Exploring Theories and Competencies of Innovation in Engineering Education: A Scoping Review

Abstract

The unprecedented dynamics of global technological development require 21st-century engineers to possess not only deep technical expertise but also a multifaceted set of innovation competencies. While higher education institutions are increasingly committing to fostering a culture of innovation, there is often a lack of conceptual clarity regarding which theories and competencies are most relevant to engineering curricula. This scoping review examines the landscape of innovation theories and innovation competencies in engineering education, identifying the main theoretical perspectives and their implications for curriculum and pedagogical design. Co-occurrence analyses indicate that many studies emphasise competencies such as collaboration, creativity, strategic thinking, and problem-solving. The findings suggest that engineering innovation is a multifaceted phenomenon encompassing the creation of novel and useful products, the adoption of new managerial and organisational practices, and the deliberate development of innovation competencies in both students and professionals. Overall, the review indicates that engineering education must move beyond “black box” technological approaches toward experiential and multidisciplinary models and provides an analytical basis for linking innovation theories with the development of innovation competencies and curriculum design.

1. Introduction

In recent years, the European Union and national strategies have been developed to promote innovation, entrepreneurial capabilities and transversal skills across academia and industry (EntreComp, 2016). This study contributes to the European debate on the role of universities’ R&D in fostering innovative solutions and supporting sustainable economic and societal growth (Filho et al., 2024; Sarpong et al., 2023) as well as the European Commission’s European Strategies for Universities. Innovation is a fundamental driver of progress in the engineering field (Asio et al., 2018), playing a critical role in addressing complex societal challenges (Cropley & Singh, 2023) and advancing Sustainable Development Goals (SDGs). There is a need to embed future-proof competencies into university curricula, organisational structures, and research and innovation strategies (Diaconu & Salaj, 2024). In line with this need, the ENTRECOMP framework (EntreComp, 2016) defines entrepreneurship as a transversal competence, emphasising the ability to turn ideas into action through creativity, critical thinking, problem-solving, and collaboration. This competence is particularly relevant in engineering education and innovation ecosystems, where entrepreneurial mindsets are crucial to translating technical research into societal impact. Complementing this, the LIFECOMP framework (LifeComp, 2020) outlines the need for lifelong learning programmes and the continuous development of competencies, including for academic staff, provides guidelines and supports the development of technical and soft skills, adaptability, resilience, and reflective learning capacities. Moreover, the European Skills Agenda (2020) provides a strategic policy framework for upskilling and reskilling Europe’s workforce in line with the green and digital transitions.

Since the beginning, engineering innovation has led to groundbreaking advancements in energy, healthcare, infrastructure, and digital technologies. However, despite its significance, innovation in academia often struggles to transition from theoretical research into tangible products and solutions (Jonsson et al., 2015). In the last two decades, the gap between academic research and real-world application has posed a significant challenge for universities, industries, and policymakers alike (Etzkowitz & Leydesdorff, 2000). The same authors found that policymakers and states have introduced incentives and policies to support universities in commercialising their academic knowledge. One of the primary issues in the academic landscape is that innovation is not always regarded as an explicit objective in engineering research (Bercovitz & Feldman, 2006). In academia, many studies focus on theoretical advancements and fundamental discoveries without a clear pathway for commercialisation or industry collaboration (Perkmann et al., 2013; Ellwood et al., 2022; Calcagnini & Favaretto, 2016; Guertler et al., 2019). As a result, numerous promising research findings remain confined within academic publications, failing to materialise into practical applications or marketable products. The most common transfer channels in academia are publications, conferences and meetings (Hayter et al., 2020; Zhou & Baines, 2024), visit exchange research, informal conversations over scientific committees, consulting and collaborative research, co-supervising PhD students and, in some fields, the industrial PhD (Jacobsson & Perez Vico, 2010; Salter & Martin, 2001). There is a significant gap in understanding innovation and knowledge sharing between academia and industry, particularly in fields like engineering and STEM, where the Valley of Death arises (Backs et al., 2019; Compagnucci & Spigarelli, 2024; Aragonés-Beltrán et al., 2017). The Valley of Death occurs during the early stages of innovation, at the transition between original scientific research and the commercialisation of associated technologies (Auerswald & Branscomb, 2003; Ellwood et al., 2022; Frank et al., 1996; Biemans & Huizingh, 2020). This translational gap prevents industries from leveraging cutting-edge research and academics from identifying real-world applications for their innovations (Figlie et al., 2024; Rossoni et al., 2024). The priorities between academia and industry can hinder practical innovation and knowledge transfer (Hidalgo & Albors, 2011). The lack of structured competency frameworks for innovation competencies development further exacerbates this issue, preventing researchers from navigating the process from ideation to commercialisation effectively (Siegel & Wright, 2015).

Despite the growing consensus that innovation is a critical outcome of engineering programmes, the current literature remains fragmented in theory and concept. Often, ‘innovation’ is treated as a generic, loosely defined skill rather than a rigorously grounded academic construct (Zazzerini, 2021; Zhang et al., 2013). Identifying this fragmentation is not enough to make a change. The research should provide actionable analysis of the practical and academic bottlenecks this lack of coherence creates, and identify where education curricula can be improved to address these needs.

Currently, this fragmentation prevents us from understanding how specific theoretical frameworks translate into actionable educational practices. Without clear alignment between underlying innovation theories, such as Diffusion of Innovations, Social Innovation, or Open Innovation, and specific engineering competencies, institutions lack the analytical foundation to design targeted curricula, establish valid and reliable assessment criteria, and implement effective faculty development programmes. Educators are left attempting to teach and measure competencies that have not been adequately operationalised within their specific socio-technical context.

Thus, this scoping review seeks to advance knowledge by mapping the existing innovation theories and competencies and investigating how they intersect and inform one another. This study aims to go beyond simple categorisation of the literature by applying an analytical lens on how to bridge the gap between high-level innovation theory and on-the-ground pedagogical practice. Bringing this connection together is a critical step toward new curriculum design that equips future engineers with the robust, multifaceted competencies needed to navigate and lead complex socio-technical transitions.

Goals and Structure of the Paper

This study is positioned at the intersection of innovation theory, innovation competencies, and the design of engineering education curricula. It responds to the need for a more conceptually grounded understanding of how innovation is framed in engineering education and how such framings shape the competencies that engineering programmes seek to develop. The paper pursues two objectives: (1) to identify and synthesise how innovation theories and innovation competencies are represented in the engineering education literature; and (2) to examine what these theoretical perspectives imply for the competencies prioritised in engineering education and how they inform curriculum and pedagogical design.

To address these objectives, the study is guided by the following research questions:

• How is innovation seen in the engineering field?
• How does existing research conceptualise the relationship between innovation theories and innovation competencies in engineering education, and what implications does this relationship have for curriculum design?

Methodologically, a scoping review was conducted to investigate current research and development in the field. The review provides both a descriptive landscape of the literature and an analytical interpretation of how different innovation theories foreground specific competence profiles and educational logics. Consequently, the study aims not only to map the field but also to provide a basis for interpreting how innovation-related competencies may be translated into more coherent curricular and pedagogical approaches in engineering education.

The remainder of the article is structured as follows: Section 2 presents the Theoretical background and sets the ground for the study, Section 3 describes the Methodological approach and research design; Section 4 presents the Results from the analysis of the content in the articles; Section 5 discusses the findings in relation to engineering education, curriculum development, and implications for future research and practice. Finally, Section 6, the Conclusions, wraps up the article and outlines directions for further research. Data collection for the scoping review took place between February and April 2025.

2. Theoretical Background

Across academic fields, the main innovation theories have evolved from classical, economic, and technology-driven models into integrated frameworks that emphasise the coevolution of institutional, systemic, behavioural, societal and network dimensions (Midgley & Lindhult, 2021; Schwabe et al., 2021). Simultaneously, innovation competencies theories highlight a duality between inherent personality attributes and observable behaviours, namely innovation capability as a set of competencies spanning technical, non-technical, and soft skills (Schindel et al., 2011; Zazzerini, 2021). While classical innovation theories were mostly market- or technology-focused, emerging perspectives now incorporate social innovation and sustainability, addressing systemic challenges such as weak institutional linkages in emerging economies, new competencies in education, innovative educational frameworks and new skills (Bathelt & Henn, 2017).

To set up this study, we first identified the main innovation theories across various fields and the innovation competencies theories, providing a comprehensive overview of their evolution and categorisation.

2.1. Theories of Innovation

Table 1. Innovation theories short mapping.

