How to teach resilience thinking in engineering education

ABSTRACT

A rapidly changing world with a high degree of uncertainty in the context of climate change requires sustainable and resilient infrastructures, for which engineers are jointly responsible. For this purpose, engineering students need to acquire competencies such as dealing with complexity and uncertainty, systems thinking and anticipatory thinking, which are linked to resilience. However, research has shown that engineering education falls short of providing future professionals with these competencies. This case study aims to give a holistic view of a teaching approach to address these shortcomings in the context of problem- and case-based learning. Based on a pre-post survey and reflective diaries, students’ perception of their competency development and their learning progress are analyzed and discussed, following a mixed-methods approach. Findings indicate that both perception of competencies related to systems resilience, such as analyzing scenarios and evaluating crisis approaches, and interpersonal competencies, such as communication and resolving conflicts have significantly improved during the course. At the same time, the former were less pronounced before the course and developed the most during the course. The results underline the need for fostering engineering students’ ability to dealing with resilience issues in order to design resilient infrastructure.

KEYWORDS:

• Resilience
• engineering education
• anticipatory thinking
• systems
• learning approaches
• competencies

1. Introduction

Facing global challenges, as formulated in the United Nations’ Sustainable Development Goals (SDGs), requires the design of resilient infrastructure, for which engineers are jointly responsible (ASCE, 2023; Martin et al., 2022; Olsen et al., 2015; Pearson et al., 2018; Scharte, 2019). In this context, resilience describes the ability of systems not only to be prepared and withstand sudden adverse events, but also to recover and to learn from these while developing adaptive capacity to better cope with similar future events (Folke et al., 2010; National Research Council, 2012; Walker, 2020; Walker et al., 2004). Resilience is part of several SDGs, such as SDG 9 ‘Industry, Innovation and Infrastructure’, SDG 11 ‘Sustainable Cities and Communities’ and SDG 13 ‘Climate Action’ (UN, 2015). In the goals 9 and 11, resilience is also mentioned as an explicit overarching goal. In the context of this study, we are concerned with resilience from an integrated social-ecological-technical systems perspective, not merely considering the technical aspects of systems, but also the stakeholders involved.

Given the fact that climate change is leading to increasing uncertainty and complexity, innovative and adaptive solutions and approaches are required (Ayyub, 2018; Chester & Allenby, 2018, 2019; Helmrich & Chester, 2020). Accordingly, future engineering professionals need to acquire corresponding competencies in their education. However, research has indicated at various levels that this is not sufficiently the case. First, there are only few studies dealing with resilient infrastructure in engineering education (Winkens & Leicht-Scholten, 2023b). Second, existing case studies with engineering students have shown a lack of knowledge and understanding regarding infrastructure resilience (Chittoori et al., 2020; Rokooei, Vahedifard, & Belay, 2022). And third, engineering curricula indicate deficits with regard to qualification goals, i.e., competencies that enable students to design resilient systems (Pearson et al., 2018; Richards & Long, 2019; Winkens & Leicht-Scholten, 2023a). Engineering education needs to address those shortcomings in order to prepare future professionals to deal with uncertainty and complexity, to know about resilience and to design resilient systems.

At the same time, resilience is hard to teach, as several misconceptions accompany the concept (Kharrazi 2018; Winkens & Leicht-Scholten, 2023b). In a preceding case study about a master’s course on resilience and socio-technical systems, we presented a didactic approach to teach resilience to engineering students (Winkens & Leicht-Scholten, 2022). Here, we found challenges in terms of how students deal with uncertainty and anticipatory and systems thinking. To address these and to mitigate the above-described gaps, we adapted the teaching concept and present and discuss the findings in this comparative case study using a mixed-methods approach. The purpose of this work is to introduce a holistic teaching and learning approach with regard to resilience thinking and its implications for students’ competency development. These are both of interest to engineering educators and to all areas concerned with systems resilience in an environmental context.

2. Theoretical background

In the following, resilience is explained as a concept as well as relevant competencies going along with it. Based on this, we give an overview of teaching approaches for fostering resilience thinking that are proposed in literature.

2.1. Designing resilient systems

The development and design of adaptive and resilient infrastructure is crucial to face global challenges, especially in the context of climate change and resulting increasing natural disasters (Ayyub, 2018; IPCC. 2023; Martin et al., 2022; Olsen et al., 2015; UNDRR, 2022). Therefore, approaches and perspectives are required that go beyond traditional safety or risk management which mainly focus on post-disaster, i.e., reactive approaches and on mitigation strategies (Hollnagel, 2014; Levin et al., 2021; Seager, Selinger, & Wiek, 2011). Instead, future infrastructure design requires flexible and adaptive (proactive) answers to extreme and sudden disturbances, such as earthquakes or floods. This implies a socio-technical systems perspective, not only focusing on physical artifacts, but also on the people interacting in the system (Doorn, Gardoni, & Murphy, 2018; Hollnagel, 2008). The above requires adaptive governance and management, where collaboration, communication and learning are part of a continuous problem-solving and learning process (Berkes, 2017). Here, the concept of resilience can be applied, where resilience is described as ‘the ability to prepare and plan for, absorb, recover from, or more successfully adapt to actual or potential adverse events’ (National 2012, p. 16).

The discourse around the concept of resilience, as well as the usage of the term have increased in research in recent years (see, e.g., Asadzadeh et al., 2022; Bautista-Puig et al., 2022; Mayar, Carmichael, & Shen, 2022 for recent literature reviews). Originating from the field of ecology (Holling, 1973), today, the concept is applied in several disciplines, such as psychology, geography, environmental science, economics and engineering (Doorn, Gardoni, & Murphy, 2018; Francis & Bekera, 2014; He & Cha, 2021). Accordingly, many definitions of resilience exist, which also brings with it a critique of the term (Brown, 2016; Walker, 2019). This relates specifically to the different contexts of resilience, i.e., objects and scales, in which the term is applied. These range widely from human beings to infrastructure systems or communities (He & Cha, 2021; Martin-Breen & Anderies, 2011). Despite these differences, the multidisciplinary definitions of resilience share common elements and characteristics: the ability of a system or individual to withstand a shock, disturbance or crisis, to recover from these and to adapt to future adverse events (Francis & Bekera, 2014; He & Cha, 2021; Mayar, Carmichael, & Shen, 2022; Rockström et al., 2023). Resilience is therefore about surviving, followed by learning and transforming to be better prepared for the future. A resilient system ‘stays the same kind of system by learning from a disturbance, to be able to better cope with a similar disturbance in the future. […] Resilient systems are learning systems’ (Walker, 2020). and therefore, learning from failure is crucial in a resilience context. However, the understandings and interpretations of resilience described here lead to various misconceptions, making the concept difficult to teach (Kharrazi, Kudo, & Allasiw, 2018). These misconceptions refer in particular to a misunderstanding between the concepts of resilience and robustness, where resilience implies adaptive capacity rather than a return to a previous state (Anderies et al., 2013; Walker, 2020).

