Software Development Projects as a Way for Multidisciplinary Soft and Future Skills Education

Abstract

The modern job market demands soft and future skills from both technical and non-technical professionals. It is often challenging to teach these competencies in a traditional academic setting. This paper presents an effective approach for developing these skills through a short, intensive, joint project. While our case study is an Erasmus+ program, the methodology can be applied within various frameworks. We use problem-based and active learning, along with group work, to teach. The approach also emphasizes diversity by arranging multidisciplinary student groups to work on software development tasks. In our project, less than half of the participants had a computer science background, demonstrating that these tasks are engaging for non-technical students. The multicultural and international environment of the project is crucial in a global working environment, and its brief, intense nature helps simulate real-world stressful situations. This methodology provides a practical way to prepare students for the demands of the modern workplace. The results confirmed the effectiveness of the project in developing certain key skills, though not all competencies showed a measurable increase during the event’s short duration.

1. Introduction

Soft and future skills are vital for graduates (Ehlers, 2021; OECD, 2018). However, many students underestimate their importance and believe that domain competencies are sufficient Succi and Canovi (2020). Students who recognize the importance of soft skills achieve higher salaries, whereas graduates with lower wages focus primarily on hard skills Lamberti et al. (2023). Additionally, the authors of Gnecco et al. (2024) predict that after COVID-19, changes in working conditions will further increase the demand for soft skills of employees. Higher education institutions (HEIs) need not only to provide students with appropriate domain competencies, but also to help them develop inter-domain and interpersonal skills. Therefore, HEIs have to modify the teaching methodologies accordingly. Many approaches have been proposed to address the mentioned demands. Most of them are based on active learning, problem solving, and group-work methods (Chen et al., 2021; Estrada-Molina, 2022; Van Den Beemt et al., 2020; Whewell et al., 2022).

Active learning and problem-based methods are easily applicable in an educational institution, but these methods alone are not enough to increase cooperation and communication skills, such as empathy. Moreover, real-life working environment, IT specialists often have to cooperate with non-technical people Frezza et al. (2019). Unfortunately, incorporating multidisciplinary and intercultural aspects into classroom teaching is not straightforward. In this paper, we present an approach to teaching soft and future skills in an international cooperation project between HEIs and analyse its effect on students’ self-assessed competencies with regard to communication, cooperation, flexibility, digital skills, creativity, critical thinking, willingness to learn, and self-reflection. In the project, during a 10-day intensive course, students worked in interdisciplinary teams with other students from different (academic) cultures, different languages, and different backgrounds. The result of increased soft and future skills in the participating students is measured using the KYSS questionnaire (Chaoui et al., 2022; De Bruyne et al., 2023). The development of KYSS (see Section 4) focused on correspondence between survey questions, language, and its understanding by participants, as well as on measuring soft and social skills. This paper assesses whether the project increases students’ future and soft skills. This can be expressed as the hypothesis that ’the results for a given category of post-tests are statistically better than those from pre-tests’. This hypothesis is assessed using the Wilcoxon one-sided test.

This paper is structured as follows: In Section 2 we discuss the problem of soft- and future-skills in modern education. The next section is dedicated to the description of the project. Later we introduce the KYSS survey. Section 5 and Section 6 focus on the results and interpretation of KYSS surveys conducted during the project. At the end of the paper, we present the Conclusions.

2. Related Works

2.1. Soft and Future Skills

The importance of soft skills has long been established (Kechagias, 2011; B. Schulz, 2008). Although hard skills usually refer to domain-specific competencies, such as databases, programming, or operating systems, soft skills are complementary skills that are important for professional success and to operate in a team in a working environment (Cimatti, 2016; B. Schulz, 2008). While there is no consensus definition of soft skills or a finite list of single skills, soft skills usually include skills related to interpersonal skills (communication, collaboration, empathy), reflection (critical thinking, problem solving), and self-development (learning, self-reflection) (Cimatti, 2016; B. Schulz, 2008). Soft skills are hard to measure, and they are best learned when they are integrated with hard skills Cimatti (2016). The concept of future skills or 21st-century skills extends the concept of soft skills towards skills that help to cope with an ever-changing professional environment. Future skills overlap with soft skills, but prioritize information management, critical thinking, creativity, problem solving, collaboration, communication, self-direction, lifelong learning, ethical awareness, cultural awareness, and flexibility (Ananiadou, 2009; Van Laar et al., 2017). Like soft skills, future skills are also difficult to measure Ananiadou (2009). An additional requirement for the future workforce is entrepreneurial readiness. Entrepreneurship and its connection to computational thinking are important in many areas of computer science as well as in the disciplines of social studies Kang and Lee (2020).