Theory	Core Proposition/Category	Author/Citations
Market/Entrepreneurship driven
Theory of Innovation (1934)	Innovation drives economic growth through entrepreneurial “new combinations” that trigger creative destruction—replacing established industries and routines; innovation can occur through new products, processes, markets, inputs, or industrial structures.	Joseph Schumpeter (Schumpeter & Swedberg, 2021)
Disruptive Innovation Theory (1997)	Disruption arises when entrants introduce simpler, cheaper, and more accessible solutions for overlooked segments, thereby forming new markets and value networks; over time, these offerings improve and can displace incumbents.	Clayton Christensen (Christensen, 1997)
Network/Ecosystem driven
Diffusion of Innovations Theory (1962)	Innovation spreads through social systems via communication over time; adoption depends on adopter categories and perceived attributes (relative advantage, compatibility, complexity, trialability, observability).	Everett Rogers (Rogers, 1971)
Open Innovation Theory (2003)	Companies and organisations improve innovation outcomes by purposely managing knowledge inflows/outflows—combining internal R&D with external ideas, technologies, and pathways to market through partnerships and boundary-spanning mechanisms.	Henry Chesbrough (Chesbrough, 2003)
Community/Knowledge driven
User Innovation Theory (2005)	Users frequently originate and refine innovations; organisations can accelerate development by systematically engaging users (incl. “lead users”) and integrating user-generated solutions into formal innovation processes.	Eric von Hippel (von Hippel, 2005)
Social Innovation Theory	Social innovation develops new ideas/services/models that address societal needs more effectively; it is cross-sectoral and judged by social impact, including new social practices, community-driven solutions, and hybrid business models.	(Murray et al., 2010; Mulgan, 2006)

synthesises complementary innovation theories that together explain why innovations emerge, how they spread, and who drives them in complex socio-technical settings such as engineering education. The table contrasts Market/Entrepreneurship-driven perspectives—rooted in economics, technological change, and market dynamics with Network/Ecosystem-driven perspectives—emphasising institutional structures and inter-organisational knowledge flows and Community/Knowledge-driven perspectives—highlighting user agency, co-creation, and social value creation. This theoretical mapping provides a multi-level interpretation of innovation theories and educational innovation, from curriculum renewal and pedagogical change to platform-enabled collaboration across academia, industry, and society.

Taken together, the theories in Table 1 show that innovation in engineering education can be interpreted through distinct but complementary analytical lenses. They differ first in their source of innovation: market- and entrepreneurship-driven theories locate novelty primarily in entrepreneurial initiative and competitive reconfiguration; network- and ecosystem-driven theories emphasise interaction, exchange, and circulation across organisations and systems; and community- and knowledge-driven theories foreground users, communities, and socially situated needs as generators of innovation. They also differ in their mechanism of change. Schumpeterian and disruptive perspectives stress transformation through new combinations and system reordering; diffusion and open innovation highlight scaling, communication, and knowledge flows; while user and social innovation perspectives emphasise co-creation, contextual responsiveness, and the collective shaping of value.

Such differences also imply distinct logics of agency and value. In the first group, agency is associated mainly with individuals, innovators, and organisations that challenge existing structures, and value is often linked to competitiveness, novelty, or reconfiguration of established systems. In the second group, agency is distributed across networks, institutions, and boundary-spanning actors, while value arises from adoption, coordination, and knowledge integration. In the third group, agency shifts further toward users, communities, and cross-sector collectives, and value is defined less by market performance alone and more by relevance, inclusion, and societal impact. Beyond their conceptual value, these distinctions inform distinct educational trajectories for engineering programmes. The innovation theories suggest different educational emphases, ranging from curriculum renewal and strategic innovation thinking to ecosystem collaboration and partnership-based learning to co-creation, ethical reasoning, and public-value-oriented design.

The market and entrepreneurship-driven theories foreground innovation as a force that reorders systems. Schumpeter’s concept of creative destruction emphasises that novelty is not merely additive, but it may replace entrenched structures and routines (Schumpeter & Swedberg, 2021). In engineering education, this is visible when emerging competence demands (e.g., sustainability, AI, interdisciplinarity) force programmes to replace legacy curricular structures rather than merely add incremental content. Christensen’s disruptive innovation theory extends this logic by explaining how apparently marginal, simplified, or lower-cost alternatives can gradually reshape dominant systems, build new markets, and create new value networks (Christensen, 1997). Educationally, these perspectives draw attention to innovation as transformation, strategic repositioning, and the questioning of established models of engineering formation.

By contrast, the network- and ecosystem-driven theories explain how innovation diffuses, scales, and is sustained across interconnected systems. While Schumpeter and Christensen primarily address origins and competitive dynamics, Rogers explains scaling: diffusion depends on the interaction of an innovation with communication channels, time, and the social system (Rogers, 1971). These elements correspond to the category of network/ecosystem-driven theories that examine where innovation fits within the ecosystem. Chesbrough’s open innovation complements diffusion by emphasising that innovation capacity depends on boundary-spanning knowledge flows—not only internal research and development—through purposeful integration of external ideas, technologies, and partners (Chesbrough, 2003). In engineering education, these theories are particularly relevant for understanding innovation as a relational and institutional process, in which pedagogical experimentation and the development of innovation competencies need to be strengthened through collaboration among universities, industry, public actors, and wider innovation ecosystems, and the curriculum needs to change accordingly.

The community- and knowledge-driven theories further shift the analytical lens by re-centring users, communities, and societal needs as active drivers of innovation. Von Hippel’s user innovation theory argues that users often originate and refine innovation and should therefore be treated not only as recipients of solutions, but also as contributors to innovation processes (von Hippel, 2005). By extension, social innovation theory adds a normative and societal-impact lens: innovation is defined by more effective responses to social needs, cross-sector collaboration, and outcomes judged by social impact rather than profit (Murray et al., 2010; Mulgan, 2006). Within engineering education, these perspectives broaden the purpose of innovation beyond technical novelty and market uptake to include co-creation, inclusion, ethical sensitivity, and responsiveness to complex societal challenges.

In aggregate, the theories in Table 1 suggest that innovation in engineering education is best understood not through a single explanatory model, but through the interaction of divergent innovation logics. While specific theories prioritise creation and disruption, others emphasise adoption and scalability, or foreground co-creation and societal responsiveness. This distinction is analytically important because it delimits what constitutes innovation, who is recognised as an innovator, which competencies become prioritised, and which curricular and pedagogical responses are considered legitimate in engineering education.

2.2. Theories of Innovation Competencies

From an engineering education perspective, theories of innovation should be examined alongside theories of innovation competencies. Theories of innovation competencies focus on the skills, knowledge, and behaviours that enable individuals and organisations to foster creativity and drive innovation (de Barros et al., 2025; Belski et al., 2018; Cropley, 2015). From an engineering education perspective, it is important to distinguish between innovation competencies and entrepreneurship competencies, while also recognising their overlap. In this article, innovation competencies serve as the umbrella concept, encompassing the knowledge, skills, attitudes, and behaviours that enable individuals and organisations to generate, develop, implement, and adapt novel solutions across technical, organisational, and societal contexts (OECD, 2011; EntreComp, 2016). This broader construct includes, for example, idea generation, problem-solving, collaboration, systems thinking, communication, experimentation, and adaptive learning. Entrepreneurship competencies, by contrast, refer to a more specific subset oriented toward opportunity recognition, value creation, initiative, risk navigation, and venture or action orientation (Kyrgidou et al., 2021; EntreComp, 2016). Entrepreneurship competencies constitute one important dimension of innovation competencies, but do not exhaust the broader competence profile required for innovation in engineering education and practice.

Table 2. Summary Table Innovation Competencies types.