To develop, manage or design such resilient systems, appropriate competencies as well as a different way of thinking (‘Resilience Thinking’) are required (Folke, 2006; Walker & Salt, 2006). Resilience thinking enables a different perspective about dealing with uncertainty and complexity (Fazey, 2010; Folke et al., 2010; Walker & Salt, 2006), thereby opening opportunities for ‘reevaluating the current situation, trigger social mobilization, recombine sources of experience and knowledge for learning, and spark novelty and innovation’ (Folke et al., 2010). Resilience is always concerned with the occurrence of disturbances whose probability is unknown or hard to assess. Therefore, anticipation of possible future events, as well as decision-making in the face of uncertainty, and especially systems thinking are crucial resilience competencies (Fazey, 2010; Francis & Bekera, 2014; Mayar, Carmichael, & Shen, 2022; Park et al., 2013; Seager, Selinger, & Wiek, 2011). Here, anticipatory thinking means understanding and evaluating possible future states and dynamics of complex systems, and systems thinking describes the ability to analyze, model and apply complex systems and problems across different scales and domains (Redman & Wiek, 2021; UNESCO, 2017).

2.2. Learning Approaches to foster resilience thinking

The literature repeatedly emphasizes the importance of engineers designing and creating resilient systems and, at the same time, frequently addresses the lack thereof: Studies and position papers predominantly criticize a gap both of engineering students’ knowledge and abilities in this field, and engineering curricula addressing this gap (e.g., Aktan et al., 2021; Bruno, 2015; Chester & Allenby, 2019; Martin et al., 2022; Pearson et al., 2018; Seager, Selinger, & Wiek, 2011). In the field of environmental education research, a different trend is evident, based in particular on the work of Krasny and colleagues (e.g., 2016, 2010, 2009) . Here, it is stated that integrating the concept of resilience into education can contribute to the development and planning of resilient social-ecological systems by educating future decision-makers and practitioners (Krasny, Lundholm, & Plummer, 2010; Lundholm & Plummer, 2010; Ruiz-Mallén et al., 2022). Thereby, competencies such as complex problem-solving, systems and anticipatory thinking can be fostered when students actively reflect on systems’ performance and underlying interactions (Demssie et al., 2022; Fazey, 2010; Plummer, 2010; UNESCO, 2017). Ban et al. (2015) reviewed literature on pedagogical approaches about engaging higher education students to deal with complex environmental issues in the context of social-ecological resilience. They found consensus in the literature that active learning approaches, such as problem- or project-based learning, experiential and case-based learning are perceived to be as most promising. Others refer to situated learning (Krasny & Tidball, 2009) or transformative learning (Ruiz-Mallén et al., 2022). On a competency-level, especially problem- and project-based learning as well as community service learning most likely address anticipatory competency, where several pedagogical approaches may address systems thinking (Demssie et al., 2022; Lozano et al., 2019; Lozano et al., 2021). Moreover, some authors propose that scenario planning can enable students’ abilities to both anticipatory and systems thinking by analyzing and reflecting on uncertain future states, which also can foster the ability to deal with uncertainty (Carpenter et al., 2012; Kharrazi, Kudo, & Allasiw, 2018; Peterson, Cumming, & Carpenter, 2003).

Regardless of the actual didactic concept, all teaching methods and approaches have in common that they are designed student-centered and emphasize active learning processes to promote students’ motivation for self-directed learning (Prince, 2004; Prince & Felder, 2006). At the same time, there is consensus in the literature that traditional lecturing is not suitable for the above-mentioned competencies (Ban et al., 2015; Lozano et al., 2019; Lozano et al., 2021). Moreover, fostering resilience thinking requires more than presenting established best practices in education. Instead, students need to critically reflect on existing and established strategies and modify these, if necessary, for example in the context of the recovery phase after a disruptive advent (Nielsen & Faber, 2021). This can be underpinned by learning from failure in the context of real-world case studies to foster engineering judgement and analysis with uncertainty (Edmondson & Sherratt, 2022; Love 2013; Pearson et al., 2018). Accordingly, applying resilience thinking to ill-structured and complex real-world problems is ‘the best way to learn about and understand resilience thinking’ (Fazey, 2010).

3. Study context and method

To address the above-described gaps and the demand for enabling engineers to design resilient systems, we designed a problem- and case-based teaching concept, in which resilience thinking is embedded in a holistic teaching and learning approach. This research is based on a case-based methodological approach. Case studies are useful to address our research purpose, as we are concerned with the specific application of innovations to improve teaching and learning and thereby generate knowledge in a particular context (Case & Light, 2011).

The context for this study is a master’s seminar called ‘Resilience and socio-technical systems’, which is an elective course in environmental, civil and industrial engineering at RWTH Aachen University, one of the largest and most reputed technical universities in Germany. The course takes place every summer semester and has capacity for 25 students.

Based on constructive alignment (Biggs & Tang, 2011) and Bloom’s taxonomy (Anderson et al., 2001; Bloom, 1956), intended learning outcomes were formulated, both at course (see Table 1) and at lesson level. These were aimed specifically at addressing the competencies discussed in literature. Note that the course is offered in German, which is why we translated all material into English.

Table 1. Intended learning outcomes at course level (see also Winkens & Leicht-Scholten, 2022).

Level of complexity	Taxonomy	Learning outcomes
	Creating	Students develop solution approaches to foster resilience for crisis situations.
	Evaluating	Students assess existing crisis management approaches regarding 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 resilience effects.
	Applying	Students apply resilience-oriented approaches to practice-related 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.