The soft skills most frequently addressed in curricula are communication, teamwork, ethics, and presentation skills Groeneveld et al. (2020). However, skills such as creativity and empathy are lacking in the curricula, although they are required by industry Groeneveld et al. (2020). Important future skills such as critical thinking and self-reflection were only found in $16\%$ and $13\%$ of the studied curricula, respectively Groeneveld et al. (2020).

Probably the most frequently cited soft skill is the ability to communicate. This includes the ability to communicate in English as the lingua franca (including the ability to communicate with non-native speakers); to communicate across disciplines, hierarchies, cultures, and genders in written and oral form; and to listen and visualize (Balaji & Somashekar, 2009; Riemer, 2007). Communication skills are often taught through presentations, peer review, role play, and team tasks Riemer (2007). Communication skills are especially important in situations such as teamwork, negotiations, job interviews, and mentoring Hargie and Hargie (1997).

The ability to jointly solve a task with others is referred to as cooperation skills. Problem-based learning (Panlumlers & Wannapiroon, 2015; Trisdiono et al., 2019) and portfolio projects Bánhegyi and Fajt (2023) have been documented to improve cooperation skills. The interdisciplinarity in education is also important in the context of cooperation and communication skills Li et al. (2025); Schijf et al. (2025).

Flexibility is the ability to adapt to changing circumstances. It is especially relevant for project management, for example, in software development Sukhoo et al. (2005). Flexibility includes the ability to change, learn, accept, and adjust (Balaji & Somashekar, 2009; Robles, 2012).

Digital skills refer to the proficient but critical use of digital information, media, and tools Sicilia et al. (2018), as well as the attitude towards those Van Laar et al. (2017). Creativity is the ability to generate new ideas or recombine existing ideas into new concepts Heye (2006). Learning creativity is associated with risk-taking, diversity of inputs, generation of ideas, and evaluating/prioritizing them later Heye (2006).

Critical thinking as a skill has been studied extensively since the 1990s Behar-Horenstein and Niu (2011). Critical thinking is related to problem solving and requires domain knowledge and skills as a basis for intellectual and cognitive analysis, interpretation, argumentation, and judgment (Alsaleh, 2020; Behar-Horenstein & Niu, 2011). Critical thinking appears to be more difficult to teach and requires longer interventions compared to other skills Behar-Horenstein and Niu (2011). Due to the link to domain knowledge, critical thinking skills improve with time spent studying and reading books Terenzini et al. (1995).

Willingness to learn is the skill that includes the notions of being responsible for one’s own learning, self-management of learning, and self-expertise of learning Simons (2008). Willingness to learn requires alertness, openness, and reflection through experience, as learning does not always take place automatically Van Eekelen et al. (2006).

Self-reflection involves the purposeful mental processing of one’s own learning process and outcomes. It is a pre-requisite for problem-based learning Lew and Schmidt (2011). Self-reflection is especially important when learners face anxiety in complex tasks in team projects S. Schulz, Garcia, and Treude (2023). Self-reflection is often taught through reflective journal writing (Black et al., 2000; Dinc et al., 2023; Lew & Schmidt, 2011).

In education, soft skills can be taught using didactic settings that require teamwork, reflection, and diversity Hazzan and Har-Shai (2013).

2.2. Active and Problem-Based Learning

Active learning and problem-based methods are commonly used in education, especially in higher education. Many classes end with real-life small projects, and probably, all higher education institutions use project-based classes in their curricula. In ACM and IEEE Joint Task Force documents, we can find explicit suggestions to enforce the growth of problem-based and active learning methods at least with the use of teamwork and group projects in study programs (ACM Computing Curricula Task Force, 2013; Cc2020 Task Force, 2020). Many articles show how these approaches are used in teaching (see implementation review articles (Angelaki et al., 2024; Chen et al., 2021; Estrada-Molina, 2022; Van Den Beemt et al., 2020)). Problem-based learning has also been successfully applied in international contexts Badets et al. (2017).