Competencies Type	Description	Sources
Professional and Creative	Idea generation, problem-solving, creative thinking	(Bjornali & Støren, 2012; Morad et al., 2021)
Communication and Championing	Effective communication, advocacy for ideas	(Bjornali & Støren, 2012; Cuenca et al., 2015)
Networking	Connecting ideas and people, facilitating collaboration	(Bjornali & Støren, 2012; Martínez-Gómez et al., 2016)
Self-Management	Intellectual and emotional capacity, personal creativity	(Lee & Park, 2019)
Entrepreneurship Education	Emphasis on entrepreneurial skills, problem-based learning	(Bjornali & Støren, 2012; Morad et al., 2021)
Problem-Based Learning	Real-life problem-solving, collaborative relationships	(Zhang et al., 2013)
Competencies-Based Learning	Frameworks for design and innovation education	(Moubdi et al., 2018)
Innovation-Development Process	Normative framework for the innovation process	(Beausoleil, 2018)
Affinity Diagram	Clustering capacities and skills	(Martínez-Gómez et al., 2016)
Big Five Personality Traits	Openness, conscientiousness, extraversion, neuroticism	(Saatci & Ovaci, 2020)
Intrapreneurial Competencies	Learnable competencies for innovation	(Bjornali & Støren, 2012)
Open Innovation Competencies	Collaboration, networking, and managing innovation processes	(Podmetina et al., 2018)
IT Competencies	Knowledge management, collaboration, and IT infrastructure	(Abina et al., 2024; Opland et al., 2022)

synthesises the main types of innovation competencies, provides an overview of the literature, and shows how innovation competencies have been framed across educational, organisational, and innovation-oriented contexts.

The research into innovation competencies theories highlighted the potential clusters that could be created when looking across different approaches:

• Core Competencies: Technical Skills—these include discipline-specific knowledge essential for innovation, such as analytical thinking and problem-solving abilities (Saatci & Ovaci, 2020; Schindel et al., 2011) and soft skills such as leadership, teamwork, communication, and resilience, which are vital for fostering an innovative culture within organisations (Morad et al., 2021; Cuenca et al., 2015).
• Entrepreneurial competencies: These competencies encompass traits such as opportunity recognition, risk-taking, and innovativeness, which are essential for entrepreneurial success and organisational innovation (Martínez-Gómez et al., 2016; Lee & Park, 2019). They help individuals navigate complex market dynamics and contribute to sustainable business performance (Podmetina et al., 2018).
• Cultural and contextual factors: The effectiveness of innovation competencies can vary significantly across different industries and cultural contexts. For instance, an organisational culture that encourages experimentation and risk-taking is crucial for innovation (Podmetina et al., 2018).

Recent engineering-education literature increasingly argues that future engineers require competence profiles that extend beyond technical expertise alone and must be supported by competence-based curricular realignment, stakeholder-responsive curriculum design, and learning environments prepared to cultivate broader human-centred and collaborative capabilities (Ahmad et al., 2026; Ferreira et al., 2024; Pacher et al., 2024; Podmetina et al., 2018). Taken together, the clusters suggest that innovation competencies in engineering education are best understood not as a fixed list of isolated attributes, but as a layered competence architecture. Core competencies provide the technical, cognitive, and interpersonal basis for engaging with complex engineering problems. Entrepreneurial competencies extend this base by strengthening opportunity recognition, initiative, and value-oriented action. Cultural and contextual factors shape whether these competencies can be enacted effectively within specific organisational, disciplinary, and societal settings.

A cross-examination of the innovation theories in Table 1 and the competencies in Table 2 reveals a secondary implication: different innovation theories foreground varied innovation competencies, reflecting their specific conceptual and pedagogical underpinnings and, by extension, different curriculum design. When innovation is framed through market- and entrepreneurship-driven perspectives, educational emphasis is more likely to fall on opportunity recognition, strategic thinking, initiative, and transformative capacity. When it is framed through network- and ecosystem-driven perspectives, competencies such as collaboration, networking, communication, and knowledge integration become more central. When innovation is understood through community- and knowledge-driven perspectives, greater importance is placed on co-creation, ethical judgement, contextual sensitivity, and responsiveness to societal needs. Viewed through this lens, innovation competencies are repositioned from supplementary skills added to technical education to a new curriculum design that can shape how innovation is interpreted, taught, and assessed in engineering education.

3. Methodology

A scoping review was conducted to explore whether any literature mentioned the theories of innovation and innovation competencies together. The scoping review followed the guidelines outlined by (Arksey & O’Malley, 2005) to map research activity in the relevant literature. The structure and steps are shown in a PRISMA flow diagram. The flow utilises the five steps which are: (1) identifying the research question, (2) identifying relevant studies, (3) study selection, (4) charting the data, and (5) collating, summarising and reporting the results (Levac et al., 2010). The scoping review approach was selected because it is well-suited to mapping the breadth, diversity, and conceptual fragmentation of an emerging field, rather than to evaluating intervention effectiveness or aggregating narrowly comparable studies. The decision was made consciously because, for this study, the flexibility of the scoping review was needed. Secondly, the citation indexes were not a determining factor when selecting the articles. Third, the study is limited in time and language, and new publications appear every day. The research is conducted in a highly emerging field. Thus, the result would be non-identical if the work were to be reproduced.

3.1. Identifying Studies: Research Strings

The scoping review was conducted by searching for books, journals, papers and conference papers in Scopus, Dimensions and Google Scholar. A personal book database and articles recommended by research colleagues were also included. At first, a general search was conducted using terms such as innovation theories, innovation approach, innovation frameworks, innovation methods, innovation concept, innovation skills, innovation competencies, innovation knowledge, and innovation abilities. The next step was to narrow it down and combine these into search queries. After refining the search strings, the final search was limited to Scopus, open-access, and English-language articles, as the scope was to examine the body of knowledge published in scientific journals and accessible to all researchers. Based on the research questions, the search followed two strings:

• “innovation theory” OR “theories of innovation” OR “innovation theories” AND “engineering”
• “innovation competencies” AND “engineering”

3.2. Inclusion and Exclusion Criteria Used

All the documents and information collected from both research strings have been analysed.

Table 3. Inclusion and exclusion criteria for the research process.

Inclusion/Exclusion	Criteria
Inclusion criteria	Studies in English Studies published between 2014 and 2024 in journals Reading the titles, abstracts and keywords and including only where it was mentioned: innovation theory for academia or university, innovation in academia/university, engineering education, academia implementation, innovation theories for students, for researchers, and/or curricula.
Exclusion criteria, screening process	Exclude theses, Proceedings, Conferences or Books Articles are to be excluded when terms in the search string have a different meaning from what is intended in the paper. E.g., the work “innovation” is mentioned in the text, but not in a way related to innovation theories or innovation competencies
Exclusion criteria, reading the titles and abstracts	Articles with a focus on enterprises Articles with a focus on business and leadership Articles with a focus on product development

presents the inclusion selection criteria and Figure 1 shows the PRISMA flowchart.

3.3. Charting the Data

Following the application of the search strategy, records were filtered using the Scopus operator TITLE-ABS-KEY and limited to publications in English published between 2014 and 2024. After removal of duplicates and the application of the inclusion and exclusion criteria described in Section 3.2, 183 records remained for screening. These records were first reviewed based on title, abstract, and keywords, and were subsequently assessed for relevance through full-text reading where necessary. Of these 183 records, 30 articles were retained for the final analysis because they explicitly addressed both innovation theories and innovation competencies within engineering, higher education, or curriculum-related contexts.

The review was designed as a bounded scoping review focused on peer-reviewed journal articles. This decision was made deliberately to capture more consolidated conceptual and analytical treatments of innovation theories and competencies. Within this bounded scope, the final sample of 30 articles was considered adequate for the review, as the aim was an analytical mapping rather than a comprehensive enumeration. More specifically, the intention was to identify how innovation theories and innovation competencies were explicitly connected in the literature and how those connections informed engineering education. This narrower focus explains why a relatively small subset of studies met the final eligibility criteria.

The selected 30 articles were then charted in an Excel spreadsheet using a structured extraction template. Each article was assigned a code indicating the search string used to identify it. In addition, the following information was recorded: article title, publication year, journal title, first and last authors, the geographical affiliations of the first and last authors, study aim, methodological approach, main results, thematic focus, and implications for engineering education. This charting process supported both the descriptive analysis of the sample and the subsequent content analysis of innovation theories, competencies types, and their educational implications.

4. Results

In this chapter, we present the results from both descriptive and content-analytic perspectives.

4.1. Description of Results

The following section outlines the findings from the scoping review of the 30 articles selected for the study. No articles from before 2014 were collected from the database search, nor any grey literature.

4.1.1. Chronology of the Study Articles

In terms of chronology, the descriptive analysis suggests that innovation in engineering education is a very recent and fragmented topic. Figure 2 represents the number of selected studies published per year. The descriptive analysis shows that this is a highly relevant trend that has grown over the last few years, especially in 2024.

The relatively small number of articles per year suggests that the discussion of innovation in engineering education has not been widely examined, creating an opportunity to examine it further.

