Evidence-based redesign of engineering education lectures: theoretical framework and preliminary empirical evidence

ABSTRACT

While the fourth industrial revolution continues to change manufacturing enterprises all over the world, not all enabling key technologies are taught sufficiently at universities. For this purpose, a new lecture at the Montanuniversität Leoben was designed, teaching students of miscellaneous engineering disciplines, the fundamentals of digitalization and digital transformation, tailored to the requirements of the industry. To elevate the necessary data from these segments, a representative part of the Austrian metal forming companies was analyzed by conducting a large-scale survey. For the sake of teaching efficiency, a survey revealing students' knowledge regarding digitalization and digital transformation and preferred learning methods were also carried out. As a result, a stakeholder-oriented lecture was developed. Furthermore, a general framework on how innovative transdisciplinary academic lectures in engineering can be developed in an efficient, effective, and practical way was derived, which aims to close the gap between modern engineering education and required practical skills.

KEYWORDS:

• Transdisciplinary engineering education
• digitalization
• digital transformation
• metal forming
• lecture design

1. Introduction

Since the official introduction of Industry 4.0 in 2011 from the German government, a multitude of publications regarding the corresponding key technologies, as well as necessary changes in the working environment were carried out (Kaur, Awasthi, and Grzybowska 2020; Oztemel and Gursev 2020; Zheng et al. 2020). While a majority of this literature indicates that key components (e.g. Cyber Physical Production Systems (CPPS), Industrial Internet of Things (IIoT), Big Data, Human Machine Interfaces (HMI)) are implemented in parts of the European manufacturing environment (Grzybowska, Sawhney, and Awasthi 2020), the degree of integration of those technologies significantly varies within different sectors of this industry (Sorger et al. 2021). As a result, highly standardised sectors, characterised through high volume and repetitive robust processes within the manufacturing operation, can be described as leaders in the digitalisation and digital transformation process, while segments that do not fulfil these requirements lag (Matt, Modrák, and Zsifkovits 2020; Peukert et al. 2020). Another important development to consider is the increasing back shoring trend of high-quality manufacturers from low-wage countries to Europe and the U.S. (Ancarani and Di Mauro 2018; Foerstl, Kirchoff, and Bals 2016; Gray et al. 2017; Johansson and Olhager 2018a, 2018b). This trend contradicts the Industry 4.0-related concern of potential job rationalisation in manufacturing companies from the point of view of the employee (Fomunyam 2019; Kovacs 2018; Müller 2019). As a result, the future role of the human workforce, especially on a shop-floor level, is not completely understood yet. While a majority of current literature implies the importance of human factors in an Industry 4.0 environment (Kadir, Broberg, and Da Conceição 2019), recent empirical-based studies often indicate that current decision-makers in industrial practice tendentially neglect this assumption (Vuksanović Herceg et al. 2020). Nevertheless, a significant change in the requirements of the future workforce cannot be neglected (Kiel et al. 2017; Sony 2018). In this respect, the majority of current research further states that a general shift to more complex and less repetitive work evolves (Kadir, Broberg, and Da Souza Conceição 2018; Müller, Kiel, and Voigt 2018; Pfeiffer 2016, 2018). This paradigm shift not only affects basic shop-floor activities but also results in a change in skill requirements for engineering academics in the manufacturing sector. Before the start of the fourth industrial revolution, specialised engineers from different sectors (e.g. mechanical engineering, materials science, automation technologies, IT) mainly operated within small, specialised groups. The modern approaches of digitalisation and digital transformation require enhanced interoperability which leads to the fact that the aforementioned experts will be forced to collaborate in a much more interdisciplinary, respectively transdisciplinary, way (Brougham and Haar 2018; Ghobakhloo 2020). Therefore, delimited responsibilities and resulting boundaries between different disciplines dilute. As a result, engineering experts must learn to act and communicate across socio-cultural boundaries more than ever before. Manufacturing companies acknowledge these developments by creating new jobs (e.g. Chief Digitalization Officer (CTOs)) or extending existing current job roles (e.g. IT managers are additionally responsible for parts of the digital transformation efforts within the company) (Culot et al. 2019; Horlacher and Hess 2016; Tumbas, Berente, and vom Brocke 2017, 2018). Some larger companies even reorganise their organisational structure by implementing in-house entities that purely focus on the digital transformation of the entire corporation (Rotter and Eder 2017). The evolution of the job perspectives of engineering students can be summarised to the two following aspects: (1) there are effectively fewer jobs in the classic manufacturing environment and (2) new jobs in specialised engineering fields that include digitalisation-related knowledge are created (Adam, Aringer-Walch, and Bengler 2019; Vermeulen et al. 2018). To prepare potential engineering experts for their future in the aspect of digitalisation-related knowledge, their educating universities must ensure that adequate knowledge tailored to the requirements of industry for a successful job entrance phase is provided. While recent literature suggests that continuous adjustments are being made in the respective curricula, the basis for these adjustments is mostly related to specific requirements of only a limited number of industrial partners (Andersen, Brunoe, and Nielsen 2019; Büth et al. 2018; Jeganathan et al. 2018; Umeda et al. 2019). In addition, the initial level of knowledge of the students is often not taken into account, leading to adaptions mainly based on the subjective estimations of the responsible lecturers and, if applicable, the respective external guest lecturers.

For this reason, this paper describes the initial development and the empirical-based redesign of a lecture for the transdisciplinary education of engineering students. The respective lecture further focuses on the specific environment of the Austrian metal forming industry and, therefore, allows students of various manufacturing manufacturing-related engineering disciplines to learn the fundaments of digitalisation and digital transformation in a specific industrial environment. Therefore, section 2 of this paper focuses on the development of the theoretical framework of this paper by creating the theoretical foundation of modern engineering education initiatives. In section 3, the initial lecture concept is defined based on literature analyses, expert interviews in the industry, and the practical experiences of lecturers. Section 4 describes the shareholder analysis and, therefore, the systematic and empirical-based identification of knowledge gaps by comparing results concerning the required knowledge from the Austrian Metal Forming Industry with current knowledge from the engineering students of the Montanuniversität Leoben. Section 5 focuses on the empirical-based redesign of the initial lecture concept by describing the redesign of the lecture in terms of learning content, area of application, target group and needs, learning outcomes, lectures and course instructors, learning location and media, teaching and learning methods and assessment, and knowledge transfer. Moreover, section 5 presents a developed Plan-Do-Study-Act (PDSA) circle for the continuous improvement of the developed lecture. Finally, section 6 describes the discussion and Section 7 the conclusion of this paper.

2. Theoretical framework: realignment of engineering education concepts towards engineering education 4.0

The advancing technology and digitalisation thrusts, enhanced by the global COVID-19 pandemic restrictions, have not only led to new markets and also challenges in the industry but also, and especially in, the entire education system. The transformational educational processes triggered by the pandemic across all societal sectors, institutions, as well as life spans, now require a so-called long-term inclusion (Zeuner 2014). The explosive adaptation of learning and educational processes to the micro, meso, and macro levels of human learning in terms of the usage of digital media and tools opens up unprecedented learning spaces and new opportunities. These transformation processes are flowing into all areas of social life and are being massively advanced by the rapidly progressing implementation of Industry 4.0 technologies (digitalisation) and technological concepts (digital transformation). These new approaches require not only a transformation of teaching and learning methods but also a new conceptualisation of learning content and imparted competencies, especially in higher education for the experts of tomorrow (Teo et al. 2021). The novel Industry 4.0-related technologies further require new and extended qualifications, knowledge, and competences of future engineers. In this regard, Roudaut (2019) stresses the need for a realignment of educational services and derives a total of eight pillars with specific implications for the realignment of higher education curricula (Roudaut 2019). Above all, it also requires an adapted mindset concerning the willingness and necessity to flexibly engage with new things (e.g. approaches, programs, work steps) and the readiness to continue learning and self-education throughout life both professionally and privately to cope with new economic and social developments of the twenty-first century. According to Teo et al. (2021), this mindset contains all relevant skills enabling a person to deal with the technological complexities of the current century, also known as twenty-first-century skills (Binkley et al. 2012; Teo et al. 2021). Thus, two major transformational processes and implications for engineering education in the tertiary sector can be derived from the current trends. On the one hand, the expansion of the understanding of education to the entire lifespan and the focus on the individual educational trajectories, which forces the resulting participant-centeredness, is mandatory. Accordingly, the increasing shift from teacher-centeredness to participant-centeredness must be made, especially in the higher education sector. On the other hand, by focusing on innovations through the implementation of new (digital) concepts in the industry, the increasing value of the human capital of a company and the entire industry can be observed. As a result, the education and training of employees are increasingly seen as an innovative force and thus represent an essential competitive advantage (Zsifkovits, Woschank, and Pacher 2021).

Figure 1 illustrates the factors influencing the engineering education of tomorrow. The requirements resulting from the LLL approach on the one hand and the human capital of companies with the respective subjective abilities, skills, and attitudes of engineers on the other hand have influences and implications on the future design of engineering education. Thus, engineering education is subject to social, economic, and individual development and change processes (Euler 2020; Geißler and Orthey 1998). The universities are now challenged to successfully implement the tendencies/demands and thus to ensure the ability to work, the understanding of the role of engineers, and the competitiveness of future generations (Ramirez-Mendoza et al. 2018). This transformation requires a new conceptualisation or adaptation in a holistic way, i.e. adaptations on the institutional level, efforts concerning transdisciplinary cooperation with industry, as well as a push towards national and international cooperation (Fomunyam 2019).