The seminar was structured in several content-related sessions, where students were guided through theoretical foundation about resilience theory, concepts and tools in order to use this knowledge to promote their motivation and comprehension (Prince & Felder, 2006). The didactic approach consists of multiple elements in the context of active learning, such as problem-based learning, collaborative learning, self-directed and reflective learning, as these teaching and learning methods have described to be promising to acquire the corresponding competencies (Ban et al., 2015; Lozano et al., 2021). For a more detailed description of the teaching and learning methods, see Winkens and Leicht-Scholten (2022).

3.1. Course development and assessment

In 2021, the seminar was conceptualized as problem- and case-based for the first time, and some challenges with respect to student elaborations became apparent (Winkens & Leicht-Scholten, 2022). Students were given a case for which they had to conduct a scenario analysis. The case was an ill-structured problem related to the COVID-19 pandemic and included various variables and unknowns that the students had to deal with. Their task was to act as advisors to the local government and to present concrete, resilience-related solutions for further handling of the pandemic. The students worked on the case in groups throughout the semester. They had the opportunity to voluntarily attend a consultation session to receive feedback. As it turned out, the student elaborations at the end were very heterogenous. Notably, groups that took advantage of the voluntary feedback sessions produced outstanding results and showed a high level of systems and anticipatory thinking in a resilience context. Contrary, groups that did not avail themselves for feedback exhibited significantly weaker results, particularly with respect to resilience thinking. Moreover, these students had difficulty separating the COVID-19 regulations in Germany in that time from their own elaborations and were rather focused on robustness and stability than on resilience.

To address these heterogeneous results, the concept was adapted in 2022 (see Table 2). The changes are presented and subsequently discussed in the following.

Table 2. Assessment changes.

	2021	2022
Case	One given case (COVID-19)	Students chose the case on their own
Method	Scenario planning	Scenario planning and resilience analysis of past disaster events
Feedback	Voluntary feedback	Obligatory midterm feedback
Assessment	recorded team presentation, written team reports and peer-assessment	recorded team presentation, written team reports, peer-assessment and reflective diaries

Based on the difficulties of several groups in 2021 and the resulting assumption that a predetermined case was perceived as too restrictive, we decided on allowing students to pick their own case as a first change. By choosing and developing the case, i.e., the problem, on their own, students already deal with scientific literature and the problem in a more profound way, as they are able to analyze the problem and make decisions on their own (Colby & Sullivan, 2008; Edmondson & Sherratt, 2022; Prince & Felder, 2006).

As a second fundamental change, the students were to work out in groups, on a scientific basis, how the selected crisis situation affected a socio-technical system in the past and what measures were subsequently taken in order to be better equipped to deal with this and similar crisis situations in the future. The overarching theme was learning from failure by purposing to foster systems and anticipatory thinking in the context of resilience. Thereby, in the context of problem-based learning, an open-ended and complex real-world problem was the starting point for the course, providing the context and motivation of the following learning process (Edström & Kolmos, 2014; Prince, 2004). Students were free to choose whether to focus on a specific system or, for example, to analyze a regional or local crisis situation and then transfer the findings to comparable systems. Most importantly, they had to set system boundaries, which is crucial when analyzing systems’ resilience, as the resilience of one part of a system may affect that of another (Carpenter et al., 2001; Meerow, Newell, & Stults, 2016). For this purpose, the students were given guiding questions to help them structure their case study. These related to the analysis of the selected crisis situation and evaluation in terms of resilience and responsiveness (see Figure A1 for a detailed description).

Figure 1. Self-assessment results for content- and methods-related resilience competencies before (n = 21) and after (n = 13) the course 2022.

Since the students were now completely free to choose their case and in order to try to bridge the gap between the students’ achievements, we introduced a mandatory midterm session for all groups. The aim was for the groups to present and justify their ideas for the cases, in particular to provide them feedback and to help them to find an adequate scope, especially for setting the systems’ boundaries. Moreover, they had the opportunity to get voluntarily feedback at any time.

In both years, students had to prepare a recorded presentation with a maximum of 30 minutes, in which they present their results. After submission, students were given time to view the presentations of the other groups. In a mandatory discussion session with a focus on peer-assessment, the groups were mixed and asked to evaluate the results of the other groups. As a final report or presentation alone is not sufficient to understand students’ work development over time (Picard et al., 2022) and to constructively align the learning outcomes, content and assessment, they also had to submit a written team report, in which they had to transparently describe and document their group process, including group meetings and justifications for assumptions made. Students had also the opportunity to address and reflect on subsequent findings from the discussion session in the report, as well as through feedback from their fellow students. Assessment criteria included the profound explanation of the cases, a stringent argumentation with regard to resilience assessment, traceability of the answers to the guiding questions, creativity and reflection (see Winkens & Leicht-Scholten, 2022).

To foster more in-depth reflection of the students and to get more insight into students’ learning process, in 2022, students were also required to write individual reflective diaries, which was inspired by and adapted from the studies by Wallin and Adawi (2018, 2016). By using reflective diaries, instructors can see how students use their knowledge and competencies and how they deal with them (Wallin, Adawi, & Gold, 2016). This not only assesses what students have learned after completing the course, but also emphasizes the process that underpinned the outcome. For each week, students should answer questions about their learning process and progress. In order to stimulate students’ abilities to reflect on both learning topics and learning behavior, it is important that diary prompts align with their current learning experience (Wallin, Adawi, & Gold, 2016). We followed the recommendations of Wallin, Adawi, and Gold (2016) for the formulation of the prompts and adapted their diary questions in the context of the categories ‘What has happened?’, ‘How did you approach the situation?’, ‘Why is it important?’ and ‘How did you learn from it?’. The questions for the diaries can be found in Appendix Table A1.

Completion of the learning diaries was part of the examination, but was not graded, as they include students’ individual and personal self-perception of their learning process. Moreover, to foster students’ ability for reflective writing, they had the opportunity to submit weekly critical reflection papers in which they were asked to reflect on a specific topic discussed in the sessions of week 1–8. These were not part of the examination, but they were able to improve their individual grade as a result. They received feedback for both weekly reflection papers and their diaries.