However, it is challenging to design collaborative learning environments based on learning objectives, learner characteristics, and contextual factors and to align assessment S. Schulz, Berndt, and Hawlitschek (2023). Most of the implementations are in-class solutions. Therefore, they use homogeneous students; the students represent the same domain or institution. We are interested in approaches that incorporate multidisciplinary and intercultural groups with active and problem-based learning. In the literature, not many methods fulfill these requirements Ndiaye and Blessing (2023).

In previous years, our group has participated in a few joint projects (Milczarski et al., 2018; Monteiro et al., 2019; O’Reilly et al., 2015) that led to the development of the MIMI methodology Dowdall et al. (2021). In this project, we decided to continue working with this approach as it fits our needs. The acronym MIMI comes from Multinational, Intercultural, Multidisciplinary, and Intensive. It is developed especially for short-term intensive projects for a diverse set of participants. It provides a schedule for such an event with a detailed plan on how to organize the work of teams. The organization of the event is suitable to enhance the selected skills. The connection of activities with expected pedagogical outcomes is outlined in Dowdall et al. (2021). The method was recognized and recommended by the authors of Estrada-Molina (2022). To date, no objective measurements of the effects have been conducted. Measurements of the effectiveness of small didactic experiments are biased by the size of pilot groups. On the other hand, the idea of organizing events outside of the general curricula leads to a small number of participants, as such events cannot be organized on a bigger scale.

3. Intensive Project Description

Within an Erasmus+ cooperation partnership, six European HEIs developed and implemented an intensive 10-day course to teach soft and future skills. The methodology implemented important elements of the MIMI methodology Dowdall et al. (2021) and developed it further. The 60 students and 10 lecturers from the six participating institutions met at the event venue in one of the HEIs. The students, all volunteers aged 19–26 and from the first and second cycles of study, were required to be proficient in English. The participants came from six different countries: Belgium, Finland, Germany, Ireland, Poland, and Portugal. The participating students, as well as the lecturers, represented different fields of study: less than half had a computer science background, and others pursued degrees in management, tourism, chemistry, and production engineering. The students were assigned to six-person teams with members from the six participating HEIs and at least three disciplines. The team had to contain a minimum of one computer science and business student, as these competencies are core to fulfill task requirements. The task of the groups was to create a prototype of an application or service related to the event theme: Digital Entrepreneurship and the Climate. As a result, groups had to prepare a working prototype focused on real-life local needs, create a business potential assessment, and present the idea to internal and external audiences. The organizers assigned a staff member to each group as their mentor. The role of the mentor was to support the team and assume the role of an advisor. In addition to providing technical support, the mentors were responsible for overseeing and resolving any ethical issues that arose within their teams. This included continuously monitoring work ethics, such as the equitable distribution of duties and the proper use of intellectual property, as well as addressing group dynamics like bullying or other inappropriate behaviors. Teams should have been self-driven, and all decisions must have been made by student members. The intensive course was divided into three stages; each stage ended with a group presentation. The first two days were devoted to team building and brainstorming. On the second day, the teams presented their ideas as a pitch speech. The second part was dedicated to the development of the idea. The teams worked on prototypes and development of the application’s content and on business elements, such as stakeholders, user personas, cost assessments, Business Model Canvas, and SWOT analysis. On the fifth day of the event, the groups presented their proposition again. During the last stage, the teams polished their business ideas and prototypes. On the ninth day of the project, more formal presentations were made with invited external partners who also provided independent feedback to the teams. In all presentations during the project, every member of the team had to take an active role. The soft and future skills were self-assessed by the students using the KYSS questionnaire Chaoui et al. (2022).

The students filled out the questionnaire on the first and last days of the intensive course. Thus, the pre-test is filled out before participants take any real activity in the project. The post-test is gathered after the last activity in the project. The students are asked to fill out tests electronically while still in the common area, for example, in the auditorium, before the event starts or after the final presentations. An important difference from the MIMI methodology Dowdall et al. (2021) was that we did not conduct lectures or workshops during the intensive course. However, short, motivating, interactive sessions, similar to TED talks, aligned the students’ knowledge on project goals, teamwork, software and service design, as well as business potential assessment. These talks allowed participating students to get acquainted with staff members who could help them later with specific problems in the course of the project.

