereiten. Da
es kaum Forschung zu Resilienz in der Ingenieurausbildung gibt, wurde der Forschungsansatz
iterativ und systematisch entwickelt, wobei jede Studie die Forschungsfragen für die folgende
Studie aufzeigt. Aus einer interpretivistischen Bildungsforschungsperspektive wurden für die
dieser Arbeit zugrundeliegende Forschung verschiedene Methoden angewandt, die sich an
den jeweiligen Forschungsfragen orientierten. Insgesamt wurden sieben Studien durchgeführt,
die aufeinander aufbauen und sich gegenseitig ergänzen. Diese haben insgesamt drei
Schwerpunkte: Resilienz in der Forschung zur Ingenieurausbildung, resilienzbezogene Kom-
petenzen in der Ingenieurausbildung sowie praktische Anwendungen und Implikationen für die
Lehre.
Da diese Arbeit sowohl einen wissenschaftlichen als auch einen anwendungsdienlichen An-
spruch hat, präsentiert sie einen holistischen Ansatz für Resilienz in der Ingenieurausbildung,
indem sie Theorie und Praxis miteinander verbindet. In diesem Kontext wird der Stand der
Forschung weiterentwickelt, indem ein theoretischer Rahmen für die Definition und Kategori-
sierung des Konzepts der Resilienz in der Forschung zur Ingenieurausbildung sowie für
resilienzbezogene Kompetenzen geschaffen wird, der sowohl zur Forschung als auch zur Pra-
xis beiträgt. Darüber hinaus werden in dieser Arbeit konkrete Beispiele für Lehr-, Lern- und
Bewertungsaktivitäten zur Förderung von resilienzbezogenen Kompetenzen von Studierenden
der Ingenieurwissenschaften vorgestellt und vorgeschlagen. Zu den Implikationen für die Pra-
xis der Ingenieurausbildung gehört die Gestaltung von Kurskonzepten, die problem- und fall-
basiertes Lernen sowie tiefgreifende Reflexions- und Feedbackmethoden ganzheitlich
integrieren.
Schließlich wird sowohl das Fehlen als auch die Notwendigkeit einer (besseren) Einbindung
von Resilienz in Forschung und Praxis der Ingenieurausbildung hervorgehoben. Die vorlie-
gende Arbeit kommt zu dem Schluss, dass die derzeitige Praxis der Ingenieurausbildung Stu-
dierende nicht angemessen auf die Gestaltung resilienter Systeme vorbereitet, da die hierfür
erforderlichen Kompetenzen im Studium fehlen. Die Ergebnisse dieser Arbeit zeigen somit
sowohl Herausforderungen als auch Chancen für einen Paradigmenwechsel in der
Ingenieurausbildung auf, hin zu einer zukunftsorientierten Ausbildung, die auch und insbeson-
dere Kompetenzen für die Gestaltung resilienter Systeme fördert.
IV
List of Publications
This thesis is based on the research that is conducted and described in the following publica-
tions:
Paper I Winkens, A., & Leicht-Scholten, C. (2023). Does engineering education re-
search address resilience and if so, how? A systematic literature review. Eu-
ropean Journal of Engineering Education, 48(2), 221239.
https://doi.org/10.1080/03043797.2023.2171852
Paper II Winkens, A., & Leicht-Scholten, C. (2021). Resilience as a key competence in
engineering education development of a conceptual framework. Proceedings
of the 49th SEFI Annual Conference 2021. Germany, Berlin: Online, 628
636.1
Paper III Winkens, A., & Leicht-Scholten, C. (2023). Competencies for designing resili-
ent systems in engineering education a content analysis of selected study
programs of five European technical universities. European Journal of Engi-
neering Education, 48(4), 682706.
https://doi.org/10.1080/03043797.2023.2179913
Paper IV Winkens, A., Engelhardt, F., & Leicht-Scholten, C. (2023). Resilience-related
Competencies in Engineering Education Mapping ABET, EUR-ACE and
CDIO Criteria. Proceedings of the SEFI 51st Annual Conference 2023. Dublin,
Ireland: TU Dublin, 14981507. https://doi.org/10.21427/B7ZX-QS662
Paper V Winkens, A., & Leicht-Scholten, C. (2022). Local Resilience Strategies for
COVID19 A PBL Engineering Case Study. Proceedings of the 18th Interna-
tional CDIO Conference. Reykjavik, Iceland: Reykjavik University, 174188.3
Paper VI Winkens, A., Lemke, C., & Leicht-Scholten, C. (2024). How to Teach Resili-
ence Thinking in Engineering Education. Sustainable and Resilient Infrastruc-
ture. https://doi.org/10.1080/23789689.2024.2356492
Paper VII Rouvrais, S., Winkens, A., Leicht-Scholten, C., Audunsson, H., & Gerwel Pro-
ches, C. (2023). VUCA and Resilience in Engineering Education Lessons
Learned. Proceedings of the 19th International CDIO Conference. Trondheim,
Norway: NTNU, 312322.4
The papers are numbered by content, not by publication date. All studies are included in the
appendix of this thesis.
1 Peer-reviewed
2 Peer-reviewed
3 Peer-reviewed
4 Peer-reviewed
V
Contribution Report
With the exception of Papers IV, VI and VII, all papers were written in sole authorship with my
supervisor. The contributions to Papers IV, VI and VII are reported below.
Paper IV Lead author. Independently conducted literature review and planned data col-
lection. Independently performed data analysis with co-authors. Derived con-
clusions from results together with co-authors.
Paper VI Lead author. Independently conducted literature review, developed and con-
ducted the course and case study. Independently collected the data. Data anal-
ysis was performed together with co-authors. Derived conclusions from results
together with co-authors.
Paper VII Independently conducted literature review. Data analysis was performed to-
gether with co-authors. Derived conclusions from results together with co-au-
thors.
VI
Table of Contents
Acknowledgements ................................................................................................................ I
Abstract ................................................................................................................................. II
Zusammenfassung ............................................................................................................... III
List of Publications ............................................................................................................... IV
Contribution Report ............................................................................................................... V
List of Abbreviations ............................................................................................................ VII
List of Figures ..................................................................................................................... VIII
List of Tables ........................................................................................................................ IX
1 Introduction .................................................................................................................. 1
1.1 State of the Art ........................................................................................................ 1
1.2 The Researcher ...................................................................................................... 8
1.3 Research Aim and Thesis Outline ........................................................................... 9
2 Engineering Education Research as a Cross-Disciplinary Field ............................ 11
2.1 WHY Motivations for EER .................................................................................. 12
2.2 WHAT Research Trends and Topics .................................................................. 15
2.3 WHERE Research Communities ........................................................................ 18
2.4 HOW Methodologies and Epistemologies .......................................................... 20
2.5 WHERE TO? Competencies in Engineering Education ......................................... 27
3 Research Results Resilience in Engineering Education ...................................... 35
3.1 Part 1: Resilience in Engineering Education Research .......................................... 35
3.2 Part 2: Resilience-related Competencies in Engineering Education ...................... 38
3.3 Part 3: Teaching Resilience in Engineering Education .......................................... 45
4 Discussion .................................................................................................................. 50
4.1 Synthesis of Results: Resilience in Engineering Education ................................... 50
4.2 Limitations and Further Research .......................................................................... 53
4.3 Contributions to and Implications for Engineering Education ................................. 57
4.4 Quality Criteria ...................................................................................................... 63
5 Conclusion .................................................................................................................. 64
References .......................................................................................................................... 66
Appendix ............................................................................................................................. 77
Paper I ............................................................................................................................. 78
Paper II ...........................................................................................................................108
Paper III ..........................................................................................................................117
Paper IV ..........................................................................................................................151
Paper V ...........................................................................................................................161
Paper VI ..........................................................................................................................179
Paper VII .........................................................................................................................211
VII
List of Abbreviations
ABET
Accreditation Board for Engineering and Technology
AGCEER
Advancing the Global Capacity for Engineering Education Research
ASCE
American Society of Civil Engineers
ASEE
American Society for Engineering Education
CDIO
Conceive Design Implement Operate
EC 2000
Engineering Criteria 2000
EE
Engineering Education
EER
Engineering Education Research
EHEA
European Higher Education Area
EJEE
European Journal of Engineering Education
ENAEE
European Network for Engineering Accreditation
EQF
European Framework of Qualifications
ERM
Educational Research and Methods Division
GAPC
Graduate Attributes and Professional Competencies
HEI
Higher Education Institution
IEA
International Engineering Alliance
IPCC
Intergovernmental Panel on Climate Change
JEE
Journal of Engineering Education
LO
Learning Outcome
NAE
National Academy of Engineering
NRC
National Research Council
NSF
National Science Foundation
PBL
Problem-based Learning
REEN
Research in Engineering Education Network
REES
Research in Engineering Education Symposium
RQ
Research Question
SDGs
Sustainable Development Goals
SEFI
European Society for Engineering Education
SLR
Systematic Literature Review
UNDRR
United Nations Office for Disaster Risk Reduction
VUCA
Volatility Uncertainty Complexity Ambiguity
VIII
List of Figures
Figure 1. Engineering education as a second-order region (Klassen & Case, 2022, p.
217) ...............................................................................................................................22
Figure 2. ABET student outcomes (ABET, 2022) ..................................................................29
Figure 3. Excerpt from the CDIO Syllabus (Malmqvist et al., 2022) ......................................33
IX
List of Tables
Table 1. Five key attributes to build resilient systems (Rockström et al., 2023, p. 7) .............. 3
Table 2. Exemplary excerpt from the EUR-ACE learning areas (ENAEE, 2021) ...................30
Table 3. Exemplary excerpt from IEA professional competency profile (IEA, 2021) ..............31
Table 4. Inclusion and exclusion criteria for the SLR (Winkens & Leicht-Scholten, 2023b) ...37
Table 5. Overview of different resilience levels and objectives of resilience within
included records (Winkens & Leicht-Scholten, 2023b) ...................................................38
Table 6. Key competencies characterizing resilience (adapted from Winkens & Leicht-
Scholten, 2023a) ............................................................................................................40
Table 7. Excerpt from the categorization of LOs (Winkens & Leicht-Scholten, 2023a) ..........42
Table 8. Resilience-related competencies in EUR-ACE, ABET and CDIO (Winkens et al.,
2023) .............................................................................................................................44
Table 9. Intended learning outcomes and resilience-related competencies addressed in
the course ......................................................................................................................46
Table 10. Overview of the four case studies on teaching resilience and VUCA (Rouvrais
et al., 2023) ....................................................................................................................49
Table 11. Quality criteria .......................................................................................................63
1
1 Introduction
This introductory chapter presents the state of the art and provides the motivation for doing
research on resilience in engineering education. Furthermore, it describes the research aim of
this thesis as well as the underlying research questions. The chapter is concluded by the out-
line of this thesis.
1.1 State of the Art
Living in a VUCA World
Volatility, uncertainty, complexity and ambiguity (VUCA) are cornerstones of the 21st century
(Kamp, 2016, 2020). As we acknowledge that we live in a VUCA world, innovations, different
ways of thinking and acting as well as future-oriented competencies are required to shape our
present and future (Kamp, 2016, 2020; OECD, 2018). Climate change, here, is a main contrib-
utor to a VUCA world, as it is characterized by emerging threats, extreme events caused by
natural hazards and several unknowns to deal with, as long-term effects are unpredictable,
unquantifiable change is nonlinear and forecasts uncertain (Ayyub, 2018; Linkov et al., 2014;
Walker et al., 2002). This means “even the uncertainties are uncertain” (Walker et al., 2002,
n.p.). Recognizing that natural hazards are increasing worldwide with regard to frequency and
impact, their consequences for the environment, people and economy are also worsening
and, at the same time, they remain highly unpredictable (EM-DAT, 2023; IPCC, 2022; Khan &
Eslamian, 2022; Ritchie & Rosado, 2022). While many natural hazards that are characterized
by low frequency and high impact, such as tsunamis or earthquakes, cannot be prevented per
se, dealing with these both proactively and reactively can reduce their impact on different
scales. This requires innovative and adaptive solutions which go beyond simple, rational prob-
lem-solving activities as in traditional risk management (Ayyub, 2018; Chester & Allenby, 2019;
Hollnagel, 2008; Levin et al., 2021; Olsen et al., 2015; Park et al., 2013). Instead, in order to
address the uncertainty and complexity of global challenges like climate change, resilience
thinking, planning and management are needed to enable the development of suitable infra-
structure (Levin et al., 2021; Linkov et al., 2014; Linkov et al., 2016; Martin et al., 2022; NASEM,
2022; NRC, 2012; Park et al., 2013; UNDRR, 2022, 2023):
Resilience thinking is about understanding and engaging with a changing world. By understand-
ing how and why the system as a whole is changing, we are better placed to build a capacity to
work with change, as opposed to being a victim of it. (Walker & Salt, 2006, p. 14)
In the context of climate change adaptation and climate resilient development, the discourse
on resilience has experienced increasing relevance (IPCC, 2022, 2023; NASEM, 2022; NRC,
2
2012; UNDRR, 2022). In their Synthesis Report of the Sixth Assessment Report, the Intergov-
ernmental Panel on Climate Change (IPCC) indicates a very high confidence that
Observed adverse impacts and related losses and damages, projected risks, trends in vulnera-
bility, and adaptation limits demonstrate that transformation for sustainability and climate resili-
ent development action is more urgent than previously assessed […]. Climate resilient develop-
ment integrates adaptation and GHG [greenhouse gas] mitigation to advance sustainable de-
velopment for all. (IPCC, 2023, p. 24)
Further, climate resilience development strategies require an integrated systems approach,
meaning that ecosystems, climate and human society need to be considered as parts of one
system, as they are interdependent (IPCC, 2023). Correspondingly, decision making pro-
cesses, actions and solution approaches also need to be developed in an integrated and ho-
listic way considering different stakeholder perspectives across all sectors.
In the Working Group II report on climate change impacts, adaptation and vulnerability, the
IPCC defines resilience as
the capacity of social, economic and ecosystems to cope with a hazardous event or trend or
disturbance, responding or reorganising in ways that maintain their essential function, identity
and structure as well as biodiversity in case of ecosystems while also maintaining the capacity
for adaptation, learning and transformation. Resilience is a positive attribute when it maintains
such a capacity for adaptation, learning, and/or transformation. (IPCC, 2022, p. 7)
Hence, resilience is inherently connected to the occurrence of a potential or actual disruptive
and often extreme event, where the ability to adapt and to learn is a necessary prerequisite for
building resilience (Scharte, 2021). A large amount of inter- and transdisciplinary research on
resilience has been carried out, also regarding strategies for enhancing resilience (e.g., Biggs
et al., 2012; Carpenter et al., 2012; Francis & Bekera, 2014; Gasser et al., 2021; Rockström
et al., 2023; Walker, 2020). Rockström et al. (2023) synthesized several key studies on resili-
ence and identified five key attributes as essential for building and enhancing resilience across
disciplines and sectors: diversity, redundancy, connectivity, inclusivity and equity, and adaptive
learning. Table 1 provides an overview of exemplary interventions to build resilience.
