Empathy is generally understood as the capacity to perceive, understand, and respond to the emotional and mental states of others. Although the term has its linguistic roots in ancient Greek, meaning “feeling into,” its scientific use emerged relatively late, first appearing in early twentieth-century psychology and aesthetics before evolving into a key concept for understanding social cognition and human interaction [1], [22]. At its core, empathy involves an affective response triggered by observing, imagining, or inferring another person’s emotional state, alongside the awareness that this state originates in the other. Modern research commonly distinguishes empathy into emotional empathy and cognitive empathy, with the latter further divided into affective theory of mind (ToM) and cognitive theory of mind [1]. Emotional empathy refers to the automatic sharing of another person’s feelings, while affective ToM involves consciously recognising and reasoning about others’ emotions, and cognitive ToM relates to understanding others’ thoughts, intentions, and beliefs. Together, these interrelated dimensions reflect the complex cognitive and emotional processes through which individuals make sense of others as thinking and feeling beings.

Empathy plays a significant and often underappreciated role in scientific learning, particularly in contexts that engage students both cognitively and emotionally. Research indicates that many effective science education interventions already involve empathising processes, even if this is not explicitly recognised [20], [23]. Emotional empathy, for instance, is activated through social interactions among students and between students and lecturers, fostering motivation and engagement in collaborative and practical learning activities. Cognitive empathy, including affective and cognitive ToM, enables learners to understand others’ perspectives, intentions, and feelings, which is particularly relevant when addressing open-ended, controversial, and morally or ethically charged socio-scientific issues. Science topics related to health and the environment are especially effective for eliciting empathic engagement, as they connect scientific concepts to real-life human and ecological concerns [21], [24]. Simulation-Based Learning (SBL) provides a concrete example of how empathy can be integrated into science education. For instance, in SBL, students actively participate in scenarios that simulate complex, real-world problems, using structured rubrics such as the Empathetic Patterns in Interpersonal Communication (EPIC) model to identify and analyse empathetic patterns. These experiences enhance students’ ability to recognise cognitive and emotional aspects of empathy, develop situational interest, and engage collaboratively in problem-solving, mirroring the processes observed in scientific practice [17]. Moreover, empathy and theory of mind are particularly crucial in medical and healthcare education, where students’ ability to understand and respond to patients’ emotions directly affects the quality of care. For instance, studies among dental students have shown that higher empathy levels, as measured by the Toronto Empathy Questionnaire and the Reading the Mind in the Eyes Test, are associated with better understanding of patients’ needs and ethical decision-making [25]. Such research highlights that incorporating structured empathy training, communication skill development, and practical experiences with patients into curricula is vital for preparing students to provide patient-centred care. These findings underscore that, beyond cognitive learning, cultivating emotional and social skills through empathy is essential for students entering professional practice in dynamic, human-centred fields.

Furthermore, recent research demonstrates that HE institutional frameworks can also influence students’ empathy and willingness to innovate [26]. Studies show that comprehensive evaluation systems that consider both the research process and output stimulate students’ empathic engagement with their work and encourage innovative thinking. By integrating dynamic, process-oriented assessments rather than focusing solely on quantity or traditional metrics, universities can foster an environment where empathy drives the responsible and sustainable use of knowledge resources. It highlights the broader impact of empathy, extending beyond classroom learning to systemic academic and research practices, and underscores its critical role in cultivating innovative solutions for sustainability challenges. Incorporating empathy into STEAM higher education not only increases student motivation but also supports the development of prosocial relationships, ethical thinking, and innovative learning approaches among professors, students, and other staff at HEIs, which is necessary for addressing current and future environmental and social challenges.

Understanding learning modalities is crucial for developing preference-aligned educational content and methodologies tailored to the diverse ways in which students absorb, process, and apply knowledge. Learning preferences refer to the individual differences in how students prefer to engage with content. There are different classifications of learning preferences, some of which are more widely used and recognised in pedagogical practice. Among the most well-known is Kolb's model of learning styles [27], which categorises learners as convergers, assimilators, divergers, and accommodators based on their preferences for experiencing, thinking, observing, and experimenting. Other common models include the VARK model (visual, auditory, reading-writing, kinesthetic) [28], Gardner’s theory of multiple intelligences [29], and the Felder-Silverman model [30].

One study on STEAM education found that learning preferences significantly affect students’ attitudes toward STEAM subjects [31]. The study revealed that students with convergent and assimilative learning preferences demonstrated more positive attitudes toward STEAM learning, while divergent and accommodative students exhibited lower levels of motivation and interest. This finding highlights the importance of adapting teaching approaches to different learning preferences and incorporating collaborative, hands-on activities that engage students, especially those who may not traditionally show a strong interest in STEAM subjects.

Despite the common belief in the effectiveness of learning preferences, recent research questions their impact on learning outcomes. A survey of UK HE teachers found that although many teachers still believe in the effectiveness of learning styles, the actual use of these classifications in teaching is relatively low [32]. This discrepancy between belief and practice suggests that although learning styles are often cited as a useful tool for adapting teaching, there is little evidence to support their effectiveness. Consequently, instead of rigidly classifying learners by learning style, it may be more beneficial to emphasise a flexible approach that incorporates a variety of teaching methods to address diverse learning needs. Therefore, it may be more useful in STEAM education to emphasise flexible teaching methods that include a variety of approaches that can appeal to a broader range of learners and stimulate a deeper interest in these subjects, whatever their learning style.