Figure 1. Influences on engineering education.

Education can be considered as a central investment in the future, especially in, what (Schäffter 1998, 2001) defines as today’s transformation society. Thereby, one of the essential goals is the ongoing development and necessity of lifelong learning (LLL) to ensure skills development, employability, and long-term competitiveness. Therefore, the teaching of relevant and up-to-date skills is indispensable and represents a central element of the European pillar of social rights. Thus, transnational high-quality education should be made available to all people, so that they can actively and self-confidently make a significant contribution as citizens to further development and ongoing innovation. The demand here lies in fundamental reforms of European education systems and their positioning towards future-oriented knowledge, skills, and competencies ‘adapted to the digital age’ (European Council 2017). Since technological progress (based on technologies like Artificial Intelligence, robotics, IoT, etc.) is developing rapidly, a lifelong investment in key skills and above all, digital skills are required. The tertiary sector is particularly called upon to push ahead with sustainable reforms in terms of skills development and the incorporation of labour market trends to ensure the availability of next-generation professionals. Practical experience, new learning instruments, and materials, the use of digital technologies, and a life-world orientation must be incorporated into modern curricula (European Commission 2018). In this context, flexibility, adaptability, resilience, and competences in the field of engineering are regarded as essential success factors to further develop the long-term competitiveness of a region at both national and international levels to strengthen its position as a business location and to increase the employability of all people. Under the postulate Industry 4.0, the permanently and rapidly developing digitalisation of the working world through the penetration of new technologies such as Augmented Reality, Virtual Reality, Cyber-Physical Systems, Digital Twins, etc. requires the implementation of new methodological-didactic teaching and learning settings, so to speak, ‘Education 4.0’ (Kuo et al. 2021). Moreover, Miranda et al. (2019) explain the concept of Education 4.0 as the provision of new teaching and learning methods and innovative facilities in line with the emerging technologies to equip future engineers with the essential competencies to solve global, regional, as well as local problems. In addition, the authors present four main elements of Engineering Education 4.0, namely: (1) the implementation of current and emerging ICT, (2) the incorporation of new learning methods, (3) the creation of innovative facilities to improve learning processes. and the (4) development of core competencies (Miranda et al. 2019). The aforementioned demands on individuals and society as a whole, require the continuous acquisition of new knowledge, qualifications, and competencies over the entire lifespan. Ergo, learning over the entire lifespan acquires a double meaning. On the one hand, LLL means for the educational subjects the chance for personal and professional development and change over the entire life span. On the other hand, the necessity of LLL implies the permanent challenge for subjects, but also for society as a whole, to maintain and further develop work and competitiveness. LLL thus influences both the individual and the societal dimension and consequently leads to the dissolution of learning boundaries in terms of time, space, and content. Thus, engagement with learning and educational processes must be considered across the entire lifespan and, therefore, permeate through all phases and domains of life. In other words, learning is implicated in the biography of each individual (Hof, Meuth, and Walther 2014; Schröer et al. 2013). To ensure the necessity of implementing the LLL approach, Figure 2 displays the concept of circular education which will be used to divide the learning over the entire lifespan into four dimensions.

Figure 2. The circular education model.

According to the circular education approach, whereby circular is understood in the dimensions that education is a continuous cycle and knowledge is not lost but learning and teaching continue to interact and develop within and with each phase, the lifespan is divided into a total of four dimensions and ranges from earliest childhood to high adulthood. Due to the increasingly blurred boundaries between life stages and ages, these four areas are to be understood as dimensions with fluid transitions, and not every person passes through each dimension, as they can also be skipped or considered at a later point in time. The first dimension covers the period from early childhood to the end of basic education. In the second dimension, higher education and all related educational formats are included. Gainful employment and its educational activities are located in the third dimension ‘vocational education and training’ (VET). The fourth dimension includes all adult education activities, whether formally, non-formally, or informally acquired. Specifically – in today’s understanding of vocational education and training – the third and fourth dimensions are becoming increasingly blurred. Vocational education and training is understood as continuous – i.e. lifelong – learning. The disruptive changes in society and the labour market require not only a high degree of self-direction on the part of individuals but also additional skills in particular. These skills include, for example, the autonomous development of information sources and the (re)modification of familiar routines and perspectives. Thus, in the future, the individual will be placed at the centre of learning, with subjective ability playing an essential role. (Arnold 2017) refers in this context of the guiding principle of the ‘reflexible man’, whereby the combination of both specialist knowledge and subjective methodological, social, and personal skills is important. Reflective appropriation processes thus come to the fore at and in the confrontation with social and professional tasks and in turn require a further development of Engineering Education towards Engineering Education 4.0 (Arnold 2020). A professional and successful design of educational activities requires the inclusion of essential core aspects in the planning, implementation, and evaluation phases. Transferred to pedagogical practice in higher education, this implies a reorientation to the entire institutional level. First, the concept of LLL and the accompanying de-standardization of learning and life phases and topics necessitates the adaptation of institutional frameworks. Ergo, the learning dimensions must be expanded to include informal and non-formal aspects, which in turn affect the macro, meso, and micro levels of learning. Thus, the focus of learning efforts also shifts to the individual level and must be adapted to the specific situation. This means the participant and their respective life context must be considered when planning educational measures. Through the concept of LLL and the accompanying shifts in learning and educational processes, the following didactic guiding principles for pedagogical practice in adult education can be derived: (1) participant orientation, (2) case reference, (3) practical relevance, (4) group dynamics, (5) orientation to everyday life, (6) self-determination, and (7) biography-orientation (Ludwig 2018). To offer high-quality lectures at the Montanuniversität Leoben, the aspects described above must be included in the program planning in advance and current contexts such as practical requirements must be considered to guarantee educational success. According to (Tietgens 1992), expectations, needs, and/or wishes of all key stakeholders involved in the learning process in the respective discipline can be emphasised as an essential success factor. Only in this way it is possible to respond to current trends and challenges in practice and to equip future engineers with the necessary knowledge, qualifications, and competencies. These must then in turn be fed back into the didactic guiding principles and maxims of higher education, to be able to guarantee professional methodological-didactic training programs. Furthermore, (Pacher, Valakas, and Adam 2020) investigated the educational needs in the extractive sector based on an extensive study within the framework of an EU project and concluded that the focus of higher education should be on the training of transversal competencies such as soft skills, decision-making skills, or digital competencies. In addition, practical testing of the technical competencies acquired during studies is essential for future careers. Due to the advancing internationalisation efforts, (Bauer et al. 2014) also highlight the need to develop language skills, especially concerning the English language. Accordingly, an expansion of the essential transversal key competencies is required to prepare the future experts of tomorrow for the challenges in their daily private and professional lives. The educational systems at universities should include new learning materials, systems, instruments, and resources (Zunk and Sadei 2015). On the one hand, this will strengthen (online) cooperation and, on the other hand, it will include the life-world orientation of the learners, thus levelling supposed socio-economic performance differences. Additionally, this approach can increase equal opportunities, as well as learning efficiency through a subjective reference to the motives and concerns of the respective target group (European Commission 2020). To ascertain further requirements and expectations of the lecture, the authors of this article carried out an additional extensive study, in addition to the literature research, to be able to further advance the professional development of teaching at the Montanuniversität Leoben and thus, on the one hand, guarantee an essential contribution to competitiveness in the metal forming industry on the other hand, to increase the employability of the future experts. The lecture was already designed in advance, according to the principles of constructive alignment (Biggs and Tang 2011), and will be adapted based on the research results from the empirical study and the implications of the COVID-19 pandemic in the course of this paper. Thereby, the authors follow the principles of the Plan-Do-Study-Act (PDSA)-circle (Deming 1998; Shewhart 1986) and adapt the lecture planning based on continuous feedback loops. As a result, the final lecture described in this work should consider all points illustrated in Figure 3 which includes all influencing exogenous and endogenous factors that are mandatory for the development, planning, and for the subsequent implementation of an Industry 4.0-related lecture. This will, therefore, serve as a pilot project for upcoming lectures and curricular adaptions at the Montanuniversität Leoben by following the Transdisciplinary Engineering Education approach (Ralph et al. 2021).

Figure 3. Transdisciplinary engineering education.

As already described in this chapter, in the future modern vocational education and training will (have to) aim at the training and application of subjective learning and reflection skills to be able to derive and thus also solve concrete action practices in and from the confrontation with complex social as well as labour market challenges. Thus, further developments in society and the economy require not only changes in the labour market, but also on the individual level (human capital) and in education and training. In this context, (Soni, Hasteer, and Bhardwaj 2020–2020) present a total of 9 pillars of Engineering Education 4.0 and their implications for the entire vocational training system. Modern Engineering Education 4.0 should follow the principles of methodological-didactic program planning and focus on participant-centeredness. The combination of knowledge and hands-on activities should be enabled by innovative methods and promote autonomous learning. By incorporating practice-oriented tasks, students should be enabled to apply professional competencies as well as interdisciplinary skills. The transdisciplinary approach to the challenges also opens up an interdisciplinary perspective for the students and should thus contribute to the expansion of the individual ability to act (van der Veen et al. 2020; Zunk and Sadei 2015).