3
Table 1. Five key attributes to build resilient systems (Rockström et al., 2023, p. 7)
Attribute
Interventions to build resilience (examples)
Diversity
Support diverse economic opportunities and livelihoods.
Diversify and decentralize energy systems, including increased investment in on- and off-grid re-
newable energy options.
Increase national crop diversity so that countries have more options to navigate disruptions such
as extreme weather events, outbreaks of pests, or economic and labor shocks.
Redundancy
Introduce universal access to social safety net programs that ensure marginalized communities
can cope with unexpected shocks.
Maintain adequate reserves and alternative supply chains in key systems such as finance, food,
energy and water.
Support informal networks and civil society providing social buffers, ranging from remittances to
healthcare and education.
Inclusivity and
Equity
Ensure that development and adaptation planning places the needs of the most vulnerable at its
center and builds on existing grassroots structures, relationships and processes.
Expand access of communities and households, and in particular women and other vulnerable
populations, to credit, risk sharing and savings facilities.
Greatly increase the proportion of climate and development finance that reaches grassroots organ-
izations and local communities
Connectivity
Stimulate local food production, especially in and around cities, to reduce systemic risks related to
disruption of distant and highly concentrated global value chains.
Decentralize and modularize energy systems, connected in regional networks, to avoid systemic
risks linked to large and overly centralized energy infrastructure.
Support and amplify existing community connectivity and increase networks of community-based
organizations to maintain the provision of basic services and programs, especially for the most vul-
nerable.
Adaptive
Learning
Shift towards agile and adaptive decision-making processes that are guided by multiple probable
scenarios of the future and not a stable-state view of the future.
Maintain memory of responses to past crises and promote practices that enable social learning
from novel crises.
Invest in research, monitoring and knowledge management capacity to accelerate adaptive learn-
ing cycles needed to build resilience to systemic, compounding and unpredictable shocks.
In summary, resilience is not about simply bouncing back after a disturbance, which would
rather refer to robustness or resistance to change terms that are often mistakenly used in-
terchangeably (Rockström et al., 2023; Scharte, 2023; Walker, 2020; Woods, 2015). Instead,
it is characterized by adaptive capacity and a forward-looking approach in order to build back
better. This perception of resilience is based on the understanding that ecosystems and hu-
mans are intertwined and that they constitute complex integrated social-ecological systems
(Folke, 2016; Folke et al., 2010; Rockström et al., 2023; Walker et al., 2002).
Several international frameworks call for resilient infrastructures. For example, the United Na-
tions Sustainable Development Goals (SDGs) formulate targets to face global challenges (UN,
2015b). Here, in several targets, dealing with climate change is a recurring theme; SDGs 11
(Sustainable Cities and Communities) and 13 (Climate Action) explicitly call for the strength-
ening of resilience to adapt to climate change. In 2015, the Sendai Framework for Disaster
4
Risk Reduction 20152030 was adopted at the Third UN World Conference in Sendai, Japan
(UN, 2015a). The Sendai Framework aims to achieve “the substantial reduction of disaster risk
and losses in lives, livelihoods and health” across all scales and sectors (UN, 2015a, p. 12).
The framework includes four priorities for action, where strengthening resilience is an explicit
target:
1) Understanding disaster risk.
2) Strengthening disaster risk governance to manage disaster risk.
3) Investing in disaster risk reduction for resilience.
4) Enhancing disaster preparedness for effective response and to “Build Back Better” in
recovery, rehabilitation and reconstruction (UN, 2015a, p. 14).
The UN Office of Disaster Risk Reduction (UNDRR) aims to reduce disaster risk and losses,
and to increase the resilience of systems and societies, thereby aiming to implement the pri-
orities formulated by the Sendai Framework (UNDRR, 2022). For example, the German Fed-
eral Government published their first “German Strategy for Strengthening Resilience to Disas-
ters” in 2022, in order to implement the requirements of the Sendai Framework. The overarch-
ing goal is that “German society is more resilient to disasters” and that Germany contributes
internationally to the implementation of the Sendai Framework (Federal Ministry of the Interior
and Community, 2022, p. 9). A brief desk research of governmental documents has shown
that prior to this report, nothing could be found on the objective of strengthening a resilient
society. In contrast, in 2012, the US National Research Council (NRC) published a report titled
“Disaster Resilience: A National Imperative”, formulating recommendations for the government
to establish and promote disaster resilience strategies (NRC, 2012). Further, they describe the
characteristics of a “Resilient Nation in the Year 2030”, stating that every individual “has em-
braced a ‘culture of resilience’” in 2030 (NRC, 2012, p. 14).
For further contextualization, the relation between resilience and sustainability is briefly ex-
plained at this point. In the literature, there is ongoing disagreement about how the terms re-
silience and sustainability are related, whether they are a component of each other or comple-
mentary (Anderies et al., 2013; Bautista-Puig et al., 2022; Bocchini et al., 2014; Elmqvist et al.,
2019; Lyytimäki et al., 2023; Marchese et al., 2018; Redman, 2014). Although the concepts
share some objectives and elements, as, e.g., both address a holistic view on future global
challenges and a motivation to understand complex system dynamics (Bocchini et al., 2014;
Marchese et al., 2018; Redman, 2014), they are fundamentally different in their primary objec-
tives, i.e., “sustainability prioritizes outcomes; resilience prioritizes process” (Redman, 2014,
n.p.). Furthermore, sustainability is inherently normative, whereas resilience is a non-norma-
tive attribute of a system that is neither good nor bad per se, although the term is usually used
5
in a positive connotation1, as in the IPCC definition above (Anderies et al., 2013; Elmqvist et
al., 2019; Lyytimäki et al., 2023; Scharte, 2021). For example, building resilience of forests to
fires by reducing fuel can reduce the resilience of some fauna species in times of drought
(Walker, 2020). Ideally, and referring back to the key attributes to build resilient systems (Table
1), the forest is characterized by diversity, redundancy and connectivity and thus able to deal
with a variety of disturbances, which makes it more resilient than to one specific disturbance,
such as fire (Walker, 2020).
The concepts also differ on a temporal scale, as sustainability efforts are usually planned and
implemented on longer time scales (focusing on future generations) than resilience, which is
also applied to sudden and immediate disturbances (Anderies et al., 2013; Marchese et al.,
2018). A key example for their conceptual difference is efficiency, where conflicting goals be-
come apparent. While efficiency is one of the common implementation strategies for sustain-
able development, efficiency contradicts the idea of redundancy and diversity which are key
attributes for and of resilience (Elmqvist et al., 2019; Luks, 2015; Park et al., 2013; Scharte,
2021; Walker et al., 2006). Thus, maximizing efficiency can, at the same time, reduce resilience
(Elmqvist et al., 2019). This can be the case, for example, in energy delivery systems or agro-
ecosystems, where maximizing efficiency leads to an increase in dependencies, as fewer
back-up systems or parallel structures exist for the case of disturbances (Elmqvist et al., 2019;
Walker et al., 2023; Walker et al., 2006). It is therefore crucial for planning and decision-making
processes to carefully examine the different objectives of and approaches to resilience and
sustainability.
Since the conceptual discourse around resilience is explained in detail in the individual publi-
cations on which this work is based, no further elaboration is provided here. In general, the
subjects of resilience can be individuals, societies, social-ecological and/or socio-technical
systems. Indeed, in this thesis, the main concerns of resilience are complex, integrated social-
ecological-technical systems, such as infrastructure, for which engineers are jointly responsi-
ble. As already broadly discussed in the publications underlying this thesis, when the term
“resilience” is used in this thesis, it always refers to those systems, not to the individuals (i.e.,
engineers) who design these systems.
1 The extent to which the development of a system’s resilience is characterized as normatively desirable depends
on the extent to which the identity of the system is normatively desirable (Scharte, 2021). Even if resilience is ana-
lyzed descriptively in the context of this thesis, the aim is to contribute to resilient infrastructure development
through appropriate education and competency development, which is normatively desirable in the understanding
of this thesis. For this reason, the term resilience also has a positive connotation in this thesis.
6
Engineering Education for Resilient Systems
As aptly put in the title of a guest editorial for the US Journal of Engineering Education, the US
leading journal in this research field: “The climate is changing. Engineering education needs
to change as well” (Martin et al., 2022). Climate change impacts engineering in so far as it
demands a reduction of greenhouse gas emissions, and to mitigate climate change impacts
by designing and building systems that are resilient to increasing natural hazards (ASCE, 2023;
Fleischmann et al., 2020; Helmrich & Chester, 2020; Martin et al., 2022; Moncomble, 2021;
NAE, 2022; NASEM, 2023; Olsen et al., 2015). The American Society of Civil Engineers
(ASCE) state in their Code of Ethics that creating safe, resilient and sustainable infrastructure
is one fundamental principle for governing the engineering profession (ASCE, 2020). Building
on that, in a recent report ASCE discusses the relevance of resilient infrastructure design for
engineers (ASCE, 2023).
To face global challenges, engineering education is key and thus needs to be reshaped to
educate future generations of engineers who are able to react to these challenges and to build
and design resilient systems (Aktan et al., 2021; Fleischmann et al., 2020; Martin et al., 2022;
NAE, 2022; Pagán-Trinidad et al., 2019; Scharte, 2019). In the context of the uncertain and
complex nature of climate change, future engineering practitioners are challenged and con-
fronted by new and even yet unknown problems, where methods and solutions of the past may
not be suitable anymore (Ayyub, 2018; Chester & Allenby, 2018, 2019; Habbal et al., 2024;
Lindsay et al., 2023; Olsen et al., 2015):
Engineers cannot predict all the potential conditions for future infrastructure and systems. The
uncertainty associated with future climate is not completely quantifiable, and therefore account-
ing for it in engineering practice would require an appropriate understanding and treatment of
uncertainty including engineering judgment. (Ayyub, 2018, p. 173)
Thus, a new paradigm for engineering practice is needed that reflects the professional practice
in a VUCA world (ASCE, 2023; Ayyub, 2018; Lindsay et al., 2023; Martin et al., 2022; Olsen
et al., 2015). This requires developing new competencies that go beyond rational problem-
solving activities, i.e., those which foster dealing with uncertainty and complexity, learning from
failure and systems thinking (Chester & Allenby, 2019; Dugan et al., 2023; Habbal et al., 2024;
Hadgraft & Kolmos, 2020; Kamp, 2020; Martin et al., 2022). As one of the engineering students
in my course on resilience (see Chapter 3.3) put it:
It is also the responsibility of engineers to consider not only the technical and known compo-
nents of a system, but also the uncertainties and unknown components. Resilience is therefore
not only about minimizing and controlling risks, but also about being prepared for the unknown,
or adapting flexibly and adaptively to a disaster/crisis. Catastrophes cannot be prevented, but
the decisive factor is how the catastrophe is responded to.
As climate change demands the design of infrastructure in the face of uncertainty and com-
plexity, engineers need to be enabled to design such socio-technical systems that are also
7
adaptive to sudden disturbances, i.e., being resilient (ASCE, 2023; Hollnagel, 2014; NAE,
2022; Park et al., 2013; Salzman et al., 2018; Scharte, 2019). But, from a resilience point of
view, engineers desire “to make things work, not to make things that break down or suddenly
shift their behavior” is contrary to the immanent character of nature (Holling, 1996, p. 38).
Complex socio-technical systems do not behave predictably or deterministically. However, en-
gineers are often taught to solve simple, well-structured problems and to think that results are
pre-determined (Hadgraft & Kolmos, 2020; Jonassen et al., 2006; Jonassen, 2000; Lindsay et
al., 2023; Lönngren et al., 2016; Scharte, 2019). Indeed, when dealing with resilient systems
and even when designing such systems, failure is crucial, as resilience is based upon the idea
of failure and crises: “Disaster happens, things break, failure is real.” (Scharte, 2019, p. 3).
Therefore, the question to ask here is not “Will it fail?”, but “When will it fail and how?” (Foley
et al., 2022, p. 1010) or “What if it fails?”. That means not only considering how climate change
may affect infrastructure design, but especially to analyze and anticipate how failure may in-
fluence other systems or even cause cascading effects (Fekete, 2012; Helmrich & Chester,
2020; Scharte, 2019). Integrating a learning habit of mind that reflects learning from failure is
important to enable engineers to better understand the systems they build, including their po-
tential failures, which may result in disasters (Edmondson & Sherratt, 2022; Foley et al., 2022;
Kamp, 2020). However, current and common infrastructure design and engineering practices
focus on the reduction of damage and consider lower levels of uncertainty and complexity than
climate change demands (Aktan et al., 2021; Helmrich & Chester, 2020; Martin et al., 2022).
To design and develop resilient systems, an integrated systems thinking approach is required,
i.e., to identify not only single critical system components, but rather to analyze and anticipate
the inherent interdependencies of a system and to evaluate feedback loops to other systems
(Aktan et al., 2021; Ayyub, 2018; Habbal et al., 2024; Hadgraft & Kolmos, 2020; Helmrich &
Chester, 2020; Martin et al., 2022; Scharte, 2019). It is crucial to understand that these systems
are characterized by interdependencies and, thus, uncertainty and complexity.
Despite the consensus that engineers need to be able to design resilient systems, existing
research suggests that engineering education hardly prepares future engineering profession-
als for this purpose. To cite another student of my course on resilience (see Chapter 3.3):
In my opinion, dealing with crisis situations plays a major role in our professional field, but one
is often not sufficiently prepared for such topics in one’s studies.
Besides the ongoing call for reforming engineering education to educate future professionals
as change agents, developing competencies that enable engineers to design resilient systems
is crucial to face climate change. However, there has been little research on how resilience is
addressed in engineering education and how engineers can be enabled to design resilient
systems. Specifically, research is needed on what competencies are required for this and what
8
pedagogical approaches are suitable to acquire these competencies. Such research could in-
form and support people involved in engineering education, engineering professionals as well
as researchers in this field.
1.2 The Researcher
Since this thesis was conducted in a cross-disciplinary research field, a brief explanation of my
role as a researcher is provided. I studied environmental engineering (B.Sc., M.Sc.) at the
faculty of civil engineering at RWTH Aachen University. Through my studies, I primarily expe-
rienced passive, teacher-centered and lecture-based teaching. While hardly an element of my
studies, the concept of resilience became a major issue for me early on. I could not understand
why we, as environmental engineers, had little or no contact with it during our studies. I had
already written my master's thesis on resilience at the Research Group Gender and Diversity
in Engineering and, building on this, decided to get to the bottom of this question as part of my
PhD thesis. During my PhD, I had the space and opportunity to design and test teaching and
learning approaches and concepts, where watching students adopt new perspectives and re-
flect on their role as engineers inspired me to contribute to engineering education practice.
Through participation in the European Society for Engineering Education (SEFI), I had the
opportunity to discuss and critically reflect on my research with other scholars in the research
field. This was particularly relevant and supportive as engineering education is a cross-disci-
plinary research field and I did not come into contact with, for example, qualitative methods or
even the term “epistemology” during my engineering studies. This allowed me to reflect on my
own epistemological beliefs and position myself between the two fields education and engi-
neering. This issue will also be elaborated in Chapter 2 of this thesis.