Building on this pedagogical perspective, the empathetic questionnaire focuses on cognitive learning preferences by examining how learners process and absorb information, rather than assigning them to rigid categories. This approach is aligned with the VARK model, which highlights sensory preferences such as visual, auditory, reading/writing, and hands-on learning. Each cognitive preference (Figure 1, left) represents distinct strengths in acquiring, organising, and retaining knowledge, providing a foundation for designing learning content that is flexible, inclusive, and responsive to diverse learning strategies. Complementing this, metacognitive learning preferences (Figure 1, right) capture how learners regulate their learning processes, including planning, reflection, and strategy adaptation. These preferences encompass structured, reflective, and holistic approaches to learning, which are particularly important when addressing complex and interdisciplinary topics such as sustainability and innovation. Table 1 synthesises both cognitive and metacognitive learning preferences, outlining their core characteristics and preferred learning strategies and serves as a practical reference for the development of adaptable and inclusive educational content in STEAM higher education.

Figure 1.

Cognitive (left) and metacognitive (right) learning preferences considered within the IGNITE empathetic questionnaire

Understanding sustainability as a meta-context from a whole-system perspective is essential for enabling students to recognise the societal, environmental, and technological implications of their decisions. Such systemic understanding is closely linked to the development of scientific empathy, as it encourages learners to consider the consequences of actions for diverse stakeholders and to navigate complex dilemmas inherent to sustainable development and innovation, as highlighted in recent research on engineering education and curriculum renewal [33]. To support this process, learning approaches that integrate multiple cognitive and metacognitive preferences offer diverse and inclusive pathways for engaging with complex sustainability-related content. One particularly effective approach is the use of concept maps, which enable learners to visually structure and interconnect interdisciplinary knowledge, making abstract systems and relationships more tangible and accessible [15].

Concept maps accommodate a wide range of learning preferences: visual learners benefit from graphical representations, auditory learners from collaborative discussions around the maps, reading/writing learners from annotating and elaborating concepts, and kinesthetic learners from actively constructing maps and simulating real-world problem-solving scenarios. At the metacognitive level, active learners engage through hands-on and collaborative tasks, reflective learners deepen understanding through analysis and synthesis; sequential learners follow logically structured pathways; and global learners grasp overarching system-level connections. In this way, concept maps not only enhance comprehension and critical thinking but also support the development of scientific empathy, innovation, and sustainable decision-making in higher education learning environments.

In this study, the primary methodological tool was an empathetic questionnaire developed to systematically capture students’ cognitive and metacognitive learning preferences, motivational factors, and emotional engagement in STEAM higher education. The questionnaire is designed to explore how learners experience different learning situations, perceive content emotionally, and how these factors influence engagement with educational materials. It focuses on the learning process rather than outcomes, providing insight into how emotional and cognitive dispositions shape approaches to learning, particularly in digital environments. To enhance transparency and reproducibility, the full questionnaire is provided in Table 2, alongside a clear explanation of which items assess which constructs.

The cognitive learning preferences part measures preferred methods of receiving and processing information, motivational factors, and emotional engagement. The metacognitive learning preferences section measures how learners organise, reflect, and structure their learning.

The use of the empathetic questionnaire supports a more nuanced understanding of how students relate to different forms of learning content, enabling educational materials, teaching methods, and learning environments to be adapted in a targeted and evidence-informed manner. Within the Erasmus+ IGNITE project, these findings will inform the design of personalised and flexible learning pathways, enhancing alignment with students’ learning preferences and inclusiveness of learning experiences. In addition, the questionnaire encourages structured self-reflection, enabling students to become more aware of how their emotional and cognitive dispositions influence their learning, thereby fostering greater self-regulation and adaptability.

In the context of e-learning, the questionnaire was applied to identify patterns of emotional engagement and cognitive preferences that influence students’ interaction with digital learning materials. The results provide a basis for developing adaptive nanolearning modules, tailored to pacing, interactivity, and content structure, which are critical for sustaining motivation and engagement in online learning environments. Importantly, the questionnaire also serves as a mechanism for monitoring the development of students’ digital and scientific empathy competencies over time. When integrated into the IGNITE competence assessment application, the results will be used by an e-assistant to recommend supplementary educational activities, such as workshops, lectures, or webinars, aligned with individual learning preferences. In this way, the empathetic questionnaire functions not only as a diagnostic tool but also as a dynamic component of an adaptive, learner-centred digital education ecosystem, suitable for culturally and educationally diverse student populations. In a similar vein, research by Kanchon et al. has shown that identifying learners’ preferred learning preferences using artificial intelligence (AI) techniques, such as analysing web-tracking logs and categorising responses, can significantly enhance the adaptation of learning content [34]. By using AI-based learning preference detection and content modification, the learning experience can be personalised to foster a more preference-responsive and engaging educational environment. This approach allows learning to be tailored to students’ specific needs, increasing the alignment with preferences and engagement in the learning process in a digital environment.