The course was not set up as a contest; there was no winning team. It was explicitly suggested that teams help each other if possible. At the beginning of each day, the assigned mentor met with the team to conduct an assessment of the tasks completed, plan the day and the next days, and discuss the idea developed by the team. Often, mentors met with their teams several times a day. The frequency and length of the meetings depended on the stage of the project and the needs of the team. In the first days, the mentor helped moderate brainstorming or improve the focus on idea development. Later, the mentor coached the team to complete the tasks that allowed the team to achieve its goals.

4. KYSS Survey

The design and evaluation of didactic methodologies require a qualitative and quantitative evaluation of the results McKenney and Reeves (2018). In our project, we need a measurement tool that can help measure the impact on the soft and future skills of the participants. The measurement of future and soft skills is not easy or obvious. The KYSS survey Chaoui et al. (2022) fits our needs. Therefore, we have decided to use this approach. The method allows for measuring the level of soft and future skills in selected categories.

KYSS comes from Kickstart Your Soft Skills and was developed within the European Social Fund project under that name. The approach divides soft skills into four domains: interaction, problem solving, information processing, and personal. For each domain, some categories were defined, such as communication, cooperation, critical thinking, etc. The creators of the KYSS survey developed a self-report questionnaire to estimate soft and future skills. It can be used as a self-assessment tool for everyone. The questionnaire results in a score that is recorded and described in an individual feedback report. In addition to the scores, this feedback report also contains score-based feedback for each of the recorded skills. In the process, they used standardization and validation procedures to estimate the importance of responses and correspondence to the measured skills (Chaoui et al., 2022; De Bruyne et al., 2023). The KYSS survey was prepared in Dutch. At first, the creators developed a vocabulary that corresponded with selected soft skills. On this basis they created a set of questions and measured if a survey participant understood the question in a proper way. The work with local government institutions for unemployed people, as well as VDAB, one of the biggest recruitment companies in Belgium, allowed us to build an adequate and verified questionnaire. All questions were connected to selected soft skills, and the correlation was assessed in a real-life environment. In our case, we used the translation of the original Dutch questions into English.

KYSS allows respondents to self-assess these skill categories using a survey questionnaire. In this project, we have decided to measure the effects using forty-six questions divided into eight categories: communication, cooperation, digital skills, creativity, flexibility, critical thinking, willingness to learn, and self-reflection.

The KYSS survey can be taken as an online survey. We asked all students to do the survey twice, at the beginning and at the end of the 10-day intensive course. We applied statistical tests to the data to determine if there was a significant statistical difference between pre- and post-tests. Differences would suggest that there is an effect on participants’ skills. Moreover, we were interested to see if the post-test results were better than the pre-test ones. Therefore, we used a one-sided statistical test to evaluate whether improvement in the selected skills could be observed.

5. Results

During the project, we assessed the project’s effects in two ways. We asked participants to fill out a simple questionnaire to map the students’ reception of the project. In addition, we used the KYSS method to measure the impact on students’ soft and future skills.

In the basic questionnaire, participants generally expressed positive reactions to the event (

Table 1. Students answers to basic questionnaire.

Question	Yes [%]
Do you feel that this project improved your communication skills?	$96\%$
Do you feel that this project improved your critical thinking?	$89\%$
Do you feel that this project improved your creativity?	$83\%$
Do you feel that the project improved your entrepreneurial skills?	$76\%$
Do you feel this project promotes excellence in learning, teaching, and skills development?	$81\%$
Do you feel that this project promotes internationalization?	$96\%$

). The answers show only a general assessment of the method given by the participants. This cannot be used as a real verification. Nevertheless, the positive feedback shows that there is some interest and acceptance for the approach.

As we can see, the students evaluated the learning experience and learning gains very positively. As mentioned above, the results of this simple questionnaire give only general information. In order to make a real assessment, we use a very different and more sophisticated tool. The KYSS survey provides a deeper and more reliable understanding of the effects of the project on the soft and future skills of the participants.