In the context of this thesis, I use the personal pronouns I or We in some places. This is
either to reflect on my position as a researcher and to emphasize that the described research
was carried out by myself or that the specific research was carried out in collaboration with
other researchers.
9
1.3 Research Aim and Thesis Outline
This thesis was started with two main assumptions: First, despite the relevance described
above, there is hardly any research on systems resilience in engineering education. And sec-
ond, engineers are not educated to design resilient systems because the necessary compe-
tencies are not sufficiently addressed in their education. This raises the question of the conse-
quences of the above in terms of dealing with increasing global challenges. The purpose of
the research constituting this thesis was to contribute not only to generating an understanding
of the relevance of resilience in engineering education, but also to developing a framework to
improve engineering education practice. This is done by questioning the current state of the
art from a resilience thinking perspective.
In the context of this introductory chapter, I presented and provided motivations and ration-
ales for the research underlying this thesis. Moreover, I explained my role and perspective as
a researcher. As this thesis is related to the research field of Engineering Education Research
(EER), the second chapter provides an overview of this field of research, covering the devel-
opment of the field, emerging trends and topics, research communities, research approaches,
methodologies and epistemologies. Further, within this chapter, the term competencies in the
context of engineering education is defined and elaborated upon.
Due to the lack of research on resilience in engineering education, the research approach was
iteratively and systematically developed, where each study raises the research questions for
the following ones. In total, seven studies were conducted that build on and complement each
other. The third chapter provides the research results of these studies which are divided the-
matically into three parts: resilience in engineering education research (EER), resilience-re-
lated competencies in engineering education (EE) and practical applications in teaching.
Part 1: Resilience in EER
The first part consists of one study (Paper I), which analyzes the state of the art of resilience
in engineering education research. Based on a systematic literature review (SLR) the following
research questions were addressed in this part:
RQ 1.1: To what extent is resilience addressed and discussed in the context of EER?
RQ 1.2: Which meanings and interpretations of resilience are considered in EER?
RQ 1.3: Which applications of resilience are considered in EER?
Part 2: Resilience-related Competencies in EE
Based on the results of Part 1, the following six research questions were formulated in order
to analyze resilience-related competencies:
10
RQ 2.1: What are resilience-related competencies? (Paper II+III)
RQ 2.2: How to specify resilience-related competencies? (Paper II+III)
RQ 2.3: How far are resilience-related competencies addressed in engineering curric-
ula? (Paper III)
RQ 2.4: How are these competencies formulated? (Paper III)
RQ 2.5: To what extent are learning outcomes suited for evaluating engineering edu-
cation curricula? (Paper III)
RQ 2.6: How (far) are resilience-related competencies addressed in engineering edu-
cation standards and guidelines on the European and international level?
(Paper IV)
Research questions 2.12.2 were addressed in Papers II and III in order to develop a concep-
tual framework for defining resilience-related competencies. This framework was then applied
to the qualification outcomes of engineering study programs in a European context (Paper III),
in which research questions 2.32.5 were addressed. Research question 2.6 refers to accred-
itation frameworks and guidelines as well as to reference frameworks in order to compare the
actual and target state of the art in engineering education. All research questions were an-
swered through a qualitative approach using primarily qualitative content analysis.
Part 3: Teaching Resilience in EE
The third part combines the state of the art of resilience in EER and the competency level of
the second part by focusing on practical applications and implications, i.e., teaching. The fol-
lowing research questions are addressed here:
RQ 3.1: How to teach resilience thinking and resilience-related competencies in engi-
neering education? (Paper VVII)
RQ 3.2: How to assess resilience thinking and resilience-related competencies in en-
gineering education? (Paper VVII)
In this part, case studies were used as the methodological approach by developing and eval-
uating a course concept aimed at addressing resilience-related competencies. This was further
elaborated in a multi case study design by comparing and contrasting different case studies
from different universities to get a holistic view on teaching resilience.
After presenting the results of each study underlying this thesis by addressing the individual
research questions, the results are synthesized and discussed in the fourth chapter. In the
remainder of this chapter, I discuss limitations and further research opportunities in order to
derive contributions to and implications for research and practice in engineering education.
Finally and to conclude, the fifth chapter summarizes the key findings of this thesis.
11
2 Engineering Education Research as a Cross-Disciplinary Field
In the last decades, Engineering Education Research (EER) has emerged as an international,
independent and interdisciplinary field of research targeted at improving engineering education
practice and promoting educational change (Borrego & Bernhard, 2011; Graham, 2012; Johri,
2023). The term EER includes three important components: Engineering, Education and Re-
search (Bernhard, 2015). In the research field of EER, these are inevitably intertwined, as EER
aims to understand student learning in engineering science2, to identify theoretical foundations
for innovations in engineering education and to provide empirical evidence for how these in-
novations impact the learning processes and outcomes of students (Bernhard, 2015; Malmi et
al., 2018). Grounded and influenced by engineering practice, EER is intrinsically context-
bound and defined by the field of engineering.” (Buckley et al., 2023, p. 719). Hence, EER is
not only concerned with how to teach or design suitable learning environments, but also with
what to teach and why to teach certain topics (Bernhard, 2015). This requires an understanding
of complex interactions within the multilevel system of engineering education, including the
actors involved in learning processes, i.e., the students themselves, teachers, educational
management and other stakeholders (Buckley et al., 2023; Cutler & Coso Strong, 2023; Malmi
et al., 2018).
The primary target of EER is improving the education of engineering students by acknowledg-
ing the identity and responsibility of the engineering profession thereby asking why do we
need to engage in EER (Borrego & Bernhard, 2011). Moreover, EER covers a broad range of
topics, such as teaching and learning approaches, competency acquisition, assessment meth-
ods, curriculum development or faculty development (Borrego & Bernhard, 2011; Malmi et al.,
2018). Furthermore, order to better understand the nature and purpose of the research field,
in the 1990s, research about EER itself has emerged and “this field started to write about itself”
(Klassen & Case, 2022, p. 214f.). This resulted especially in bibliometric analyses, focusing on
different aspects (Klassen & Case, 2022; Malmi et al., 2018). These studies are often con-
cerned with getting an understanding of what the emerging research trends are and where
EER is conducted (e.g., Jesiek et al., 2011; Qiu & Natarajarathinam, 2023; Williams et al.,
2016). Others focus on how research is done within EER, including meta-analyses (e.g., Koro-
Ljungberg & Douglas, 2008), analyses on used methodologies and research frameworks (e.g.,
Malmi et al., 2018) or discourses and discourse analyses on quality, rigor and scholarliness
(e.g., Edström, 2017; Klassen & Case, 2022; Riley, 2017).
2 In German Ingenieurwissenschaften
12
According to the above four main concerns within EER (why, what, where and how) and in-
spired by Borrego and Bernhard (2011), the following chapter is structured as follows: First,
motivations for doing EER will be presented, especially focusing on engineering practice (2.1).
Second, a brief overview of emerging research trends in EER is given (2.2). Third, the emerged
and involved research communities and actors within EER are illustrated, with a special focus
on Europe and the US (2.3). Fourth, discourses in EER on methodologies and epistemologies
as well as their underlying tensions are presented (2.4). Finally, the last subchapter (2.5) fo-
cuses on competencies and accreditation in engineering education to provide the thematic
focus of this thesis, i.e., asking where to.
2.1 WHY Motivations for EER
Motivations for doing EER range widely from addressing global challenges, increasing diversity
and inclusion in the field, improving the public image and understanding of the engineering
profession, to preparing students for complex problem-solving (Borrego & Bernhard, 2011;
Johri, 2023). One of the main issues in doing EER is to improve the practice of engineering
education to provide a more purposeful learning experience for students becoming profes-
sional engineers (Borrego & Bernhard, 2011; Dart et al., 2021; Edström, 2017; Jesiek et al.,
2009; Johri, 2023; Kolmos, 2015).
The purpose of engineering education is to provide the learning required by students to become
successful engineers. (Crawley et al., 2014, p. 1)
In other words, “we must educate engineers who can engineer” (Crawley et al., 2014, p. 13).
The need for reforming engineering education is not new and was increasingly addressed in
the last three decades in academia, industry and government to discuss and develop perspec-
tives on desired attributes and skills of engineers (Crawley et al., 2014; Graham, 2012, 2018;
IEA, 2021; NAE, 2004; RAE, 2007; Sheppard et al., 2008; Steuer-Dankert et al., 2019). This
need primarily results in an often-reported misalignment between engineering education and
practice which cause difficulties in the transition process of graduates entering the field of
practice (Brunhaver et al., 2018; Crawley et al., 2014; Flening et al., 2021; Jesiek et al., 2017;
Sheppard et al., 2008; Trevelyan, 2019). Higher Education Institutions (HEIs) have the respon-
sibility to educate engineering students which are experts in their field, are socially responsible
and focused on innovation and thereby are able to conceive, design, implement and operate
systems, products, processes and projects (Crawley et al., 2014; Kamp, 2020). Moreover,
HEIs need to adapt to changing conditions of a VUCA world by recognizing that the acquisition
of knowledge itself is insufficient and instead, focusing on a learner-centered perspective in
order to enable students to cope with uncertainty, complexity and to be flexible to change their
13
perspectives (Habbal et al., 2024; Hadgraft & Kolmos, 2020; Kamp, 2020; Lindsay et al., 2023;
OECD, 2018). Hadgraft and Kolmos (2020) identify three major challenges for the future de-
velopment of engineering education, i.e., sustainability and climate change according to the
SDGs, the fourth industrial revolution, and competencies for entrepreneurship and innovation.
The three challenges represent an increasing complexity for engineering practice, requiring
corresponding competencies. Handling complexity is seen to be an emerging requirement in
engineering curricula, for which a more systemic approach is needed (Dugan et al., 2023;
Habbal et al., 2024; Hadgraft & Kolmos, 2020).
Within the ongoing discourse on reforming engineering education, it has been widely acknowl-
edged that engineers are required to possess not only technical skills and knowledge, but also
competencies that enable engineers to work and act as engineering professionals, i.e., pro-
fessional competencies. This goes along with an often-discussed criticism of the current state
of the art in engineering education focusing primarily on technical skills and knowledge, theo-
ries and mathematical foundations, while underestimating practical applications and related
professional competencies (ASEE, 2020a; Brunhaver et al., 2018; Crawley et al., 2014;
Flening et al., 2021; IEA, 2021; Jesiek et al., 2017; Lindsay et al., 2023; Ramnath et al., 2023;
Sheppard et al., 2008; Trevelyan, 2010b, 2019). However, within discourses about relevant
sets of competencies of engineers, technical and non-technical (so called soft3, social,
transversal or professional) competencies are often separated (Beagon & Bowe, 2023;
Berdanier, 2022; Flening et al., 2021; Passow & Passow, 2017; Shuman et al., 2005). In this
context, non-technical competencies are often not considered as “real engineering”
(Trevelyan, 2010a, n.p.). This (false) dichotomy leads to a false understanding of what the core
of engineering is about (Berdanier, 2022; Jesiek et al., 2017; Passow & Passow, 2017;
Trevelyan, 2010b). Bernhard (2015) states that “educating engineers is a social discipline with
an engineering content” (p. 410), meaning that “the social and technical are inextricably inter-
twined” (Trevelyan, 2009, p. 1). This also applies for addressing complex socio-technical prob-
lems that require systems thinking and the consideration of interdependencies between social
and technical dimensions (Dugan et al., 2023; Habbal et al., 2024).
Looking at several definitions about roles and responsibilities of engineers, they have all in
common that engineers provide services to society (e.g., Crawley et al., 2014; IEA, 2021;
Sheppard et al., 2008) and that one of the central tasks of engineering is the design of systems.
In 2004, the National Academy of Engineering (NAE) defined engineering as
3 I have used quotation marks here because the term “soft” skills is criticized in the EER community. Berdanier
(2022), for example, calls for “A hard stop to the term ‘soft skills’”, as the term “soft” implies a devaluation of these
professional skills. Using this “soft/hard” language leads to students believing that these skills are extras and op-
tional, and not essential to their future engineering career.
14
[…] a profoundly creative process. A most elegant description is that engineering is about design
under constraint. The engineer designs devices, components, subsystems, and systems and,
to create a successful design, in the sense that it leads directly or indirectly to an improvement
in our quality of life, must work within the constraints provided by technical, economic, business,
political, social, and ethical issues. (NAE, 2004, p. 7)
With their report “The Engineer of 2020”, the NAE intended to raise awareness for the increas-
ing global complex problems engineers need to face. They concluded that the educational
system needs to change in order to prepare them for these challenges (Borrego & Bernhard,
2011; NAE, 2004). As crucial attributes for future engineers they emphasize creativity, ingenu-
ity, communication, business, leadership, ethics, professionalism, dynamism, agility, resili-
ence, flexibility and lifelong learning (NAE, 2004). Following on from this, in their book “A Whole
New Engineer”, Goldberg et al. (2019) describe collaborations and approaches to transform
engineering education and define engineering as follows:
Engineers solve problems in complex real-world situations, they design new systems and strat-
egies to adapt to changing times; they make structures and products more user-friendly, re-
sponding to the real needs of communities and people. At its heart, engineering is about serving
people. That role is enhanced by the rapid changes on the planet, which demand a facile, flex-
ible response. (Goldberg et al., 2019, p. 107)
Trevelyan (2019) points out shortcomings in the realm of curriculum design and calls for
stronger collaborations between HEIs, industry and government to ensure that engineers learn
engineering practice, as
Engineers are people with technical knowledge and foresight who conceive, plan and organise
delivery, operation and sustainment of man-made objects, processes and systems that enable
productivity improvements so people can do more with less effort, time, materials, energy, un-
certainty, health risk and environmental disturbances (Trevelyan, 2019, p. 831).
According to these exemplary definitions, serving society by critically reflecting on societal
needs and designing systems lies at the core of what engineers do and what engineering is.
Based on this understanding, engineering education needs to enable to develop these roles
and competencies which requires (disruptive) change to the way engineers are educated
(Borrego & Bernhard, 2011; Crawley et al., 2014; Lindsay et al., 2023; Sheppard et al., 2008).
One of the central movements in the last decades in engineering education is a shift from
teaching to learning, i.e., shifting from passive teacher-centered and lecture-oriented approach
towards active student-centered and competency-focused (i.e., outcome-based) education, as
these increase students’ motivation, deep learning and competency development (Borrego &
Bernhard, 2011; Felder & Brent, 2009; Graham, 2012, 2018; Kamp, 2020; Lucena et al., 2008;
Prince, 2004; Prince & Felder, 2006). By doing EER, these developments can be systemati-
cally understood and thus serve to increase visibility among engineering educators for experi-
ences within their education (Borrego & Bernhard, 2011). Dart et al. (2021) surveyed engineer-
ing education researchers with regard to their rationales for pursuing EER. The participants
outlined intrinsic motivations, characterized by personal interests in teaching and learning and
15
the desire to positively impact both students’ learning experiences and the engineering profes-
sion. However, the authors also found that formalized structures for EER are missing in most
universities. By supporting EER and establishing structures for pursuing EER as a research
career, the educational quality in engineering education could be enhanced (Dart et al., 2021).