The empathetic questionnaire used in this study was specifically designed to explore students’ cognitive and metacognitive learning preferences regarding sustainable and entrepreneurial innovation. It consisted of nine multiple-choice questions, divided into two main sections. The first section focused on cognitive learning preferences, examining how students prefer to receive and engage with information visually, auditorily, through written content, or via hands-on experience. This part also addressed emotional engagement and motivation in learning contexts, particularly in relation to sustainable and entrepreneurial topics. The second section assessed metacognitive learning preferences, looking into how students structure their learning processes, their preferred pace of content delivery, and their use of digital technology and social media for learning. The responses provided insights into students’ reflective habits, their preference for sequential or contextualised content, and their interaction with online learning materials such as short videos and interactive quizzes. Data were collected through a combination of methods; invitations were sent to students via institutional mailing lists of participating HEIs, and the questionnaire was also shared on social media platforms to increase reach and participation.

Participants were recruited through convenience sampling within partner higher education institutions participating in the Erasmus+ IGNITE project. The inclusion criterion required participants to be currently enrolled in a STEAM-related higher education programme at the bachelor’s, master’s, or doctoral level. Participation was voluntary and anonymous. The questionnaire did not collect personal demographic data such as gender, age, or study level. No information on the year of study, prior e-learning experience, or prior exposure to sustainability and entrepreneurship topics was collected. The only background variable recorded was the higher education institution the participant was currently enrolled in. This decision was made to ensure anonymity and to encourage participation across institutions. Given the exploratory and descriptive nature of this study and the non-probabilistic sampling strategy, the analysis focuses on descriptive statistics rather than inferential statistical testing. Therefore, comparisons between institutions are reported cautiously, and no causal claims are made.

A total of 108 participants took part in this study, with their distribution by current higher education institution (HEI) shown in the chart below. The participants were from different HEIs across various European countries, providing broader insight into students’ learning preferences across diverse cultural and educational contexts. The distribution of participants is presented in Figure 2. The highest proportion of participants came from the University of Lorraine (27.8%), followed by students from the Norwegian University of Science and Technology (25%). A slightly smaller percentage of participants was from Polytechnic University of Catalonia (13.9%), the University of Gent (14.8%), and Jozef Stefan International Postgraduate School (18.5%). This diverse distribution of participants supports descriptive comparisons of learning preferences across institutions while acknowledging that the lack of detailed demographic and prior experience data limits broader generalisation.

Figure 2.

Distribution of survey participants by higher education institution

The chart presented in Figure 3 depicts the distribution of preferred information delivery methods among the 108 survey participants. These findings can inform the design of educational materials and instructional strategies aligned with learners’ predominant cognitive preferences. Visual learning was the most frequently preferred modality, reported by 47.2% of participants, indicating that nearly half of the respondents may favour acquiring information through graphical representations such as images, diagrams, and charts. Written learning was identified as the second most prevalent preference, selected by 26.9% of participants, suggesting a substantial inclination towards text-based materials and written explanations. Hands-on learning, preferred by 13.9% of respondents, underscores the importance of experiential, practice-oriented approaches, particularly in applied learning contexts. Auditory learning was the least preferred modality, chosen by 12% of participants, indicating that learning primarily through listening may play a comparatively smaller role among the surveyed population.

Figure 3.

Preferred methods of receiving information among students

Figure 4 illustrates the key motivational factors influencing content engagement among the 108 survey participants. The most prominent motivator, reported by 45.4% of respondents, was the perceived relevance of the content to their personal lives or future professional goals, suggesting the potential importance of practical applicability and goal-oriented learning in sustaining learner engagement. The second most influential motivational factor, selected by 27.8% of participants, was the opportunity to gain hands-on experience or actively experiment with the content, suggesting a possible role of experiential learning and active participation in fostering deeper engagement and motivation. In contrast, more narrative-based motivational elements were less influential: only 13.0% of participants identified hearing personal stories or testimonials related to the content as motivating, while 13.9% reported being motivated by reading inspiring articles and case studies. These findings suggest that, although storytelling and reflective materials may support engagement among a subset of learners, they are generally less preferred motivators than experiential and relevance-driven approaches in STEAM education.

The largest proportion of respondents (38.9%) reported the highest level of emotional engagement when they could interact with the content through practical application, suggesting the central role of experiential and hands-on learning in fostering affective involvement.

Figure 4.

Key motivators for content engagement among survey participants

Visualisation ranked second among the most influential factors, with 25.0% of participants indicating that visual representations may enhance their emotional connection, reflecting previous findings on the affective impact of visually mediated learning. Social interaction also seems to play a notable role, as 24.1% of respondents reported increased emotional connection when discussing content with others, suggesting the importance of collaborative and dialogic learning processes. These patterns may reflect key dimensions of scientific empathy, as learners appear to engage more deeply when they can relate scientific content to real-world actions, shared perspectives, and meaningful contexts.

