Applicability of Education 4.0 in higher education: Engineering students’ survey


Eva Beke* , Andrea Tick

Óbuda University (Hungary)

Received July 2022

Accepted January 2024


The purpose of the study is to examine how Industry 4.0, and the digital environment, have together created a new situation for companies and universities in terms of soft skills for employability. While companies aim to introduce a new structure, universities try to align with these changes by developing new educational methods, curricula, and models. Many researches are focusing on – rightfully so – Industry 4.0 skills and competences to gain throughout higher education. However, we have shifted our research interest and asked students to what degree their university years added to their knowledge, self‑management and skills. 147 engineering and technical manager students’ responses from two faculties at Óbuda University, Hungary were analyzed to see their evaluations of the role of the university in the framework of Education 4.0, and their chances in the job market. Quantitative and CHAID analyses were used. Students’ responses show significant differences between the two faculties regarding languages, teamwork, self-management and in the different order of the skills seen as most paramount to employability. Engineering students attach greater importance to field-relevant knowledge, while technical manager students find decision-making more useful. The research proved that Education 4.0 is here and Z generation studying at universities prefers problem-based learning, including creativity, analytical, and critical thinking while would like to have good communication skills. Universities need to adapt to these changes and integrate hard as well as soft skills development in tutoring. The importance of technical-IT knowledge is just as important as having interpersonal skills, excellence in problem-solving, so students need to be taught how to analyze problems, engage in scientific debate, or express themselves clearly as previous literature indicated.


Keywords – CHAID analysis, Education 4.0, Industry 4.0, Skills for employability.

To cite this article:

Beke, E. & Tick, A. (2024). Applicability of Education 4.0 in higher education: Engineering students’ survey. Journal of Technology and Science Education, 14(2), 529-552.



    1. 1. Introduction

Since Industry 4.0 has paved the way for artificial intelligence, a much more autonomous supply chain, collaborative work, and the consequent digitization of connected systems, we are now living in a globally linked world characterized by a rapidly changing working environment, robotized manufacturing, and artificial intelligence used by numerous fields. Based on the World Economic Forum Survey, “41% of surveyed companies plan to expand their use of contractors for task-specialized work, only 34% plan to expand their own workforce due to technology integration.” (World Economic Forum, 2020: page 5).

In parallel with COVID-19, fully connected automation systems create a completely new situation for students, universities, and companies as well. Many universities will change their structure and workforce due to the rapid change of new technologies while trying to adhere to these changes and introduce new curricula, methodologies, and structures. Skills gaps remain high, as demand for new job skills is set to change over the next five years. Key competences include critical and analytical thinking, problem-solving and self-management skills, life-long learning, perseverance, and flexibility (Hecklau, Galeitzke, Flachs & Kohl, 2016; Nelson, Martindale, McBrid, Checkland & Hodgson, 2018). Companies estimate that about 40% of employees will need retraining in six months or less, and 94% of business executives say employees are expected to acquire new skills in the workplace to keep up with technological advances and retain their jobs (Manjunath, Shravan & Dechakka, 2019).

This paper includes the analyses of data from 147 student surveys to understand how students evaluate the role of their university education within the framework of Education 4.0 as well as their acquired skills in the changing job market as new graduates. The paper is organized as follows. After the introduction, relevant literature is reviewed. Then after presenting the data and methodology, the results are detailed. Findings are followed by a discussion and finally, the limitations and future research possibilities are given in the conclusion section.