3. Development of the initial lecture concept

To be able to include preferences and requirements from students and industry during the developing phase, a first concept including the core technologies and frameworks of digitalisation and digital transformation was designed (Ralph, Pacher, and Woschank 2020). This concept is based on state-of-the-art learning techniques and was initially designed without Covid-19 based restrictions. In the sense of ‘constructive alignment’ according to (Biggs and Tang 2011), the teaching and learning concept is aligned with the learning outcomes, the teaching and learning activities, and the final assessment. The focus of the concept is participant-orientation by using the method of (Cohn 1989) (topic-centered interaction is used to place topics, questions, or ideas in the centre elaborated on by the participants in mutual exchange). Accordingly, all teaching and learning materials are designed to meet the needs of the target group. Through the experience and competence of the lecturers, the integrated lecture conveys fundamentals and in-depth knowledge that are essential for understanding and assessing current digitisation processes in industrial practice. Fundamentals and theory are illustrated and reflected by concrete practical examples (Coşkun, Kayıkcı, and Gençay 2019; Edward 2002).

The lecture is built up modular in a blended-learning format. In module I to III, the teaching content is essentially conveyed through compact lectures with the help of multimedia support, as well as interactive phases (workshops, question rounds, etc.). The four modules are coupled and are each held in the summer semester and over one month. Block 2 and 4 are held as classroom sessions and block 1 and 3 as online learning via the online-platform ‘CISCO WEBEX’. In addition, the theory blocks are supported by synchronous and asynchronous teaching methods. This supports a more flexible scheduling of the learning content for students. Derived from current literature, as well as the authors’ practical teaching experience, after successful completion of the lecture the students should be able to: (1) create and evaluate concepts for digitalisation in metal forming related production systems, (2) apply the theoretical concepts in a case study, (3) implement them together with experts from different disciplines, and (4) understand and implement the applied procedures in practice based on the theoretical and practical knowledge acquired. Figure 4 illustrates the fundamental scope and module-dependent learning objectives of the lecture.

Figure 4. Module definition and corresponding learning outcomes for the lecture.

Another restriction to consider is the strategic fit within the curricula of potential participants. For the first implementation, a workload of 2.5 European Credit Transfer System (ECTS) credit points (CP) was set up, resulting in a maximum overall workload of 75 h (Directorate-General for Education and Culture 2005; European Commission 2008; Grosges and Barchiesi 2007). Based on all mentioned requirements and restrictions, the following Tables 1–4 summarise the initial module definitions.

Table 1. Initial lecture definition for the first module, adapted from (Ralph, Pacher, and Woschank 2020).

Module I: Scope and duration (h)	Applied methods	Used materials	Learning objectives
Introduction into opportunities and issues of digitalisation technologies in the metal forming environment (2)	Icebreaker and subsequent presentation; Group discussion	PPT; Handouts; Videos	Awareness of the potential impact of key technologies of the fourth industrial revolution
Fundamentals of digitisation, including sensor and actuator technologies (7)	Self-study using e-learning platform	Online script; State of the art research papers; videos	Knowledge about the basics of state-of-the-art digitisation technologies in the metal forming environment
Fundamentals of digitalisation, including networking technologies, state of the art protocols, interfaces, data management, and IT-security (7)	Self-study using e-learning platform and external tutorials	Script; State of the art research papers; Videos; Prepared scripting examples	Understanding the potential of sophisticated and non-proprietary networking solutions; Ability to connect requirements of digitisation to a digitalisation framework
The importance of CPPS and corresponding HMI in the metal forming environment (7)	Self-study using e-learning platform and external tutorials	Script; State of the art research papers; Case study videos from the SFL	Ability to define and understand CPPS in the metal forming environment; Realisation of the importance of accurate HMI options
Definition of Big Data, AI, DT, and DS within the metal forming industry (7)	Self-study using e-learning platform	Script; State of the art research papers; Case study videos from the SFL	Accurate definition of DT, DS, AI, and Big Data; Awareness of the connection between simulation engineering, digitalisation, and data management

Table 2. Initial lecture definition for the second module, including practical exercises, adapted from (Ralph, Pacher, and Woschank 2020).

Module II: Scope and duration (h)	Applied methods	Used materials	Learning objectives
Practical demonstration of the fundamentals of networking technologies, state of the art programming languages, and resulting layer architecture at the SFL (2)	Face to face lecture; group discussion	Digitalised forming machine systems at the SFL; corresponding IT-infrastructure	Knowledge transfer from theory to practice on a holistic basis
Practical demonstration of a developed CPPS and corresponding HMI at the SFL (2)	Face to face lecture; group discussion	Digitalised and retrofitted rolling mill aggregate at the SFL	Knowledge transfer of CPPS and HMI and underlying technologies from theory to practice
Demonstration of different possibilities of interface design and layer architectures at the SFL (2)	Face to face lecture; group discussion	SFL infrastructure; Case study of digitalised CNC-lathe	Awareness of benefits and downsides of different commonly used interfaces within a manufacturing digitalisation environment in practice

Table 3. Initial lecture definition for the third module, adapted from (Ralph, Pacher, and Woschank 2020).

Module III: Scope and duration (h)	Applied methods	Used materials	Learning objectives
Recap block (0.5)	World Café (break out session)	MIRO	Stepping up and deepening the learning process for information provided in module I and II
Discussion of major issues arising within the implementation of digitalisation approaches within an industrial environment (0.5)	Face to face lecture; group discussion	PPT; Board	Realisation of the importance of social-cultural aspects within a digitalisation project
Introduction in appropriate frameworks to overcome social-cultural tensions within the manufacturing environment (0.5)	Face to face lecture; group discussion	PPT; Board	Awareness of the most common frameworks of change management
Possibilities of implementation of change approaches in the manufacturing environment (0.75)	Face to face lecture; group discussion	PPT; Board	Deepened theoretical knowhow regarding overcoming of change based resistance

Table 4. Initial lecture definition for the fourth module, including final examination, adapted from (Ralph, Pacher, and Woschank 2020).

Module IV: Scope and duration (h)	Applied methods	Used materials	Learning objectives
Handing out and guidance for elaborating on prepared case study (1)	Face to face lecture; Self-study using e-learning platform	Prepared case studies	Know how to elaborate a given project (case study)
Preparation for final group presentation (20)	Individual group lectures;	Prepared case studies; Script and external sources	Know how to transfer gained knowledge into a practical case
Final group presentation (1)	Presentation; feedback loop	PPT; Board; Other available media sources	Know how to present results as a project leader within a presentation to superiors in a clear and professional way

The workload determined by the scope of the module blocks sums up to a total of 61 work hours. Leaving an additional 14 work hours for self-study activities, where the scope of this activity is not exactly defined. Furthermore, recommended comprehensive literature is made available to all participants by the used online-platform ‘Moodle’, allowing students to elaborate on a specific topic of interest more deeply.

4. Stakeholder analysis and systematic identification of knowledge gaps

To provide the most efficient and effective educational experience, it is necessary to know the main stakeholders and their respective needs to involve them in the continuous development. Table 5 shows a comprehensive overview of the identified stakeholders, derived from (Meyer and Bushney 2009).

Table 5. Identified stakeholders for the lecture (re-)design (Meyer and Bushney 2009).

Stakeholders	Reason for inclusion	Way of inclusion in the lecture development
Participating engineering students	The most important stakeholders are at the centre of attention	Representative survey; adaption of initial teaching methods scope
Employers	Provide jobs for graduated students; know what skills are important to become successful	Representative survey; adaption of weighting of different module parts within the lecture
Alumni and experts (have worked, or are currently working, in the metal forming environment with an engineering or IT background)	Know which skills are important in industrial practice for their specific engineering discipline	Personal interviews; recommendations were included in the development of the first structure
Local universities	Possibility of using external know-how and lessons learned from their local initiatives	Personal interviews with academic staff from other technical universities within Austria; gathered information was included in the development of the first structure of the lecture
International universities	Comparing other international curricula to the planned initiative	Research about similar engineering programs and how they included digital transformation in their curricula; gathered information was included in the development of the first structure
Government departments	Legal basis; special consideration of restrictions due to ongoing Covid-19 crisis (e.g. limitation of students; mandatory distance learning)	Including a variety of different teaching techniques for each part of a module to sustain a proper educational experience for all participating students regardless of actual restrictions (from face-to-face to completely online)
Lecturers	Mainly responsible for creating a stimulating environment for the best possible knowledge transfer to lectures’ participants	Did the development of the first structure and carried out the research, personal interviews, and surveys; adapt the first structure of the lecture based on the results of the gathered information