4.1.2. Geographical Affiliation

In Figure 3, the geographical affiliations of the first authors are shown. Fifteen countries are represented. It suggests a strong concentration of research contributions from the United States, which accounts for 12 publications (McCaffreya & Krishnamurty, 2015; Merhi, 2015; Kopcha et al., 2016; Chan et al., 2016; Friedrichsen et al., 2017; Shtivelband et al., 2019; Joseph & Wood, 2020; Call et al., 2024; Tisdale & Bielefeldt, 2024; Mil’shtein & Tello, 2019; Wells et al., 2021; Call & Herber, 2022), significantly higher than any other country. This dominance indicates that a considerable proportion of the selected publications are from researchers based in the U.S., possibly reflecting a concentrated interest in the topic. Beyond the U.S., if we count European countries, there are 7 publications, with Spain (3) (Bordel et al., 2024; Wells et al., 2021; Charosky et al., 2022), France (1) (Robert et al., 2019), the Nederlands (1) (Wijnker et al., 2015), Norway (1) (Anthony et al., 2022), United Kingdom (1) (Pel et al., 2020) showing a good presence in the field, but also contributions originate from a diverse international and cultural base. Furthermore, Australia (2) (Currie et al., 2021; Gunness et al., 2023), China (2) (Nie et al., 2021; Fenzhi, 2014) and Lebanon (Boustani & El Boustani, 2017), India (Achuthan et al., 2020), Nigeria (Morales & Heredia, 2018), Saudi Arabia (Zogheib, 2024), Brazil (Charosky et al., 2022), Malaysia (Aris, 2024), and Mexico (Morales & Heredia, 2018) each have one publication, illustrating a broad yet less intensive participation in the field.

This distribution suggests that, while the U.S. leads in research output among the selected studies, there is noticeable global engagement with the topics covered. The presence of multiple continents in the dataset indicates the international nature of the research field, with Europe, Asia, and Australia each having notable contributions. It is interesting to note that five articles have only one author.

4.1.3. Scientific Journals

The reviewed articles were published in a wide range of journals, reflecting the field’s interdisciplinary and still-dispersed character. No single journal clearly dominates the sample; only Sustainability and Computers & Education contain more than one article, while the remaining studies are distributed across multiple outlets. This pattern suggests that research on innovation theories and innovation competencies in engineering education has not yet consolidated into a stable core of publications, but instead remains dispersed across several scholarly communities.

The distribution of journals also reveals the multiple entry points through which the topic is being approached. Education-oriented journals for a first cluster: International Journal of Educational Technology Research (Chan et al., 2016), British Journal of Educational Technology (Kopcha et al., 2016), World Journal of Education (Morales & Heredia, 2018) and International Journal of Education (Osuagwu, 2023), which indicates a strong emphasis on educational innovation, competencies development, pedagogy, and digital learning platforms.

A second cluster is represented by engineering and applied sciences journals, including the European Journal of Engineering (Charosky et al., 2022), Advanced Engineering Informatics (Aris, 2024), and the Journal of Agricultural Education (Wells et al., 2021), where the emphasis is placed more strongly on engineering innovations, system integration, and technology applications in specialised fields.

A third cluster covers policy, strategy, and management perspectives in journals such as Production Planning and Control (Robert et al., 2019), Policy Res (Pel et al., 2020), and Journal of Library Administration (Shtivelband et al., 2019), highlighting an interest in the institutional and organisational aspects of introducing innovation and fostering an innovation culture.

Beyond indicating interdisciplinarity, this distribution of publication venues suggests that innovation in engineering education has not yet established a consolidated core of journals. Instead, the topic is dispersed across education, engineering, sustainability, information systems, and policy-oriented journals, suggesting it is approached through multiple scholarly fields. This pattern is analytically important because it reflects a dual orientation in the literature: some studies treat innovation primarily as a curricular and pedagogical matter, while others frame it as an organisational, strategic, or ecosystem-level issue. The spread of journals, therefore, reinforces the argument that the field remains fragmented not only in its theoretical foundations but also in its publication structure, which may partly explain why innovation theories, innovation competencies frameworks, and curriculum design have not yet been integrated consistently.

4.1.4. Methods Used in Articles

Figure 4 shows the methods that were used in the different studies.

The methods identified can be grouped into six categories, with quantitative research and case studies appearing most frequently, at 11 times each (Wijnker et al., 2015; Friedrichsen et al., 2017; Robert et al., 2019; Joseph & Wood, 2020; Currie et al., 2021; Call et al., 2024; Mil’shtein & Tello, 2019; Zogheib, 2024; Charosky et al., 2022; Fenzhi, 2014; Morales & Heredia, 2018). These articles focus on the practical implementation of theoretical frameworks and either on the need for new systems or on the functions of the new programmes, courses, or actions introduced.

Qualitative research was used in three articles (Boustani & El Boustani, 2017; Wells et al., 2021; Osuagwu, 2023) to demonstrate the need for an in-depth understanding of the specific phenomena in engineering education.

Framework development, implementation, and survey-based evaluation were used in three articles, suggesting a need to test, validate, and calibrate new programmes, courses, and approaches in the engineering field to introduce innovative thinking and innovation competencies (McCaffreya & Krishnamurty, 2015; Nie et al., 2021; Aris, 2024).

The figure shows that only one article used the literature review method (Anthony et al., 2022) and only one used empirical research (Pel et al., 2020). It suggests that most publications used in this study are primary studies that involve new data collection and direct observations rather than secondary analyses that rely on past research.

4.1.5. Focus Area of the Articles

Table 4. Main focus areas represented in the reviewed studies.

Focus Area	Share of Sample % and n	Representative Studies *
Engineering education	47% (23)	(McCaffreya & Krishnamurty, 2015; Wijnker et al., 2015; Merhi, 2015; Kopcha et al., 2016; Chan et al., 2016; Friedrichsen et al., 2017; Shtivelband et al., 2019; Achuthan et al., 2020; Currie et al., 2021; Anthony et al., 2022; Gunness et al., 2023; Tisdale & Bielefeldt, 2024; Bordel et al., 2024; Mil’shtein & Tello, 2019; Wells et al., 2021; Nie et al., 2021; Zogheib, 2024; Charosky et al., 2022; Fenzhi, 2014; García-Aracil et al., 2024; Aris, 2024; Morales & Heredia, 2018)
Organisational development	25% (13)	(Kopcha et al., 2016; Chan et al., 2016; Boustani & El Boustani, 2017; Robert et al., 2019; Shtivelband et al., 2019; Pel et al., 2020; Joseph & Wood, 2020; Currie et al., 2021; Call & Herber, 2022; Call et al., 2024; Charosky et al., 2022; Fenzhi, 2014)
Entrepreneurship education	10% (5)	(Wijnker et al., 2015; Call & Herber, 2022; Call et al., 2024; Mil’shtein & Tello, 2019; García-Aracil et al., 2024)
Management and Leadership	8% (4)	(Boustani & El Boustani, 2017; Robert et al., 2019; Pel et al., 2020; Joseph & Wood, 2020)
Science Communication	4% (2)	(Friedrichsen et al., 2017; Osuagwu, 2023)
Strategy	2% (1)	(Osuagwu, 2023)
Psychology	2% (1)	(McCaffreya & Krishnamurty, 2015)
Policy	2% (1)	(Osuagwu, 2023)

* In the analysis, the articles could be assigned to more than one focus area. Therefore, percentages reflect the relative distribution of coded occurrences across focus areas rather than the mutually exclusive counts of articles. The total number of coded occurrences in this table is 50, while the review sample comprises 30 articles. The table should therefore be interpreted as showing thematic emphasis within the sample, rather than a one-to-one classification of studies.

summarises the main focus areas represented in the reviewed studies. The distribution shows that engineering education is the most prominent focus area, accounting for 47% of the sample, followed by organisational development with 25%. By contrast, entrepreneurship education (10%) and management and leadership (8%) appear less frequently, while areas such as strategy, science communication, psychology, and policy are represented only marginally.

This distribution suggests that the literature approaches innovation in engineering primarily through two dominant lenses. On the one hand, the prominence of engineering education indicates a strong emphasis on pedagogical design, technology integration, and the development of innovation-related competencies in students. On the other hand, the substantial presence of organisational development indicates that innovation is also treated as an institutional and cultural process, shaped by organisational dynamics, leadership structures, and universities’ capacity to support change. Taken together, these two dominant categories suggest that innovation in engineering education is being studied in terms of educational implementation and institutional enabling conditions, rather than as a purely technical or disciplinary matter.