2. Literature Review

The effects of Industry 4.0 cannot be discussed without considering its effects on education, as the primary custodians of professional education for skilled and trained employees are the educational institutions (Paisey & Pasey, 2018). To keep up with technological-industrial advances, universities must change their curricula, and the structure and model of their teaching, and include more practical elements in their courses (Cranfield, Tick, Venter, Blignaut & Renaud, 2021; Fitsilis, Tsoutsa & Gerogiannis, 2018; Valero, 2022). Digital transformation is a more recent academic concept, driven primarily by the COVID‑19 pandemic, although it is rooted in previous theories of IT-enabled change (Besson & Rowe, 2012). Recent studies suggest that digital transformation is not only a demand but a process of extensive, systematic change that appears through the integration of various technologies and inherently redefines institutional attitude and identity (Trenerry, Chang, Wang, Suhaila, Lim, Lu et al., 2021). All these changes and the main features and framework have collectively been termed Education 4.0 (Afrianto, 2018). Companies and other industry stakeholders with strong information and technology infrastructures require advanced digital technology knowledge and skills, which are described as 21st century skills (Ghafar, 2020). According to the European Union Digital Competence Framework,

“digital competence comprises the following dimensions: (a) information and data literacy that allows people to locate, retrieve, store, manage, and organize digital data, information, and content; (b) communication and collaboration through digital technologies; (c) digital content creation and knowledge about giving the right instructions to a computer system; (d) identity and security management of devices, content, personal data, and privacy protection in digital environments; and (e) the ability to solve conceptual problems and unsettled situations in digital environments” (Carretero, Vuorikari & Punie, 2018: pages 11-13).

3. Education 4.0

Education 4.0 is a reflection of the Industry 4.0 era (Beke, Horváth & Takacs-Gyorgy, 2020) and refers to a period in which educational paradigms, approaches, curricula, and technologies are changing (Kamaruzaman, Hamid, Mutalib & Rasul, 2019). There is continuously growing demand for personalized and adaptive learning (Tick, 2019), blended learning courses, and practical learning methods (Ciolacu, Tehrani, Binder & Svasta, 2018). Online and later blended learning types of teaching became especially crucial because of the COVID19 outbreak, which affected every region and most, if not all educational institutions worldwide. Higher education institutions faced a rather challenging situation where they had to make prompt decisions regarding policies, access to the internet and online materials, continuing education, and ongoing evaluation and monitoring (Vlachopoulos, 2020). The pandemic was also a warning signal to have students prepared with Information and Communication Technologies (ICT) and collaborative skills and educate them to remain interested in life-long learning (Hirschi, 2017). This technological-digital shift affects profoundly not only education but future employees and business structures as well: knowledge and talent replace raw materials and capital and become the most competitive assets (Bartram, 2005; Pásztor, 2021). Implementing strategic workforce planning and talent management can give each organization a more agile approach and a new dynamic for progress and development (de Lucas-Ancillo, del Val-Núñez & Gavrila, 2020).

Education 4.0 is considered a new paradigm that reinterprets concepts such as learning, student, teacher, and school according to the needs of Industry 4.0 (Benešová & Tupa, 2017; Tick & Beke, 2021). Harkins (2018) called Education 4.0 an innovation producing process, where concepts like content, technology, teaching, schools, and teacher have been redefined. Based on the OECD recommendations, the main features of Education 4.0 can be summarized as follows (Asian Society/OECD, 2018):

“When today’s students enter the world of work, they will be working with the world itself. … To be effective participants in this increasingly complex, diverse, and interdependent global economy, students will need to be highly literate and able to analyze situations and solve novel problems in creative ways. They will need to be knowledgeable about issues of global significance in areas such as engineering, business, science, history, politics, and the environment. Students also will need to be comfortable in unfamiliar settings and willing to learn from others… Preparing today’s students to live and thrive in this increasingly interdependent world, characterized by international markets, unprecedented migration of peoples, growing economic inequalities, increasing ethnic and religious tensions and violence, and massive changes in the environment will require the transformation of education.” (pp. 10-11)

3.1. Competences in Education 4.0

Gómez, Redondo and López (2018) emphasized the need to orient students to the professional world throughout higher education and educate them so that their skills match with industry demand. They noted that the European business community requires a range of personal attributes in addition to university degrees that would allow graduates to be integrated faster into working environments and cultures. Duarte and Rodriguez (2021) noted that for digital competences in university settings, there are definitions to clarify them. Examples include instant communication, which means interacting with the teachers through digital technologies, and problem-solving, which refers not only to identifying a problem but to proposing solutions as well. Content creation involves editing and creating digital content and class activities that involve engagement with digital skills (Aberšek, 2017; Duarte & Rodriguez, 2021).