As illustrated above, seven key stakeholders were identified. Alumni and other experts, as well as lecturers from other local universities, were included in the adaption of the initial technical scope of the lecture. In the course of this research, alumni mainly contributed to the further development by suggesting practical cases from their daily work-life experience, which the lecturers subsequently use to exemplify the theoretical fundaments in module 1 and 3, as well as for the validation of the practical demonstrations carried out in module 3 at the SFL. The in-depth interviews with staff from other universities led to a further broadening of the initial context, as these institutions have a different research focus and, therefore to some extent, a slightly different point of view on the overall topic. The investigation of similar academic lectures in international curricula specifically contributed to the initial elaborated lecture concept, whereby the essential focus here was also on the technical scope of the lecture that had to be addressed. The Covid-19 pandemic induced additional legal and governmental restrictions in terms of the teaching methodology which resulted in additional effort for the lecturers by increasing the amount of distance learning methods required. The main objective of the empirical study was to develop evidence-based implications for the redesign of the initially conceptualised engineering education lectures which focused on the topics of digitisation and digital transformation in the Austrian metal forming industry. Based on the current state of the art and guidelines for empirical research studies, the authors therefore designed and subsequently conducted two questionnaire surveys (Bortz and Döring 2009; Kromrey 2009; Maylor and Blackmon 2005). Based on the focus of the research study, the authors identified (1) potential manufacturing companies in the Austrian metal forming industry and (2) engineering students as key informants for this empirical-based lecture redesign approach and subsequently for the design of the pedagogical framework for the intended teaching and learning approaches. Therefore, two independent surveys were conducted to increase understanding of the empirical reality for the systematic development of the competencies for the engineers of tomorrow. The scope and resulting questions within the carried-out survey are a result of profound literature analysis, expert interviews in the industry, and the practical experiences of lecturers. Additionally, the authors working closely with their respective industry partners were asked during personal meetings within joined projects, presentations, and conferences about the most important content they think should be included in such a survey. The resulting scope was then further concretised under consideration of the other stakeholders, with a special focus on the respective lecturers and their personal industry experience. As a result, three different question categories were created. The variable and the underlying indicators of DIG (digitalisation) are focused on the current knowledge in terms of digitalisation by reflecting the digitalisation maturity and the variable and the underlying indicators of DAT (data analytics) is reflecting the state-of-the-art knowledge in data analytics, meaning the abilities regarding data gathering and processing of the respective companies. Moreover, the variable and the underlying indicators of ATT (attribute) report the attitude of the respective companies regarding the fourth industrial revolution and corresponding organisational changes. To be able to connect the results of this survey to student expectations, the student survey consists of a transformed version of DIG and DAT, intending to identify the gap between state of the art in potential employers’ companies and the already gained skill set of the questioned students. Like the company survey, the variable and its underlying indicators of LEC (lecture requirements) were additionally created for the potential participants, asking for their preferred way of knowledge transfer. For the data collection, the authors used a triangulated approach whereby random sampling was used within the student’s survey and theoretical sampling was applied to the company’s survey in the timeframe between September 2020 and November 2020. Within this combined approach, theoretical sampling is applied to decrease potential difficulties in obtaining relevant data, to avoid misunderstandings of the survey items by the target population, and to isolate confounding variables, while random sampling was chosen to compensate potential shortcomings in terms of validity and generalisation from the theoretical sampling approach (Zhu, Sarkis, and Lai 2008).

4.1. Research methodology and research results: empirical findings from the Austrian metal forming industry

To adapt the learning outcomes to fit the requirements of the industry, a total of 200 companies from the Austrian metal forming industry were surveyed. From the total number contacted, 64 questionnaires (32.00%) were completed, valid, and therefore, usable for the subsequent statistical procedures. Again, a non-response bias test (Armstrong and Overton 1977) did not show any significant differences between early and late respondents, which additionally indicates a high degree of transferability, respectively representational, of the established research results (Lippe 2011). All items were operationalised by using a 5-point LIKERT scale from 1 (e.g. not agree) to 5 (e.g. fully agree). The resulting questionnaire contains three major theme blocks: (1) DIG: asking for the digitalisation maturity of the respective company, (2) DAT: evaluating the knowledge regarding data analytics, and (3) ATT: analyzing the attitude of the respective companies regarding the fourth industrial revolution and corresponding organisational changes. The questions were derived from the authors’ experience, as well as expert interviews carried out in advance, to ensure the comprehensibility of potential participants. The scope and results of the survey are illustrated in Table 6.

Table 6. The Austrian metal forming industry: Survey scope and results from valid responses.

Item	Text	N	Min.	Max.	Mean	Std.Dev.
DIG_1	All production processes that occur are recorded by a higher-level ERP system.	64	1	5	3.33	1.574
DIG_2	All production processes that occur are controlled and timed automatically using an MES system, PPS, or ERP system with similar functionality.	64	1	5	2.69	1.457
DIG_3	The machines used all have at least one interface to higher-level systems (SCADA on MES/ERP).	64	1	5	2.72	1.397
DIG_4	Captured processes and general production data are stored and processed via cloud solutions.	64	1	5	1.97	1.403
DIG_5	Data can be made fully available through an interface for external use by other applications such as business intelligence.	64	1	5	2.47	1.345
DIG_6	Internet of Things solutions are used on a large scale in production (e.g. IIoT gateways, transmission using IoT protocols such as MQTT).	64	1	5	1.81	1.296
DIG_7	Collected data is analyzed using big data technologies.	64	1	5	1.81	1.332
DIG_8	Important production processes are modelled with simulation programs (e.g. finite element simulation).	64	1	5	2.36	1.396
DIG_9	The visual representation of production data is structured and user-friendly.	64	1	5	2.64	1.289
DIG_10	All production processes are fully described using standards.	64	1	5	3.25	1.297
DIG_11	Finite element simulations are used for troubleshooting as well as process optimisation.	64	1	5	2.23	1.488
DIG_12	Simulations interact directly with a higher-level production system (e.g. SCADA, MES, ERP)	64	1	5	1.80	1.311
DAT_1	Process data is archived completely digitally.	64	1	5	3.45	1.126
DAT_2	All production processes include controls and auditing bodies to ensure conformity with internal and external requirements.	64	1	5	3.56	1.320
DAT_3	Quality controls are fully digitised and archived.	64	1	5	3.17	1.279
DAT_4	(Short-term) changes in the production plan are fully and transparently integrated into the existing control systems.	64	1	5	2.97	1.357
DAT_5	Process data is collected completely automatically.	64	1	5	2.42	1.206
DAT_6	In the event of a failure of the production control system, production can be carried out completely manually if necessary (until repairs are made).	64	1	5	3.78	1.362
DAT_7	The provision of data for internal purposes is completely digital.	64	1	5	3.25	1.113
DAT_8	The data collected is transparent and used for analysis and comparison.	64	1	5	3.00	1.141
DAT_9	The value chain (purchasing, logistics, production, sales, after-sales service) is fully digitised and can be viewed transparently by all areas of the company.	64	1	5	2.83	1.121
DAT_10	Data is always the basis for improving the business process.	64	1	5	3.31	1.220
DAT_11	Sufficient IT security is ensured at all digital levels (data security and protection of all systems).	64	1	5	3.84	1.224
ATT_1	There is a clearly defined digitisation strategy in the company.	64	1	5	2.83	1.077
ATT_2	There is a dedicated person responsible for digitisation issues (internal or external).	64	1	5	2.86	1.435
ATT_3	The management level promotes the digital transformation in the company credibly and believes that progressive digitisation will ensure the company’s success in the long term.	64	1	5	3.33	1.235
ATT_4	Digitisation solutions that have already been implemented make an important contribution to business success, especially during the ongoing Corona crisis.	64	1	5	3.36	1.302
ATT_5	Digitisation solutions that have already been implemented have increasingly led to redundancies in your company in the past.	64	1	5	2.09	1.519
ATT_6	Workers and employees in the company fully welcome digitisation and digital transformation in the company.	64	1	5	3.13	.968
ATT_7	The productivity of your company is much higher than that of your competitors.	64	1	5	2.95	.785
ATT_8	The economic success of your company (profit) is significantly higher than that of your competitors.	64	1	5	2.92	.841
DIG	Mean from DIG_1 to DIG_12	64	1	5	2.42	.898
DAT	Mean from DAT_1 to DAT_11	64	1	5	3.24	.792
ATT	Mean from ATT_1 to ATT_8	64	1	5	2.93	.735

In the next step, the variables DIG, DAT, and ATT were computed as an amalgamation of the underlying indicators. The resulting Cronbach’s alpha values (CBA_DIG = .875; CBA_DAT = .860; CBA_ATT = .779) are above the recommended threshold of 0.600 and therefore, ensure the internal consistency of the respective scales (Hair, Da Gabriel, and Patel 2014; Heath and Jean 1997). Table 7 shows the result of the correlation analysis. Thereby, the results showed no significant correlations between DIG and DAT (.212), highly significant correlations between DIG and ATT (.435**), and highly significant correlations between DAT and ATT (.583**).

Table 7. The Austrian metal forming industry: Correlations between DIG, DAT and ATT.

		DIG	DATA	ATT
DIG	Correlations (Pearson)	1	.212	.435**
	Significance (2-tailed)		.093	.000
	N	64	64	64
DAT	Correlations (Pearson)	.212	1	.583**
	Significance (2-tailed)	.093		.000
	N	64	64	64
ATT	Correlations (Pearson)	.435**	.583**	1
	Significance (2-tailed)	.000	.000
	N	64	64	64

The statistical analysis of the conducted survey demonstrates the differences between theoretical and practical state-of-the-art in this specific industry segment. Reviewing the degree of automation and digitalisation (DIG), a majority of participating companies did not fulfil the requirements for the implementation of Industry 4.0 technologies according to the literature (e.g. CPPS, DT). This hypothesis is supported by the results of the DAT block, which reveals a lack of effective data gathering and, as a result, in-transparency of a majority of production processes outside the main domain. Despite this, data visualisation and user-friendly HMIs are already standard. On the contrary, commitment and therefore, willingness to change from involved staff on different levels can be observed. For the adaption of the first lecture concept, the following main outcomes can be stated: (1) basic knowledge about ERP/MES/PPS systems are mandatory, (2) know-how about SCADA related technologies and tools is a requirement to work in this industry segment, (3) enhancing valid data gathering can add significant value to a majority of participating companies, although the importance of this skill is not recognised by most of them, and (4) numerical simulation of production processes, IIoT, Big Data solutions, as well as, the ability to integrate (numerical) simulations into the production network is a distinguishing factor for potential employees and can, therefore, be seen as an asset for applicants that are capable of using these tools (Table 8).