The lower scores for entrepreneurship education, management-related studies and others suggest that innovation is often discussed as something to be introduced into curricula or supported institutionally, but less often as something that requires explicit strategic leadership or entrepreneurial orientation within engineering education itself. The focus-area distribution reinforces the broader finding of this review that the field remains unevenly developed. For engineering education, this suggests that future curriculum development may benefit from moving beyond competence delivery alone toward more integrated models that also address leadership, institutional strategy, stakeholder communication, and the wider ecosystem conditions that shape innovation

4.2. Overview of the Results—Content Analysis

From a content-analysis perspective, the findings are organised into three sub-sections: innovation theories; innovation competencies in engineering education; and innovation competencies in other fields, as identified in the articles included in the literature review. Where relevant, engineering is contrasted with other disciplines to distinguish field-specific features from shared characteristics.

4.2.1. Mapping Innovation Theories

Early definitions of innovation in engineering were often narrow, focusing primarily on incremental improvements within existing systems. (McCaffreya & Krishnamurty, 2015) highlights that such narrow definitions can limit the scope of potential innovative solutions by excluding possibilities that could lead to groundbreaking designs. This perspective underscores the importance of adopting a more expansive view of features to foster innovation in engineering, focusing on real-world design that integrates cognitive and psychological theories of innovation (McCaffreya & Krishnamurty, 2015).

Discussions of innovation theories appear in various articles, and Figure 5 shows the incidence of these theories across the articles.

According to the analysis of the articles, the Diffusion of Innovations theory is the most used, with 57% of the studies (17 in total) basing their objectives on it. Rogers’ theory provides a comprehensive framework for understanding how new ideas and technologies spread within social systems (Chan et al., 2016). Rogers’ model outlines the innovation-decision process, which includes stages such as knowledge acquisition, persuasion, decision-making, implementation, and confirmation (Friedrichsen et al., 2017). This iterative process is crucial for the successful adoption and integration of innovations in engineering, making it one of the most used theories (Merhi, 2015; Kopcha et al., 2016; Chan et al., 2016; Friedrichsen et al., 2017; Robert et al., 2019; Shtivelband et al., 2019; Achuthan et al., 2020; Currie et al., 2021; Anthony et al., 2022; Call & Herber, 2022; Tisdale & Bielefeldt, 2024; Bordel et al., 2024; Wells et al., 2021; Nie et al., 2021; Osuagwu, 2023; Call et al., 2024; Zogheib, 2024) in the field and in engineering education. The diffusion of innovation in educational contexts, as explored by (Kopcha et al., 2016) highlights the challenges associated with clearly defining innovation. The term is often used without considering its varied interpretations, which can affect the adoption and implementation of new ideas (Wijnker et al., 2015).

Only two articles (7%), (Boustani & El Boustani, 2017) and (García-Aracil et al., 2024) mentioned Schumpeter’s theory of innovation, emphasising the importance of entrepreneurs in driving technological progress. Boustani and El Boustani (2017) discusses the significance of imparting business perspectives to students, highlighting the role of entrepreneurs in fostering innovation at both individual and systemic levels.

The theory of disruptive innovation was discussed in three articles (10%) selected for the study, which emphasised the crucial need to understand how small, incremental changes can lead to major industry transformations over time (Kopcha et al., 2016; Joseph & Wood, 2020; Charosky et al., 2022). The articles also mention the importance of case studies in engineering education that show the technology path from the lower end of the market, gradually moving up and eventually overtaking existing technologies, reflecting the essence of disruptive innovation theory.

Open innovation theory is mentioned in only one article considered for the study (Wijnker et al., 2015), emphasising the value of leveraging the collective expertise and resources of a broader network, such as universities, research institutions, and other companies, to facilitate the development of more robust, diverse, and inclusive solutions and innovation.

User innovation theory is comparatively recent and particularly relevant in engineering, where the usability and functionality of products are paramount and linked to user-centred design, as mentioned in one article (Aris, 2024), and also in connection with the development of innovation competencies and engineering education.

Social innovation, found in two articles (7%) of the study, is presented as important for addressing complementary challenges. García-Aracil et al. (2024) argue that social innovation requires interdisciplinary collaboration to develop feasible solutions. Pel et al. (2020) emphasises the importance of social interactions, which provide vital access to resources and collective efforts in driving innovation and transformative change (Pel et al., 2020).

From an engineering education perspective, these theoretical differences matter because they imply different conceptions of learning, different roles for students and stakeholders, and different expectations regarding how innovation-related competencies should be cultivated and assessed.

The literature selected for the study indicates that Rogers’ Diffusion of Innovations theory is dominant in the field of innovation competencies, as it is a well-established, research-supported framework that has been validated across diverse disciplines for decades (Call & Herber, 2022; Bordel et al., 2024). It is important because it provides a systematic way to predict adoption rates based on human perception rather than just technical merit (Call & Herber, 2022). However, in education, it is limited by its inability to measure actual academic performance and the challenge of applying it to the highly independent and often resistant social systems of academia (Currie et al., 2021; Anthony et al., 2022; Zogheib, 2024). The theory has become particularly prominent because of its interdisciplinary versatility and analytical clarity. It has been applied across a wide range of domains, including engineering, education, sociology, agriculture, and information technology, thereby strengthening its transferability to engineering education research (Call & Herber, 2022; Bordel et al., 2024; Achuthan et al., 2020). A further reason for its dominance is its human-centred orientation: rather than assuming that objectively superior technologies or practices will naturally prevail, the theory explains innovation as a social process shaped by how individuals perceive, interpret, and respond to change (Call & Herber, 2022; Wells et al., 2021; Achuthan et al., 2020). Its enduring appeal also lies in the structured framework it offers for analysis, combining four core elements—innovation, communication channels, time, and the social system—with five perceived attributes of innovations: relative advantage, compatibility, complexity, trialability, and observability (Osuagwu, 2023; Achuthan et al., 2020; Call & Herber, 2022; Call et al., 2024). This conceptual architecture has given the theory strong explanatory and predictive utility, with prior studies suggesting that these perceived attributes account for a substantial proportion of the variance in adoption rates.

The theory is particularly important because it helps explain why innovations that appear technically superior may nevertheless fail to achieve widespread uptake if they are not perceived favourably by potential adopters (Call & Herber, 2022; Call et al., 2024). In this sense, it offers a useful lens for analysing adoption failures and for designing strategies to accelerate uptake, for instance by reducing perceived complexity through training, support, or improved interfaces. Moreover, the theory highlights the importance of interpersonal communication and opinion leaders in fostering actual adoption, suggesting that innovation spreads less through abstract dissemination than through socially mediated processes of trust and influence (Osuagwu, 2023; Achuthan et al., 2020; Friedrichsen et al., 2017).

Because the theory has been used across multiple domains, it provides engineering education with a flexible analytical lens for examining how new pedagogies, technologies, and curricular models are introduced, communicated, and embedded. In terms of innovation competencies, it covers creativity, problem-solving, collaboration and teamwork, leadership, and strategic thinking (Kopcha et al., 2016; Robert et al., 2019; Bordel et al., 2024; Call et al., 2024).

At the same time, applying the Diffusion of Innovations theory in education has important limitations. A recurring challenge is the lack of a shared, precise understanding of what counts as “innovation,” which can lead educators to hold divergent assumptions, expectations, or scepticism about the term (Kopcha et al., 2016). In addition, the pedagogical innovations are often tacit, context-dependent, and difficult to codify, which makes them harder both to justify the innovation competencies before implementation and to evaluate afterwards (Robert et al., 2019). The theory has also been criticised for a pro-innovation bias, since empirical work often concentrates on visible or successful cases while paying less attention to failed or resisted adoption processes (Pel et al., 2020; Call & Herber, 2022). Reflecting these factors, Diffusion of Innovations theory remains highly useful for understanding implementation dynamics, but in educational contexts it often benefits from being complemented by other theoretical approaches that consider additional concepts, such as innovation competencies and the broader socio-cultural dimension of engineering curricula.

4.2.2. Innovation Competencies in the Engineering Field

The second part of the study and the second research question focused on how innovation competencies in the engineering field are reflected and how a new curriculum could be shaped. In this regard, the results show a tendency towards an equal distribution among creativity (10 articles, 33%), collaboration or teamwork (11 articles, 37%), strategic thinking (10 articles, 33%), and problem-solving (6 articles, 20%). The results show that fostering a culture of creativity, problem-solving, and collaboration or teamwork in engineering education is essential for the successful implementation of innovative solutions in engineering (Mil’shtein & Tello, 2019; Wells et al., 2021; Charosky et al., 2022; García-Aracil et al., 2024; Aris, 2024). This distribution suggests that innovation competencies in engineering education are framed predominantly as implementation-oriented capacities. The prominence of collaboration, strategic thinking, creativity, and problem-solving indicates that the reviewed studies tend to view innovation less as an isolated act of invention and more as a process of developing, adapting, testing, and embedding solutions in technical and educational settings. This interpretation aligns with the broader thematic pattern identified in this review, namely that innovation in engineering is often understood in terms of adoption, organisational adjustment, and pedagogical change rather than through differentiated conceptions of innovation.