Furthermore, Diwan (2017) listed all those competences with which today’s students will be able to gain employability and success in their future work. He calls them “future specializations” (Diwan, 2017, para 12). They include financial analysis and technology, business analytics, digital marketing, supply chain and e-commerce related skills (Sánchez-Ramírez, Íñigo-Mendoza, Marcano-Lárez & Romero-García, 2022). Graduates need the ability to understand skills associated with future specializations and to interpret data. Strong, Burkholder, Solberg, Stellmack, Presson and Seitz (2020) surveyed 25,000 students, faculty, staff, and employers across more than 30 countries. Their results showed consistency in critical competences and show many similarities with the present research in terms of industry-needed competences (Hebles, Yániz-Álvarez & Alonso-Dos-Santos, 2022). These include decision-making, communication, problem-solving and analysis, participating in teamwork, and self-management. They concluded that regardless of the job type the critical competences are consistent across industries.

In summary, the basic components of Education 4.0 are highlighted in Figure 1.


Figure 1. Basics of Education 4.0 (Kozák, Ruzicky, Stefanovic & Schindler, 2018)

3.2. Job Skills for 2050

The World Economic Forum (2020) identified the top 10 job skills for 2050. These 10 skills can be grouped into four categories that include (a) problem-solving, (b) self-management, (c) working with people and (d) technology use and development. These skills within the four groups are presented in Figure 2. The numbers denote the place of the job skills in the ranked list. As Figure 2 presents, four out of the first five skills are problem-solving skills, the sixth top skill is related to working with people and two-two skills are grouped under technology use and development and self-management, respectively.


Figure 2. Types of top 10 job skills by the WEF in 2020 (World Economic Forum, 2020)

Szabó and Bartal (2020) found that most Hungarian and Russian students agreed with the top 5 skills based on World Economic Forum research; however, the authors suggested new methods and structure of teaching required to motivate and engage Generation Z students. Consistent with the expected demand, Bonfield, Salter, Longmuir, Benson and Adachi (2020) recommended courses be added to the curriculum, such as Industrial Internet of Things for Advanced Manufacturing, Managing a Smart City with Business Intelligence (data science), Introduction to 3D Printing, Machine Learning, Robotics and Automation, and Intelligent Sensors, which all belong to the group of skills related to technology use and development.

There are several research studies examining students’ perceptions of current skills studying at various faculties (Yelkikalan, Hacioglu, Kiray, Ezilmez, Soylemezoglu, Cetin et al., 2012). Yelikalan et al. in their research have not found any significant differences between students’ perception of emotional intelligence apart from sociability. Patrik in their 2020 survey claimed that subtle perception differences among the faculties became apparent when they asked students about active learning possibilities and teaching reform (Patrik, 2020). Kalkan in his 2020 research investigated students’ views – studying at different departments – about e-learning readiness as far as computer efficacy and online communication skills are concerned among other skills (Kalkan, 2020). He has concluded that there are differences between faculties as those who have English language skills are more effective users of computer and online communication skills than those without language knowledge (Kalkan, 2020).

Based on the literature reviewed, the concept of Education 4.0 in the light of required industry competences, and the digital competences discussed, the following conceptional framework was developed and is depicted in Figure 3. The basic components and competences in Education 4.0 call for delivering knowledge strongly focusing on specialization while the training of hard as well as soft skills are brought to the focus as well. The four groups of job skills in Figure 2 require active learning leading to practice-oriented education including new forms and new methodologies, for instance, digital online learning or problem-based learning etc. Self-management as well as skills for effective collaboration with people require good communication and networking skills which can be developed through international experience.