Table 8. Engineering students at the Montanuniversität Leoben: Survey scope and results from valid responses.

Item	Text	N	Min.	Max.	Mean	Std.Dev.
DIG_1	Can you distinguish between the terms ‘digitization’ and ‘digital transformation’?	233	1	5	2.41	1.122
DIG_2	Can you define the term ‘digitization’?	232	1	5	2.91	1.155
DIG_3	Are you familiar with the term ‘internet of things’ or ‘industrial internet of things’ and can you define it?	232	1	5	2.88	1.429
DIG_4	Are you familiar with and able to define the term ‘cyber physical systems’ or ‘cyber physical production systems’?	233	1	5	2.23	1.335
DIG_5	Can you define the term ‘human machine interface’ and do you know what is meant by it in industrial practice?	230	1	5	2.56	1.296
DIG_6	Are they familiar with the definition and distinction of ‘big data’ in an industrial context?	234	1	5	3.13	1.243
DIG_7	Can you define the term ‘digital twin’?	231	1	5	2.64	1.465
DIG_8	Do you know the difference between a ‘digital model’, ‘digital shadow’, and ‘digital twin’?	232	1	5	1.76	1.196
DIG_9	Do you know what exactly is meant by ‘retrofitting’ in the context of digitisation?	232	1	5	1.69	1.205
DIG_10	Can you define the terms ‘vertical and horizontal integration’ in production?	234	1	5	2.31	1.462
DIG_11	Are you familiar with the basic concepts of IT security in an industrial context?	232	1	5	2.27	1.252
DIG_12	Do you know the ‘OSI reference model’?	233	1	5	1.58	1.150
DIG_13	Are you familiar with the term ‘cloud computing’ and do you know what it means?	231	1	5	3.06	1.360
DIG_14	Are you familiar with the concepts of change management in the industry?	231	1	5	2.44	1.422
DIG_15	Are you familiar with the basics of data and database management?	232	1	5	3.04	1.383
DAT_1	Are you familiar with the different levels of the automation pyramid?	234	1	5	2.11	1.203
DAT_2	Do you know one or more of the following programming languages: Python, R, C, C++, Java?	234	1	5	3.44	1.479
DAT_3	Can you define the term ‘MES’?	232	1	5	1.76	1.299
DAT_4	Can you define the term ‘ERP System’?	233	1	5	2.21	1.572
DAT_5	Can you define the term ‘SCADA’ in the context of production?	232	1	5	1.62	1.106
DAT_6	Do you know the most common protocol formats in the context of production planning and control?	232	1	5	1.65	1.062
LEC_1	In general, would you be interested in your course on the fundamentals of digitisation and digital transformation in industrial practice?	226	1	5	4.43	.837
LEC_2	Would you like to see most of the required theory taught via the Moodle platform (anytime access, text, image, and video material)?	225	1	5	4.31	1.000
LEC_3	Would you like a significant portion of the course to include practical components (demonstration of various technologies in a digital factory)?	227	1	5	4.57	.786
LEC_4	Would you welcome the opportunity to work on a case based on reality as a project manager? (Management of a digitalisation project)?	226	1	5	3.96	1.082
LEC_5	Would you welcome the opportunity to briefly present such a project as part of the course? (Presentation technique in practice)?	227	1	5	3.60	1.220
LEC_6	Do you feel able to take over project management or assistance in a digitisation project in industrial practice?	223	1	5	2.78	1.299
DIG	Mean from DIG_1 to DIG_15	234	1	5	2.46	.837
DAT	Mean from DAT_1 to DAT_6	234	1	5	2.14	.927
LEC	Mean from LEC_1 to LEC_6	227	1	5	3.94	.655

4.2. Research methodology and results: empirical findings from engineering students

For the design of the respective survey for students, the third block (for companies ATT) was changed to LEC (lecture: what requirements students have on a transdisciplinary lecture?). Additionally, questions within the item blocks DIG and DAT were adapted according to more accurate scientific definitions and extended with upcoming technologies that have the potential to become future standards in the metal forming industry segment. This approach should if necessary, ensure that future engineering experts also have the fundamental knowledge to execute independent LLL in this field of interest. For an upcoming analysis of potential deviations between students from different engineering disciplines and study progress, the enrolled field of study, as well as, study progress (bachelor, master, or Ph.D.) were additionally surveyed. To gain a valid overview of students’ actual knowledge and abilities, a total of 3,495 students from the Montanuniversität Leoben were surveyed. From the total number contacted, 234 questionnaires (6.70%) were completed, valid, and therefore, usable for the subsequent statistical procedures. Following the same tests for representativeness as in section 4.1, the results can be seen as valid. For the operationalisation, the same LIKERT scale as for the company survey was used (Armstrong and Overton 1977; Lippe 2011).

As with the company survey, the variables DIG, DAT, and LEC were computed as an amalgamation of the underlying indicators. Similarly, the resulting Cronbach’s alpha values (CBA_DIG = .899; CBA_DAT = .811; CBA_LEC = .688) are above the recommended threshold of .600 and therefore, ensure the internal consistency (Hair, Da Gabriel, and Patel 2014; Heath and Jean 1997). Table 9 shows the results of the correlation analysis. Thereby, highly significant correlations were found between DIG and DAT (.788**) and DIG and LEC (.222**). However, the results showed no significant correlations between DAT and LEC (.106).

Table 9. Participating engineering students at the Montanuniversität Leoben: Correlations between DIG, DAT, and LEC.

		DIG	DAT	LEC
DIG	Correlations (Pearson)	1	.778**	.222**
	Significance (2-tailed)		.000	.001
	N	234	234	227
DAT	Correlations (Pearson)	.778**	1	.106
	Significance (2-tailed)	.000		.110
	N	234	234	227
LEC	Correlations (Pearson)	.222**	.106	1
	Significance (2-tailed)	.001	.110
	N	227	227	227

The analysis of the questionnaire’s results reveals a very low degree of knowledge regarding Industry 4.0 enabling and corresponding technologies. Furthermore, know-how defined as mandatory from the industry’s point of view is specifically lacking within the majority of the participants. This evaluation indicates a fundamental change in the scope of the first concept of the lecture, changing the weighting of the topics of module I to more fundamental technologies topics (e.g. automation technologies, SCADA, MES). Additionally, the authors used an ANOVA to calculate significant differences in the variables DIG, DAT, and LEC between the bachelor, master, and Ph.D. students (Figure 5). The results showed statistically significant differences in the variable DIG (F = 4.248; Sign. = .001), statistically significant differences in the variable DAT (F = 4.248; Sign. = .015), but no statistically significant differences in the variable LEC (F = .393; Sign. = .676). By considering the relatively low deviation between the initial knowledge level of undergraduate and graduate students in comparison to the initial knowledge gap between postgraduate students and those parties, the authors decided to not differ between bachelor and master students. As the forecasting of potential participants on postgraduate level, derived from actual student statistics implies that the amount of this group will be relatively low in comparison, these students will also be offered the same lecture experience. This approach has an additional advantage for all three parties: postgraduate students can support the lecturers by giving additional examples from their experiences to those who are less familiar with the topic, which should increase the level of interaction between attendees and lecturers and finally should lead to an overall higher engagement of all parties with the topic. Furthermore, this study reveals that in the past, no educational efforts at the Montanuniversität Leoben, independent from the degree level, were able to successfully build up knowledge in a majority of Industry 4.0-related topics, especially data management, among engineering students.

Figure 5. Differences in the mean value of the defined item blocks: comparison between bachelor, master, and Ph.D. students.

To identify potential differences in initial knowledge about the lecture’s topics, students were grouped according to two summary disciplines: (1) core manufacturing disciplines (CMD): engineering disciplines that have a direct connection to manufacturing processes (e.g. mechanical engineering, metallurgy, and materials science, industrial logistics, industrial energy technology) and (2) supportive manufacturing disciplines (SMD): engineering disciplines that are indirectly related to manufacturing processes or the metal forming environment (e.g. raw materials engineering, recycling). In this case, the results showed no significant differences in the variable DIG (T-value = −.715; p-value = .475), no significant differences in the variable DAT (T-value = −.203; p-value = .839), and no significant differences in the variable LEC (T-value = −.249; p-value = .804) between the CMD and SMD groups. The descriptive results of this analysis are illustrated in Table 10.

Table 10. Descriptive results: Core manufacturing disciplines (CMD) versus supportive manufacturing disciplines (SMD).

	Sample	N	Mean	Std.Dev.	Std.Err.
DIG	CMD	189	2.401	.790	.058
	SMD	26	2.522	.917	.180
DAT	CMD	189	2.090	.872	.064
	SMD	26	2.128	1.117	.219
LEC	CMD	185	3.927	.646	.048
	SMD	23	3.964	.782	.163

The feedback from participating students regarding the lecture design leads to the conclusion that the general scope, as well as proposed learning methodologies, are reasonable and will result in proper engagement from participating students. The relatively low score regarding question LEC_6, as well as within the DIG and DAT item block implies that the learning objectives initially defined (section 3) are suitable.