At the beginning of the course, the whole teaching concept in the context of constructive alignment was explained to the students, including learning outcomes, expectations, active learning and the planned workload. Similarly, the relevance of reflective writing about their learning process was explained to the students. The course concept and schedule are presented in the following table.

Table 3. Overall course schedule.

Week	Topic	Diary
1	Introduction and Motivation	X
2	Terms and Basics: Resilience and Risk	X
3	Methods and Tools	X
4	Groupwork	X
5	Resilience in Engineering	X
6	Urban Resilience	X
7	Midterm Session (mandatory)
7	Group Work
8	Resilience Thinking	X
9	Group Work
10	Group Work	X
11	Submission of Presentations	X
12	Watching the Presentations of the Other Groups
13	Plenary Discussion	X
14	Feedback and Closure	X
14	Submission of Documentations and Diaries

3.2. Data collection and analysis

In order to holistically evaluate the course concept as well as the intended acquisition of competencies, a mixed-methods study design was applied by combining quantitative and qualitative data.

On a quantitative level, we conducted a pre-post survey at the beginning (April 2022) and end (July 2022) of the course, in which students were asked to self-assess their competencies on a five-point Likert-scale: 1 – strongly disagree, 2 – disagree, 3 – neither, 4 – agree, 5 – strongly agree. The items are divided into two sections (see Table 4): Questions about resilience-related knowledge, understanding, and application and analysis of it (R1–R7), referring to the learning outcomes from Table 1, and professional competencies (P1–P10), which are skills that students have on themselves or on working with others (ASEE, 2020; Picard et al., 2022; Shuman, Besterfield-Sacre, & McGourty, 2005). Here, items P6–P9 also refer to aspects of individual resilience in order to examine how students assess themselves in this regard.

Table 4. Items of the pre-post survey (* marks items that were only queried in 2022).

Item		Question
R1	Resilience-related: Content and methods	I know scientific discourses with regard to resilience.
R2		I am able to explain the term ‘resilience’ in my own words.
R3		I understand the relevance of resilience with regard to global risks and crises
R4		I understand the relevance of resilient systems for my work as an engineer
R5		I am able to apply the concept of resilience to different situations
R6		I am able to analyze scenarios with regard to their implications for resilience
R7		I am able to evaluate existing crisis management approaches regarding their potential for resilience
P1*	Professional Competencies	I am able to assess my learning progress and check it independently.*
P2		I feel confident in giving a digital presentation and presenting my findings convincingly.
P3		It is easy for me to exchange ideas, communicate and discuss with my fellow students.
P4		It is easy for me to resolve conflicts.
P5		I can empathize with other perspectives and take them into account when designing processes.
P6		I can cope well with sudden crises.
P7		I am resistant and adaptable.
P8*		I learn from my mistakes.*
P9*		I consider myself to be resilient.*
P10		I am motivated to look into the topic of ‘resilience’.

The pre-post survey belongs to the self-perceiving assessment tools for the acquisition of competencies for sustainability (Redman, Wiek, & Barth, 2021), as in these both anticipatory and systems thinking are included (UNESCO, 2017; Wiek, Withycombe, & Redman, 2011). For these tools, Redman, Wiek, and Barth (2021) elaborate that the data can be statistically analyzed in different ways, but also that the self-assessment of the students is improved by using these tools.

In total, 22 students attended the seminar, 21 of whom participated in the pre- and 13 in the post-self-assessment. The introduction of personal IDs preserved the anonymity of the survey and allowed us to match pre- and post-data for analysis for n = 11 participants. The pre- and post-data were compared using a Wilcoxon signed-rank test for dependent samples.¹ The test was performed directionally, as we assumed there to be an increase in competency assessment. This assumption is supported by the descriptive evaluation (see Section 4, Table 5). All evaluations were done using the software R. The pre-post survey is also compared to the data from 2021. Note that the latter contained no IDs and therefore did not allow for matched pre- and post-data.

On a qualitative level, an analysis of students’ learning diaries was conducted by inductively categorizing their reported thoughts, expectations, challenges and fears. In the following, both quantitative and qualitative data results will be presented and discussed. These will also be related to findings from the student elaborations in order to see how they have dealt with a resilience-related problem both at the content and on an individual level. Furthermore, a course-related evaluation was conducted in which students assessed the teaching concept. This was discussed at the end of semester during a joint final discussion, and desired changes for the future were noted. Both will be presented and elaborated on in the context of the teaching concept in the following section.

Note that we do not claim generalizability of this study, due to a case study approach and the exploratory nature of this work (Case & Light, 2011). Thus, we acknowledge the corresponding limitations, especially concerning the small sample size, which is a common limitation of case-based approaches. Indeed, by using a case-based approach, we want to suggest a novel teaching approach to foster resilience thinking among engineering students and discuss how this can contribute to the education of adaptable and lifelong learning practitioners.

4. Results and discussion

Overall, in 2022, students reported positive development in most of the competencies. This is shown by both the descriptive statistics and the Wilcoxon test for the matched students (n = 11). Both are presented in Table 5 and show that students’ self-assessment of most of the competency items is significantly higher (p < 0.01, in bold) when surveyed after the course.

Table 5. Results of the pre-post survey, bold: significant at p < 0.01, * only evaluated in 2022.

Item	p-value (Wilcoxon signed-rank test)	Mean (pre)	SD (pre)	Mean (post)	SD (post)
R1	0.0018	1.64	0.67	4.36	0.50
R2	0.0041	3.18	1.08	4.64	0.50
R3	0.0042	2.82	1.25	4.73	0.57
R4	0.0027	3.09	1.04	4.83	0.40
R5	0.0026	2.36	0.81	4.36	0.50
R6	0.0018	2.00	0.89	4.82	0.52
R7	0.0041	1.82	0.75	4.73	0.70
P1*	0.0209	4.09	0.54	4.36	0.47
P2	0.0010	3.55	0.82	4.09	0.69
P3	0.0089	3.36	1.12	4.55	0.65
P4	0.0051	3.36	0.92	4.73	0.47
P5	0.0088	4.00	0.63	4.55	0.40
P6	0.0168	3.27	1.01	4.27	0.75
P7	0.0209	3.82	0.75	4.27	0.69
P8*	0.0131	4.09	0.54	4.82	0.42
P9*	0.0445	3.70	0.67	4.18	0.60
P10	0.9772	4.73	0.47	4.64	0.50

This is especially the case for all content- and methodological related competencies as well as for some professional competencies. Therefore, we will look at and discuss both areas in detail below.