Figure 6, designed as a heatmap, shows the relationships and occurrences among the study articles regarding the theories of innovation and the identified innovation competencies. For example, the Diffusion of Innovation theory is most frequently linked with strategic thinking (4 articles) and collaboration or teamwork (3 articles).

Rather than indicating simple co-occurrence, Figure 6 suggests that different innovation theories privilege different competencies profiles. The clustering of Diffusion of Innovation theory with strategic thinking and collaboration or teamwork can be interpreted as a consequence of its implementation-oriented logic: when innovation is understood as adoption and institutional uptake, competencies related to stakeholder alignment, communication, teamwork, and strategic change become particularly important. This interpretation is reinforced by studies that combine diffusion-oriented perspectives with entrepreneurial, leadership, and organisational development skills, and that treat innovation in engineering education as a managed process of embedding new pedagogical, technological, or organisational practices.

Similarly, many articles argue that incorporating business and entrepreneurial skills into the engineering curriculum, alongside technical competencies and the application of Diffusion of Innovation theory, can produce engineers who are not only proficient in science and technology but also skilled in leadership, strategic thinking and mindset change (Wijnker et al., 2015; Anthony et al., 2022; Friedrichsen et al., 2017; Boustani & El Boustani, 2017; Robert et al., 2019; Pel et al., 2020; Joseph & Wood, 2020; Call & Herber, 2022; Bordel et al., 2024; Mil’shtein & Tello, 2019; Charosky et al., 2022; Fenzhi, 2014; García-Aracil et al., 2024; Morales & Heredia, 2018).

Articles (Achuthan et al., 2020; Aris, 2024; Bordel et al., 2024) note that, given the practical aspects of technology adoption, engineering professionals can develop innovative solutions that improve processes, products, and systems through the stages of idea generation and concept development. Having an arena and competencies developed for prototyping, testing, and applying necessary adjustments and improvements to the prototype helps engineering education develop the mindset for innovation and enhance the overall quality of the final product, as mentioned in articles (Pel et al., 2020; Achuthan et al., 2020; Gunness et al., 2023; Currie et al., 2021; Friedrichsen et al., 2017). Among the articles that mentioned leadership and strategic thinking important for innovation in engineering, some also mentioned that improving organisational processes and practices towards innovation culture and innovation management will help add innovation in the engineering education field (Currie et al., 2021; Friedrichsen et al., 2017; Boustani & El Boustani, 2017; Robert et al., 2019; Pel et al., 2020; Joseph & Wood, 2020; Call et al., 2024; Charosky et al., 2022; Fenzhi, 2014; Morales & Heredia, 2018).

The less-represented theories suggest broader and partly distinct competencies configurations. In the reviewed sample, open innovation is associated with leveraging expertise and resources across universities, research institutions, and other organisations, pointing to competencies such as networking, mindset, and knowledge integration. User innovation shifts attention toward user-centred design and the usability and functionality of solutions, thereby placing greater emphasis on creativity and responsiveness to user needs. Social innovation, as represented in two studies, further broadens the competence profile by foregrounding interdisciplinary collaboration, social interaction, access to resources, and collective efforts to address contemporary challenges. Compared with the diffusion of innovation competencies, these perspectives suggest a broader architecture of innovation competencies in which co-creation, external engagement, and societal responsiveness are more visible and should be valuable for innovation competencies in engineering education.

For curriculum design, these findings indicate that the theoretical lens adopted in engineering education is not neutral. If diffusion of innovation theory is considered, then it is more likely to support curricula that emphasise implementation, teamwork, leadership, strategic planning, prototyping, and organisational readiness for change. By contrast, the presence of open, user, and social innovation suggests that curricular elements that support external collaboration, user engagement, interdisciplinary work, and responsiveness to societal challenges are important and should be given value in curriculum design. The same distinction applies to assessment: when innovation is framed primarily in terms of adoption and implementation, assessment is likely to privilege project execution, problem-solving, and organisational application, whereas broader innovation framings would require evaluation of co-creation, contextual responsiveness, and collaboration across institutional and social boundaries.

4.2.3. Comparison with Other Disciplines

Innovation competencies in engineering education can be contrasted with those in other disciplines to highlight unique aspects and shared characteristics. In the field of educational science, Charosky et al. (2022) noted that the focus is often on integrating theoretical knowledge with practical application, aiming to foster social responsibility and connect academic disciplines with professional issues. This approach emphasises the importance of straightforward lecturing to facilitate learning and inspire participation in technological incubators, which is somewhat similar to the engineering emphasis on problem-solving and collaboration mentioned in (Friedrichsen et al., 2017; Currie et al., 2021; Gunness et al., 2023; Mil’shtein & Tello, 2019; Wells et al., 2021; Charosky et al., 2022; Fenzhi, 2014; García-Aracil et al., 2024; Aris, 2024; Morales & Heredia, 2018).

In the natural sciences, García-Aracil et al. (2024) argue that innovation competencies are often centred on rigorous experimentation and empirical validation, which parallels the engineering process of prototyping and testing.

The integration of sustainability concepts into engineering education is another area for comparison. According to (Wijnker et al., 2015; Pel et al., 2020; Currie et al., 2021; Tisdale & Bielefeldt, 2024; Mil’shtein & Tello, 2019; Nie et al., 2021), incorporating sustainability topics into engineering courses requires well-established, objective curriculum materials that treat these concepts with rigour. This perspective highlights the need for quantitative assessments of student learning, a common approach in engineering but one that may differ from the more qualitative assessments used in other disciplines.

Furthermore, the implementation of innovative pedagogical strategies in engineering education parallels established practices in other academic disciplines. For instance, the use of virtual laboratories in engineering education has overcome barriers such as insufficient resources (Achuthan et al., 2020). This approach is similar to using technology in other disciplines to enhance learning experiences and provide interactive content. However, the hesitance towards technology as a substitute for face-to-face dialogue in engineering education reflects a cautious approach that may be less prevalent in other fields (Kopcha et al., 2016).

5. Discussion

The objective of this study was to determine how the main innovation theories and innovation competencies are identified within the engineering body of knowledge, and how they influence innovation competencies requirements, and how they could sharpen curriculum design.

The Section 5 is designed to address the two main research questions of this paper: (1) How is innovation perceived in the engineering field, and (2) How does existing research conceptualise the relationship between innovation theories and innovation competencies in engineering education (Section 5.1). Furthermore, the chapter will also present the implications and research gaps identified in the field (Section 5.2 and Section 5.3).

5.1. From Innovation Theories to Innovation Competencies in the Engineering Field

The mapped articles show that innovation in the engineering field is viewed as a multifaceted process that encompasses the development of new and useful products, the implementation of novel management practices, and the cultivation of specific innovation competencies among both students and practitioners (Robert et al., 2019; Fenzhi, 2014; Charosky et al., 2022). Innovation is a critical aspect of the engineering field, influencing both educational practices and professional applications. Innovation is increasingly recognised as a human-driven factor, dependent on highly qualified scientists and engineers who possess not only technical expertise but also entrepreneurial skills such as visionary leadership, strategic thinking, team collaboration, and opportunity-seeking (Mil’shtein & Tello, 2019; Wijnker et al., 2015).

The research adopts two analytical lenses within engineering: innovation theories and theories of innovation competencies. Across the selected articles, these lenses are interdependent and collectively provide an integrated understanding of the field, exerting reciprocal influence on the development of innovation competencies and further impact on engineering education curricula.

In engineering education, innovation is still most often operationalised through implementation-oriented lenses, particularly challenge-based learning, competence-based curricular realignment, and the institutional uptake of strategies for new pedagogical models, rather than through sustained engagement with broader social, user, or open innovation perspectives (van den Beemt et al., 2023; Doulougeri et al., 2024; Pacher et al., 2024; Helker et al., 2025). At the same time, open and social innovation are becoming more conceptually developed, especially through work on knowledge exchange, university–industry collaboration, faculty capability, curriculum transformation, community partnerships, and helix-based collaboration (Jekabsone & Anohina-Naumeca, 2024). The authors indicate that the field is moving toward more ecosystem- and challenge-based models, but that this shift is still more visible in pedagogical design and institutional experimentation than in explicit theoretical diversification. The discussion has important implications for competencies development because an implementation-dominant framing tends to privilege collaboration, problem-solving, and project execution. In contrast, competencies related to co-creation, societal responsiveness, and boundary-spanning innovation remain less systematically articulated.