During the event, we measured students’ soft and future skills using KYSS surveys. One survey was completed on the first day of the project, and the other on the last day. Both answers were connected, and we were able to pair up the pre- and post-test answers. Students answered the questions on a five-level Likert scale: ‘Strongly agree’, ‘Agree’, ‘Neither agree nor disagree’, ‘Disagree’, ‘Strongly disagree’. We assign values of 2, 1, 0, −1, and −2 for each answer. This allows us to apply statistical tests and test the hypothesis of whether the project improves the students’ skills.

We could have analyzed the effect on the basis of individual questions, but we decided to work on categories, as the questions individually are less informative than when combined. In order to assess the effect on a given category, we have summed up all the answers of a given student. We can say that the students obtained some points for answers in each of the categories for the pre- and post-tests. For each category, we have the null hypothesis $H_0$ that both sets of results for a given category have the same statistics. Additionally, we believe that the results of the post-test are better than those of the pre-test. We test the hypothesis $H_1$ that the results for a given category of post-tests are statistically better than those from pre-tests. In all categories the results of post-tests have a higher mean and median than in the pre-test, but it is not enough to validate the increase in skills. Therefore, we use a statistical test to verify our hypothesis. One-sided rank statistical tests are much more appropriate for hypothesis testing in similar scientific problems (Blair & Higgins, 1980; Conover, 1999). In this research, we use the Wilcoxon one-sided test (Cureton, 1967; Wilcoxon, 1945), implemented in the Python scipy library Virtanen et al. (2020). For all tests, we used a significance level $\alpha$ equal to $0.05$, which means that if the p-value obtained for a given statistical test is lower than the significance level, we can reject the null hypothesis in favor of hypothesis $H_1$. On the other hand, if the p-value is higher than the significance level, we have no reason to reject the null hypothesis $H_0$.

In the following subsections, the results are presented for each category independently.

5.1. Category: Communication

This category contains eight questions. All answers for a student were summarized and paired. A histogram of the results of the pre- and post-surveys is presented in Figure 1. The histogram presents the sum of scores for all questions in the category. Each answer is assigned an integer value from −2 to 2. Each bar represents how many participants gave answers for the category communication with a given sum of scores. The parameters of the distribution of the results are shown in

Table 2. Results for the category communication.

Parameter	Pre	Post
Mean	6.368	7.763
Median	7.000	8.000
$\sigma$ (std. deviation)	4.737	4.386
Wilcoxon test results
p-value	0.020

.

Using the Wilcoxon one-sided test, we obtained a p-value equal to $0.020$. As this is lower than $0.05$, we can reject the hypothesis of $H_0$. Therefore, we accept the $H_1$ hypothesis that the results of the post-event test are statistically better than those obtained by a student in the pre-test.

5.2. Category: Cooperation

The category cooperation contains six questions; we proceed in the same way as in the previous category (see Figure 2 and

Table 3. Results for the category cooperation.

Parameter	Pre	Post
Mean	5.447	6.579
Median	5.500	6.000
$\sigma$ (std. deviation)	3.118	2.769
Wilcoxon test results
p-value	0.012

).

The Wilcoxon test returned a p-value equal to $0.012$, and as before, we could accept the $H_1$ hypothesis for this category.

5.3. Category: Flexibility

The category flexibility contains six questions (see Figure 3,

Table 4. Results for the category: flexibility.

Parameter	Pre	Post
Mean	4.763	5.211
Median	5.000	6.000
$\sigma$ (std. deviation)	3.638	3.197
Wilcoxon test results
p-value	0.117

).

The Wilcoxon test returned a p-value equal to $0.117$, so we could not accept the $H_1$ hypothesis for this category. The conclusion is that the distribution of the pre- and post-results is statistically similar and can represent the same background statistics.

5.4. Category: Digital Skills

The category digital skills contains four questions (see Figure 4 and

Table 5. Results for the category digital skills.

Parameter	Pre	Post
Mean	2.605	3.395
Median	3.000	4.000
$\sigma$ (std. deviation)	2.651	2.700
Wilcoxon test results
p-value	0.013

). The Wilcoxon test returned a p-value equal to $0.013$, and we could accept the $H_1$ hypothesis for this category.