By acknowledging all these discourses and motivational aspects for changing engineering ed-
ucation, it is important to consider the aims of EER, i.e., improving engineering education. EER
is not done for its own sake, i.e., the production of and seeking for knowledge must align with
usefulness in an engineering education context, so that knowledge production must imply
knowledge application (Edström, 2017; Kolmos, 2015). This is why EER should rather be con-
sidered a field, and not a discipline (Edström, 2017; Jesiek et al., 2009):
[…] the vision of a ‘pure’ EER discipline with educators reading the journals and implementing
the results, a linear model, cannot be the only model for change. When there already exists so
much valuable and published knowledge, which is not implemented in engineering education,
how can producing more publications be the answer? (Edström, 2017, p. 10)
Research results and publications can be an implicit driver for engineering educators by mak-
ing efforts and innovations in education visible, but they need to be linked (Graham, 2012;
Kolmos, 2015), as “knowing how an innovative educational system could be and how to get
this in place from where you are now is not an easy or a trivial problem(Kolmos, 2015, p.
375).
2.2 WHAT Research Trends and Topics
As an interdisciplinary research field that exists at the intersection of engineering and educa-
tion, EER investigates a broad range of topics, covering students’ learning attitude and pro-
cess, desired competencies, diversity and inclusiveness, teaching contents, approaches and
methods for teaching and learning, assessment, curriculum development, faculty development
or the nature of engineering knowledge, to name a few (Borrego & Bernhard, 2011; Buckley
et al., 2023; Finelli et al., 2016; Katz et al., 2023; Malmi et al., 2018). The recently published
International Handbook of Engineering Education, edited by Aditya Johri (2023), reflects the
diversity of the research field by providing an overview of major and emerging developments
in EER over the past decade. The handbook addresses historical and global analyses of en-
gineering education in order to take an international perspective. One part deals with theoreti-
cal orientations and methodological approaches in EER while another focuses on students’
backgrounds. Other foci deal with pedagogical and curriculum issues, the intersection of tech-
nology and computing in engineering education, and EER methods and assessment.
16
Moreover, the broadness of the research field as well as the development of emerging trends
is well studied through several bibliometric analyses conducted in the last thirty years. Wankat
(2004) performed an analysis of publications in the Journal of Engineering Education (JEE)
from 19932002 by categorizing each article according to its keywords, which describe the
topic of the article. He built his work upon a previous analysis (Wankat, 1999), in which he
analyzed JEE articles from 19931997. The five most assigned keywords are teaching, com-
puters, design, assessment and groups/teams, finding that assessment in particular occurred
more frequently between 19972002. More recently, Qiu and Natarajarathinam (2023) also
analyzed JEE publications, finding an increasing diversity of the keywords used over the period
20042021. Until 2009, the most frequently used keyword was assessment and most papers
focused on learning and assessment. In the period 20052010, psychological topics became
more relevant, especially motivation, self-efficacy, but also gender. In the period 20162021,
the most common keyword was qualitative, related to an increased interest in applied research
methods in EER, followed by gender and a general increase in gender and diversity related
topics. In a special report and guest editorial by JEE, Katz et al. (2023) analyzed trends in
topics and methods applied in JEE publications from 19932022. They found that learning
mechanisms, learning systems, diversity and inclusiveness, assessment and diverse topics
focusing on, e.g., student experiences, faculty development or well-being have emerged
through the years. Moreover, general research trends over time have shown an increasing
focus on topics regarding equity, diversity and inclusion as well as on students’ academic and
professional experiences (Katz et al., 2023). At the same time, articles focusing on assessment
and learning systems decreased during the analyzed time period. Osorio and Osorio (2002)
analyzed articles from JEE and the European Journal of Engineering Education (EJEE) from
19982002 and found the subjects courses, programs, assessment, and society to be most
common in both journals. More extensively, Jesiek et al. (2011) analyzed 2,173 articles and
conference papers from 20052008 in several leading EER journals and conferences and
identified 38 major categories of EER topics. They compare their results and categories to
those from Wankat (2004) and Osorio and Osorio (2002), finding that research topics such as
assessment, design and collaborative learning were still leading. Moreover, they found that
learning was the most common category, followed by assessment and educational technolo-
gies. Students, problem-based learning (PBL) and competencies were also among the most
common categories. Compared to Wankat (2004) and Osorio and Osorio (2002), the authors
assume their high-ranked learning category, instead of teaching, reflects the ongoing shift from
teaching to learning within engineering education (Jesiek et al., 2011). A similar pattern can
be observed for PBL, for which neither Wankat (2004) nor Osorio and Osorio (2002) have
similar categories. In addition, the common categories competencies and engineering skills
might reflect an ongoing movement towards outcomes-based accreditation in several countries
17
(Jesiek et al., 2011). Although not a bibliometric analysis, but more recent, Hadgraft and
Kolmos (2020) identify four emerging trends in learning methodologies in engineering educa-
tion, namely student-centered learning, contextual and practice-based learning, digital learning
and professional competencies. These trends intersect with the above-described development
of research trends within EER, as especially the focus on active and student-centered learning
as well as an outcome-based education focusing on competencies have increasingly devel-
oped during the last decades. This issue is addressed in Chapter 2.5 and is thus not explained
any further at this point.
Applying a self-developed taxonomy, Malmi et al. (2018) analyzed 155 papers published in the
EJEE in 2009, 2010 and 2013. They found 128 different explanatory frameworks, i.e., theoret-
ical and conceptual frameworks in the context of EER, which were clustered in 19 different
categories, each containing several explanatory frameworks. These include theories and/or
models for learning, societal development, assessment, motivation, student attitudes, gender,
creativity or institutional development. A similar pattern, but much more diverse, was observed
when analyzing 62 SEFI conference papers with the same taxonomy (Malmi et al., 2013).
Here, the authors found 89 instances of explanatory frameworks, where the most common
themes were PBL, active learning, constructivism and conceptual understanding. Considering
the small set of analyzed papers, the authors point out the richness of the field covered by the
diverse theories and models applied. In order to map and connect the growing diversity of the
research field, Finelli and Borrego (2015) developed a standardized taxonomy of keywords for
EER which was first published in 20154. Moreover, the taxonomy aims to guide researchers to
consistently assign keywords regarding context, purpose and research approach of their study
(Finelli et al., 2016). The taxonomy consists of 14 branches with several keywords each.
Branches cover assessment, design, diversity, educational level, educational setting, educa-
tional technology, instruction, outcomes, professional practice, recruitment and retention, re-
lated fields, research approaches, theoretical frameworks and teams.
The presented variety of topics, explanatory frameworks and branches reflect not only the
broadness of the research in EER, but also the deficits in engineering practice, and the chal-
lenges and opportunities of the current state of the art of engineering education.
4 In 2021, a third version was published, which can be accessed here: https://taxonomy.engin.umich.edu/taxon-
omy/
18
2.3 WHERE Research Communities
The research field has developed increasingly across the globe and nowadays contains sev-
eral research departments, doctoral programs, journals and conferences (Bernhard, 2018;
Borrego & Bernhard, 2011; Johri, 2023). As EER is an interdisciplinary field of research, stud-
ies are published in a broad range of journals and conference proceedings covering general
educational, engineering discipline-specific or specific engineering education journals and con-
ferences (Borrego & Bernhard, 2011). This chapter will focus on the EER communities in Eu-
rope and the US, as these two regions are characterized by a long history and visibility of EER
and different research approaches in each case, which in turn enables to illustrate the diversity
within the research field (Borrego & Bernhard, 2011; Jesiek et al., 2009).
The research field has its origins in the US and has a high visibility there, going along with a
well-established funding policy for educational innovation, led by the National Science Foun-
dation (NSF) (Edström, 2017; Jesiek et al., 2009; Lucena et al., 2008; Wankat et al., 2002).
The role of the NSF was crucial for the development of the research field by enabling research
careers through funding research on engineering education, e.g., by introducing PhD programs
(Edström, 2017; Lucena et al., 2008). This is well reflected in the rapid growth of the US Journal
of Engineering Education (JEE), published by the American Society for Engineering Education
(ASEE), where most US authors acknowledge NSF grants (Edström, 2017; Valentine et al.,
2023; Wankat, 2004; Wankat et al., 2014). ASEE is an organization aiming to improve engi-
neering education and engineering technology (Osorio & Osorio, 2002), formulating the vision
“excellent and broadly accessible education empowering students and engineering profession-
als to create a better world” (ASEE, 2020b). Since 1993, ASEE has published the peer re-
viewed journal JEE and runs an annual conference. JEE is “the most important venue for dis-
seminating engineering education research in the United States” (Wankat, 2004, p. 13). The
mission and vision statement of JEE is to serve “to cultivate, disseminate, and archive scholarly
research in engineering education” by seeking “to help define and shape a body of knowledge
derived from scholarly research that leads to timely and significant improvements in engineer-
ing education worldwide” (JEE, 2024b).
In Europe, a funding agency as such in the US is absent, and the EER movement has devel-
oped more slowly and was based primarily on bottom-up processes (Edström, 2017; Lucena
et al., 2008). For example, as part of the ASEE, the Educational Research and Methods (ERM)
division has existed since more than 40 years, whereas the European Society for Engineering
Education (SEFI) established working groups focused on EER in 2008 (Borrego & Bernhard,
2011; Edström, 2017). The non-profit organization SEFI was created in 1973 aiming to directly
connect institutions of Higher Engineering Education in Europe and “to create a common iden-
tity for European engineering education” (Osorio & Osorio, 2002, p. 53). Nowadays, SEFI is
19
the largest network focused on engineering education in Europe (Côme & Maffioli, 2013; SEFI,
2017). The mission of SEFI is “to contribute to the development and the improvement of engi-
neering education in Europe, to emphasise the need for and to strengthen the image of both
engineering education and engineering education professionals in society” (SEFI, 2017). SEFI
holds an annual conference, and publishes the European Journal of Engineering Education
(EJEE) since 1975. Originally, EJEE aimed to provide news and information to SEFI members,
with no intentions “to become the major research journal it has matured to” (Wankat et al.,
2014, p. 8), as the financial burden would have been too huge for the non-profit organization
SEFI. However, EJEE has developed in the last two decades towards more research-based
content while still aiming to support the interdisciplinarity of the field (de Graaff, 2017; Jesiek
et al., 2011; Neto & Williams, 2017) and is nowadays described as “a forum for scholarly dia-
logue to further engineering education” (EJEE, 2024a). EJEE has the policy of inviting different
types of publications (e.g., research papers, position papers, case studies), in particular con-
tributions which combine scholarliness and usefulness to improve engineering education (de
Graaff, 2014, 2017; EJEE, 2024a). EJEE thus explicitly emphasizes both aspects, while JEE
refers to scholarliness only (see also Edström, 2017). Moreover, in January 2024, SEFI re-
leased its Journal of Engineering Education Advancement, aimed at supporting innovations
and practice experiences in engineering education (JEEA, 2024).
Despite the slower development of the EER community in Europe, the European research
community is more diverse than the one in the US (Edström, 2017; Valentine & Williams,
2024). Most people in Europe entered EER from other backgrounds than being trained in EER,
as it is the case in the US (Edström, 2017). Some people are researchers of engineering edu-
cation related disciplines, others are faculty members, university leaders or academics en-
gaged in reform activities (Edström, 2017). This is also reflected in the research foci of individ-
ual EER authors, as Valentine and Williams (2024) found that most European authors who
published in EE journals have produced considerably more non-educational publications than
educational ones.
The diversity of the European and US research communities can also be observed in the re-
spective editorial boards of JEE and EJEE. In the EJEE, the distribution of members from
European and non-European universities is quite balanced, whereas in the JEE, members
from US universities are dominant (EJEE, 2024b; JEE, 2024a). The European diversity of the
research community is also well represented in the geographical distribution of authors pub-
lishing in the conference proceedings of the two societies (SEFI and ASEE) as well as in the
respective published journals (EJEE and JEE) (Williams et al., 2016). In their citation analysis,
Williams et al. (2016) analyzed contributions from these four publication venues, finding that
in European publications both US and authors from other countries are cited and thus, covering
20
a broader view of EER perspectives. They also found that US publications primarily reference
other publications with US affiliations. The authors conclude “As the latter group of researchers
is numerically larger, this suggests that the EER community as a whole is not yet global in its
perspective.” (Williams et al., 2016, p. 9). This may be caused by the huge funding agency in
the US, but also because of different research foci or even unawareness of scholars in other
countries (Williams et al., 2016). Earlier studies on authors and citations in JEE compared to
EJEE show similar findings regarding an US-centric perspective of JEE authors and a greater
geographical diversity in EJEE (e.g., Osorio & Osorio, 2002; Wankat et al., 2014). The recent
bibliometric analysis of JEE publications by Qiu and Natarajarathinam (2023) also shows a
high dominance of US authors in this journal. Besides JEE and EJEE, the predominance of
US scholars is also reflected in other major EER journals, as the study by Jesiek et al. (2011)
has shown. Their analysis of 2,173 empirical research papers in several EER journals and
conference proceedings up to 2008 found that the three top author locations were the US
(36%), the EU (29%) and Australia (23%).
Despite the described national differences, there have been efforts to cultivate an international
research community in order to develop a global network of researchers and practitioners
within EER and to intense the exchange among the specific communities (Edström, 2017;
Jesiek et al., 2010; Jesiek et al., 2011; Lucena et al., 2008; Williams & Wankat, 2016). Re-
garding the European and US communities, one example is the partnership project between
JEE and EJEE, called Advancing the Global Capacity for Engineering Education Research
(AGCEER), which was initiated by the former editors of the two journals in 2007. The goals of
the initiative were to build a network among the community, to identify the critical infrastructure
needed to develop a global community and to report on the role of EER for research and
practice (Lohmann & de Graaff, 2008). In this project, workshops were conducted on several
engineering education conferences in 2007 and 2008 and the results were published in both
journals (Jesiek et al., 2010). Based on this initiative, the Research in Engineering Education
Network (REEN) was established where people involved in EER were invited to biannually
Research in Engineering Education Symposia (REES) in order to share their research (de
Graaff, 2014, 2017).
2.4 HOW Methodologies and Epistemologies
Several studies on methodological approaches in EER were published, with some focus on
the use and differences of quantitative, qualitative and mixed research methods (Borrego et
al., 2009; Case & Light, 2011). Similarly, some studies provide taxonomies in order to classify
and conceptualize different research approaches and topics within EER (e.g., Finelli et al.,
21
2016; Malmi et al., 2012). Others focus on reviews and meta-analyses in order to analyze how
authors in EER apply research methods to provide an overview of the various research para-
digms in the field (e.g., Koro-Ljungberg & Douglas, 2008; Malmi et al., 2013; Malmi et al., 2012;
Osorio & Osorio, 2002; Wankat, 2004). Furthermore, e.g., Case and Light (2011) and Baillie
and Douglas (2014) discuss the concepts of methodology and epistemology focusing on qual-
itative research and Goncher et al. (2023) on the use of theories within EER. Moreover, some
authors focus explicitly on the aspect of quality in EER, such as Klassen and Case (2022),
Borrego et al. (2009) or Bernhard and Baillie (2013). In this chapter, those discourses are
presented and summarized in order to provide a methodological context for the research un-
derlying this thesis.