Figure 3. Conceptual framework of the present research

4. Purpose of the Study and Hypotheses

The primary research goal was to shed light on the skills engineering and technical management students at a university in Hungary identified as important for their future careers, which of these skills they regard essential to be taught, trained, and developed at the university and which skills students can improve the most during international studies, and scholarships. Finally, the study aimed to analyze how engineering and technical management students differ in their attitudes to such skills. In our study we refer soft skills as a person’s interpersonal, social and communication abilities. Soft skills include teamwork, adaptability, problem-solving, creativity, empathy, conflict resolution. It often can be a deciding factor in hiring especially in careers require interaction with professionals (Teng, Ma, Pahlevan‑Sharif & Turner, 2019).

Based on the literature review the following hypotheses were formulated:

H1. Engineering and Technical management students have different priorities regarding necessary soft skills and competences.

H2. Engineering students, opposite to technical management students find different skills important for their future career.

H3. Engineering and technical management students have different expectations from higher educational training.

4.1. Participants

Participant of the research were undergraduate students in their second year of studies registered at a Hungarian University. A purposive, non-probability sampling strategy was applied, and a cross-sectional survey design was employed. The present study is part of a wider scale research project that beyond surveying the digital competences of students needed for employability skills, the competences of lecturers as well as students’ expectation of the labor market was also surveyed. Second year university students were the target population, as first year students are new in their higher education studies and have other prioritizes than focusing on employability skills at the beginning of their studies. Third year students, on the other hand, are already employed in large numbers and focus on gaining knowledge for their specialization. Participants’ consent to take part in the survey was obtained and 165 students filled in the questionnaire, out of which 147 responses could be analyzed. It must be noted that in this study the primary focus was on the orientation of the students rather than on their gender.

4.2. Procedures

The research was carried out in 2019 and 2021, partly during the lockdown due to the pandemic. A self‑administered questionnaire was employed at one faculty via an internet google survey (in Hungarian and English as well). The questionnaire was distributed among students of the two faculties at the participating university in Hungary. At the Engineering faculty, the survey was conducted paper-based in classrooms, where students were given 10-15 minutes to reply. At the Business and Management faculty, an online format was used because of COVID-19 regulation of distant learning and teaching. No special ethical approval was required by the university. Students were invited via email or were asked for their consent to participate in the study. Participants were informed about consent under the European Union Law on the Protection of Personal Data. Anonymity was ensured, and the responses were automatically recorded in an online database or were given directly to the researchers in paper format.

4.3. Instrumentation

The initial survey questions were decided after a literature review process (Aberšek, 2017; Diwan, 2017; Duarte & Rodriguez, 2021; Gómez et al., 2018; Hecklau et al., 2016; Nelson et al., 2018; Strong et al., 2020) and the results of 22 deep interviews with industry representatives in Hungary regarding their views and opinions about needed employability skills and digital competences (Beke & Kelemen-Erdős, 2021). The selection of questions is also supported by the top 10 job skills identified by the World Economic Forum (2020). The survey questions were to explore which skills students considered the most important during their studies, and which ones they thought needed to be trained the most. Therefore, content validity was ensured based on the interviews, a through content analysis, and the top 10 job skills by WEF (2020). The following skills were included in the survey: (1) creativity, (2) technical and IT preparedness, (3) problem solving, (4) learning decision making techniques, (5) analytical thinking and skills, (6) communication skills, (7) participation in teamwork, (8) knowledge gained in relation to specialization, (9) technical and mathematical knowledge, (10) foreign language skills and knowledge, and (11) self-management. Since the research aimed to identify the skills and competences students find important for their future careers, they were invited to pick the three most relevant ones to compare their views with previous findings. Finally, students rated their experiences during their studies abroad. In most of the questions, students were asked to select the three most important aspects.