5.5. Category: Creativity

The category creativity contains six questions; we have proceeded in the same way as in previous categories (see Figure 5,

Table 6. Results for the category creativity.

Parameter	Pre	Post
Mean	4.974	5.447
Median	5.000	5.500
$\sigma$ (std. deviation)	2.748	2.468
Wilcoxon test results
p-value	0.095

).

The Wilcoxon test returned a p-value equal to $0.095$, so we could not accept the hypothesis $H_1$ for this category.

5.6. Category: Critical Thinking

The category critical thinking contains five questions; we proceed in the same way as in the previous categories (see Figure 6 and

Table 7. Results for the category critical thinking.

Parameter	Pre	Post
Mean	4.526	5.263
Median	5.000	5.000
$\sigma$ (std. deviation)	2.613	2.244
Wilcoxon test results
p-value	0.058

).

The Wilcoxon test returned a p-value equal to $0.058$, so we could not accept the hypothesis $H_1$ for this category. The conclusion is that the distribution of the pre- and post-results is similar.

5.7. Category: Willingness to Learn

The category willingness to learn contains six questions (see Figure 7 and

Table 8. Results for the category willingness to learn.

Parameter	Pre	Post
Mean	5.632	6.237
Median	5.000	6.000
$\sigma$ (std. deviation)	2.630	2.538
Wilcoxon test results
p-value	0.073

).

The Wilcoxon test returned a p-value equal to $0.073$, so we could not accept the hypothesis $H_1$ for this category. The conclusion is that the distribution of the pre- and post-results is statistically statistically similar.

5.8. Category: Self-Reflection

The category self-reflection contains five questions (see Figure 8,

Table 9. Results for the category self-reflection.

Parameter	Pre	Post
Mean	3.974	4.895
Median	4.000	5.000
$\sigma$ (std. deviation)	2.253	2.186
Wilcoxon test results
p-value	0.003

).

The Wilcoxon test returned a p-value equal to $0.003$, so we could accept the hypothesis $H_1$ for this category.

6. Discussion

6.1. Interpretation and Evaluation of Results

While the quantitative results are detailed in the previous section,

Table 10. Influence of project aspects on skill development.

Project Aspect	Observed Impact	Skills Affected
Problem-based learning	Required participants to independently define and solve complex problems.	Creativity, Flexibility, Critical Thinking, Willingness to Learn
Intensive, short duration (10 days)	Caused a significant increase in skills that can be developed quickly.	Communication, Cooperation, Digital Skills
Working in high-stress, real-life situations	Led students to discover their ability to perform well under pressure.	Self-reflection
Multicultural environment	Required participants to collaborate with members from different countries and cultures.	Communication, Cooperation, Critical Thinking

offers a summary of how various aspects of our project contributed to the observed changes in student skills. The MIMI approach is developed around these aspects. Moreover, they are important for other didactic approaches presented by other research groups Li et al. (2025); Panlumlers and Wannapiroon (2015); Schijf et al. (2025); Trisdiono et al. (2019).

The results obtained for each category are presented in

Table 11. Statistical results for all categories.

Category	Wilcoxon Test Result	Conclusion
Communication	$0.020$	Accept $H_1$
Cooperation	$0.012$	Accept $H_1$
Flexibility	$0.117$	Reject $H_1$
Digital skills	$0.013$	Accept $H_1$
Creativity	$0.095$	Reject $H_1$
Critical thinking	$0.058$	Reject $H_1$
Willingness to learn	$0.073$	Reject $H_1$
Self-reflection	$0.003$	Accept $H_1$

. We can deduce that for four categories—communication, cooperation, digital skills, and self-reflection—the test results prove the increase in appropriate skills during the event. There is no reason to deduce similar implications for other categories such as willingness to learn, critical thinking, flexibility, and creativity. In truth, the results are not very surprising. The event is only ten days long and not all measured skills can be influenced in the same way during such a short time. Skills related to communication, cooperation, and digital skills can be trained in a relatively short time. We think that self-reflection increased as the participants discovered that they could obtain good results in a real-life task. The students learned that they can work and achieve the required goals in a high-stress environment with an emphasis on results. On the other hand, skills like creativity, flexibility, critical thinking, and willingness to learn cannot be increased in the short term and require a longer process. It is worth mentioning that the applied tests do not decide whether the $H_1$ hypothesis is improbable to be true, which shows that there is no reason to reject $H_0$. Additionally, all results are statistical, so the effects among students could be different.