4.1. Resilience thinking

At the content level, i.e., regarding knowledge and understanding as well as analysis and application, students reported a strong subjective improvement of their competencies (see Table 5). The following two figures serve for a better illustration of the competency development. Here, the percentages of the respective answers on the Likert scale of each (strongly) agree and (strongly) disagree have been cumulated to display the trend regarding competency development during the course.

Relating to all students (Figure 1), this is especially the case for items R5–R7, which at the same time represents competencies with the highest complexity level (applying, analyzing and evaluating). Moreover, these competencies were consistently rated lower before the course than most of these on a lower competency level (R2–R4), except for R1, describing the knowledge about scientific discourses on resilience, which was not pronounced before the course.

A similar development was observed in 2021 (see Winkens & Leicht-Scholten, 2022 and Figure 2). However, the self-perception of improvement was much more pronounced in 2022; with the exception of the ability to evaluate existing crisis management approaches in terms of resilience, all items are rated at 100%.

Figure 2. Self-assessment results for content- and methods-related resilience competencies before (n = 20) and after (n = 12) the course 2021.

Students’ group work results confirmed the positive development of resilience-related competencies as a clear outcome. In the course, a total of four groups submitted presentations, all of which included very good approaches and outcomes. It was already obvious during the midterm session that the individual groups had dealt with the task in a well-founded manner. It was also evident there that, although they were completely free in choosing the case, all four groups had chosen (different) water-related cases. Two groups chose national past disasters, the North Sea flood of 1962 and the 2021 flood in Germany, the other groups analyzed two international disasters, Hurricane Katrina 2005 and the earthquake caused tsunami in Thailand and Sri Lanka in 2004. In the midterm session and in subsequent consultation hours, the overall cases were narrowed down to specific aspects related to the crisis situation, always guiding the students to be concerned with a socio-technical system and setting corresponding system boundaries (see guiding questions in Appendix Figure A1. Full task 2022). In the reflective diaries,² it also became apparent that this was one of the biggest challenges:

The biggest challenge this week was defining our system boundaries. It was a challenge because we didn’t realize at the beginning that we needed to focus on certain countries and industries in our case in order to work successfully on the case.

(S10)

All groups showed a deep understanding of resilience theory and provided sound rationales for their assumptions. However, in the individual diaries, students pointed out several difficulties with literature research relating to their cases. They realized that profound literature research is essential for their argumentation, especially because of either a lack of available and/or trustworthy data or because of a perceived overwhelming data availability. Moreover, they pointed to difficulties with English-written studies and that they had to decide about the relevancy of aspects in literature, as one student wrote:

Most of it is in English and the sources are often only informative and do not inherently relate to resilience already. So we have to do a lot of analysis ourselves.

(S08)

How the groups approached their cases varied: Some referred to existing resilience assessment frameworks and applied these methods to their own analysis. Others developed their own resilience assessment criteria and even developed action plans for future crises, thereby demonstrating anticipatory competency. This was especially the case for groups which had chosen a case with only little data available. Overall, all groups showed a high level of creativity and independent work.

The recurring theme in all elaborations and the diaries was the reflection on the difference between resilience and traditional risk management approaches. This was already apparent after introducing students the differences in weeks 2 and 3 (see Table 3). In their diaries, they highlighted two aspects: First, noting that resilience has no universal definition and is a complex interdisciplinary concept and, second, recognizing that uncertainty is a key aspect that distinguishes resilience from traditional risk management. Regarding the understanding of resilience, students recognized that they misunderstood the term before the course:

I have realized that the topic of resilience is much more complex than I had initially assumed. This makes particularly clear the vagueness of the term and, along with it, the variety of possible definitions. It seems particularly important to me that the use of the term depends on the discipline.

(S05)

In terms of the most important learning experiences in weeks 2 and 3, one student wrote:

That the way we try to anticipate future events often results from past experiences, but that these are not necessarily determined by the past. Thinking the possible and not only the probable is therefore one of the most important core elements to build resilient systems.

(S07)

Moreover, some students referred to the specific relevance of engineers in this regard:

I have learned that there is a difference between risk analysis and resilience and that, especially in engineering, people tend to work with risk management rather than resilience. Maybe I can do this differently in my career as an engineer and look beyond old established patterns.

(S11)

It is also the responsibility of engineers to consider not only the technical and known components 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.

(S06)

In the group elaborations, the differentiation between resilience and risk approaches became particularly clear again and was also pointed out as another challenge:

One challenge is knowing the transition from risk management to resilient systems. Even if concepts worked in the past, that doesn’t mean they will suffice or work again. Resilience thinking again underscores the importance of building resilience. The choice of words when describing a problem plays an essential role.

(S03)

Some groups realized that their intended resilience analysis resulted in finding risk management approaches and only few resilience-related outcomes, such as adaptive capacity or learning from failure.

The main result of our elaboration is that the system’s risk was managed, but it was not transformed to be more resilient. Originally, we intended to find out how the system was designed more resilient, as this is also the focus of the seminar. However, in the end we found out that this did not happen in our case study, which was a good result in the end.

(S02)

As the student (S02) pointed out correctly, finding an absence of real resilience approaches is a very relevant finding in itself. Fostering resilience thinking is exactly this kind of approach by critically reflecting on existing structures and systems and, if appropriate, modifying these (Nielsen & Faber, 2021). By learning that the intended results do not correspond to the actual findings, students learn about and from failure, re-organizing and change their perspectives accordingly, especially in the context of ill-structured problems (Fazey, 2010; Jonassen, Strobel, & Lee, 2006; Prince & Felder, 2006). On a similar point, one student was afraid to choose a case which may not be able to connect to resilience:

It is therefore necessary to select a good case, which can also be linked to the term resilience. After the disaster, the socio-technical system should have adapted and be resilient to future disasters to a certain extent. Therefore, the biggest risk is to choose a case in the group work that has a good risk management after the disaster but is not sufficiently resilient to renewed disasters or crises.