The researchers surveyed more general skills applicable to numerous positions and industries rather than very field-specific, often unique expertise. This decision was based on the fact, that the authors surveyed two different faculties with diverse orientations.

The following questions were posed to the students:

  1. 1.Skills development: In your opinion, which skills development are the most important during your university years? 

    The response option included all the 11 skills listed previously and students were asked to select the three most important ones that apply to them. 

  2. 2.Competences developed through international studies: Why do you consider the experience gained during your studies abroad to be important?  

    Seven, mainly soft skills were listed that students could select from. These options were (1) it improves language skills and communication in a foreign language, (2) it extends networking and networks, (3) it develops adaption skills to international norms, (4) it gets to know foreign culture, mindset, and mentality, (5) it creates a possibility of new research platforms and projects, (6) it gives a new approach to structure and interpreting learning material (7) it is easier to accept otherness. Students were asked to select the three most important ones that apply to them. 

  3. 3.Future career options: In your opinion, what does the employment success of graduates depend on? 

    The response options included soft skills as well, which are built into the conceptual framework, therefore the question was analyzed in the study. The response options were: (1) on knowledge gained at the university, (2) on the stable foreign language knowledge (3) on the professional devotion of students, (4) on the excellent network, (5) on the network built during the university years, (6) on individual talents and skills, (7) on the current labor market requirements, out of which the three most important ones were selected by the respondents. 

  4. 4.Higher education’s contribution: In your opinion, to what extent has your higher education contributed to the knowledge, experience and self-awareness you have acquired in recent years? 

    The response alternatives were seven statements, which are (1) knowledge related to future workplace and job, (2) being able to write and present clearly and precisely, (3) ability to use computers and other information technologies, (4) analyzing quantitative problems, (5) work effectively and efficiently in teams, (6) better understanding of yourself and your own aims and (7) better understanding of the people around you. 

The response options ranged from 1=fully to 4=not at all. To check the reliability of the statements measured on the 4-point Likert scale Cronbach’s alpha was used. It equaled 0.726, which means high reliability of the question group (Taber, 2018). Deleting any of the items would decrease reliability.

5. Data Analysis

The study used SPSS V25 for quantitative analysis and MS Excel and SPSS V25 were used for data visualization. After descriptive analysis to determine the skills and competences that students find important, contingency analysis using CHI2 test was conducted to reveal significant differences between the faculties two-sided tests were used.

For confirmative analysis the CHI-squared Automatic Interaction Detector (CHAID) decision tree segmentation and visualization was used to confirm and interpret the significant differences between engineering and technical management students. CHAID is a multivariable recursive classification process that allows a segmentation process in case of categorical data as well. (Dudás, 2018; Hámori, 2001; Kass, 1980; Mai & Tick, 2021). The decision tree, which uses CHI2 tests for splitting is applied because it provides a visual representation of the questions along which engineering and technical management students’ approach to skills for employability significantly differ. The target variable was set to the engineering faculty and all the questions analyzed in the paper were included as independent variables. As there are no restrictions on the measuring scale of the variables and their distribution, which is an advantage of the method, both categorical and numerical data could be loaded. In this research the response options were categorical, or students could rate statements on a Likert scale ranging from 1-4. Splitting in the tree is conducted by CHI2 tests, the algorithm first unifies the categories that are the least different concerning the selected questions and then splits according to the strength of the faculty. At each level the node highlights which faculty is more dominant, which means the splitting question is more characteristic of the students of that specific faculty. When the algorithm finds an optimal tree depth and no relevant changes would happen in the segments, it terminates. The Exhaustive CHAID method is different from CHAID since non stopping criterion is defined. The splitting variables are used to characterize the different approaches of students to the relevant competences, and their attitudes on what they expect more from higher education skills, competences, or specialized knowledge. The SPSS program was used for growing the tree.