4.3. Identified knowledge gap: Austrian metal forming industry versus engineering students

The authors evaluated significant differences between the student sample and the company sample in the variables DIG and DAT. The results showed no significant differences in the variable DIG (T-value = .296; p-value = .768) but highly significant differences in the variable DAT (T-value = −8.668; p-value = .000) between the student sample and the company sample. The descriptive results are displayed in Table 11.

Table 11. Descriptive results: Austrian Metal forming Industry versus Engineering Students.

	N	Minimum	Maximum	Mean	Std.Dev.
DIG	298	1	5	2.451	.849
DAT	298	1	5	2.372	1.006
	Sample	N	Mean	Std.Dev.	Std.Err.
DIG	Students	234	2.459	.837	.055
	Companies	64	2.423	.898	.112
DAT	Students	234	2.135	.927	.061
	Companies	64	3.236	.792	.099

Especially in the data segment, a significant gap between the actual knowledge of engineering students and requirements from potential employers can be seen. This result is particularly interesting, as companies from the Austrian metal forming industry are already behind in terms of effective and efficient data management for Industry 4.0 purposes compared to literature. This context will be considered in the final lecture redesign, to be able to prepare future experts in the metal forming field for their career and thus enhance respective companies’ performance in a digitalised working environment.

5. Empirical-based redesign of the initial lecture concept

For the sake of comprehensibility, the result section is divided into two parts. In subsection 5.1, the adaptions are described using the transdisciplinary engineering education approach as outlined in chapter 2. In addition, the adaptions regarding scope based on results from 4.1 and 4.2 for the initial concept (section 3) are demonstrated. In 5.2, the further improvement of the initial lecture based on the Plan-Do-Study-Act (PDSA) cycle is defined, ensuring competitiveness and therefore, enabling the Montanuniversität Leoben to use this didactical framework and corresponding lecture as a basis for the successful transformation of current lectures or creation of other transdisciplinary lectures. Figure 6 shows the resulting redesign approach, based on the implications from sections 2, 3, and 4 by dividing the conceptualised redesign approach for a state-of-the-art digitalisation and digital transformation lecture into the following steps: (1) required initial data, (2) resulting initial inputs, (3) fundament for further optimisation, (4) data driven improvement, and (5) stakeholder orientated lecture concept.

Figure 6. (Re)design approach for a state-of-the-art digitalisation and digital transformation lecture: A stakeholder-oriented approach.

5.1. Lecture redesign

5.1.1. Learning content: adaptions in scope

The technical fundamentals of the fourth industrial revolution are mainly the scope of the first two modules of the initial lecture design (Figure 4, Table 1, Table 2). Based on the analysis of participated engineering students and metal forming companies, adaptions in scope and scope weighting within these two modules were conducted, as illustrated in Table 12 (module I) and Table 13 (module II).

Table 12. Adaptions made in the module I based on results of the executed stakeholder analysis.

Module I: Initial scope	Initial duration (h)	Adapted scope	Adopted duration (h)
Introduction into opportunities and issues of digitalisation technologies in the metal forming environment	2	Introduction into fundamentals of automation and networking technologies and the correlation with digitalisation technologies in the metal forming environment	3 (+1)
Fundamentals of digitisation, including sensor and actuator technologies	7	No adaption	7 (−)
Fundamentals of digitalisation, including networking technologies, state of the art protocols, interfaces, data management, and IT-security	7	Additional fundamentals of Computer Integrated Manufacturing (CIM), MES, and ERP	15 (+8)
The importance of CPPS and corresponding HMI in the metal forming environment	7	Fundamentals of CPPS and HMI	5 (−2)
Definition of Big Data, AI, DT, and DS within the metal forming industry	7	No adaption	7 (−)

Table 13. Adaptions made in module II based on results of the executed stakeholder analysis.

Module II: Initial scope	Initial duration (h)	Adapted scope	Adopted duration (h)
Practical demonstration of the fundamentals of networking technologies, state of the art programming languages, and resulting layer architecture at the SFL	2	No adaption	4 (+2)
Practical demonstration of a developed CPPS and corresponding HMI at the SFL	2	No adaption	2 (−)

The identified lack of knowledge about fundamentals in production technologies, as well as industry requirements on knowledge about SCADA systems, led the authors to the conclusion to increase the workload on the fundamentals of these technologies, in theory (Table 12) and in practice, as well (Table 13). As CPPS are not a focus of the industry and due to the lack of required knowledge from the potential participants’ point of view, a decrease in focus on this Industry 4.0 concept was defined. As a result of the higher amount of required workload (9 h), the preparation time for the final examination (initially 20 h), based on a group presentation (Table 4) will also be adapted. To ensure fair grading, a new concept for the performance evaluation was developed.

5.1.2. Area of application

Through the experience and competence of the lecturer, the integrated lecture conveys, on the one hand, fundamentals and in-depth knowledge that are essential for understanding and assessing current digitisation processes in industrial practice. Fundamentals and theory are illustrated and reflected by concrete practical examples.

5.1.3. Target groups and needs

This compact lecture is aimed at students from all fields of study who are interested in digitisation concepts and their practical implementation. In addition, a certain affinity for the development of innovative solution approaches concerning the challenges in the digital transformation is essential. The selection procedure is based, on the one hand, on submitted qualification certificates (diploma, work certificate) and on the other hand, on the respective positions in the curriculum. A prerequisite for admission to the lecture is the fulfilment of one of the following qualifications: (1) completed bachelor’s degree or degree from a university of applied sciences in a relevant field of study, (2) prerequisites and position of the lecture in the respective curriculum, or (3) freely accessible for all enrolled students at the Montanuniversität Leoben. The admission decision is made by the scientific management based on the submitted qualifications and the submitted case study. The maximum number of participants is 100. Two lecturers take turns in the practical part, due to COVID-19 divided into groups of five students each, i.e. ten groups per lecturer in the practical, two hours each, divided into three days per unit (currently one practical unit per group is planned). Depending on the current pandemic restrictions, the delivery of the practical sessions will be adapted to ensure the safety and health of all participants.

5.1.4. Learning outcomes

After successful completion of this lecture, students will be able to: (1) create and evaluate concepts for the digitalisation in metal-forming-related production systems, (2) apply the theoretical concepts in a case study, (3) apply and implement them together with experts from different disciplines, and (4) understand and implement the applied procedures in practice based on the theoretical and practical knowledge acquired.

5.1.5. Lecturers and course instructors

Lecturers play a crucial role regarding the learning success and the overall satisfaction of the participants respectively the students. The lecturers are highly diverse in terms of their disciplinary background, to be able to illuminate the contents and practical examples from different perspectives and points of view and thus to be able to demonstrate to the student’s comprehensive areas of application and practical feasibility in the engineering discipline. The lecturers are employed as Senior Researcher or Senior Lecturer at the Montanuniversität Leoben and therefore familiar with scientific research as well as teaching in their respective fields. To be allowed to teach at the Montanuniversität Leoben, it is necessary to have completed a didactic training, which is especially dedicated to the preparation, implementation, and evaluation of adult education measures. Thus, the lecturers have both technical and methodological-didactic expertise (Woschank and Pacher 2020).

5.1.6. Learning location and media

As outlined in the following section, the lecture will be held as a hybrid event. This means that two lecture blocks each will be held online via the CISCO WEBEX platform and on-site at the Montanuniversität Leoben. The lecture room of the Montanuniversität Leoben have been technologically updated in recent years and are therefore equipped for the latest teaching and learning methods. In addition, the Montanuniversität Leoben has a license for the CISCO WEBEX platform. With the help of this platform and the corresponding add-ins and tools, synchronous teaching can be carried out in a participant-oriented manner. Synchronous online teaching is supplemented by the use of other freely available online tools, such as MIRO board or MOODLE so that teachers and students can interact with each other.

5.1.7. Teaching and learning methods

In the sense of ‘constructive alignment’ according to (Biggs and Tang 2011), the teaching and learning concept is aligned with the learning outcomes, the teaching and learning activities, and the final assessment. The focus of the concept is participant orientation and for this, the method of Ruth Cohn (Cohn 1989) of topic-centered interaction is used to place topics, questions, or ideas in the centre and these are worked on by the participants in mutual exchange. Accordingly, all teaching and learning materials are designed to meet the needs of the target group. The selection of the main topics was made utilising an extensive survey of potential students and industry needs. The conceptual design, implementation, and results of the surveys are described in Chapter 4. The lecture is modular in a blended-learning format. The lecture consists of a total of four blocks and includes two semester hours of 50 contact hours and 25 h of self-study, for a total of 2.5 ECTS credits. In modules I to III, the teaching content is essentially conveyed through compact lectures with the help of multimedia support, as well as, in interactive phases (workshops, question rounds, etc.). The four modules are coupled and are each held in the summer semester over two months. Block II and IV are held as classroom sessions and block I and III as online learning via the platform CISCO WEBEX. In addition, the theory blocks are supported by synchronous and asynchronous teaching methods. This supports the more flexible scheduling of the learning content for students. In both learning formats, the principle of learning by doing will be in the foreground, i.e. the participants will take an active role in the learning setting and will also be encouraged to discuss their own examples, experiences and opinions on the respective topics in the plenum, thus contributing to the active exchange and knowledge transfer within the group. The theoretical inputs will be taken over directly by the lecturer on the one hand and within asynchronous sections the method of the flipped classroom will be applied, so that the students will work on different content-related questions on the topic beforehand in the context of individual or team settings and then present the results to the remaining students using presentation methods such as the Gallery Walk or the Think-Pair-Share method. The practical application-oriented contents are worked on by means of different settings and methods. Depending on the topic, either group work, business games, station learning, VR experiences, case vignettes, collaborative sketching, world café method, etc. are carried out. Here again, the social forms will alternate and ergo, the acquisition of knowledge and experience in individual, pair, or group work settings will be ensured. These hands-on methods should promote autonomous learning and place the participants, together with their expertise and experiences, at the centre. For the completion of the lecture, a sales ‘Elevator Pitch’ (module IV), has been integrated into the assessment. Here, the technical knowledge is combined with business know-how, or in other words ‘science to business’. It also affords the training of transdisciplinary soft skills required by the industry. A final discussion on the chosen methods and theories will be held, to ensure the highest possible practical relevance and to guarantee knowledge transfer from theory into practical applications.