(S06)

This quote underlines the relevance of understanding that exactly these aspects of learning, i.e., lifelong learning and learning from failure, are central competencies regarding self-directed and reflective learning. The task was not about right or wrong solutions or even certain knowledge, it was rather about uncertainty and trial and error. However, many students think in this way when entering university (Felder & Brent, 2004).

In the plenary discussion session (week 13), students peer-assessed each other. This was done by mixing the group members and reflecting on the strengths and weaknesses of each group presentation on a collaborative digital whiteboard (Miro). The aim was to promote both learning and reflection skills by giving students the opportunity to learn from their mistakes, to take them on board and to make suggestions for improvement. Students received guiding questions for doing so before the session. Notably, the results of session underlined students’ profound understanding of resilience thinking, as they managed to critically assess the work of the other groups. In most cases, both strengths and weaknesses mentioned corresponded to the aspects that we had also already identified during the presentations. After this session, students had the opportunity to incorporate or comment on the feedback they received into their final reports, which all groups made use of.

Compared to 2021, both the self-assessment of competency development and the group work elaborations including the peer-feedback regarding resilience were significantly better. Not only did the students engage more intensively with the theoretical foundations, but they also achieved significantly better results overall regarding resilience thinking. This may be due to both the free and independent selection of the case instead of working on a given one and the obligatory feedback session in order to guide students’ work.

4.2. Professional competencies

There is also a positive development in students’ assessment of their professional competencies. Presentation skills, communication, resolving conflicts and emphasizing other perspectives show a significantly stronger subjective improvement after the course (see Table 5, P2–P5). These describe interpersonal competencies, i.e., skills that refer to the interaction and communication with others (Beagon et al., 2022; Holgaard & Kolmos, 2019). The development cannot be observed for items related to individual resilience, such as coping with sudden crises (P6) or learning from own mistakes (P8). However, looking again at the cumulative distribution of percentages of all students (see Figure 3), a positive development of all competencies can be observed, except for the motivation for dealing with the topic of resilience (P10), which is rated 100% before and after the course. The cumulative distribution shows strongest improvement in the ability to resolve conflicts (P4), coping with sudden crises (P6) and the self-assessment to be resilient (P9).

In 2021 (Figure 4), the development is similar for items P2–P5, but there is a deterioration in the two items regarding the ability to cope with sudden crises (P6) and the self-perception to be resistant and adaptable (P7). Since it was not possible to match the students here and the total number also varies, this does not allow any conclusions to be drawn regarding further interpretation. Moreover, items P1, P8 and P9 were not yet part of the pre-post survey in 2021.

Figure 3. Self-assessment results for professional competencies before (n = 21) and after (n = 13) the course 2022.

Figure 4. Self-assessment results for professional competencies before (n = 20) and after (n = 12) the course 2021.

With regard to motivational factors to take part in the course, six common topics were identified: learning (more) about resilience, exchange and interaction, teamwork/groupwork, learning about different perspectives, self-reflection and becoming more open in social interactions and presentations. These refer to the first questions in the reflective diary, asking for students’ interest, motivation and expectations. In all diaries, students highlighted an interest to learn (more) about resilience, especially regarding their engineering profession. Here, they also questioned why they had not learned about resilient systems in their studies so far, which stresses the lack of these topics in engineering education (Chester & Allenby, 2019; Richards & Long, 2019).

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.

(S03)

The most important thing will probably be the mindset of establishing and developing new and resilient systems and not always sticking to the tried and true in order to be able to counteract problems of today, such as climate change. Providing this mindset and the basic tools to do so could be achieved by participating in this course.

(S04)

Moreover, they reported on the demand for interactive, engaging and small courses which are only seldomly part of their curricula.

I wanted to take one more course at the end of my degree that was not one of the ‘standard’ civil engineering courses.

(S11)

The self-perceived improvement of the significant items is also mirrored in the reflective diaries. Overall, the students reported several challenges concerning the groupwork, especially with regard to time management, self-organization, trusting their peers and a structured approach at the beginning. At the same time, most students highlighted well-functioning teamwork, reliable team partners and a sense of community:

Although we had the feeling that we were on the right track and on schedule, we realized that we could have done much more at the beginning. The beginning was slow, but at the end we worked even more intensively together. We felt the time pressure.

(S01)

This statement is mirrored in all diaries, as students reported on slow or stagnating groupwork at the beginning of the course and on time stress at the end. Moreover, some students pointed out that they experienced this time management in other groupworks too and intended to change but did not manage to. Notably, this aspect was reported in the context of ‘learning from failure’ in the diaries, which showcases a self-reflection of the students.

Moreover, the midterm session was highlighted as very helpful to estimate the learning progress and to focus on a structured approach. The students emphasized that the case selection alone was very work-intensive at the beginning because they also had to find a consensus in the group on the case. This was solved either by individual pitches, in which the individual group members had to present their selection, or by brainstorming and working with the collaboration tool Miro.

The ability to trace their learning progress (P1) shows only little positive self-perceived development among all students. In the reflective diaries themselves, no student pointed out explicitly that the diaries helped them to reflect on their learning process and progress, but in their answers we could observe a profound dealing with the topic.

4.3. Overall course feedback

The course concept was evaluated based on three aspects: A survey was conducted for evaluation, which is mandated by the university. Furthermore, a feedback session was held with the students at the end of the seminar, in which they were able to discuss in groups the course concept, their biggest challenges as well as their key messages. Finally, the last question in the learning diary (week 14) provides information on whether the students were able to fulfill their expectations formulated at the beginning and what they took away from the course overall.

Overall, the feedback was very positive. In all three evaluation parts, students highlighted the active learning experience regarding the groupworks, interaction with their peers and an open space for discussion while sharing ideas and perspectives, especially compared to their experience with more traditional lectures.

I found the processing of the case study very interesting and I also find this learning method much better than the lectures and events that we usually have, because you approach the matter so much more practically and the whole thing is more vivid and exciting. I think that the seminar will definitely be helpful for personal and professional everyday life. We learned, as you generally learn in seminars and group work, to work with other people, and to compromise, communicate with others and show consideration for the other members.

(S02)

Students perceived the time and goal management in their group works, to narrow down their case and to explain what resilience actually is to be most challenging. As their key takeaways, they stressed the relevance of uncertainty, i.e., to plan with the possible, and not with the probable, and to accept uncomplete information and knowledge.