In contrast, only 12.0% of participants indicated that deep reading of textual materials elicited the strongest emotional connection, suggesting that text-based approaches alone may be insufficient to stimulate affective engagement for most learners. These findings suggest that traditional instructional models, which predominantly rely on reading and writing, may not adequately address the emotional dimension of learning, particularly in digital and self-directed learning environments. Conversely, pedagogical approaches that integrate experiential activities, visual elements, and opportunities for social interaction may be more likely to promote both emotional and cognitive engagement. This interpretation is consistent with prior research indicating that creativity-oriented learning preferences, e.g., active idea generation and immersive engagement, can enhance learning motivation and engagement in STEAM education [35]. Accordingly, the design of preference-aligned online learning environments should consider prioritising practical, visual, and socially interactive components to strengthen emotional connection, support scientific empathy, and enable deeper learning outcomes.

Figure 5.

Factors that foster emotional connection to content

Figure 6 presents students’ preferred methods for understanding concepts related to sustainable and entrepreneurial innovation. In the context of sustainable innovation, the most frequently selected approach (37.0%) involved visual representations, suggesting the potential importance of visualisation in facilitating comprehension of complex sustainability-related systems and processes. Experiential learning through hands-on projects or experiments was identified as the second most preferred method (30.6%), reflecting the value of active engagement when exploring sustainable solutions. A smaller yet substantial proportion of participants (20.4%) preferred learning through reading articles, research papers, or case studies, indicating reliance on in-depth textual analysis. Auditory approaches, including podcasts, discussions, or presentations, were least favoured in this context (12.0%), suggesting limited preference for listening-based learning for sustainability-related topics among many respondents.

In contrast, preferences related to entrepreneurial innovation appeared to exhibit a different pattern. The most preferred method reported by participants (32.4%) was listening to expert panels or podcasts, indicating the relevance of auditory learning and real-world experiences in understanding entrepreneurial approaches to social and economic challenges. Participating in collaborative workshops or innovation labs ranked second (26.9%), suggesting the importance of interactive, practice-oriented learning environments that support teamwork, networking, and problem-solving. Visual tools, such as infographics or concept maps, were preferred by 25.0% of respondents, reflecting their continued relevance for structuring and understanding entrepreneurial frameworks. Reading case studies, research reports, or academic articles was identified as the least preferred method (15.7%), indicating that purely text-based learning may play a more limited role in this domain.

Figure 6.

Preferred learning methods for understanding sustainable innovations and exploring entrepreneurial innovation

The contrasting patterns observed between sustainable and entrepreneurial innovation can be attributed to the differing epistemic and contextual demands of these fields. Sustainable innovation often involves analysing complex environmental, technical, and systemic interactions, which benefit from visualisation and experiential learning strategies that support systems thinking. Entrepreneurial innovation, by contrast, is more closely linked to real-world practice, market dynamics, and socio-economic contexts, where learning from practitioners’ experiences and peer interaction becomes particularly valuable. Listening to experts provides access to tacit knowledge and applied insights, while workshops and collaborative activities align with the entrepreneurial emphasis on iterative problem-solving and innovation in dynamic settings.

Overall, these findings indicate that the preference-aligned design of educational content in innovation-oriented higher education should adopt differentiated pedagogical strategies. Visual and experiential approaches appear particularly well-suited to sustainability education, whereas entrepreneurial education benefits from a stronger integration of auditory, interactive, and experience-based learning methods. A balanced combination of visual, practical, and dialogic approaches is therefore essential for supporting diverse learning preferences and fostering meaningful engagement with both sustainable and entrepreneurial innovation.

Figure 7 presents participants’ preferences for approaches that help them understand and remember new material, reflecting different metacognitive learning preferences. The largest proportion of students (32.4%) prefers breaking down complicated topics into smaller, simpler steps, indicating that step-by-step learning is the most preferred method for many learners. The second most preferred approach, chosen by 31.5%, involves taking time to reflect on the material, highlighting the importance of self-reflection and processing in learning. In addition to self-reflection, self-assessment is crucial for effective learning. This can be achieved through short tests and tracking the development of competencies before and after a lecture or workshop. Such methods enable learners to evaluate their progress, identify gaps in understanding, and reinforce their learning outcomes, making the process more structured and impactful. Engaging in group discussions or hands-on activities was preferred by 21.3%, showing that some learners benefit from active application and collaboration. Lastly, 14.8% of participants favour understanding how new concepts fit into a larger context, suggesting that fewer learners prioritise a broader conceptual framework as their primary strategy.

Figure 7.

Preferred approaches for understanding and retaining new material

These findings emphasise the diversity of metacognitive learning preferences and the need to incorporate a range of approaches in educational settings to accommodate different learner preferences. The lower preference for "understanding how new concepts fit into a larger context" could stem from the fact that this approach requires broader knowledge, general awareness, and a deeper background of understanding, which learners develop over time through education and experience. Without a solid foundation of interdisciplinary knowledge and the ability to connect concepts across different domains, it can be challenging for learners to prioritise this strategy. This situation highlights the importance of fostering critical thinking, interdisciplinary learning, and broader contextual awareness throughout education to support this metacognitive approach.