As EER has developed into an independent and interdisciplinary field of research, quality is-
sues have emerged and have been addressed accordingly (Malmi et al., 2018). This is espe-
cially due to the fact that most people entering EER are primarily trained in engineering disci-
plines and are not familiar with educational research (Bernhard & Baillie, 2013; Borrego, 2007;
Borrego et al., 2009; Borrego & Newswander, 2008; Buckley et al., 2023; Dart et al., 2021;
Wankat et al., 2002). Borrego and Newswander (2008) argue that “engineering education work
is inherently cross-disciplinary” (p. 131, my emphasis) and others describe EER as a “complex
melding of disciplines” (Buckley et al., 2023, p. 718). Klassen and Case (2022) describe EER
as a second-order region, as EER is based on its two first-order (or parent) regions, i.e., edu-
cation and engineering (see Figure 1).
22
Figure 1. Engineering education as a second-order region (Klassen & Case, 2022, p. 217)
Thus, knowledge and methodologies from the first-order regions need to be recontextualized
in EER. Accordingly, several challenges with regard to methodological and conceptual bound-
aries or difficulties arise (Borrego, 2007; Borrego & Bernhard, 2011; Borrego & Newswander,
2008):
Beyond perspectives from the traditional disciplines in which engineering educators were
trained, engineering education researchers try to balance practical implications of the work with
experimental control. (Borrego & Bernhard, 2011, p. 24)
Borrego (2007) identified five conceptual difficulties for trained engineers becoming engineer-
ing educational researchers, i.e., framing research questions with broad appeal, grounding
research in a theoretical framework, fully considering operationalization and measurement of
constructs, appreciation of qualitative or mixed-methods approaches, and pursuing interdisci-
plinary collaboration (p. 100). These difficulties can be contextualized epistemologically. En-
tering a new field of knowledge and collaborating cross-disciplinarily require a view on episte-
mology, as it implies the perceived legitimacy of research questions, aims and methods
(Borrego & Newswander, 2008). Epistemology, as a person’s “way of knowing and under-
standing the world” (Borrego & Newswander, 2008, p. 125), is crucial when it comes to cross-
disciplinary collaborations, as one’s individual epistemology cannot be applied to other
23
disciplines. Initially, cross-disciplinary research starts with the recognition of one’s limited ex-
pertise in a discipline and the need for other perspectives. Furthermore, a person’s way of
knowing and understanding affects collaborations with people from different academic fields,
particularly when these are completely different (Borrego & Newswander, 2008). Thus, for en-
gineers, entering EER as a new, cross-disciplinary and second-order field of research and
collaborating with educators and social scientists means to realize that other ways of knowing
and understanding exist and to identify their own epistemological framework (Baillie & Douglas,
2014; Bernhard & Baillie, 2013; Borrego & Newswander, 2008; Seniuk Cicek et al., 2023). In
an engineering context, this is especially relevant because
The scientific paradigm of engineering is so widely accepted and understood that many tech-
nical research decisions need not be defended. Thus, education research requires additional
explicit steps that are implicit in engineering research. (Borrego, 2007, p. 101)
Further, as in engineering science “the nature and discovery of knowledge is historically a
given, […] the term epistemology is not necessarily discussed, or used (Seniuk Cicek et al.,
2023, p. 4). Thus, engineers entering EER may perceive a tension between the epistemologi-
cal beliefs of engineering and social science-based education causing “epistemological strug-
gles” (p. 2).
In a study on the transition process of engineers towards EER, the participants report on an
evolution in their epistemological beliefs, especially regarding research design, validity and
theory (Dart et al., 2021). In order to work within and learn about EER, interdisciplinary re-
search collaborations are therefore important and purposeful (Borrego & Newswander, 2008;
Dart et al., 2021). This can be supported by formalized structures, as networking and institu-
tional factors were shown to be positive impact factors for developing an EER identity (Dart et
al., 2021; Gardner & Willey, 2016). However, most universities lack these structures (Dart et
al., 2021). Moreover, Rodrigues et al. (2021) found that having the support of a community
positively influences an engineering education researcher’s motivation to “overcome the chal-
lenges of thriving in a dual-disciplined field and pushing against resistance to change” (n.p.).
Those transition challenges are particularly relevant when applying qualitative or mixed-
method research. Both are perceived as more difficult and unfamiliar for engineers, as they
are primarily trained in quantitative research. This may lead to an overestimation and predom-
inance of quantitative research in EER (Bernhard & Baillie, 2013; Borrego, 2007; Borrego et
al., 2009; Case & Light, 2011; Koro-Ljungberg & Douglas, 2008). Typically, applying quantita-
tive research and often following a (post-)positivist tradition, engineering is frequently con-
cerned with identifying “how outcomes are determined by reducing plausible causes to a dis-
crete set of indicators or variables” (Borrego et al., 2009, p. 54). The post-positivist perspective
assumes the existence of an empirical truth which can only be falsified and not confirmed,
24
where the positivist perspective states that the truth can be identified (Borrego et al., 2009;
Koro-Ljungberg & Douglas, 2008). Quantitative research, usually relying on (post-)positivism,
aims to use statistics on data in order to test hypotheses generated by theory and developed
in advance (Bernhard & Baillie, 2013; Fenner et al., 2023; Koro-Ljungberg & Douglas, 2008).
Put in an educational context this would mean that “one teaching method is ‘better than an-
other’. Qualitative researchers would rarely make such a claim but might question what ‘better’
actually means.” (Bernhard & Baillie, 2013, p. 2) Educational research follows rather an inter-
pretivist perspective, where multiple subjective realities are assumed to exist and truth is so-
cially constructed, situational and context-dependent (Fenner et al., 2023; Koro-Ljungberg &
Douglas, 2008). Thus, interpretivist educational research is inherently concerned with qualities
such as learning in highly variable human beings in not controllable environments and settings
(Dart et al., 2021; Wankat et al., 2002), as
students are far more difficult to categorize than I-beams or transistors or even fruit flies, and
the factors that influence their learning (including inherited traits, home environments, prior ed-
ucational experiences, current knowledge and skill levels, learning styles, personality types, and
present life circumstances) are virtually uncountable. (Wankat et al., 2002, p. 6)
For that reason, Fenner et al. (2023) question whether (quantitative) EER can be considered
as positivist in any case, as EER is concerned with the subjective nature of human experience
(p. 444). As EER covers multiple topics, perspectives and cross-disciplinary collaborations, the
underlying research approaches should also reflect this diversity. For example, Case and Light
(2011) provide an overview of qualitative methodological approaches developed in neighbor-
ing disciplines “emerging” in EER, such as case studies, grounded theory or discourse analy-
sis, but point out that these “are promising but as yet not well represented in engineering edu-
cation research” (p. 190) at that time. However, a development has also taken place in this
regard in recent years, which is briefly outlined in the following.
In their review and meta-analysis of qualitative research in EER, Koro-Ljungberg and Douglas
(2008) analyzed JEE papers published in 2005 and 2006. They found not only a predominance
of quantitative research articles, but also a limited discussion on methodology in EER, i.e., why
a method was used, and a lack of epistemological consistency, i.e., integrating theory, re-
search design and methodology in those few articles which were qualitative. As qualitative
research is based on epistemological and theoretical assumptions that might not be familiar to
engineering education researchers, this requires a deeper understanding of qualitative re-
search practice (Borrego et al., 2009; Koro-Ljungberg & Douglas, 2008). The authors point out
that
one of the dangers in conducting qualitative research is that it may appear easy and less rigor-
ous than quantitative research. While quantitative research requires use of statistical methods
which can provide an aura of trustworthiness, qualitative research can appear at first glance as
if it simply involves interviewing a few people and then writing up a summary. […] In fact,
25
qualitative research can be just as difficult to conceptualize, and be as methodologically and
theoretical challenging, if not more challenging, than quantitative research. (Koro-Ljungberg &
Douglas, 2008, p. 172)
By enrichening and increasing the applied research approaches within EER, especially regard-
ing qualitative research, more areas of interest, such as students’ ways of learning or how they
interact with each other, can be understood better (Koro-Ljungberg & Douglas, 2008).
Malmi et al. (2012) developed a taxonomy of the research process in EER which was designed
to improve EER by providing an overview of different research approaches and to raise aware-
ness for the variety of research paradigms applied in this field. The taxonomy categorizes re-
search papers in six dimensions: Nature (empirical, case reports, theory or position pa-
pers/proposals), explanatory framework (theories, models, frameworks), research strategy
(i.e., research design, such as experimental and survey research), data source (e.g., inter-
views, questionnaires, examinations etc.), data analysis (quantitative, qualitative or mixed
methods), and reporting (i.e., how clearly the research has been reported). In a further study,
they analyzed 155 EJEE papers focusing on how the research process was carried out (Malmi
et al., 2018). They found that most analyzed papers were classified as empirical work and have
a clear research strategy, but data analysis methods include mainly simple descriptive statis-
tics or, in the case of qualitative studies, simple or undocumented research methods. Moreo-
ver, they point out shortcomings in terms of formulating research questions, methodology and
limitations. Goncher et al. (2023) report on a similar pattern, focusing particularly on theoretical
frameworks and find a lack of consistency in the use of theories. Qiu and Natarajarathinam
(2023) call for more quantitative studies in EER, as a result of a bibliometric analysis of JEE
papers. The criticism of the dominance of quantitative methods in EER has already been noted
above. The fact that Qiu and Natarajarathinam (2023) arrive at a different result might be due
to the methodology used, as they only report on the occurrence of keywords related to quan-
titative methods, which does not provide an insight into the methods used or their quality. How-
ever, also in terms of JEE publications, Katz et al. (2023) point out that quantitative methods
were used primarily for several years, but the number of qualitative studies has increased and,
in 2022, the two methodological approaches were almost used equally. In addition, mixed-
methods approaches have also been increasingly applied in recent years (Katz et al., 2023).
In any case, methods in EER have become more diverse over the years, and researchers have
become more open towards using diverse methods. Given the different research communities
in the US and Europe (see Chapter 2.3) it is noteworthy that the various analyses of papers
from both JEE (US) and EJEE (Europe), nevertheless, come to similar conclusions with regard
to the quality of research. Thus, the research communities are not further differentiated here
either, even though they are characterized by different traditions to educational research
26
approaches5 (Bernhard, 2015; Borrego & Bernhard, 2011). The different research traditions
are also mirrored on the journal websites, where, as described in Chapter 2.3, EJEE explicitly
invites contributions which combine scholarliness and usefulness (such as case studies),
whereas JEE refers to scholarliness only.
Quality issues in EER are widely discussed, as presented above. To ensure quality in EER,
Borrego and Bernhard (2011) propose the following criteria, as quality scholarship in engineer-
ing education is:
- Inspired by real educational problems.
- Informed by theory and other literature describing prior work within and beyond the
field/home country.
- Systematic and intentional, with documented decisions ideally based on well-planned
collection and analysis of empirical data.
- Consistent with the perspectives and methodologies chosen (quantitative, qualitative
or mixed).
- Presented (at least in part) in a form that engineering academic staff can understand
and use, including by discussing implications of the research.
- Situated in international and interdisciplinary contexts, by demonstrating awareness of
how common the problem is, what is being pursued elsewhere, and the likelihood that
results are or are not generalizable/transferable to other contexts (disciplines and/or
countries) (Borrego & Bernhard, 2011, p. 38).
Bernhard and Baillie (2013) discuss and expand these criteria further, focusing on the quality
of the study in general (e.g., awareness and acknowledgment of different knowledge traditions
and cultures, the use of theory, setting research questions, consistency within a study), the
quality of the results (e.g., richness in meaning, structure of the results, contribution to theory
development and new knowledge) and the validity of the results. Following these criteria, it is
important to understand and reflect deeply on the underlying epistemology to be able to com-
prehend and judge quality in EER (Baillie & Douglas, 2014; Bernhard & Baillie, 2013; Borrego
& Bernhard, 2011). This accompanies the choice of methodology which is always determined
by the research question to be asked (Borrego et al., 2009; Case & Light, 2011). The opposite
approach to methodology would imply to constrain the kinds of questions to be asked. Thus,
the discourse on quality in EER should not be based on an apparent dichotomy of quantitative
or qualitative methods. Indeed, the broad range of approaches, topics and cross-disciplinary
collaborations within EER enables, accordingly, to ask a broader range of questions (Borrego
et al., 2009; Case & Light, 2011).
5 See Borrego and Bernhard (2011) for further details about the Europe vs US differences in research approaches
in an educational context. These especially intersect the European Didaktik- and Bildung-traditions which are be-
yond the scope of this thesis.
27
Klassen and Case (2022) describe EER as a region due to its relationships to other academic
fields and fields of practice. They further consider the strength of boundaries between these
fields from which theory and methods are usually applied and suggest looking at parent disci-
plines with regard to both theoretical and methodological direction as well as the field of prac-
tice from which the problems for EER studies are guided. This is in line with the objectives of
doing EER (cf. Chapter 2.1), as it is especially important to always consider the aspect of
practical application, i.e., usefulness. Otherwise, “There is some danger that EER may develop
into a silo that does not communicate with technically oriented engineering professors”
(Wankat et al., 2014, p. 7). Malmi et al. (2018) also refer to this concern, stating that “For EER
researchers, the most interesting papers are obviously found among research papers, but for
engineering education practitioners the case reports could be more relevant” (p. 185). In their
recent work, Buckley et al. (2023) show that a very large portion of the references of 1,407
papers published since 2018 are relating to EER journals or conference proceedings. The
authors advise to consider research beyond EER publication venues and to engage more
broadly in higher education research, as often similar questions are asked there. Finally, in
order to contribute to both scholarliness and usefulness, the above-described quality criteria,
based on epistemology, can contribute to more quality in the research field (Edström, 2017).
2.5 WHERE TO? Competencies in Engineering Education
This chapter briefly summarizes current discourses on competencies in engineering education,
as competencies are a central aspect of this thesis. However, this thesis does not aim to syn-
thesize all discussed competencies or to provide a list of all mentioned competencies in the
literature. Instead, the focus is set on providing an overview and background of the current
discourses.
A Competent Engineer
It is important to acknowledge that several definitions and understandings on competency exist
in multiple contexts (OECD, 2005; Rychen & Salganik, 2000; Woollacott, 2009). Within this
thesis, the definition provided by Passow (2012) will be used, as it includes several domains
of knowledge and language from other disciplines. Hence, competencies are defined as
the knowledge, skills, abilities, attitudes, and other characteristics that enable a person to per-
form skillfully (i.e., to make sound decisions and take effective action) in complex and uncertain
situations such as professional work, civic engagement, and personal life. (Passow, 2012, p.
97)
Thus, competencies include more than knowledge and skills, as the concept of competency
implies complex action systems and refers “to the ability to meet demands of a high degree of
28
complexity” (Rychen & Salganik, 2000, p. 8). According to Woollacott (2009), three basic ele-
ments of the concept of competency apply:
- It is a latent, acquired, or developed attribute (an ability, capacity, or characteristic)
possessed by a person.
- It is related to the intentional execution of tasks.
- It implies a value judgment on the quality of the ability, capacity, or characteristic and
that this quality is assessed against formally or informally defined criteria by observing
or measuring how effectively intended tasks are performed (p. 261).