It should be mentioned that there are differences between the KYSS results and the results obtained from the direct questions from the participants (see Table 1 and Table 11). For example, about $89\%$ of the participants believed that their critical thinking improved, but the analysis of the KYSS surveys did not prove that assessment. It could mean that the general positive emotions about the event increase the percentage of positive responses. In addition, students are not always able to properly assess their skills.

The findings of this study contribute to the existing body of knowledge on interdisciplinary project-based learning. While many studies, such as the qualitative research by Schijf et al. (2025), have focused on the student experience of navigating different disciplinary cultures, our work provides a distinct contribution by offering a quantitative perspective. Our pre- and post-event survey data allowed us to provide statistical evidence that specific soft skills, including communication and cooperation, can be measurably improved with a short, intensive project.

In contrast to our case study approach, other studies, like the work of Trisdiono et al. (2019), have used more rigorous quasi-experimental designs to validate their educational models. Their use of objective assessment tools, such as essay tests and observation sheets, provides a stronger causal link between their teaching model and skill development. We acknowledge that our study’s reliance on self-assessment is a limitation, but it also highlights a clear direction for future research. A similar quasi-experimental approach, combined with objective assessment tools, would be a valuable next step to further validate the effectiveness of our educational model.

6.2. Limitations and Future Work

Despite the promising results, it is important to emphasize that the conducted research has certain limitations. Our findings are based on self-assessment questionnaires, which are prone to errors due to respondents potentially overestimating or underestimating their skills. Furthermore, to ensure the full anonymity and confidentiality of the participants, our survey did not collect data on their specific academic disciplines. While this ethical approach was crucial for encouraging candid feedback, it prevented us from conducting a more granular analysis of potential differences in skill development across various fields of study. It would be worth paying attention to this aspect in future research.

This study marks the beginning of research into the impact of this teaching method on improving students’ soft skills. At this stage, more in-depth comparative analyses, such as with a control group, are not yet feasible. Future research is planned within similar projects and through ongoing work with university students. It would be worthwhile to examine how the skills acquired during the project impact the students’ performance in further education. Such a study would require more time and the development of an appropriate methodology. In the longer term, a longitudinal study could be conducted to assess the career development of graduates who participated in the project. These long-term studies would provide valuable insights into the impact of these new teaching methods on students’ professional lives after graduation.

7. Conclusions

The method used in the project was expected to have a positive impact on the participants. Moreover, the event we describe is the second event of this type organized together. Staff members who have worked with students on the previous event observed a positive impact on students’ soft and future skills. The observations in the following academic year suggest a higher increase in skills in the project participants when compared with the other students in the degree program. This time during the event, we have incorporated KYSS surveys as a measurement tool. The results support the expectations and previous observations. Not all aspects measured with KYSS show similar growth. The different effects of the project on different skill categories were expected. Moreover, the KYSS gives a more reliable assessment of the project’s effects than a simple direct questionnaire. Based on the presented results, the consortium will conduct a similar study and measure its impacts on the participants.

The effects show that software development projects can be used for multidisciplinary education. This type of team task allows for increased communication and cooperation in diverse groups. Young people are eager to use and create new solutions that use modern technologies. What is important is that this type of activity is very appreciated by non-technical students.

The results suggest that this type of solution is worth implementing not only for occasional projects but also as a regular part of student education. Naturally, each academic institution would need to adapt the described teaching method to its specific conditions and capabilities. Implementation would require changes to the curriculum and may not allow for the full realization of all benefits from the project described in this article. However, certain elements could be effectively utilized by academic staff on a daily basis. Preparing short, multi-day courses that require students to work intensively, thereby simulating real-world, high-pressure situations, appears relatively simple to implement. In many cases, it would also be possible to form interdisciplinary groups within a single university. Conversely, organizing international groups would be more challenging due to the need for student mobility and the associated higher financial costs.

The results show that intensive international and multidisciplinary projects can have a significant impact on the soft and future skills of participants. Moreover, our research provides, for the first time, objective measurements of the effects of the MIMI methodology.