I also took away from the course that you have to come to terms with the fact that there is no clear definition for some things and that understanding certain processes sometimes takes a lot of time. I also think that the ability to reflect on situations can help me in the future.

(S09)

Moreover, they were asked to reflect on their acquired competencies, where problem solving, critical thinking, adaptive capacity, self-reflection and a differentiated approach to problems were highlighted. In their reflective diaries, all students stated that their expectations were met. They emphasized the importance of dealing with future natural disasters in the context of climate change, especially concerning their work as engineers.

The most important insight for me is the fact that engineers bear a great social responsibility with their work and that in this context the strengthening of resilience must be considered.

(S05)

Not only as future professionals, but also as individuals they reflected on resilience thinking in their daily lives:

In general, I now think about resilience more often in everyday life. What was essential for me was that resilience is not easy to grasp in a general way but has to be considered individually for each situation and goes beyond simple risk management.

(S11)

Students’ perception and feedback on the teaching concept suggest a successful application of active learning methods as well as of constructive alignment.

5. Implications and limitations

Overall, the course results have shown that the students achieved a significant increase in competencies both on a subject-related content level and on an interpersonal level. Following a case-based and mixed-methods approach, this could be determined based on pre-post surveys, the group work presentations, the individual learning diaries as well as in personal feedback discussions with the students, thereby presenting a holistic perspective on students’ learning processes. Moreover, students perceived a stronger subjective improvement for competencies related to resilience with a higher level of complexity, which were only marginally pronounced before the course. Interpersonal competencies, especially presentation skills, communication, resolving conflicts and emphasizing other perspectives were also perceived as significantly stronger after the course. At the same time, several challenges the students had to overcome became apparent: time management and self-organization in the groups, data collection and analysis, defining system boundaries, and distinguishing resilience from risk analysis. Compared to 2021, there were both significantly improved results in the student elaborations and greater perceived improvement in competency acquisition. This can be attributed to the changes we made in 2022, particularly with respect to the independent selection of a case based on guiding questions and the introduction of a mandatory midterm office hour. Even though it is central in the context of problem-based-learning that students are owners of their learning process, guidance is needed especially for complex and in this case new tasks and learning processes (Edström & Kolmos, 2014).

However, it is not clear in detail which teaching and learning methods have influenced each other in which way and how they have strengthened the positive effects (Picard et al., 2022). It remains to be said that a combination of teaching and learning methods is target-oriented in order to promote the acquisition of competencies, especially for the analysis of complex systems (Demssie et al., 2022). A deeper analysis, for example through interviews with participating students, could be informative here, also with regard to the experience with learning diaries (Wallin & Adawi, 2018).

As formulated in Section 3.2, the results of this case study cannot be generalized, especially due to the small sample. The quantitative data of the pre-post survey should therefore be interpreted with caution. Furthermore, the pre-post survey is about the students’ self-assessment and also their interpretation of the respective competencies. Here, the understanding of the respective statement or competency, but also the scale, may vary (Murray, Pytharouli, & Douglas, 2022). There are various discourses on the advantages and disadvantages of self-assessment surveys in the field of engineering education (Boelt, Kolmos, & Holgaard, 2022; Murray, Pytharouli, & Douglas, 2022; Picard et al., 2022). Students’ self-assessments are always based on their respective epistemological beliefs and represent their respective understanding and knowledge accordingly (Boelt, Kolmos, & Holgaard, 2022). Furthermore, an optimism bias (see Dunning-Kruger effect, Kruger & Dunning, 1999) cannot be ruled out, since the students in particular rated the statements regarding their intrapersonal competencies comparatively high already before the beginning of the course (e.g., ‘I am resistant and adaptable’ and ‘I learn from my mistakes’), whereas Murray, Pytharouli, and Douglas (2022) found similar results with regard to the self-perception of intrapersonal competencies. Nevertheless, self-assessment surveys can be beneficial by, for example, initiating student self-reflection, which in turn can positively influence self-directed learning (Schmitz & Perels, 2011). However, the implementation of the learning diaries allowed us to track the learning process as well as self-assessment in detail for all students. This was reinforced by the documentation of the groups in which they were asked to log their entire work process.

To engage engineering students with resilience thinking, learning from failure is an important perspective. For this purpose, case-based learning in the context of problem-based learning can be promising by analyzing real past failures and their implications for future planning (Edmondson & Sherratt, 2022; Foley, Foley, & Kyas, 2022; Love, Lopez, & Edwards, 2013). This case study supports this finding but also recommends designing a case that is problem-framed and guided by the instructors, while at the same time allowing students to decide what specific context they want to focus on (e.g., by choosing a water-related case). This can be especially useful for open-ended complex problems in the context of designing resilient systems. By analyzing all systems’ components, scales and (possible) interactions, students developed not only systems thinking ability, but also anticipatory and holistic thinking (Demssie et al., 2022; Lozano, Barreiro‐Gen, Pietikäinen, et al., 2021). Moreover, it is crucial to address the misconceptions when teaching resilience, as reported in the literature (Kharrazi, Kudo, & Allasiw, 2018). This was done carefully, and students’ diaries and elaborations have shown a deep understanding and reflection of these, especially with regard to the definition of resilience in distinction to risk and robustness. Furthermore, to constructively align intended learning outcomes, teaching content and assessment methods is important to support and engage students’ learning process in a holistic way. For doing so, we need to provide learning environments that can enable students to own their learning experiences and the problems to be solved as well as to enhancing self-reflection by asking questions like ‘what do we (not) know?’, ‘how can the problem be approached’? (Wallin, Adawi, & Gold, 2016) and ‘why do we want to solve this problem?’. This is especially the case for engineering education, where traditional teaching methods, like lectures, are still used frequently and the problems to be solved are rather well- than ill-defined (Chester & Allenby, 2018, 2019; Jonassen, Strobel, & Lee, 2006).

Although all available and analyzed data as well as the personal feedback from the students were overwhelmingly positive, we acknowledge that this case study is based on a single master’s course focusing on civil, environmental and industrial engineering. This represents a common limitation of a case-based approach (Case & Light, 2011). However, this approach is purposeful for discussing a specific application of an innovation in teaching and learning, which was done in the context of our study.