These elements emphasize that competency and performance are linked, as the assessment
of competencies is accompanied by the intended consequences of a performed task. Moreo-
ver, the development of competencies is a process of (lifelong) learning, occurring in multiple
settings. In the context of an outcome-based education, related terms are learning outcomes
or graduate attributes, specifying the competencies students are expected to acquire after
completing their study programs (Passow & Passow, 2017). Referring to engineering educa-
tion, the development of competencies reflects the ongoing process of the development of an
engineering professional (IEA, 2021).
There is a body of literature identifying and classifying which competencies are required for
successful engineering practice and which ones are most important. These studies often in-
clude surveys with different stakeholders, such as students, faculty members or industry per-
sonnel (e.g., Beagon & Bowe, 2023; Flening et al., 2021; Male et al., 2011; Murray et al., 2022;
RAE, 2007) or literature reviews and meta-analyses (e.g., Beagon et al., 2019; Passow &
Passow, 2017; Winberg et al., 2018). The research on competency development in engineer-
ing education is grounded in the often-reported difficulties in the transition process of engineer-
ing graduates entering engineering practice and a lack of competencies besides technical skills
and knowledge (Beagon & Bowe, 2023; Brunhaver et al., 2018; Flening et al., 2021; Jesiek et
al., 2017; Trevelyan, 2019, see also Chapter 2.1).
Moreover, several frameworks exist which classify engineering work and translate this work
into higher-level outcomes or competencies, such as accreditation standards and guidelines
(Crossin et al., 2023; Lucena et al., 2008). These competency frameworks usually provide
preliminary lists of higher-level outcomes for engineering work and seek to narrow down the
expected competencies of engineers (Crossin et al., 2023).
In 1997, the US Accreditation Board for Engineering and Technology (ABET) adopted the En-
gineering Criteria 2000 (EC 2000), which represents the movement towards an outcome-
based education by focusing on students’ competencies (ABET, 2021b; Lucena et al., 2008).
To be accredited, engineering programs were required to formulate learning objectives that
29
include both technical and professional skills (Wankat et al., 2002). This movement represents
an “important milestone” within engineering education, by “transforming ABET from a con-
servative regulator of engineering curricula to an agent of change” (Lucena et al., 2008, p.
435). In the current version of EC 2000, seven student outcomes are formulated, and additional
outcomes can be formulated by specific engineering programs (ABET, 2022, see
Figure 2).
Criterion 3. Student Outcomes
The program must have documented student outcomes that support the program educational objectives. Attainment
of these outcomes prepares graduates to enter the professional practice of engineering. Student outcomes are out-
comes (1) through (7), plus any additional outcomes that may be articulated by the program.
1. an ability to identify, formulate, and solve complex engineering problems by applying principles of engineering,
science, and mathematics.
2. an ability to apply engineering design to produce solutions that meet specified needs with consideration of public
health, safety, and welfare, as well as global, cultural, social, environmental, and economic factors.
3. an ability to communicate effectively with a range of audiences.
4. an ability to recognize ethical and professional responsibilities in engineering situations and make informed judg-
ments, which must consider the impact of engineering solutions in global, economic, environmental, and societal
contexts.
5. an ability to function effectively on a team whose members together provide leadership, create a collaborative
and inclusive environment, establish goals, plan tasks, and meet objectives.
6. an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering
judgment to draw conclusions.
7. an ability to acquire and apply new knowledge as needed, using appropriate learning strategies.
Figure 2. ABET student outcomes (ABET, 2022)
This movement towards an outcome-based education in engineering education is also well
reflected in bibliometric analyses by, e.g., Jesiek et al. (2011) or Wankat (2004), where the
authors each found a rise in EER on competencies. Wankat (2004) found that ABET EC 2000
was the most cited reference from 19982002 in JEE papers, indicating how much these cri-
teria attracted the attention of engineering educators and researchers. In Europe, the Bologna
Reform shaped the movement towards outcome-based education and the formulation of learn-
ing outcomes in study programs (Bologna Working Group on Qualifications Frameworks, 2005;
Lucena et al., 2008). With regard to engineering programs, the European Network for Engi-
neering Accreditation (ENAEE) was founded in 2006 and implemented the EUR-ACE® system
which labels accredited engineering programs. The EUR-ACE® Standards and Guidelines for
Accreditation of Engineering Programs include eight learning areas, each with specified learn-
ing outcomes for bachelor’s and master’s degrees (see Table 2 for an excerpt).
30
Table 2. Exemplary excerpt from the EUR-ACE learning areas (ENAEE, 2021)
The learning process should enable bache-
lor’s degree graduates to demonstrate:
The learning process should enable master’s de-
gree graduates to demonstrate:
Knowledge and
Understanding
knowledge and understanding of the
mathematics, computing and other basic
sciences underlying their engineering
specialization, at a level necessary to
achieve the other program outcomes;
knowledge and understanding of engi-
neering fundamentals underlying their
specialization, at a level necessary to
achieve the other program outcomes, in-
cluding some awareness at their fore-
front;
awareness of the wider multidisciplinary
context of engineering.
in-depth knowledge and understanding of
mathematics, computing and sciences underly-
ing their engineering specialization, at a level
necessary to achieve the other program out-
comes;
in-depth knowledge and understanding of engi-
neering disciplines underlying their specializa-
tion, at a level necessary to achieve the other
program outcomes;
critical awareness of the forefront of their spe-
cialization;
critical awareness of the wider multidisciplinary
context of engineering and of knowledge issues
at the interface between different fields.
These are compliant with the European Framework of Qualifications (EQF) for the European
Higher Education Area (EHEA) (ENAEE, 2021).
Internationally, the Washington Accord is the leading agreement among national accreditation
bodies for engineering programs from several countries. On signing the Accord countries
agree to grant the same rights to graduates of programs by other signatory organizations (IEA,
2014). Today, organizations from 20 different countries are signatories of the Washington Ac-
cord (IEA, 2024). It was initially signed by six organizations from Australia, Canada, Ireland,
New Zealand, the UK and the US in 1989, as they found their individual accreditation pro-
cesses, requirements and criteria to be equivalent. The Washington Accord alongside other
agreements led to the formation of the International Engineering Alliance (IEA) in 2007, serving
as an umbrella organization for those agreements (IEA, 2014). The IEA formulates its vision
as to
Improve the global quality, productivity and mobility of engineers by being an accepted inde-
pendent authority on best practice in standards, assessment and monitoring of engineering ed-
ucation and professional competence. (IEA, 2014, p. 6)
Since 2013, IEA also has a relationship with ENAEE to maximize understanding and benefits
of the two organizations, as it was recognized that their accreditation processes are similar
(IEA, 2014). The former Washington Accord Graduate Profile contained several elements
which include graduate attributes that are generic to all engineering disciplines. These were
refined over years and adopted by the signatories as a reference point to assess the substan-
tial equivalence of their own accreditation requirements (IEA, 2014). The current and revised
version (2021.1) represents the Graduate Attributes and Professional Competencies (GAPC)
international benchmark and reflects the current state of the art in engineering practice and
addresses global challenges, as the SDGs (IEA, 2021). Here, a distinction is made between a
graduate attribute (11 characteristics) and a professional competency (13 characteristics) pro-
file (see Table 3 for an excerpt). Graduate attributes are those expected of graduates from an
31
accredited program and “form a set of individually assessable outcomes that are the compo-
nents indicative of the graduate’s potential to acquire competence to practise at the appropriate
level” (IEA, 2021, p. 3). Professional competencies, conversely, “must be assessed holistically”
and build upon the individual students’ attributes to independently work in practice (IEA, 2021,
p. 6).
Table 3. Exemplary excerpt from IEA professional competency profile (IEA, 2021)
Differentiating Characteristic
Comprehend and apply universal
knowledge:
Breadth and depth of education and
type of knowledge
Comprehend and apply local knowledge:
Type of local knowledge
Problem analysis:
Complexity of analysis
In their extensive and often cited review, Passow and Passow (2017) synthesized several
quantitative and qualitative studies aimed at developing a comprehensive list of generic engi-
neering competencies and their relative importance. Their analysis resulted in 16 engineering
competencies which were mapped to the former Washington Accord and ABET competencies.
The authors found problem solving to be the core activity of engineering practice and that
technical competency is “inseparably intertwined with effective collaboration” (Passow &
Passow, 2017, p. 491). Moreover, the comparison to the ABET and Washington Accord com-
petencies have shown that the competencies considered important for engineering practice
differ from the required outcomes and attributes of the accreditation bodies. This is because a
separation of learning outcomes does not provide a holistic view on engineering approaches,
in which competencies are intertwined (Passow & Passow, 2017). To provide a unified classi-
fication of engineering activities and competencies, Crossin et al. (2023) recently developed
an engineering practice taxonomy. Their final taxonomy consists of 86 common engineering
activities, paired to 17 engineering competencies (including the 16 competencies by Passow
& Passow, 2017) and paired to the eleven IEA graduate attribute characteristics. Moreover,
the EER Taxonomy by Finelli and Borrego (2015) (see Chapter 2.2) covers a broad range of
competencies, categorized in the outcomes branch. Keywords include communication, crea-
tivity, leadership, problem solving or teamwork, to name a few.
Besides different views on the relevance of specific competencies, a lack of consensus in de-
scribing and defining competencies is often reported. First, there are several terms used to
describe the set of competencies engineering graduates should acquire, such as professional
skills (e.g., Beagon & Bowe, 2023; Shuman et al., 2005), transversal competencies (e.g., Cruz
32
et al., 2020), professional competencies (e.g., Craps et al., 2021; Lowe et al., 2022) or generic
competencies (e.g., Boelt et al., 2022; Male et al., 2011). Second, the understanding and def-
inition of specific competencies differ widely, as, for example, the systematic literature reviews
by Craps et al. (2021) and Cruz et al. (2020) have shown. The authors point out that the ana-
lyzed studies rarely define competencies and highlight a lack of rules for identifying or as-
sessing competencies which may lead to different interpretations of similar concepts. Beagon
(2021) provides several examples of different ways in describing competencies and stresses
“a lack of consistency in terminology and interpretation conceptually” (p. 21). This becomes
particularly relevant when different stakeholders are surveyed primarily using a pre-defined list
of competencies, as their epistemological beliefs may vary. Beagon et al. (2019) suggest re-
viewing and defining the different conceptions of each competency beforehand in order to
avoid misunderstandings by the participants. This point is, again, underlined by the study by
Passow and Passow (2017), who also found the wordings of competencies to be very diverse,
which is central to stakeholders making decisions about curricula.
The CDIO Approach
A more holistic perspective on relevant competencies and attributes of engineers is reflected
in the Conceive-Design-Implement-Operate (CDIO) approach. In response to the lack of con-
vergence between engineering education and practice, the CDIO Initiative was formed in 1999
by Massachusetts Institute of Technology, Chalmers University of Technology, KTH Royal In-
stitute of Technology and Linköping University (Crawley et al., 2014; Edström & Kolmos, 2014).
The CDIO approach has the aim to educate students who are able to
- Master a deeper working knowledge of technical fundamentals.
- Lead in the creation and operation of new products, processes, and systems.
- Understand the importance and strategic impact of research and technological devel-
opment on society (Crawley et al., 2014, p. 13).
Crawley et al. (2014) state that an absence of rationale and an absence of detail are the key
reasons for the misalignment between engineering education and practice. Thus, lists of de-
sirable engineering skills often lack a rationale why these skills are desirable. Furthermore,
they often do not provide more detail to be understood or implemented, which is also reflected
in the study by Passow and Passow (2017). Therefore, the starting point for the CDIO ap-
proach was restating the underlying need for engineering education:
We believe that every graduating engineer should be able to: Conceive-Design-Implement-Op-
erate complex value-added engineering products, processes, and systems in a modern, team-
based environment. The rationale is essentially a restatement of the fact that it is the job of
engineers to be able to engineer. (Crawley et al., 2014, p. 50)
33
Thus, the acronym CDIO represents engineering practice and, accordingly, an integrated sys-
tem approach to curriculum development (Crawley et al., 2014; Edström & Kolmos, 2014).
Taking the CDIO premise as a foundation for engineering education, more detailed and under-
standable learning outcomes can be derived. For this purpose and to address the described
shortcomings, the CDIO Syllabus was developed “by creating a clear, complete, and con-
sistent set of goals for engineering education, in sufficient detail that they can be understood
and implemented by engineering faculty” (Crawley et al., 2014, p. 50). The Syllabus was first
published in 2001 (1.0), with revised versions in 2011 (2.0) and 2022 (3.0) (Crawley, 2001;
Crawley et al., 2011; Malmqvist et al., 2022). Based on stakeholder input and validation, the
Syllabus lists and categorizes topics and qualities that reflect desirable competencies of engi-
neering graduates to be prepared for engineering practice. It can be used as a reference frame-
work for setting goals for curricula (Edström & Kolmos, 2014; Malmqvist et al., 2022).
In the current version 3.0 (Malmqvist et al., 2022), the Syllabus addresses global challenges
and change drivers in a VUCA context in more detail, as the topics sustainability, digitalization
and acceleration were added. In total, the Syllabus includes five overarching sections, each
with additional levels of detail regarding graduate qualities: (1) Fundamental Knowledge and
Reasoning, (2) Personal and Professional Skills and Attributes, (3) Interpersonal Skills: Col-
laboration, Teamwork and Communication, (4) Conceiving, Designing, Implementing and Op-
erating Systems in the Enterprise, Societal and Environmental Context The Innovation Pro-
cess, and (5) the expanded CDIO Syllabus: Leadership, Entrepreneurship and Research. Fig-
ure 3 showcases an excerpt from the Syllabus with all levels of detail.
Figure 3. Excerpt from the CDIO Syllabus (Malmqvist et al., 2022)
Moreover, the Syllabus was validated by comparing it to other accreditation frameworks, such
as EUR-ACE (Malmqvist, 2009) and ABET (Crawley et al., 2011). As the Syllabus contains
more detail and rationale (i.e., covering the whole lifecycle of a process, system or product), it
34
was found that engineering programs based on the Syllabus would also meet the other ac-
creditation standards. Paul et al. (2015) analyzed the specific lists of graduate attributes of 17
national organizations accredited according to the Washington Accord and compared these to
the second version of the CDIO Syllabus. The authors found that all categorized graduate
attributes were represented in the CDIO Syllabus, which indicate a similar use of attributes
within accreditation bodies and the CDIO Syllabus.