The most frequently used theory of innovation in engineering, according to the selected articles, is the Diffusion of Innovation theory (Merhi, 2015; Kopcha et al., 2016; Chan et al., 2016; Friedrichsen et al., 2017; Robert et al., 2019; Shtivelband et al., 2019; Achuthan et al., 2020; Currie et al., 2021; Anthony et al., 2022; Call & Herber, 2022; Tisdale & Bielefeldt, 2024; Bordel et al., 2024; Wells et al., 2021; Nie et al., 2021; Osuagwu, 2023; Call et al., 2024; Zogheib, 2024). The relationship between innovation in engineering, technological advances and innovation competencies is characterised by a continuous interplay of advancements, adaptations and new methods in engineering education (Tisdale & Bielefeldt, 2024; McCaffreya & Krishnamurty, 2015; Nie et al., 2021; Robert et al., 2019; Boustani & El Boustani, 2017; Friedrichsen et al., 2017). Furthermore, the distribution of articles across different journals highlights a multidisciplinary approach, with strengths in education, engineering, sustainability, and technology adoption. While some journals are more prominent, no single publication dominates, which suggests that the research is reaching diverse academic audiences.

Although the Diffusion of Innovation theory is widely used to explain how new technologies spread within cultural systems, applying it in the context of education highlights the challenges of clearly defining innovation. This observation underscores the need for precise definitions and a shared understanding of the innovation theories used in engineering education. If the concept of innovation is clearly defined and includes the elements that drive it, such as technological developments, technical skills, soft skills, innovation competencies (Call & Herber, 2022; Mil’shtein & Tello, 2019; Call et al., 2024), this will better facilitate the adoption of innovation theories in engineering education (Tisdale & Bielefeldt, 2024; Wells et al., 2021; Shtivelband et al., 2019). Theoretical concepts such as disruptive innovation, open innovation, and user innovation theories, which guide the development and implementation of innovative solutions in engineering (Wijnker et al., 2015; Aris, 2024; Pel et al., 2020; García-Aracil et al., 2024), could be more appropriate for discussing innovation in engineering education. These theories provide a structured approach to innovation, ensuring that new ideas are effectively integrated into existing systems and processes. As argued by (Kopcha et al., 2016; Joseph & Wood, 2020; Charosky et al., 2022), the theory of Disruptive Innovation, focusing on how new technologies can displace established ones, leading to significant shifts in industry standards, practices, and services, could create a significant change if it were more widely used in engineering education. However, as trends in engineering education increasingly include new competencies such as creativity, mindset, and entrepreneurial skills, a shift is underway (Charosky et al., 2022).

Challenges and opportunities in engineering innovation are multifaceted and require a comprehensive understanding of factors ranging from the definition of innovation and the innovation process to the resources and technologies to use, the innovation ecosystem, and the development of the right skills and competencies. As identified by (Charosky et al., 2022), one of the primary challenges is the need for engineering students and professionals to develop competencies in creative problem-solving, critical thinking, and design thinking. According to (Morales & Heredia, 2018; Wijnker et al., 2015; Aris, 2024; Mil’shtein & Tello, 2019), developing innovation competencies in students is crucial for fostering a culture of innovation.

Furthermore, cultivating essential competencies such as creativity, problem-solving, and collaboration is crucial for engineers, empowering individuals to navigate the complexities of modern engineering challenges and contribute to the creation of innovative solutions. Current trends in engineering education reflect a strong commitment to fostering these competencies among students. Examples of the successful integration of innovation competencies into engineering education are through challenge-based projects, design thinking, product development, collaboration with industry and case study work (Friedrichsen et al., 2017; Robert et al., 2019; Joseph & Wood, 2020; Currie et al., 2021; Charosky et al., 2022; Fenzhi, 2014; García-Aracil et al., 2024). The emphasis on collaboration, particularly in the context of open innovation, highlights the importance of engaging external partners and stakeholders to leverage diverse expertise and resources.

However, an innovation-oriented mindset and leadership skills remain comparatively underrepresented in engineering education, reflecting a long-standing curricular emphasis on disciplinary expertise and technical problem-solving rather than broader innovation practice (García-Aracil et al., 2024). This imbalance is consequential because innovation theories are not merely descriptive frameworks—they implicitly prescribe the competence profiles required to enact the innovation processes they theorise, and to determine when innovation is successful. More precisely, different theoretical lenses tend to privilege different professional competencies. For example, the evidence from the reviewed studies indicates that work drawing on Diffusion of Innovation theory places greater weight on competencies such as strategic thinking (e.g., anticipating adoption dynamics, segmenting stakeholders, and planning implementation pathways) than on mindset-oriented dimensions (Kopcha et al., 2016; Robert et al., 2019; Bordel et al., 2024; Call et al., 2024).

It is important to note that some articles in the study also mentioned the need for teachers and academic staff to understand innovation and to have access to courses, technologies, and organisational support (Charosky et al., 2022; Tisdale & Bielefeldt, 2024; Currie et al., 2021).

Not long ago, the term innovation was often used to describe practices that derived from standard or well-entrenched methods. Current initiatives are correctly aligned with the transition toward a broader competency framework by adding new competencies. The systemic development of innovation competencies, especially soft competencies for engineering programmes, requires further acceleration to meet evolving industry demands.

5.2. Where the Field Needs to Go Next: Implications and Research Gaps

This scoping literature review found that the current trends in innovation in engineering education are characterised by the integration of new ideas and technologies aimed at enhancing processes, products, and systems, as well as new teaching techniques and new competencies such as creativity, problem-solving, collaboration, leadership, and strategic thinking (Boustani & El Boustani, 2017; Robert et al., 2019; Mil’shtein & Tello, 2019; García-Aracil et al., 2024). Another focus is teaching entrepreneurship concepts, equipping students with the knowledge, skills, and attitudes necessary to contribute to economic and societal prosperity and combine with technical skills (Mil’shtein & Tello, 2019; Wijnker et al., 2015; García-Aracil et al., 2024; Aris, 2024).

Organisational development is another critical area identified by the study, focusing on improving management innovation, organisational innovation culture, and leadership (Osuagwu, 2023; Aris, 2024; Kopcha et al., 2016). For example, Anthony et al. (2022) is discussing the organisation’s development and the training of academic staff to integrate the course’s innovation theories and competencies, thereby creating an opportunity to transfer these skills to students.

In the context of innovation competencies in engineering education, it is important to acknowledge that areas such as science communication, policy and psychology could make useful contributions (McCaffreya & Krishnamurty, 2015; Pel et al., 2020; Gunness et al., 2023; Call & Herber, 2022; Joseph & Wood, 2020). From a practical perspective, the study’s findings suggest that these areas can enhance engineering innovation (Charosky et al., 2022; Osuagwu, 2023).

This study has significant implications for engineering education and innovation research. As shown, a few studies have applied innovation theories in engineering and combined them with innovation competencies.

The articles identify several critical research gaps across engineering, education, and innovation. These gaps range from a lack of empirical performance data to the need for more complex theoretical models, as shown in

Table 5. Research gaps categorised.

Education curricula	Many innovation methods are currently limited to specific market needs and exist as discrete solutions; there is a gap in developing “sustainable” innovation processes that can generate new ideas continuously (Aris, 2024). There is limited understanding of which specific innovation competencies are developed through project-based versus challenge-based courses (Charosky et al., 2022).
Impact on performance	There is a significant lack of research examining the direct impact of technological tools and platforms on engineering students’ classroom performance (Zogheib, 2024). Current studies often focus on perceptions rather than measurable academic outcomes (Currie et al., 2021). Very few studies have concurrently explored the constructs and factors of innovation adoption while considering the perspectives of students, lecturers, and administrators (Anthony et al., 2022). Future research is needed to understand the complex interactions and feedback mechanisms between instructors and students within technology-enhanced environments (Zogheib, 2024).
Academic staff	Researchers often assume a shared meaning for the word “innovation,” leading to a gap in understanding how different faculty members and administrators may project their own biases or prejudices onto the term (Kopcha et al., 2016).
Organisational structure and long-term sustainability	Research has not yet sufficiently explored changes in organisational structures, the long-term maintenance of innovation adoption behaviours, or how these behaviours adapt over several years (Achuthan et al., 2020).