5.1.8. Assessment and knowledge transfer

The assessment includes the active participation in the lecture, as well as, the contribution and presentation of the case study, and a short final discussion on the chosen methods and theories in the case study. To reduce the workload for the final examination and further enhance fairness and transparency in final grading, the group presentation initially developed is replaced by a short stand-alone version. Within this presentation, which should not exceed five minutes (‘Elevator Pitch’ (EP)), participants should demonstrate a possible solution to a case study previously handed out within module III. The prepared case study will include different aspects from all previous modules, whereas the given information within ensures that a suitable outcome can be realised within the calculated (reduced) preparation time of 11 h. The case studies prepared are slightly different for each participant, ensuring comparable but not identical solutions are proposed. The style, as well as, media mix used for the presentation is not restricted in any direction, allowing each candidate to choose what fits best to her/his needs. To actively involve the participants in the evaluation process and the results, each student is asked to evaluate his or her fellow for the performance in the EP scenario according to the criteria listed in Figure 7 (peer assessment). Consequently, both technical and soft skills knowledge should be deepened and reflected upon by following this approach.

Figure 7. Peer evaluation of a student’s performance in the final elevator pitch.

This presentation contributes to 75% of the final grade. After the presentation, a short discussion with the respective teacher is carried out, in which related theory to the presented topic is discussed. The students’ performance within this discussion is also part of the peer-review process. Additionally, the performance of the candidate within this discussion contributes to an additional 25% and is the only contribution to the final grade awarded by the corresponding teacher. Students are required to work independently on a case study (beginning of module 3) from an industrial context. The example will be handed out to the students by the instructor. In the final presentation, the results, including reflection and subsequent discussion, must be presented in the form of a so-called ‘elevator pitch’ of max. five minutes. The presentation of the case study, as well as, the presentation itself, will be written down in advance and submitted to the lecture instructor. The medium of the presentation is open, different forms are desired (e.g. videos, PowerPoint presentations, cards). The form of presentation must be agreed upon in advance with the instructor. The following explanations of the elevator pitch method should be presented to the students during the introduction in the first module (Denning and Dew 2012): (1) What is an elevator pitch? An elevator pitch is a short speech (verbal presentation) that is typically carried out within 1–5 min. The pitch outlines the most pertinent information and was devised around the concept that you could sell your idea in the time that it took for an elevator to reach its’ designated floor. So how much could be said in a typical elevator journey could depend on how many floors the elevator needs to travel, but in most cases, it is not too long, and ergo, not too much can be said. So, you need to make what you say, count! and (2) What are the typical components of an elevator pitch?: (i) introduction: Who are you and what do you do? (ii) services: What can you offer? (iii) target audience: Who is your target audience? (iv) Unique Value Proposition: How can you help your target audience and why? and (v) … and now? (next steps): What are you going to / How can you help them and what do you need from them? Afterward, the applied theories and methods, as well as their fundamentals, will be summarised and briefly reflected upon in a short final discussion to ensure the knowledge transfer.

5.2. Continuous improvement process

Although not adopted as part of the quality standards of the Montanuniversität Leoben, a continuous improvement of the lectures’ scope and teaching methods is planned according to the Plan-Do-Study-Act (PDSA) circle (Deming 1998; Shewhart 1986). Figure 8 illustrates the methodology, where one adaptation phase per semester will be executed.

Figure 8. Developed PDSA circle for the continuous improvement process of the developed lecture.

In detail, the PDSA cycle comprises four sections with 11 sub-steps from (1) mobilising a transdisciplinary team (internal/external) to 11) exclusions based on prefixed requirements for the upcoming lectures. The approaches depicted in Figure 6 ((Re)design approach of a state-of-the-art digitalisation and digital transformation lecture: a stakeholder-oriented approach) and Figure 7 (Developed PDSA circle for the continuous improvement process of the developed lecture) should also be used as a general concept for the adaptation of transdisciplinary engineering education lectures. If a new lecture needs to be developed, the approaches from both Figures should be applied. If an existing lecture needs to be adapted in terms of scope or teaching methods, the implications from Figure 8 can be used.