Figure 8 highlights the respondents’ preferences for using digital technology and social media, such as short videos, for learning. Most respondents (34.3%) prefer videos that break down concepts into clear, sequential steps, making the content easier to follow and understand. A significant portion (26.9%) enjoys videos that first provide a quick overview, followed by detailed explanations, which helps them grasp the bigger picture and connect new information to existing knowledge. Another 25.9% prefer videos with interactive quizzes or questions throughout, keeping them engaged and facilitating real-time application of the material. Lastly, 13% prefer watching videos at a slower pace, allowing them to pause, reflect, and take notes as they learn. This distribution indicates that learners value structured, clear, and interactive content delivery when using digital media for education.

Figure 8.

Preferred use of digital media and social videos for learning

Recent research on short educational movies demonstrates that these tools can be particularly effective in conveying complex environmental problems and promoting sustainable practices [36]. The cinemetrics and psychophysiological analyses show that careful planning of frame length, colour distribution, and narrative structure can significantly enhance viewer engagement and comprehension. For example, transition points in the videos, identified through Red-Green-Blue colour statistics, align with plot climaxes and emotional peaks, guiding attention, evoking specific feelings, and reinforcing key messages about environmental protection. Colours like red emphasise tension and urgency, blue fosters trust and reflection, and green restores balance and promotes renewal. These findings highlight that, when designed thoughtfully, short videos are not only visually appealing but also powerful pedagogical tools that structure information, maintain attention, and stimulate cognitive and emotional engagement in learners, making them highly suitable for sustainability education.

Understanding the differences in learning preferences across countries is crucial when designing educational content for platforms like YouTube, Facebook, Instagram or TikTok. These platforms are increasingly used for learning, especially among younger generations, and their global reach means that content must resonate with diverse audiences. Cultural and educational contexts shape how students engage with learning materials. Adapting content to these preferences ensures greater engagement and accessibility of learning. For instance, while some cultures prioritise structured, step-by-step explanations, others may value hands-on learning or interactive elements. Moreover, differences in national skill structures and the path-dependent development of capabilities can further influence learners’ engagement and the types of skills they are likely to acquire.

Studies show that European countries exhibit substantial variation in skill portfolios, with northern and western nations tending toward socio-cognitive skills. In contrast, southern and eastern countries demonstrate comparative advantages in sensory-physical skills, and strong path dependence limits convergence across regions [37]. Additionally, students and learners from countries outside the EU often face challenges related to differences in educational systems, qualification recognition, and language barriers, which can influence their learning preferences, engagement, and ability to integrate effectively into local educational and professional contexts [38]. Addressing these factors through tailored content and support mechanisms is essential for ensuring equitable learning opportunities and skill development for third-country nationals. It implies that learners from different countries may approach, process, and prioritise content differently, reflecting not only cultural and educational traditions but also broader structural and economic conditions that shape their skills and competencies. By tailoring educational strategies to both learning preferences and these contextual skill patterns, educators and content creators can create resources that foster deeper learning, enhance skill development, and promote equitable access to knowledge across diverse global audiences.

The data presented in Figure 9 depict the distribution of preferred learning preferences – auditory, hands-on, visual, and written among students from five countries: Belgium, France, Spain, Norway, and Slovenia. Each bar represents the relative proportion of students adopting a particular learning preference, with the numerical values in each segment indicating the number of respondents selecting that option. Visual learning emerges as the predominant preference across the sample, with the highest prevalence observed in Norway, France, and Slovenia. In contrast, written learning is notably preferred in Belgium and Spain, whereas it is less prominent in Slovenia. Hands-on learning is consistently reported by a smaller fraction of students across all countries, highlighting a generally lower preference for experiential approaches in these contexts. Auditory learning has the lowest prevalence overall, with minimal representation and no respondents selecting this preference in Norway. However, a slight increase is observed in Spain, suggesting potential influences of cultural or contextual factors. The observed patterns underscore a strong inclination toward learning methods that involve visual observation and structured textual information, while the cross-country variability reflects underlying cultural, pedagogical, or systemic differences in educational practices that may shape students’ learning preferences. These findings are consistent with prior research on European skill structures, which shows that northern and western countries such as Norway, Belgium, and France tend to emphasise socio-cognitive skills, reflected in these results by the predominance of visual and written learning preferences. Conversely, in Spain, where sensory-physical skills are more prominent, students demonstrate relatively higher preferences for auditory and hands-on learning, aligning with the regional differences in skill specialisation identified in previous studies.

Figure 9.

Distribution of learning preferences among students by participating country

The next graph in Figure 10 shows the proportions of students across all five countries by their preferred methods of emotional connection to learning content. Students in Norway and Belgium feel the strongest emotional connection when they can visualise the information, indicating a preference for imagery and visual aids in learning. France, Spain and Slovenia show the highest percentages of students who emotionally connect when they can try out the material practically. This observation suggests a preference for experiential and hands-on learning in these countries. A notable proportion of students in Norway and France connect emotionally through discussions, highlighting the importance of collaborative and social learning experiences. Very few students prefer to connect emotionally through deep reading, with the highest percentage in Belgium and almost negligible levels in Spain and Norway. Practical application and visualisation are the two most preferred ways for students to feel emotionally connected to learning content across countries.