.

The articles (Boustani & El Boustani, 2017; Pel et al., 2020; Bordel et al., 2024; Mil’shtein & Tello, 2019; Charosky et al., 2022; Fenzhi, 2014; García-Aracil et al., 2024; Aris, 2024; Morales & Heredia, 2018) indicate that innovation competencies in engineering education share commonalities between the areas and with other disciplines, such as the emphasis on creativity, problem-solving, and the integration of theoretical knowledge with practical application. Moreover, the articles (Kopcha et al., 2016; Aris, 2024; Zogheib, 2024; García-Aracil et al., 2024; Achuthan et al., 2020; Currie et al., 2021; Shtivelband et al., 2019; Tisdale & Bielefeldt, 2024; Anthony et al., 2022; Call & Herber, 2022) show distinct differences in assessment methods, the adoption of innovative teaching practices, and organisational preparedness.

5.3. Illustrative Pathways for Translating Innovation Theories into Curricular and Pedagogical Practice

This sub-section elaborates on the existing research and findings presented in the results section by addressing the research questions and analysing the implications of innovation theories for the development of innovation competencies and curriculum design.

Figure 7 presents an analytical division of pathways, illustrating how different theoretical lenses may guide different curriculum designs. Translating innovation theories through pedagogical and curriculum design lenses yields distinct competencies profiles, educational priorities, and assessment approaches. Thus, translating innovation theories into engineering education requires shifting the focus from which theory is present in the literature to which innovation competencies a given theory helps develop. The pathways outlined above are therefore not intended as prescriptive models but as analytically derived examples of how different theoretical perspectives may guide curriculum design, assessment, and faculty and institutional development in engineering education.

A first pathway can be derived from Schumpeterian and Disruptive Innovation perspectives. These perspectives are grouped because of the similarities in how they approach innovation and the competencies required to support it. This pathway frames innovation as reconfiguration and system change, which places greater emphasis on opportunity recognition, experimentation, and the capacity to challenge established assumptions and structures. The curricular significance of this pathway resides in encouraging a more transformative understanding of engineering education, in which students are prepared not only to improve existing systems but also to envision and justify alternative futures.

A second pathway emerges from the dominance of Diffusion of Innovation theory in the reviewed literature. Its main implication is that engineering education tends to frame innovation as a matter of adoption, implementation, and institutional uptake, thereby privileging competencies in strategic planning, stakeholder engagement, and change management. In consequence, this orientation can strengthen students’ capacity to understand how innovations gain legitimacy and scale. However, it may also narrow innovation education toward transfer and uptake rather than creation, critique, or systemic transformation.

A third pathway is associated with Open Innovation theory. Its educational impact lies in repositioning innovation as a boundary-spanning process that foregrounds the importance of collaborative capacity, knowledge integration, and engagement with actors beyond the university. As a result, innovation, learning, and competencies shift from an internally bounded curricular activity toward a more networked and relational model of engineering practice, with implications for partnership-based pedagogy and more process-oriented forms of evaluation.

A fourth pathway arises from User Innovation and Social Innovation perspectives. We grouped these perspectives because of their shared approaches to innovation and the competencies required to support them. Within them, the central implication is that innovation is valued not only for technical novelty but also for its responsiveness to users, communities, and broader societal challenges, thereby expanding the competence profile toward co-creation, ethical judgement, and contextual sensitivity. It broadens the impact of engineering education by linking innovation more explicitly to inclusion, sustainability, and public value, rather than to market or organisational performance alone.

The explicit application of these theoretical distinctions enables engineering education programmes to move beyond generic rhetoric about “more innovation” and to develop more coherent, evidence-informed approaches to curriculum design, assessment, and faculty development. Collectively, these pathways indicate that innovation theories do more than describe innovation in engineering education: they also structure distinct educational logics. Each of these logics carries distinct implications for the prioritised innovation competencies. Each legitimises particular forms of learning and educational curriculum. Each also shapes the broader organisational and societal impact that engineering programmes are expected to achieve.

To conclude this section, future research in engineering innovation should focus on new educational models, curriculum design, the inclusion of more innovation theories, human factors, sustainable technologies, and new technologies for education and learning. These areas offer promising directions for advancing the field and addressing current limitations, ultimately leading to more effective and innovative engineering education programmes.

5.4. Limitations

In Section 3, the limitations of the method used when scoping the literature are explained. Although an attempt has been made to design this study to avoid or mitigate potential limitations (such as performing two string searches to identify articles specific to the study), there will always be limitations that can affect the identification and analysis of results and findings. There is a good representation of articles from the US, Europe, and Asia. However, the relatively low representation from Africa and Latin America, apart from Nigeria, Brazil, and Mexico, each with one article, may indicate a selection bias in the dataset. It should not be forgotten that the present analysis is from the authors’ perspective and may not be interpreted the same way by other researchers or professionals in the field. Likewise, it is possible that certain literature in the field has been overlooked, or that some more recent evidence on the studies has not yet been published at the time of the search and selection. The analysed articles were limited to English, potentially omitting knowledge in other languages. Consequently, to mitigate the risks in this regard, several authors analysed and interpreted the data and results obtained here, thereby contributing to the final consensus and reducing bias among them. Finally, a limitation is that valuable insights might have been missed because grey literature and books were excluded, although they lack the same quality assurance as peer-reviewed articles.

6. Conclusions

This paper aimed to examine how innovation is framed in the engineering field and to identify the main gaps in the literature concerning the relationship between innovation theories and innovation competencies in engineering education. The review shows that, although innovation is increasingly acknowledged as critical to engineering education and practice, the field still lacks a sufficiently coherent theoretical foundation for connecting innovation theories, innovation competencies development, and curriculum design.

Among the theoretical frameworks, the Diffusion of Innovation theory remains the most widely referenced (Rogers, 1971), suggesting that the adoption and spread of ideas are central concerns in engineering innovation discourse. However, other perspectives, such as Disruptive Innovation (Christensen, 1997), Open Innovation (Chesbrough, 2003), and User Innovation (von Hippel, 2005) remain underrepresented despite their potential to contribute to engineering pedagogy and practice. This underuse of diverse theoretical approaches limits the scope of current educational models and does not fully reflect the complexity of contemporary engineering challenges.

The review also shows that the integration of innovation competencies in engineering education is gaining traction, particularly through the incorporation of creativity, collaboration, problem-solving, and strategic thinking (Charosky et al., 2022). These competencies are increasingly being introduced into curricula through project-based learning, design thinking frameworks, and interdisciplinary collaboration. However, entrepreneurial skills, leadership, and an innovation mindset are still underexplored and insufficiently embedded in engineering programmes. The literature emphasises that fostering these competencies in students—as well as equipping faculty and institutions with the necessary tools and mindsets—is essential for developing engineers capable of driving societal change and technological advancement, and of achieving the Sustainable Development Goals (García-Aracil et al., 2024; Mulgan, 2006).

This study further suggests that innovation theories are more than descriptive tools for innovation in engineering education; they also imply different competencies priorities and different curricular and pedagogical logics. Consequently, the contribution of the review lies not only in mapping the field but also in providing an analytical basis for aligning innovation theories with competencies profiles and with implications for curriculum design, assessment, and faculty development.

The findings indicate that engineering innovation research is not yet consolidated around a unified framework or set of best practices, which continues to create gaps in application and outcomes. Future work should therefore aim to deepen the theoretical foundation of innovation in engineering by incorporating a broader range of innovation theories and by examining more systematically how these translate into curriculum reform, assessment approaches, faculty development, and organisational transformation within higher education. Thus, as future work, we are conducting new studies to design new curricula and robust frameworks for cultivating innovation competencies, especially soft skills, among both students and academic staff in engineering faculties. Additionally, we intend to conduct future studies to explore organisational transformation strategies within academia that support innovation, including curriculum reform, faculty strategies and action plans to foster an innovation culture.

If we take the lens that we used at the start of the article and look at the innovation competencies from the point of view of the innovation theories and we take as example an Schumpeter’s five innovation types—new products, methods, markets, sources of supply, industrial structures—we would interpret innovation competencies beyond “new teaching methods” alone: curricula—products, assessment/pedagogy—methods, new learner—markets, new knowledge inputs—sources of supply, and reorganised institutions to integrate innovation culture—industrial structures. In short: if engineering education aims to educate innovators, it must itself innovate across the full system—not only in the classroom.