After the survey, the collected data were cleaned to retain only properly answered papers for further analysis. Out of a total number of 165 responses participants have been excluded based on the following criteria:

  1. 1.they did not respond on time; 

  2. 2.they chose more answers than they were asked to do;  

  3. 3.they have not responded to all the questions, or have not responded at all. 

The analysis of the data focused on the three hypotheses formulated including the foreign language practices and the acknowledged need for students in an international working environment. The following sections present the results of the survey and will discuss the implications and limitations.

5.1. Demographic Profile of the Participants

The participating students are students at the same university; however, they are students of two different faculties, the engineering faculty, and the business and management faculty. Almost two-thirds of the students (65.3%) are enrolled in Mechanical and Safety Engineering degrees while 34.7% of them are Technical Management students. All of them are between 19-22 years old. Of the engineering students, 98% were male 2% female, while at the business faculty, 62.7% of females and 37.3% of males participated in this study. The males are over-represented in the engineering faculty, while the male -female ratio is more balanced in the technical management course. Table 1 describes the characteristics of the participants.



Percentage (%)


Engineering (Mechanical and Safety Engineering)

Business and Management (Technical Management)







Engineering faculty





Business and Management faculty





Table 1. Demographic profile of participating students

6. Results

The section presents the results and findings on the research questions and hypotheses. The questions were first analyzed based on the responses of all the participating students, then the significant differences between the faculties were tested.

6.1. Skill Development for Employability

According to hypothesis 1 engineering and technical management students have different priorities regarding soft skills and competences.

The first question asked students to select the training of which skills they prioritize during their university studies. Figure 4 presents what percentage of students selected the different skills. The top three skills selected by the students were Problem Solving (66.7%), Communication Skills (29.9%) and Knowledge Gained in Relation to Specialization (51.7). Students found Self-Management (8.2%) and Analytical Thinking and Skills (13.6%) to be the least important.


Figure 4. The most important skills during the academic years (% distribution)

Table 2 shows the similarities and differences grouped by the faculties. Skills such as Problem Solving (66.7% at both faculties) and Knowledge Gained in Relation to Specialization (58.3% at Engineering and 39.2% at business and management faculty) were among the top three choices at both faculties. Decision‑Making Techniques at business and management faculty (37.3%) and Technical and IT preparedness (30.2%) at engineering faculty came third in student choice. While Communication Skills were among the top three skills to be trained at the university, separately the two groups did not select this specific type of training among the top three ones. It came third for technical management students while Technical and IT preparedness was more important for engineering students.

Communication skills (35.3%) came fourth in the ranking by students at the business faculty while there was a tie for Technical and Mathematical Knowledge and Communication Skills at engineering faculty (27,1%). The least important for students at the engineering faculty was Self-Management (93.8% did not select) and interestingly the fewest number of business management students marked Foreign Language Skills and Knowledge (90.2% did not select) with a tie for Technical and Mathematical Knowledge (90.2% did not select).

The training of which skills do you think is the most
important during academic studies?









problem solving




knowledge gained in relation to specialization




communication skills




technical and IT preparedness




learning decision making techniques




participation in teamwork








technical and mathematical knowledge




foreign language skills and knowledge




analytical thinking and skills








Table 2. Similarities and differences between the faculties

When comparing the preferences of the students from the two faculties it was found that a significant difference was found in specific skills related to their main studies (CHI2 = 27.24, p = 0.004) (Table 2).

The four skills that showed a significant difference among the participating students from the two faculties were choices 4, 5, 8 and 9 (see Table 3). Students at the engineering faculty rather selected Knowledge Gained in Relation to Specialization (p=0.027) and Technical and Mathematical Knowledge (p=0.015) while more students at the business faculty chose the options Learning Decision-Making Skills (p=0.005) and Analytical Skills (p=0.04) which can be attributed to the special knowledge students need for their profession. Apart from these skills students find similarly important the training of all the other skills.

The training of which skills do you
think is the most important during
the academic studies?