These preferences suggest the importance of engaging, hands-on tasks and visually appealing materials. Discussion-based learning plays a significant role, especially in Norway and France, where students value group interactions as a means of emotional connection. Deep reading is consistently low, indicating that written content alone is less effective at fostering an emotional bond with learning material. To emotionally engage students across diverse cultural contexts, educational resources should emphasise hands-on activities, visual aids, and opportunities for discussion and collaboration, while using deep reading sparingly as a supplementary tool. Moreover, these patterns of emotional connection and preferred learning preferences align with broader trends in the distribution of skills across European countries [37]. Northern and western nations, such as Norway, Belgium, and France, are generally characterised by stronger socio-cognitive skills, as reflected in this study by a predominance of visual and written learning, as well as emotional engagement through visualisation and discussion. Conversely, Spain, which places greater emphasis on sensory-physical skills, shows a stronger preference for hands-on and auditory learning, as well as emotional connection through practical activities. This correspondence suggests that students’ emotional engagement and cognitive processing of learning content are influenced by underlying national skill profiles, highlighting the interplay between educational culture, skill specialisation, and the development of scientific empathy through contextually appropriate learning strategies.

Figure 10.

Emotional connection to learning content by preferred method and country

The following graph in Figure 11 shows the preferred learning methods for understanding sustainable innovations among students from different countries. The numbers in the columns represent the actual count of student responses for each category in each country. For Belgian students, the preference for hands-on projects (blue, 5) and visual aids (green, 5) is evenly distributed. Fewer students chose reading articles (yellow, 4) or listening to audio-based content (red, 2). In France, visual aids (green, 10) are the most preferred, followed by reading articles (yellow, 8). Hands-on projects (blue, 9) are also popular, while listening to audio content is less favoured (red, 3). In Spain, hands-on methods (blue, 5) and visual aids (green, 6) are almost equally preferred. Reading articles (yellow, 3) is less popular, with podcasts and discussions (red, 1) receiving minimal interest. Norwegian students strongly prefer visual aids (green, 13) over any other method. Hands-on projects (blue, 7) and audio-based content (red, 5) are moderately chosen, while reading articles is the least selected (yellow, 2). In Slovenia, visual aids (green, 6) and hands-on projects (blue, 7) are almost equally significant. Articles (yellow, 5) are moderately chosen, and audio content (red, 2) is less favoured.

Visual aids (green) are consistently among the top preferences across all countries, particularly in Norway, Spain and France. Hands-on projects (blue) are highly favoured, especially in France, Spain and Slovenia, indicating the importance of practical engagement in learning about sustainable innovations. Listening to podcasts and discussions (red) is the least chosen method across all countries, suggesting this mode of learning is less preferred for students in this context. Reading articles and case studies (yellow) is moderately popular but generally ranks below visual and hands-on methods. These patterns align with recent findings in sustainability education, which show that visual and hands-on methods support a systemic understanding of complex socio-environmental issues and foster scientific empathy, enabling students to consider the consequences of actions for diverse stakeholders [33]. Incorporating interactive visuals and practical, hands-on experiences provides diverse pathways for engaging different cognitive and metacognitive learning preferences, enhancing comprehension, critical thinking, and empathetic reasoning in sustainability contexts [15]. Thus, the observed preferences suggest that educational content designed for international audiences should combine visual, experiential, and collaborative approaches to preference-aligned support both cognitive understanding and emotional engagement with sustainability challenges.

Figure 11.

Preferred learning methods for understanding sustainable innovations among students by country

The graph in Figure 12 presents the preferred learning methods for exploring entrepreneurial innovation among students from five countries. The numbers within the columns indicate the actual count of student responses for each category in each country. Belgian students value visual methods and listening to expert discussions in the context of entrepreneurial innovation. Case studies (4 responses) are slightly less popular, while workshops (2 responses) are the least favoured. The most preferred method in France is podcast (10 responses). Both visual aids and case studies are equally popular (7 responses each), while workshops (3 responses) are the least favoured. Spanish students prefer practical and visual methods, while reading case studies does not appeal to them at all. Workshops (6 responses) and visual aids (6 responses) are equally favoured, while podcasts (3 responses) are moderately preferred. Norwegian students have a strong preference for hands-on and interactive learning, with less interest in traditional reading materials. Most students favour podcasts (12 responses), followed by workshops (7 responses). Visual aids (6 responses) are moderately preferred, while case studies (2 responses) are the least favoured. Slovenian students have a balanced preference for most methods, with workshops slightly leading. However, visual aids are less appealing.

Workshops (red) are a popular learning method overall, particularly in Spain and Norway, highlighting the importance of interactive, hands-on approaches. Visual aids (green) are favoured in Belgium and Spain but are less popular in Slovenia. Podcasts (blue) are notably popular in France and Norway, but are less preferred in Spain. Case studies (yellow) are the least popular overall, except in Slovenia, where they are moderately appreciated. The graph shows that students generally prefer interactive, practical learning methods, such as workshops, across most countries. Traditional approaches like reading case studies or journal articles are less appealing, particularly in Spain and Norway, suggesting the need for more engaging or innovative methods to attract students. The data also reflect regional preferences, with visual and auditory methods (e.g., podcasts) varying in popularity across countries.

Figure 12.

Preferred learning methods for exploring entrepreneurial innovation among students by country

Educational programs aimed at fostering entrepreneurial innovation should focus on interactive workshops and visual tools to actively engage students. While podcasts have potential, traditional reading materials might need to be supplemented with more engaging formats to appeal to students across all countries.