6. Discussion

The Industry 4.0 strategy, which is essentially based on the two pillars of digitalisation (technologies) and digital transformation (organisational and infrastructural change), aims to increase the competitiveness of local companies and thus strengthen the entire economy and society. However, this strategy seems to require substantial adaptations in the present teaching and learning concepts of engineering education, as existing approaches ultimately do not lead to the necessary acquisition of the required professional and/or transversal competences (Kaur, Awasthi, and Grzybowska 2020; Matt, Modrák, and Zsifkovits 2020; Matt, Modrák, and Zsifkovits 2021; Oztemel and Gursev 2020; Zheng et al. 2020; Zsifkovits, Woschank, and Pacher 2021). In this context, literature shows that the role of the human workforce in modern production and logistics systems of manufacturing companies is not completely understood yet. Recent studies indicate a significant change in the necessary competencies, but profound results of systematic literature analyses and especially substantial implications from empirical investigations are still missing to deduce necessary measures based on theoretical and practical elaborations (Kadir, Broberg, and Da Conceição 2019; Kiel et al. 2017; Sony 2018; Vuksanović Herceg et al. 2020). In line with the current literature, the authors state that Industry 4.0 will not only lead to a change on the shop-floor level but also lead to a paradigm shift in the necessary understanding of the required skills of the engineers of tomorrow (Kadir, Broberg, and Da Souza Conceição 2018; Müller, Kiel, and Voigt 2018; Pfeiffer 2016, 2018). The strict functional separation of engineering tasks (e.g. mechanical engineering, automation, IT, management) that has existed up to now will progressively become less distinct since the modern tasks of engineers in the environment of Industry 4.0 will require a more transdisciplinary perspective (Brougham and Haar 2018; Ghobakhloo 2020). In this regard, current studies further report the emergence of new jobs and point out that, from today’s perspective, 40% of the jobs that will be needed by the industry in 2030 have not even been invented yet (A21DIGITAL 2021). To prepare engineering students for these changing requirements, the authors recommend, in line with the current literature, not only an ongoing adaptation of the curricula but also a continuous and empirically-based adaptation of the educational content and/or the new development of modern teaching and learning concepts. Therefore, both the requirements from the industry and the background of the students, and their current level of knowledge should be considered. The empirically-based redesign of a lecture for the transdisciplinary education of engineering students described in this paper is intended to provide a comprehensive basis in this respect. Ultimately, the Industry 4.0 concept should lead to Education 4.0, by ensuring require the continuous acquisition of new knowledge, qualifications, and competencies over the entire lifespan, to secure the long-term competitiveness of manufacturing companies and thus the industry and the prosperity of regions in a sustainable manner (Kuo et al. 2021). Therefore, the introduced model of circular education should be used to ensure continuous development over the entire lifespan from the earliest childhood to high adulthood in the four areas of (pre)school education, tertiary education, vocational education and training (VET), and andragogy in a formally, non-formally, or informally manner on the macro-, meso, and micro levels of learning focused on the individual learning and adapted to the respective participant-orientated situation (Arnold 2017, 2020; Hof, Meuth, and Walther 2014; Schäffter 1998; Schröer et al. 2013). The introduced lecture at the Montanuniversität Leoben was designed based on the didactical principles of (1) participant orientation, (2) case reference, (3) practical relevance, (4) group dynamics, (5) orientation to everyday life, (6) self-determination, (7) biography-orientation, the theory of constructive alignment, and the principles of the Plan-Do-Study-Act (PDSA) circle leading to continuous feedback loops by following the transdisciplinary engineering education approach (Biggs and Tang 2011; Ludwig 2018; Ralph, Pacher, and Woschank 2020; Tietgens 1992). As described, the empirical-based approach of this paper should ultimately lead to an essential contribution to competitiveness in the metal forming sector and the entire industry as well and, therefore, increase the performance, job satisfaction, and employability of the engineers of tomorrow. Therefore, the initial concept was designed in a modular and blended-learning format in four modules to finally qualify engineering students to (1) create and evaluate concepts for digitalisation in metal forming related production systems, (2) apply the theoretical concepts in a case study, (3) implement them together with experts from different disciplines, and (4) understand and implement the applied procedures in practice based on the theoretical and practical knowledge acquired in the metal forming industry. In this regard the authors identified, the participating engineering students, potential employers, alumni, and experts (who have worked, or are currently working, in the metal forming environment with an engineering or IT background), local universities, international universities, government departments, and lecturers as the key stakeholders for the proposed empirical-based approach. While all identified parties contributed qualitatively to the development, the quantitative part of this paper focused on a survey of (1) potential employers, hence companies in the metal forming industry and (2) the participating students of the initial lecture, as the two main stakeholders for deriving measures for this empirical-based lecture redesign approach and subsequently for the design of the pedagogical framework for the envisaged teaching and learning methods. In the first block of the empirical results, the survey shows tremendous differences between the currently existing and required knowledge in the specific metal forming industry. In a nutshell, most participating companies did not show profound knowledge regarding the requirements of digitalisation based on Industry 4.0 technologies and, therefore, report a low degree of digital maturity of the surveyed companies and the respective human workforce, as well. Moreover, the survey reveals a lack of knowledge regarding the adequate evaluation, the gathering, and processing of data. Surprisingly, in the industrial environment, no correlation between the existing knowledge in digitisation and the existing skills in data analytics can be found which leads to the fact that there is an increasing need for more holistic-oriented teaching and learning approaches in the transdisciplinary educational field of Industry 4.0. However, the survey shows a positive correlation between the attitude towards Industry 4.0, based on the already fulfilled changes in the mindset of the respective organisation according to the principles of the digital transformation, and the existing knowledge in digitalisation and data analytics. However, due to the tendentially low degree of maturity in the present attitude of the companies, more purely more management-related skills for the digital transformation are also required in the industrial environment. The second block of the empirical results indicated a tendentially low degree of knowledge regarding digitalisation, meaning knowledge regarding Industry 4.0 enabling and corresponding technologies, and also a tendentially low degree in data analytics in the student sample. The results showed significant differences regarding the knowledge in digitalisation and data analytics among bachelor, master, and Ph.D. students but, surprisingly no statistically significant differences regarding the requirements and expectations for a new transdisciplinary lecture among them. Furthermore, the results showed a significant correlation between digitisation and data analytics indicating a meaningful transdisciplinary linkage of the two topics in the initial course conceptual. Likewise, the relationship between an affinity for digitisation and the increasing need for new transdisciplinary courses and the course content was demonstrated in the empirical study. Surprisingly, no significant differences in knowledge (digitisation and data analysis) were found between the individual engineering disciplines (core manufacturing disciplines and supportive manufacturing disciplines), which means that, within the initial lecture(s), the educational approach is generic and not discipline-specific. The third block of the empirical results was conceptualised to investigate knowledge gaps between the student sample and the industry sample. The results showed no significant differences in digitalisation but highly significant differences in data analytics and, therefore, indicate the first success of educational initiatives in the field of digitisation and the potential for optimisation in the field of data analytics from the perspective of the respective university. The results from theory, literature, and the evidence from the empirical analysis were used to redesign the initial lecture concept by referring to the underlying fields of action of the conceptualised transdisciplinary engineering education approach, namely learning content, area of application, target group and needs, learning outcomes, lectures and course instructors, learning location and media, teaching and learning methods and assessment, and knowledge transfer. Therefore, the identified research findings from the redesign of the engineering education lecture lead to the subsequent implications for both the theory and practice. The adequate alignment of the initial lecture design for a transdisciplinary engineering education approach with a focus on the metal forming industry was validated by the feedback of the two empirical studies. In this context, is it worth noticing that the success of this stakeholder-oriented approach depends to a large extent on the quality of underlying data from the targeted employers (the respective industry segment) and their potential employees. If no valid information gathering from these groups can be maintained, the resulting (re)design will be inefficient or not in the actual scope of the proposed empirical environment. For this reason, responsible lecturers must exactly know all of their targeted stakeholders before starting with the proposed (re)design. If this requirement is fulfilled, a suitable research methodology for data gathering must be defined. Thereby the suitability largely depends on the decomposition of the target group within identified stakeholders (e.g. which industry segment replies to which data-gathering instruments and how must a questionnaire be designed to reach the target auditorium in the relevant field of interest) and the targeted audience (e.g. which engineering disciplines should participate in the lecture, level of education, prior knowledge). Additionally, the learning methods must be aligned to the respective scope of the lecture (e.g. grade of practical experiments within the lecture, estimated lecture size, available human and physical resources). As a result, the developed PDSA circle for the continuous improvement process of the developed lecture allows a proactive reaction of involved teaching personnel on possible changes in the stakeholder environment. By requiring continuous feedback from participants during the different modules of the lecture, it is possible to rapidly implement important changes. Therefore, this approach ensures a higher satisfaction of the participating engineering students, as their contribution to enhancing the quality of the lecture is directly visible to them.

7. Conclusion

Based on Industry 4.0, the concepts of digitalisation and digital transformation require a tremendous alignment of the human workforce in modern production and logistics systems. This can only be achieved through sustainable and continuously improved education of core personnel. This paper, therefore, presents a modern approach to engineering education, where basic theoretical concepts, qualitative inputs from all related stakeholders, and quantitative data from two questionnaire surveys are combined to achieve a transdisciplinary redesign of an Engineering Education Lecture. This lecture was developed using modern teaching and learning methods and has been successfully implemented using the example of digitalisation and digital transformation in the lecture for engineers in the field of metal forming. In this regard, the authors stated that modern engineering education must consider a combination of teaching and learning formats, such as teaching students in a classroom, blended/hybrid, or fully online format to open up a new world of learning by enabling methodological flexibility. The presented lecture design approach can be used as a starting point for ensuring that future experts have the essential knowledge, skills, and competences to develop and implement fruitful measures for the ongoing improvement of production and logistics by addressing current challenges like the need for continuous optimisation of the overall efficiency, the search of counter-strategies to the climate change, and the development of resource-saving initiatives for within a sustainable corporate strategy. In addition, a significant contribution can thus be made to cross-regional exchange to counteract the brain-drain phenomenon and to legal migration. The ongoing exchange of external experts in the field of engineering education is intended to counteract the phenomenon of brain drain at the national and international level and to contribute to legal migration. Moreover, there is a need for uniform learning analytics in Europe and also at a national level, for collecting, evaluating, and making use of data, based on the development of skills and knowledge in a targeted manner so that education systems and content can be adapted to subjective educational needs. In many cases, however, this approach is only in a pilot phase and for this reason, further approaches and holistic reforms at the university level are essential (European Commission 2020). To be adequately trained for the future and to be able to design appropriate Engineering curricula, the educational needs and key competencies for future Engineers must first be defined. In this regard, targeted, up-to-date skills intelligence (European Commission 2020) is needed, which must be embedded in national competence strategies and educational systems.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Benjamin James Ralph

Benjamin James Ralph holds a master's degree and a Ph.D. in metallurgy from the Montanuniversität Leoben, Austria and a master's degree in international industrial management from the University of Applied Sciences, FH JOANNEUM, Graz. He currently works as a Senior Lecturer at the Chair of Metal Forming at the Montanuniversität Leoben, Austria. He is also an MBA candidate at the Warwick Business School, Coventry, England. Before his academic career, he served four years in the Austrian Armed Forces and was part of the United Nations Interim Forces in Lebanon (UNIFIL). His research interests include the areas of digitalization and digital transformation, materials science, numerical modeling, and management, mainly but not exclusively in metal forming.

Manuel Woschank

Manuel Woschank received a diploma degree in industrial management and a master's degree in international supply management from the University of Applied Sciences, FH JOANNEUM, Graz, Austria, a Ph.D. in management sciences with summa cum laude from the University of Latvia, Riga, Latvia, and the habilitation in industrial management from the Montanuniversität Leoben, Austria. He is currently a Senior Researcher, Senior Lecturer, and the Deputy Head of the Chair of Industrial Logistics at the Montanuniversität Leoben and an Adjunct Associate Professor at the Faculty of Business, Management and Economics at the University of Latvia. He was a visiting scholar at the Technical University of Kosice (Slovakia), and at the Chiang Mai University (Thailand). His research interests include the areas of logistics system engineering, production planning and control systems, logistics 4.0 concepts and technologies, behavioral decision making, sustainable logistics management, and industrial logistics engineering education.

Corina Pacher

Corina Pacher is an Education Project Manager at the Institute of Lifelong Learning at Graz University of Technology. At the institute, she is mainly responsible for project management of European projects, for the support in the development and expansion of further education offers, and for the development of didactic concepts. She studied pedagogical and educational science at the University of Klagenfurt, Austria with a specialization in social and inclusive education (master's degree) as well as on professional education (master's degree). During and after her studies, she gained work experience, e.g., as the head of educational programs. Currently, she is mainly focusing on raising awareness for engineering education 4.0 by connecting research, education, and society.

Mariaelena Murphy

Mariaelena Murphy is the Education Portfolio Manager at the Resources Innovation Center in Leoben. She holds a master's degree in Business Ethics and Social Responsibility. She worked as a Senior Lecturer at the Hanze University of Applied Sciences for 17 years specializing in the Management discipline, also with a focus on cultural competences through the creation and involvement in learning labs. Alongside this, she was actively involved in cross-border projects connecting education, business and communities. Currently, her focus is on (co)creating partnerships and projects that implement new teaching & learning pathways that promote a transdisciplinary approach in connecting research, education, business, and society for the future of T-shaped raw material engineers.