4. learning decision making techniques



5. analytical thinking and skills



8. knowledge gained in relation to specialization



9. technical and mathematical knowledge



*: p < 0.05.

Tests are adjusted for all pairwise comparisons using the Bonferroni correction.

Table 3. Skills where significant differences were detected between the faculties

6.2. Internationalization to Support Career Success

Special attention is being paid to the internationalization at the faculties of the participating university, whether the experience relays on foreign students studying here with a Hungarian state-funded scholarship – Stipendium Hungaricum – or Hungarian students finishing courses abroad with a European funded scholarship – Erasmus – program. The authors found important to emphasize the training of language skills as a lot of companies’ value foreign students arriving from less developed, low or middle-income countries outside the EU studying under the Hungarian state-funded scholarship.

“This scholarship is considered to be the most prestigious higher education scholarship program of the Hungarian Government that offers a wide range of courses for international students with an excellent academic track records. The scholarship aims to support the internationalization of Hungarian higher education and its constant development, to strengthen the international relations of the academic and research community, and to promote the good reputation and competitiveness of Hungarian higher education throughout the world.” (Stipendium Hungaricum, 2022: page 1.)

The response options of the question related to the development of skills and competences abroad. In general, 84.6% of the responding students agreed that studying abroad improves their Language Skills and more than half of the students (53.1%) found Network Building important (Table 4). Furthermore, the development of Adaption Skills to different cultures also overcome factors like Knowing a Foreign Culture, or to Accept Otherness, 45.5% of the students fund it as one of the three most important benefits of foreign studies.

Why do you consider your experiences with Erasmus
or Stipendium Hungaricum scholarship important?


n %





improves language skills and communication in a foreign language




to extend networking and networks




developing adaption skills to international norms




get to know foreign culture, mindset, and mentality




possibility of new research platforms and projects




a new approach to structure and interpreting learning material




it is easier to accept otherness




Significance level for * <0.05.

a. Tests are adjusted for all pairwise comparisons using the Bonferroni correction.

Table 4. Importance of foreign experiences: Erasmus – Stipendium Hungaricum

Comparing the three top factors why students consider foreign studies important, students at both faculties chose the possibility to improve their Foreign Language Skills with similar percentages (85.4% at engineering and 83% at business faculty), however, even though the second most frequent choice was the possibility to Extend Networking only half of the respondents at the engineering faculty selected the option, and over 60% of respondents at the business faculty was in favor of this factor. For engineering students Get to know Foreign Culture, Mindset and Mentality came third in the list while for technical management students developing adaption skills to international norms was more important (Table 4, Figure 5). While students at the engineering faculty regard a new structure as important, students at the business faculty seem to find the Networking and Adaptation to International Norms more important. Joining an International Project is more essential for the engineering students even if it does not show a significant difference than for future technical managers.

Soft skills gained at the two special scholarship programs showed a significant difference between the students of the two faculties (CHI2=15.545, p=0.03). The significant difference is linked to the learning method and the approach to Structure and Interpreting Learning Material, which is a cognitive skill among soft competences (Table 4). Only 10.6% of the students at the business and management faculty selected the option, while over one-third of the participating students at the engineering faculty voted for it.

Figure 5. Differences in the top three factors’ choices of benefits of foreign studies

The rankings of skills and competences gained through foreign studies by the two faculties also show a strong positive significant rank correlation (Spearman’s ρ=0.8571, p=0.014), i.e. should students at one faculty ranked a factor ahead then students at the other faculty do so, which is in compliance with the significant difference of approaches to experiences in studying abroad (Figure 6). Figure 6 visually presents where students from the two faculties differ the most. The third and fourth places are interchanged while engineering students find the skill To Easily Accept Otherness the least important as opposed to technical management students placing this skill as number 6. The numbers in Figure 6 denote the order given by engineering students while the colors show where the order is different between the students of the two faculties e.g., number 6 (dark blue, Project Possibilities) by engineering students is placed number 5 by technical management students (orange).