Figure 13 illustrates students’ preferences in participating countries regarding the use of digital media and videos for learning. The vertical bars represent the number of students in each country who prefer specific video-based learning, with different colours indicating different approaches. Green preference (a slower pace with time to pause and reflect) is consistent but not highly popular across countries, showing similar numbers. Videos incorporating interactive quizzes or questions (yellow) are most preferred by students in France (9). Norway, Spain and Slovenia show moderate interest. The red approach (clear, sequential steps) is a leading choice among students in France (10), Norway (10), and Slovenia (9). Spain (3) and Belgium (5) exhibit a slightly lower preference, though it is still significant. Videos that provide an overview first and then go into detail (blue) are particularly preferred in Norway (9) and France (9). Spain (3), Slovenia (4), and Belgium (4) show less interest in this approach.

The data show that videos breaking down concepts into clear, sequential steps (red) are the most favoured approach across several countries, particularly in Spain, Norway, and Slovenia. Interactive videos with quizzes (yellow) and videos offering a quick overview followed by details (blue) are also quite popular in most regions, reflecting an emphasis on engagement and structured content delivery. On the other hand, videos presented at a slower pace (green) have consistently lower appeal across all surveyed countries except Spain. This result indicates a preference for dynamic, interactive, and well-structured video content for learning purposes.

Figure 13.

Preferred use of digital media and social videos for learning among students from different countries

The results of this study suggest that visual learning is a dominant cognitive learning preference among participants, with 47.2% preferring methods such as diagrams, charts, and infographics to process information. Additionally, 33.3% of students indicated diagrams and charts as the most helpful tools for learning new concepts. These findings suggest the value of clarity, organisation, and the rapid comprehension of complex ideas through visual representations. Visual learning may support cognitive processing by reducing cognitive load, enhancing retention, and facilitating the understanding of abstract or complex topics.

Sequential learning appeared as the most prevalent metacognitive learning preference, with 32.4% of participants favouring the breakdown of complex topics into smaller, structured steps. Similarly, 34.3% preferred video materials that present information in clear, sequential stages. This observation may indicate a preference for structured and logical approaches to understanding and retaining new material. Sequential learning can provide learners with a systematic framework for incremental progress, ensuring clarity and reducing cognitive strain when processing complex information.

The study also suggests that the subject matter may influence learning preferences. For sustainable innovation, students tended to prefer visual and practical methods that supported understanding of environmental systems and interrelated processes. In contrast, entrepreneurial innovation appeared to benefit more from auditory and experiential approaches, indicating the importance of real-world practice, market dynamics, and peer interaction. These findings suggest that pedagogy might be optimised by aligning learning strategies with the subject’s characteristics and demands while combining structured, visual, and experiential elements to enhance both cognitive and affective engagement, potentially.

Despite the widespread popularity of visual and sequential learning preferences among participants, extensive literature questions the effectiveness of rigidly assigning students to specific learning preferences. Research indicates that labelling learners as visual, auditory, or hands-on primarily affects perceptions of intelligence and ability rather than actual learning outcomes, highlighting the risk of neuromyths [39]. Newton and Miah note that although most educators believe in the utility of learning preferences, only about one-third actively apply them in practice, suggesting that pedagogical strategies grounded in evidence may be more impactful than adherence to preference categorisations [32]. Hattie and Leary further emphasise that while learning preferences remain attractive due to their simplicity and the sense of individualised instruction, the research consensus favours adaptable strategies that cultivate critical thinking, self-regulation, and problem-solving over tailoring instruction to presumed learning preferences [40].

As Robert Loo suggests, educators should employ a variety of learning methods and encourage students to remain open to different strategies [41]. This flexibility can allow for a more personalised and inclusive learning experience. Integrating flexible learning strategies alongside awareness of student preferences may therefore be essential. Evidence shows that while learners with converger and assimilator tendencies might respond positively to structured and visual approaches, diverger and accommodator learners may benefit more from collaborative, experiential, and hands-on activities. This study supports these insights by suggesting that visual and sequential methods appear to enhance comprehension and retention, particularly for sustainable innovation, whereas entrepreneurial innovation may benefit from auditory and experiential strategies, such as workshops, discussions, and real-world case analysis.

By combining structured visual methods with opportunities for active experimentation, reflection, and social interaction, educators can create more inclusive, adaptable, and preference-aligned learning experiences. Such approaches may not only enhance cognitive understanding but also foster scientific empathy, allowing learners to connect with complex socio-environmental systems, consider the consequences of actions for diverse stakeholders, and engage meaningfully with sustainability challenges. This alignment of evidence-based strategies with learning preferences suggests support for the development of both cognitive and affective skills in STEAM contexts, potentially promoting innovative, reflective, and responsible decision-making.