Further, students’ outcomes underline that they experienced the same lack of knowledge, understanding and methodological competencies in their studies with regard to resilience, as described in the literature (Bruno, 2015; Richards & Long, 2019; Winkens & Leicht-Scholten, 2023a). This lack underpins the relevance of integrating competencies as resilience, system and anticipatory thinking as well as dealing with uncertain and complex problems systematically and holistically in engineering curricula. At the one hand, acquiring these competencies cannot be provided on a single course level (Hadgraft & Kolmos, 2020; Pearson et al., 2018). On the other hand, the presented course indicates that this can be a first step for sensitizing engineering students to be aware of both the need to acquire those competencies and to reflect on their responsibility as engineers to design resilient systems. Moreover, the self-perceived positive development of interpersonal competencies and the associated reported challenges show that there is also a need for better and systematically embedding these competencies into engineering education. Yet competencies, such as communication, emphasizing other perspectives or self-organization, are also central for engineers to design and develop resilient systems, as different people from different disciplines are working and communicating together (Pearson et al., 2018).

In the context of climate change and the resulting higher frequency and intensity of natural disasters, engineering education needs to set a different focus on competencies in order to educate future engineering professionals being able to design resilient systems and thereby serving society (Martin et al., 2022; Scharte, 2019; UNESCO, 2021). This requires the development of a new paradigm of both engineering education and practice to acknowledge a rapidly changing world with low degree of certainty (Ayyub, 2018; Martin et al., 2022; Olsen, Ayyub, Barros, et al., 2015).

Acknowledgments

The authors would like to thank all students who participated in the course and those who gave their permission to use their thoughts and feelings about their learning progress. We also thank Felix Engelhardt for his input.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of this study are available within this article.

Additional information

Notes on contributors

Ann-Kristin Winkens

Ann-Kristin Winkens studied environmental engineering (M.Sc.) and is a PhD candidate at the Research Group Gender and Diversity in Engineering (GDE) at the Technical University in Aachen (RWTH) in Germany. Her research is focused on teaching and learning in engineering education, with a specific focus on future skills related to designing resilient systems, and training competencies in engineering sciences.

Clara Lemke

Clara Lemke studied economics and political science (M. Ed.) and is a PhD candidate at the Research Group Gender and Diversity in Engineering (GDE) at the Technical University in Aachen (RWTH) in Germany. Her research interests are teaching and learning in engineering education, education for sustainable development and political education.

Carmen Leicht-Scholten

Carmen Leicht-Scholten, political scientist by training, is director of the Responsible Research and Innovation Hub at the Technical University in Aachen (RWTH) in Germany. She is professor for Gender and Diversity in Engineering (GDE) at the Faculty of Civil Engineering, and professor at the Faculty of Arts and Humanities. Her focus in research and teaching addresses the embeddedness of social factors in research and innovation processes, i.e., the social construction of science and technology (STS). She is engaged in integrating participatory processes as key factor for sustainable transformations in engineering curricula on national and international level, i.e., as deputy member of the German Accreditation Council.

Notes

1. The Shapiro-Wilk test yielded a value below α = 0.05 for most items, so that no normal distribution can be assumed (Appendix, Table A2), which disallows t-tests.

2. Note that all diary quotes were translated from German into English. Students (S) gave their permission to use the quotes.

Appendix

Figure A1. Full task 2022.

Table A1. Questions for the reflective diaries (adapted from Wallin & Adawi, 2018; Wallin, Adawi, & Gold, 2016.)

Week	Topic	Questions
1	Your expectations	What were your motivations for taking the course? What are you particularly looking forward to in the course ‘Resilience and Socio-Technical Systems’? Why do you think this part will be so interesting? What do you think will be important for you to get the most out of the course? How do you think the course can help you for the future?
2–3	Your learning experience	What was the most important thing you realized/learned this week? Why do you think it is important? What helped you to recognize this? What can you do to create/have more learning experiences like this?
4	Your next steps	What do you think will be the most important next step in your group’s work? Why do you think it will be important? How will you approach this step? What are some possible risks? How do you feel about it?
5	Learning from scientific literature	What was/is the most difficult part of obtaining information from the scientific literature about your case study? In what ways was/is it difficult and how did you approach this challenge? How did you work with the literature? What was your most important learning outcome from reading/viewing the scientific articles? To what extent do you think literature search and review are important? How will this help you for the case study?
6	Progress of your case study	What have been the most important steps you have taken so far in the group work? How are these steps related to the overall task/work? How will they help you with the next steps you need to take? How would you rate the progress of your work so far? Do you feel you are on the right track? What important step comes next – and why?
7	Midterm Session
8	Your challenges this week	What was the biggest challenge this week? Why was it a challenge? How did you overcome this challenge? How was it important to your progress? Would you approach the challenge again in the same way or differently?
9	Groupwork
10	Progress of your case study	What have been the most important steps you have taken so far in the group work? How are these steps related to the overall task/work? How will they help you with the next steps you need to take? How would you rate the progress of your work so far? Do you feel you are on the right track?
11	Learning from failure	Were there things that did not work? How important are these things for your elaboration? How did you proceeded to solve the problems? How did you find out the reason for the failure? What did you learn from the experience? Do you think you could have avoided the problems?
12	Viewing the other group works
13	The key message of your case study	What is the key message of your elaboration? How does it relate to your original plan and the focus of the seminar? How do you feel about the outcome of your group work? What would you do differently if you were to do it again?
14	Retrospective	When you think back to your expectations at the beginning – were they met? What did you take away from the course overall? To what extent can the course be useful for you personally and for your professional future?

Table A2. Shapiro-Wilk-Test.

Item	p-value (Shapiro-wilk-test, pre)	p-value (Shapiro-wilk-test, post)
R1	0.0062	0.0001
R2	0.0474	0.0001
R3	0.0117	0.00001
R4	0.0230	0.0001
R5	0.0689	<0.0001
R6	0.0080	0.0001
R7	0.0183	0.0184
P1	0.0010	<0.0001
P2	0.1504	0.0005
P3	0.1405	0.0076
P4	0.2172	<0.0001
P5	0.0080	<0.0001
P6	0.1341	0.0183
P7	0.0183	0.0025
P8	0.0010	<0.0001
P9	0.0154	0.0043
P10	0.00001	<0.0001