Today, the CDIO Initiative is a worldwide community with member institutions who adopt the
CDIO approach, but with a comparatively large European share, especially in Nordic countries
(Crawley et al., 2014; Malmqvist et al., 2019; O’Connor et al., 2023). Since 2005, it runs its
own annual conference and publishes the related CDIO proceedings. Over the last years, more
emphasis has been placed on EER, as a specific EER track was introduced at the conference
in 2016 and the review criteria for papers related to this track were developed based on
Bernhard and Baillie (2013) (see Chapter 2.4, Edström, 2017; Edström et al., 2020). Thus,
CDIO can strengthen EER and vice versa, as CDIO connects many people from diverse insti-
tutions, backgrounds and experiences, where the CDIO perspective is a common ground
(Edström, 2017). However, as the systematic literature review by O’Connor et al. (2023) has
shown, publications with a focus on EER have plateaued since then and studies with a focus
on implementing CDIO or experiences from practice are still the main part of contributions of
the conference (see also Kamp, 2021). By prioritizing “educational impact above all else”
(Edström, 2017, p. 11), the CDIO community is, indeed, concerned with usefulness and pri-
marily focused on practitioners in engineering education (Kamp, 2021). However, the approach
does not only contribute to an intersection of usefulness and new understandings (Edström,
2017; Edström et al., 2020). Going beyond that, adapting a CDIO perspective also contributes
to a holistic view of engineering practice by educating engineering students who are “ready to
engineer” in a systemic way (Crawley et al., 2014, p. 34).
35
3 Research Results Resilience in Engineering Education
After having presented the research context of EER in which this thesis took place, the results
of the individual papers are summarized in the following section. As already described in Chap-
ter 1.3, the research approach was iteratively developed, whereby the results of each study
led to the research questions for the following ones. The aim of the research underlying this
thesis was to contribute not only to generating an understanding of the relevance of resilience
in engineering education, but also to developing a framework to improve engineering education
practice by questioning the current state of the art from a resilience thinking perspective in
order to better prepare engineering students to design resilient systems. Thus, this thesis is
based on an interpretivist educational research perspective (see Chapter 2.4 for further de-
tails). In this context, I used different methodological approaches in each study. As explained
in Chapter 2.4, the choice of methodology should always be determined by the research ques-
tion (Borrego et al., 2009; Case & Light, 2011). Correspondingly, the methodological approach
of each study emerged and was developed according to the respective research questions
and purpose.
In total, seven studies were conducted that build on and complement each other. These have
three foci: resilience in engineering education research, resilience-related competencies in en-
gineering education and practical applications in and implications for teaching.
3.1 Part 1: Resilience in Engineering Education Research
The first part of this thesis consists of a systematic literature review (SLR), which is part of
Paper I, aimed at answering the following research questions:
- RQ 1.1: To what extent is resilience addressed and discussed in the context of EER?
- RQ 1.2: Which meanings and interpretations of resilience are considered in EER?
- RQ 1.3: Which applications of resilience are considered in EER?
Thus, the SLR served as a starting point for analyzing the state of the art of resilience in EER.
Context of the Study
Initially, the motivation for the review was to find out to what extent resilience-related compe-
tencies are addressed within European EER by analyzing all EJEE and SEFI publications.
Synonyms for resilience used in the resilience literature served as keywords for the initial
search. However, it became apparent during the peer review process that this research pur-
pose was based on the assumption that resilience is covered adequately in EER, i.e., looking
at resilience-related competencies is only possible if resilience itself is a research area.
36
For this reason, we completely changed the narrative of the study and instead examined the
extent to which resilience is addressed in EER publications and how the term is used. Although
the focus of this thesis is systems resilience, we deviated from this as we wanted to examine
more generally what understanding of resilience underlies EER. This is especially important
as the concept of resilience is used in various disciplines and has different meanings and def-
initions (Alexander, 2013; Brand & Jax, 2007; Martin-Breen & Anderies, 2011). These differ
both in context and in terms of the object of resilience. There are several literature reviews on
the use of the term that illustrate this, such as the studies by Gasser et al. (2021) and Mayar
et al. (2022) on systems resilience, Ropp and Belt (2020) on individual resilience, or Norris et
al. (2008) on community resilience. Therefore, it is crucial to examine which or whose resilience
to what disturbance is considered. This means, the question “Resilience of what to what” needs
to be answered to clearly define the underlying context and object of resilience (Carpenter et
al., 2001). Correspondingly, we addressed this question on resilience in EER in order to create
a theoretical foundation for this thesis and further research.
Methodology
Systematic Literature Reviews (SLRs) are conducted in several disciplines and follow trans-
parent and reproducible procedures in order to synthesize the literature on a given topic
(Borrego et al., 2014; Petticrew & Roberts, 2006; Phillips et al., 2023). As explained in Chapter
2.4, EER is an interdisciplinary field of research, drawing on different methodologies and com-
munities. To better access and synthesize the literature in EER, Borrego et al. (2014) published
a study on SLRs in EER, serving as a guide for EER practitioners and researchers. Corre-
spondingly, their study was the methodological foundation for our literature review. As we
aimed to derive implications for the use of the concept of resilience in EER and to direct future
research by generating an overview of this topic, we decided to conduct a SLR as a starting
point for this thesis.
For this purpose, a literature search in the databases Education Resources Information Center
(ERIC), Web of Science and Scopus was conducted. Following a transparent research proto-
col and formulating inclusion and exclusion criteria according to Borrego et al. (2014) (see
Table 4), 67 out of 526 publications were included in the final analysis. In order not to narrow
down the results and to acknowledge the cross-disciplinary nature of the EER field, only the
keywords ‘Resilien*’ and ‘Engineering Education’ were used for selecting the publications.
37
Table 4. Inclusion and exclusion criteria for the SLR (Winkens & Leicht-Scholten, 2023b)
Category
Criterion
Inclusion criteria
Exclusion criteria
Explanation
Publication
type
(i)
Peer reviewed journal arti-
cles, conference papers,
books or book chapters,
written in English.
Not peer reviewed articles
and non-English articles
and/or other publication
types, such as editorials or
reviews about resilience in
the context of engineering
education.
Quality assurance of the re-
search. Reviews focusing on re-
silience are excluded, as re-
views do not review other (simi-
lar) reviews, but they are consid-
ered for the discussion of the re-
sults.
Educational
context
(ii)
Research was conducted
in the context of engineer-
ing education in colleges
or universities.
Research was conducted
in the context of primary
and secondary school ed-
ucation.
The research questions focus on
engineering education in higher
education institutions.
Resilience
context
(iii)
Resilience is addressed in
the context of engineering
education.
Resilience and engineer-
ing education are dis-
cussed independently of
one another (e.g., “The
university is a resilient uni-
versity because of [...].
Furthermore, the univer-
sity is a leader in engi-
neering education be-
cause of [...].”).
The research questions focus on
resilience in engineering educa-
tion research.
Purpose
(iv)
Resilience is addressed in
the study as part of the
study.
Resilience is mentioned
only indirectly and is not
discussed or further men-
tioned (e.g., only a project
title contains “resilience”).
The focus of this study is to ex-
plore the application of resili-
ence in engineering education
research. Therefore, resilience
must be an aspect of the study
under review.
Results
In terms of demographic distribution, most publications included were conducted in the US,
which reflects the predominance of US contributions in EER (see Chapter 2.3). In total, 27
journal articles and 40 conference papers were included in the review. The majority of confer-
ence papers were published in EER conference proceedings and most of them in the leading
US (ASEE) conference. However, the results are more heterogeneous in terms of journals, as
about half of the included papers were not published in specific EER journals. Furthermore,
the taxonomy by Malmi et al. (2012), which was presented in Chapter 2.4, was applied to
differentiate between the nature dimension (i.e., empirical, case reports, theory or position pa-
pers/proposals) of the included studies. We found that most studies used qualitative methods
and of these, most used a case study approach.
In terms of resilience, we based our analysis on the questions formulated by Carpenter et al.
(2001): 1) Resilience of what? 2) Resilience to what? We found that question 1) could be an-
swered on two levels: individual and systems resilience. These two levels served as overall
categories for answering question 2). In total, resilience is either addressed as a personal at-
tribute of engineering students to, e.g., stress or failure in their studies, or as a teaching content
for engineering students learning about resilient systems. Two studies deal with resilience on
both levels. Table 5 provides an overview of the results.
38
Table 5. Overview of different resilience levels and objectives of resilience within included records (Winkens &
Leicht-Scholten, 2023b)
Resilience of what?
Records
Resilience to what?
Objective
Engineering students
38
Temptation to give up their studies
(Persistence)
Change of educational settings
(Adaptation)
Failures and errors
(Learning)
Stress, adverse and challenging
situations
(Coping)
Students should be resilient
Resilience as a desired
attribute/competency
Systems (Infrastructure,
cities, communities)
27
Natural hazards
(General) hazards, disasters, threats
Social threats and disasters
Students should learn about (de-
signing) resilient systems
Both
2
Natural hazards
Temptation to give up their studies
Both of the above
The majority of studies deals with resilience on an individual level. Within this category, most
studies were part of education related publications and are concerned with engineering stu-
dents’ resilience to stress, failure or temptation to give up their studies. Here, resilience was
often used synonymously with terms such as grit, persistence or mental toughness. On a sys-
tem level, most publications either deal with natural hazards or threats in general. Within these,
a common theme was the call for integrating systems resilience into teaching and curricula of
engineering students, and, at the same time, several studies pointed out a gap in this regard.
Furthermore, civil engineering students were addressed most frequently, as most studies deal
with resilient infrastructure. Publications in this category are broadly distributed in terms of
research areas and not exclusively linked to EER venues.
During the analysis, it became apparent that less than half of the included studies provide a
definition or explanation of resilience. We were able to derive the respective meaning of resil-
ience from the research context in order to categorize the studies, but for future work, using
clear theoretical concepts or definitions could clarify the discourse on resilience in engineering
education. At the same time, those papers that provide a definition strongly differ in the used
theoretical framework for defining resilience. No canonical definition of resilience was appar-
ent.
3.2 Part 2: Resilience-related Competencies in Engineering Education
As explained in Part 1, the first version of the SLR was aimed at synthesizing resilience-related
competencies within EER. However, we found that this approach was based on the assump-
tions that: First, resilience itself being covered adequately in EER and second, it being clear
how resilience-related competencies are actually specified. These assumptions turned out to
39
be questionable, which is why we then deviated from them. Instead, we took a generalist look
at how the concept of resilience is understood and applied in EER (see Part 1) and turned to
resilience-related competencies as a next step. These are the focus of Part 2 of this thesis.
Based on the results of Part 1, the following six research questions were formulated in order
to analyze resilience-related competencies:
- RQ 2.1: What are resilience-related competencies? (Paper II+III)
- RQ 2.2: How to specify resilience-related competencies? (Paper II+III)
- RQ 2.3: How far are resilience-related competencies addressed in engineering curric-
ula? (Paper III)
- RQ 2.4: How are these competencies formulated? (Paper III)
- RQ 2.5: To what extent are learning outcomes suited for evaluating engineering edu-
cation curricula? (Paper III)
- RQ 2.6: How (far) are resilience-related competencies addressed in engineering edu-
cation standards and guidelines on the European and international level? (Paper IV)
Note that the definition for competencies used in this thesis was already provided in Chapter
2.5:
the knowledge, skills, abilities, attitudes, and other characteristics that enable a person to per-
form skillfully (i.e., to make sound decisions and take effective action) in complex and uncertain
situations such as professional work, civic engagement, and personal life. (Passow 2012, p. 97)
What are resilience-related competencies? How to specify resilience-related compe-
tencies? (RQ 2.1 and 2.2)
A first approach to specify resilience-related competencies is given in Paper II. Here, we de-
veloped a conceptual framework for defining and characterizing resilience-related competen-
cies. Based on theoretical concepts and definitions of resilience we derived competencies that
are linked to resilience, such as dealing with uncertainty, complexity or systems thinking. This
was done based on the work by Francis and Bekera (2014) who summarized abilities that
accompany different definitions and contexts of resilience. However, we realized that a speci-
fication with regard to the relevance of single competencies for resilience is required, as it
cannot be stated that a single competency addresses resilience. Thus, we proposed the fol-
lowing division for characterizing resilience-related competencies (see Winkens & Leicht-
Scholten, 2021):
Specific resilience-related competencies (SR): Included are competencies that are inherent to
the idea of resilience, such as dealing with uncertainty, the ability to adapt or anticipating future
scenarios. The competencies in this category can be described as sufficient for characterizing
resilience., i.e., possessing these competencies enables engineers to design resilient systems.
40
General resilience-related competencies (GR): Included are all competencies that are only
implicitly linked to resilience, like problem solving or critical thinking. However, these may be
necessary preconditions for a practical application of resilience.
Nevertheless, the categorization of resilience-related competencies presents a significant chal-
lenge. For example, there are competencies that are closely linked to engineering work and
that also address resilience, such as complex problem solving or systems thinking. However,
if a student is able to solve complex problems, the same student is not necessarily capable of
designing resilient systems. Therefore, researchers have to consider the overall context and
how individual competencies can be linked to actually address resilience. This was done in
Paper III, in which we analyzed selected learning outcomes of engineering study programs of
European universities (see next subchapter).
Since the definition and characterization of resilience-related competencies proved to be diffi-
cult, but we still wanted to examine study programs in terms of their resilience-related compe-
tencies, in Paper III, we collected different competencies based on several relevant definitions
of resilience that correspond to the SR mapping described above (Table 6). All selected com-
petencies characterize abilities in the context of disturbances or disasters and may refer to
either resilience of individuals or systems or both, relating to the definitions provided.
Table 6. Key competencies characterizing resilience (adapted from Winkens & Leicht-Scholten,
2023a)
Competencies
Sources (selection)
Anticipating
Francis and Bekera (2014); Hollnagel (2014); NASEM (2022); Park et al. (2013)
Adapting
Carpenter et al. (2001); Hollnagel (2014); NRC (2012); Park et al. (2013)
Absorbing
Folke (2016); Holling (1973); NRC (2012); Walker et al. (2004)
Preparing
NASEM (2022); NRC (2012); Park et al. (2013); UN (2015a)
Recovering
Linkov et al. (2016); NASEM (2022); NRC (2012); Walker et al. (2004)
Responding
Berkes (2017); Francis and Bekera (2014); Park et al. (2013); UN (2015a)
Transforming
Carpenter et al. (2012); Folke (2006); Meerow et al. (2016); Walker et al. (2004)
Learning (from failure)
Carpenter et al. (2001); Folke (2006); Hollnagel (2014); Park et al. (2013)
Recognizing/
monitoring threats
Francis and Bekera (2014); Hollnagel (2014); Linkov et al. (2016); Park et al. (2013)
Dealing with uncertainty
Carpenter et al. (2012); Folke et al. (2021); Linkov et al. (2016); Park et al. (2013)
Dealing with complexity
Carpenter et al. (2012); Folke et al. (2021); Linkov et al. (2016); Park et al. (2013)
Developing with change
Carpenter et al. (2001); Folke et al. (2010); Meerow et al. (2016); Walker et al. (2004)
Systems thinking
Francis and Bekera (2014); Hollnagel (2011); Meerow et al. (2016); Walker et al. (2004)
How far are resilience-related competencies addressed in engineering curricula? How
are these competencies formulated? (RQ 2.3 and 2.4)
After having provided an overview on how far resilience is covered within EER (Chapter 3.1)
and having conceptualized resilience-related competencies, the next step was to analyze how
far these are covered in engineering curricula. For this purpose, in Paper III, we analyzed 35
41
Master of Science engineering programs of five leading technical universities in Europe, called
the IDEA League: Chalmers University of Technology (Sweden), Delft University of Technol-
ogy (The Netherlands), ETH Zurich (Switzerland), Polytechnic University of Milan (Italy) and
RWTH Aachen University (Germany). These universities are each among the universities with
the highest number of engineering graduates in their respective countries. Thus, they are taken
as examples of the state of engineering education in Europe. As this thesis is concerned with
resilient systems in the context of climate change and natural hazards, the selection of study
programs was focused on environmental-related study programs. Moreover, we focused our
analysis on master’s degree programs, as they present the second cycle of the qualification
framework of the EHEA. This means that master’s degree programs build on and include the
acquired competencies in the first cycle, i.e., bachelor degrees (Bologna Working Group on
Qualifications Frameworks, 2005; EHEA, 2018b).