Cross-cultural research suggests that students’ learning preferences may be influenced not only by individual cognitive preferences but also by cultural contexts. Studies using Kolb’s Learning Preference Inventory and frameworks [27], [42] such as the GLOBE study indicate that cultural dimensions, such as collectivism, uncertainty avoidance, future orientation, and gender egalitarianism, may play a role in shaping whether learners prefer abstract conceptualisation, reflective observation, or active experimentation [43]. Similarly, empirical analyses of cross-cultural differences in learning preference suggest that specific cultures may be associated with distinct learning preferences and abilities, indicating that cultural background can guide how students approach learning tasks [44]. While some universal tendencies exist, such as the appreciation of visual aids and structured explanations, the emphasis on collaborative, hands-on versus structured, analytical learning may vary across nations. In addition, employers in different countries have varying expectations regarding the competencies students should possess, including sustainability and innovation skills, which further influence the skills that students need to develop during the education process [45]. Recognising these cultural and economic patterns is crucial for designing educational materials and digital learning content that are preference-aligned, relevant, and engaging for international audiences, while accommodating diverse ways of processing, reflecting, and applying knowledge.

Building on this theoretical background, the present study’s findings provide insight into how cultural tendencies may manifest in specific European contexts. The findings also suggest that while visual aids and structured explanations are universally appreciated, there are clear cultural differences in how students prefer to learn. Countries like France and Norway appear to emphasise collaborative, hands-on learning, whereas Belgium and Spain may lean more towards structured and interactive formats. Slovenia, with its balanced preferences, reflects the value of integrating multiple methods to cater to diverse needs. Recognising these cultural nuances may be essential for creating educational content that resonates with international audiences. This approach is especially relevant when considering global social media platforms like YouTube, Facebook and TikTok, where educational content must appeal to diverse learner preferences. Tailoring content to different cultural and educational contexts enhances engagement, promotes scientific empathy, and supports preference-aligned learning outcomes, particularly for sustainability and innovation education.

These findings are particularly important in the context of internationalised higher education. Given that most HEIs include international students from diverse cultural backgrounds, learning materials must integrate elements that accommodate a range of cognitive and metacognitive preferences. This trend is particularly important for digital learning materials, which are accessible worldwide to learners with diverse cultural and educational backgrounds. The study suggests that preferences for different approaches to learning new concepts vary across EU countries, reflecting broader regional patterns in skill portfolios, with northern and western nations demonstrating stronger socio-cognitive skills (visual and written learning) and southern countries showing comparatively higher sensory-physical skills (hands-on and auditory learning). These patterns highlight the potential need for culturally sensitive learning approaches that combine visual, experiential, and collaborative methods to support preference-aligned, inclusive, and empathetic education.

However, cultural dimensions alone cannot fully account for the observed differences. Several factors may explain the observed differences in learning preferences among students from different countries. Cultural dimensions such as individualism vs. collectivism, uncertainty avoidance, and power distance can shape how students approach learning tasks and interact with peers and instructors, thereby influencing their preferences for collaborative, hands-on, or structured learning [46]. However, comparative research indicates that learning preferences cannot be explained by culture alone, but are shaped by complex interactions between educational context, disciplinary background, institutional practices, and students’ developmental stage [47]. Learning patterns are also not fixed but adaptable; students’ strategies, conceptions, and orientations may change in response to instructional design, assessment methods, and the broader learning environment. This observation suggests that well-designed learning environments can foster more constructive and self-regulated learning approaches regardless of cultural background. Therefore, the differences observed between countries in the present study should be interpreted as context-dependent tendencies rather than static cultural traits.

In addition to cultural and pedagogical influences, structural and socio-economic factors may further shape learning preferences. Exposure to technology and digital learning tools, as well as prior experience with sustainability and entrepreneurship topics, could further shape students’ engagement and preferred learning modalities. Socio-economic factors and the pedagogical culture within each HEI may also influence whether students favour visual, auditory, or experiential learning, reflecting both institutional practices and broader cultural norms [48]. Differences in access to educational resources, parental educational background, and levels of academic support may further contribute to variation in cognitive development, self-efficacy, and learning strategies. Students from lower socio-economic backgrounds may experience additional stressors related to financial insecurity or limited access to technology, which can affect concentration, motivation, and adaptability in learning environments. At the same time, disparities in education funding, teacher practices, and peer academic culture across institutions and countries may shape students’ expectations, participation patterns, and responsiveness to different instructional formats. Finally, the intersection of cultural norms and socio-economic conditions may produce unique learning adaptations, meaning that observed differences in this study likely reflect a combined effect of cultural, structural, institutional, and psychological factors rather than any single explanatory variable.

Given these multiple interacting influences, it is also important to clarify the methodological positioning of the present research. This study was designed as an exploratory and descriptive investigation of students’ learning preferences across multiple European higher education institutions. Given the use of a convenience sampling approach and the non-probabilistic nature of the sample, the primary aim was to provide a descriptive overview rather than to test causal relationships or statistically significant differences between countries, topics, or institutions. Consequently, the results are reported using percentages and figures, and comparative interpretations are presented cautiously. The study is therefore positioned as a descriptive exploration of learning preferences rather than a comparative study that relies on inferential statistics. This limitation suggests that the findings should be interpreted with caution, and future research could expand the study by using larger, probabilistic samples, including additional demographic variables (e.g. gender, age, study level, past experiences), and applying inferential statistical methods. Such an extension would allow for more robust comparisons across countries, HEIs, and topics, enhancing the generalisability and explanatory power of the results.