The basis for the analysis were the intended learning outcomes (LOs) of each study program.
LOs were selected for analysis, as they represent and specify the competencies students are
expected to acquire after graduation and demonstrate what students are able to do and know
(Passow & Passow, 2017), see Chapter 2.5. Further, LOs can be differentiated in their levels
of complexity, as several taxonomies suggest (e.g., Bloom's taxonomy of educational
objectives Bloom, 1956).
All material was available in English and analyzed in the summer of 2022. We analyzed the
LOs by applying a directed content analysis. As a directed content analysis aims “to validate
or extend conceptually a theoretical framework or theory” (Hsieh & Shannon, 2005, p. 1281)
by applying “conceptual categories to a new context” (Humble, 2009, p. 37), this method is
especially useful for our research purpose. By deductively using the pre-defined competencies
as presented in Table 6 as initial coding categories, we assigned each LO to these categories
in a first step. Next, all LOs not directly coded were analyzed again to examine whether they
describe a further sub-category. In addition to the competencies listed in Table 6, resilience
itself was also searched for, as well as disaster-related terms, to avoid LOs referring to it but
perhaps not containing the appropriate words. Finally, we inductively formed sub-categories
to summarize the respective context of the LOs per category. Table 7 presents an excerpt from
the final categorization, as an example for “dealing with uncertainty”.
42
Table 7. Excerpt from the categorization of LOs (Winkens & Leicht-Scholten, 2023a)
Initial
Categories
Sub-Categories
Learning Outcomes
Ability to
deal with un-
certainty
Recognize un-
certainty
Are able to recognize uncertainties in solutions and allow for them
Are able to recognize and take into account the uncertainties of approaches
Coping with un-
certainty
Cultivate professional attributes, such as a willingness to make qualified estimations
and assumptions and a readiness to face open-ended problems and uncertain data
Can solve engineering problems professionally, including: Conceptual modelling,
Qualitative and quantitative design, Analysis with respect to uncertainty, Finding solu-
tions and, information for decisions
Convincingly communicate results to specialist and non-specialist audiences, both
verbally and in writing, with due attention to uncertainties
Is competent in spatial planning, understands the contribution of urbanism to critical
challenges in society and is able to manage uncertainty
Is able to cope with the uncertainty involved in multi-actor system behavior, system
context and futures, and can justify methods choices, while taking into account these
uncertainties
The results of the analysis in Paper III indicate the following aspects with regard to resilience:
- Five out of 35 study programs did not contain any resilience-related competencies.
- Eight study programs imply a strong reference to system’s resilience.
- One study program contains an LO which explicitly names system’s resilience.
- All resilience references refer to system’s resilience, not to individual resilience.
- Most study programs contain LOs that refer to the ability to deal with complexity, i.e.,
complexity was assigned most frequently.
In summary, our analysis verifies the assumption that resilience is insufficiently covered in
engineering programs. Most of the time, we had to combine different competencies to derive
a specific resilience reference. For example, removing the competencies relating to complexity
or lifelong learning would result in only a few assignments which underlines the difference
between what we defined as “general” and “specific resilience” above (see RQ 2.1 and 2.2).
To what extent are learning outcomes suited for evaluating engineering education cur-
ricula? (RQ 2.5)
This research question arose from Paper III and was not originally intended. Even though it
does not explicitly refer to resilience, it is a relevant finding from the research results concern-
ing engineering education in general. From a normative point of view, the Diploma Supple-
ments of each study program should be analyzed with regard to LOs, as these serve as stand-
ardized documents for ensuring transparency and comparability of qualification frameworks
within EHEA (2018a). However, only two universities provided these documents, the others
refer to their official regulations for degree programs as they include the same LOs as the
Diploma Supplements.
When analyzing the LOs for resilience-related competencies, we found that they were formu-
lated very heterogeneously regarding scope, comprehensiveness, depth of content and
43
reference to the respective subject. This was the case not only when comparing different uni-
versities, but also when comparing study programs from the same university. In the case of
two universities, several study programs contained identical LOs, thereby not differentiating if
the graduate studied, e.g., civil or electrical engineering. Thus, we also assessed the EUR-
ACE learning outcomes for engineering degree programs, as they are compliant with the EQF
(see Chapter 2.5), to find out whether the duplications at least meet the EUR-ACE criteria.
However, this was not the case either. That finding was surprising as we initially assumed a
corresponding implementation of the EQF and instead found indications for difficulties in the
transition caused by the Bologna Reform. Furthermore, in some cases, we could find more
differentiated LOs on the websites of the universities than in the Diploma Supplements. How-
ever, we deliberately did not use these for the analysis since Diploma Supplements are sup-
posed to contain the official graduate attributes.
The results of the analysis of the LOs of selected engineering degree programs then led to the
following research question to find out to what extent the results from Paper III meet the re-
quirements of frameworks and accreditation specifications.
How (far) are resilience-related competencies addressed in engineering education
standards and guidelines on the European and international level? (RQ 2.6)
In both Papers II and III, an obvious implication was to also examine accreditation standards
and guidelines for engineering programs in terms of resilience-related competencies, espe-
cially when trying to identify reasons for the absence of resilience in curricula. In Paper IV, we
did this as a follow-up study to Paper III, using the EUR-ACE and ABET criteria as well as the
CDIO Syllabus as examples (see Chapter 2.5 for further details). As already described in
Chapter 2.5, all three are relevant as they serve as blueprints for learning outcomes of engi-
neering programs. Further, in this study, we also consider the US perspective and do not ex-
clusively focus on master’s degree programs. Moreover, an additional author from a different
discipline was involved in this study to further validate the categorization of LOs to resilience-
related competencies of Paper III.
In case of ABET, we analyzed the seven general student outcomes (see
Figure 2 in Chapter 2.5) and all additional discipline-oriented outcomes as given in the current
version of ABET criteria (ABET, 2021a). For EUR-ACE, we included the LOs for both bache-
lor’s and master’s degrees in the last version from 2021 (ENAEE, 2021). The CDIO Syllabus
as well as its connection to the other two frameworks was presented in detail in Chapter 2.5
and was included in this analysis.
Table 8 shows the mapping of the pre-defined resilience-related competencies to the three
frameworks.
44
Table 8. Resilience-related competencies in EUR-ACE, ABET and CDIO (Winkens et al., 2023)
Framework \
Competencies
ABET**
EUR-ACE:
Bachelor***
EUR-ACE:
Master
CDIO 3.0
Anticipating
4.1.6, 4.1.7, 4.2.6, 4.2.5, 4.4.1,
5.1.2*, 5.1.7*
Adapting
2.3.2, 2.4.3, 4.3.2, 4.3.4, 5.1.8*
Absorbing
Preparing
CYS, FRP
4.2.1
Recovering
Responding
2.4.3, 4.1.2, 4.2.1
Transforming
Learning
(from failure)
General Outcomes
x
x
2.2.4, 2.4.7
Recognizing/ moni-
toring threats
CYS, CBB
x
x
2.1.5, 4.2.6, 4.3.1, 5.1.6*, 5.1.7*
Dealing with
uncertainty
ENV, PET, CIV,
SYS, CON
3x
2.1.1, 2.1.4, 2.2.2, 2.2.3, 2.2.4,
2.3.1, 2.4.1, 4.3.2, 4.5.2, 5.1.7*
Dealing with
complexity
General Outcomes,
CYS, ECT, MIN,
NCR, SFT, SRV,
SYS
5x
7x
2.1.2, 4.1.2, 5.1.7*
Developing with
change
x
x
2.3.4, 2.4.6, 4.3.1, 4.3.2, 4.3.5,
4.4.1, 4.6.3, 4.6.4
Systems thinking
CYS, ENV, PET,
CIV, SYS, ARC,
BIM, CON, EMG,
EME, IND, MEX,
NAV, OPT
x
2.3: 2.3.1, 2.3.2, 2.3.3, 2.3.4
4.3.2, 4.3.3, 4.3.4, 4.3.6, 4.4.3,
4.4.6, 4.5.5, 5.1.8*
* indicates items from the CDIO Extended Syllabus
** Abbreviations for ABET engineering program categories: CYS Cybersecurity, ENV Environmental, PET Petroleum, CIV
Civil Engineering, ECT Electrical, Computer, Communications, Telecommunication(s), MIN Mining, NCR Nuclear, Radio-
logical, SFT Software, SRV Surveying, SYS Systems, CBB Chemical, Biochemical, Biomolecular, ARC Architectural,
BIM Bioengineering, Biomedical, CON Construction, EMG Engineering Management, EME Engineering Mechanics, IND
Industrial Engineering, MEC Mechanical, NAV Naval Architecture, Marine Engineering, Ocean Engineering, OPT Opti-
cal, Photonic, FRP Fire Protection
*** x indicates a mention, 3x/5x/7x indicate multiple mentions
We found that resilience itself was mentioned only once in all analyzed documents, that is in
the CDIO 3.0 Syllabus. Compared to our analysis in Paper III, resilience-related competencies
were covered in more detail. The general ABET student outcomes as requirements for all study
programs contain no resilience-related competencies that go beyond dealing with systems and
solving complex problems, which is also mirrored in our previous study. However, some spe-
cific degree programs contain a strong reference to resilience, such as Cybersecurity. In case
of EUR-ACE criteria, the results are similar with regard to the bachelor’s level. At the master’s
level, the criteria show a broader set of resilience-related competencies compared to ABET.
Finally, the CDIO Syllabus contains a strong reference to resilience-related competencies. Not
only is resilience itself mentioned here, but the Syllabus also calls for a broad set of compe-
tencies suitable to enable engineers to design resilient systems. Correspondingly, systemati-
cally integrating the CDIO Syllabus could serve to address resilience-related competencies in
engineering curricula.
In summary and in comparison to the results of Paper III, we can see a discrepancy between
accreditation requirements as well as the CDIO Syllabus and the practical implementation in
45
engineering study programs in terms of resilience-related competencies. Especially CDIO
stands out, as it contains strong references to resilience, which is very different from most
study programs.
3.3 Part 3: Teaching Resilience in Engineering Education
After Part 1 dealt with the state of research on resilience in EE and Part 2 with resilience-
related competencies and their representation in engineering curricula, this last part addresses
the concrete application in EE, i.e., teaching. The third part combines three case studies (Pa-
pers VVII). For each case study the research aim was to introduce and discuss a teaching
and learning concept with regard to resilience thinking and its implications for students’ com-
petency development. Thus, they all address the following research questions:
- RQ 3.1: How to teach resilience thinking and resilience-related competencies in engi-
neering education?
- RQ 3.2: How to assess resilience thinking and resilience-related competencies in en-
gineering education?
Case studies were chosen as the methodological approach, as case studies are suitable for
addressing research purposes which are concerned with the specific application of innovations
to improve teaching and learning within EER by generating knowledge in a particular context
(Case & Light, 2011). Further, case studies are useful to underline the validity of the findings
emerged from the previous analyses of Part 2 and 3 (Case & Light, 2011). So far, we found
that resilience is not addressed comprehensively either in research or in selected engineering
curricula. In particular, the analysis of LOs, which describe competencies, only allows limited
conclusions to be drawn about which competencies students actually acquire in practice. For
this purpose, case studies are needed that examine teaching and learning approaches for
acquiring resilience-related competencies.
Context
When dealing with complex, ill-defined and real-world problems, which are inherent to resili-
ence, teaching and learning approaches are required that enable engineering students to ap-
proach these problems (Hadgraft & Kolmos, 2020; Kolmos et al., 2020). As resilience is an
interdisciplinary and complex concept, it is difficult to teach (Kharrazi et al., 2018). However,
research has shown that student-centered teaching and learning approaches which empha-
size active learning, such as collaborative and problem- or project-based learning are suitable
for dealing with resilient systems in education (Ban et al., 2015; Fazey, 2010; Kharrazi et al.,
2018). At the same time, the SLR from Part 1 revealed that while some case studies exist, they
have shown a lack of students’ knowledge and understanding regarding systems resilience
46
(e.g., Chittoori et al., 2020; Pagán-Trinidad et al., 2019; Rokooei et al., 2022; Salzman et al.,
2018). To address this gap, I developed a course concept for a master’s seminar, called “Re-
silience and socio-technical systems” which serves as a basis for all three papers in this part.
Papers V and VI present and discuss the course concept and its development.
The course is an elective in the master’s programs civil, environmental and industrial engineer-
ing at RWTH Aachen University. Table 9 presents the intended learning outcomes of the
course, following Bloom’s taxonomy (Bloom, 1956).
Table 9. Intended learning outcomes and resilience-related competencies addressed in the course
Taxonomy
Learning Outcomes (see Winkens et al., 2024)
Resilience-related Competen-
cies (see Table 6)
Creating
Students develop solution approaches to foster resilience for cri-
sis situations.
Anticipating
Adapting
Preparing
Responding
Recognizing threats
Learning from failure
Dealing with uncertainty
Dealing with complexity
Developing with change
Systems thinking
Evaluating
Students assess existing crisis management approaches regard-
ing their resilience potential.
Students reflect on resilience-oriented approaches and ways of
thinking in their future work as engineers. Moreover, they reflect
on the relevance of resilience-oriented approaches to local and
global crises.
Analyzing
Students analyze different scenarios with regard to their resili-
ence effects.
Applying
Students apply resilience-oriented approaches to practice-re-
lated decisions.
Understanding
Students outline, compare and contrast different interdisciplinary
discourses regarding the concept of resilience. They understand
the relevance of crises in the 21st century.
Remembering
Students define resilience with its various conceptions.
During the course, students are not only introduced to the concept of resilience and its inter-
disciplinary discourses, they also independently develop a case study of their own. As part of
that, they both assess crisis events that have already occurred, such as the 2021 flood in
Germany or Hurricane Katrina in 2005, in terms of resilience, and also develop resilience-
related solution approaches themselves. With regard to resilience-related competencies, as
presented in Part 2, the course and its tasks address particularly complex problem solving,
dealing with uncertainty, systems thinking, anticipating, adapting and learning from failure (see
Table 9 for all addressed competencies).
By applying problem-, case-based, self-directed, reflective and collaborative learning, students
deal with a case they chose on their own in the context of resilience thinking. As resilience is
closely linked to learning from failure, students were required to write a learning diary in order
to foster more in-depth reflection and to trace their learning process during their groupwork in
the course. This allows me to assess what students have learned after the course with regard
to resilience-related competencies, and to emphasize the learning process which has under-
pinned their learning outcomes. For a detailed description of the course concept, content and
didactic approaches, I refer to Papers V and VI.