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Article

Digital Competences of Digital Natives: Measuring Skills in the Modern Technology Environment

by
Danijela Pongrac
*,
Marta Alić
and
Brigitta Cafuta
Department of Computer Science, Zagreb University of Applied Sciences, 10000 Zagreb, Croatia
*
Author to whom correspondence should be addressed.
Informatics 2025, 12(1), 23; https://doi.org/10.3390/informatics12010023
Submission received: 25 November 2024 / Revised: 14 February 2025 / Accepted: 19 February 2025 / Published: 21 February 2025
Versions Notes

Abstract

:
The fourth industrial revolution has ushered in a new era in which technology is seamlessly integrated into daily life. The digital transformation has created new media formats that require the development of robust digital skills to navigate this landscape. By utilising the Youth Digital Skills Indicator (yDSI) and integrating it with the Digital Competence Framework for Citizens (DigComp 2.2), this research examines media habits and digital competences among Croatian youth aged 10–24, corresponding to Generations Alpha and Z. A sample of 231 participants across three competence domains—information literacy, security and communication—revealed statistically significant generational differences in the first two areas of digital skills. Furthermore, gender-based analyses, conducted using the Mann–Whitney U-test and Spearman correlations for Likert scale responses, showed no significant differences. These findings deepen our understanding of digital natives, how media habits evolve and influence their digital skills, highlighting the need for more tailored strategies to enhance their competences and bridge generational gaps.

1. Introduction

In just 50 years, media and communication tools have changed profoundly and spread across the world. Technological innovation has become the driving force behind the digital transformation, the fastest, most comprehensive and far-reaching paradigm shift in human history, revolutionising every aspect of daily life. The impact of the fourth industrial revolution is evident in the way people work, form relationships, maintain their health, spend their leisure time and entertain themselves [1]. The media has become a new “habitat” in which individuals must acquire the necessary skills and competences for its proper use, contributing to the creation of a global culture.
The processes of “digitalisation” of everyday life are being driven by the transition from an industrial to an information-based economy, in which data are becoming a key resource that is reshaping business practises and developing new digital business models. These models, enabled by sharing economy platforms, are disrupting traditional markets [2]. Today, supply and demand are virtually interconnected, fuelled by continuous investment in the telecoms industry (telephone networks, satellites, etc.) that serve as the backbone of a new wave of internet expansion. This shift is increasingly targeting not only people but also things, as new technologies focus on capturing all possible data points, transforming the internet from a tool for democratising civil society, as originally expected, into an economic instrument [3]. In addition, the field of digital skills has experienced rapid growth in recent decades and has stimulated research in various areas. These include topics such as education and workforce development [4,5], digital skills in the knowledge economy [6] and the digital divide [7], as well as their role in engaged citizenship [8], to name a few.
The new generations, born in the information age and often referred to as digital natives [9], have adapted to their environment where technology has become a fixed, integral and essential part of life. Unlike previous generations, the so-called digital immigrants, there is a growing digital divide [10], a knowledge gap that is reflected not only in the availability of communication technologies, but also in the skills required to use them [11]. Thus, digital competences become the basis for the future success of the individual in the entire digital environment.
Research shows that young people’s ability to search for information can improve their academic performance [12,13], while better technical and operational skills related to communication are associated with positive coping behaviour towards the risks of the online environment [14,15,16], civic participation [17] and overall life satisfaction [18]. As digital natives enter the workforce and become active members of society, they will play a crucial role in shaping future policy. The importance of developing and improving digital skills is therefore undeniable. Both individual habits and systematic educational processes significantly influence the acquisition and development of these skills.
While Generation Z has been studied extensively over the past decade, particularly by grey research [19,20,21] as it approached the working population and gained greater purchasing power, research on Generation Alpha is still at an early stage. The results of this study contribute to this emerging field of research, which holds great promise for the future.
To better understand the capabilities of young people growing up in an information society—especially their digital competences—we took their immersion in digital technologies as a baseline. To investigate the attitudes of two generations of digital natives in Croatia towards acquired digital skills, the Youth Digital Skills Indicator (yDSI) measurement tool [22] was used, and the results are compared with the “Digital Competence Framework for Citizens” or DigComp 2.2. The questionnaire was analysed with regard to media habits and assumed digital skills in three competence areas: information literacy, communication and security.
Seeking to explore how media habits have shaped their digital competences, the paper is structured as follows. Consecutive to this section, we provide a brief overview of the characteristics of digital natives to establish the research context, followed by the background on the concept of digital literacy and how it is operationalised and measured within the European Union as a reference framework. In the methodology and methods section, we describe the research design, materials, sample and statistical methods used for data analysis. The findings are then presented in the context of media habits and digital competences, where the results are shown for the entire sample and then separately by gender and age group. Next, in the discussion section, we reflect on the findings, note research limitations and suggest possibilities for future research. Finally, we conclude the paper with key research findings.

1.1. Digital Native Characteristics

Nowadays, technology is present in all areas of our lives, especially among Generation Z and Alpha. Generation Z includes everyone born between 1990 and 2010, and Generation Alpha includes everyone born after 2010 until today [23,24]. Generation Z has developed technological skills to a greater extent, as they tend to work remotely, they do not like to live under stress, they like travelling and they are prone to trends because they want freedom and want to be creative [25]. Even more interesting is the fact that Generation Z favours online contacts over face-to-face contacts compared to other generations [26], as they spend up to 9 h a day on various technologies and are said to be the generation of virtual and augmented reality [27]. Despite the fact that they are surrounded by technologies that they rely on in all areas of life, research shows [28] they do not have developed digital skills. Despite that, they tend to think in four dimensions, unlike previous generations who only think in three dimensions, as their thought patterns correlate time and space differently having grown up in high-resolution and surround sound technologies [29]. Although Generation Alpha is also referred to as the digital generation, it should be seen as the first generation of the 21st century. Life without technology and the internet is unimaginable for its members as they suffer from a lack of attention and are not good at building relationships with other people [30]. The Alpha generation is considered the most intelligent generation of all previous generations and is focused on digital technologies [24]. Alphas are also referred to as screenagers and need to prepare for the future labour market by developing their social skills, entrepreneurial and financial literacy, teamwork and critical thinking [29]. Furthermore, ref. [30], as negative characteristics research, finds that generation Z often tends to be pessimistic and critical, as they are realists who find it difficult to concentrate on completing just one task. We could conclude that generation Alpha has been exposed to various technologies from an early age, which often leads to social distancing and a lack of interest in personal interaction and communication with others. Their communication skills are less developed compared to other generations, which emphasises the need for targeted efforts to promote and improve these skills in the early stages of life. Generation Z enjoys using technology but still shows a desire for direct, face-to-face interaction without the mediation of technological devices. This generation will need to work on improving their ability to concentrate on completing a single task and reduce their level of self-criticism.

1.2. Conceptualisation of Digital Literacy

In the environment of the digital economy and society, individuals’ ability to adapt to new trends and demands depends largely on their attitudes, habits and knowledge related to the use of digital skills. The process of acquiring such skills and its outcomes is known as digital literacy, which the United Nations Educational, Scientific and Cultural Organisation (UNESCO) describes as “the ability to access, manage, understand, integrate, communicate, evaluate and create information safely and appropriately using digital technologies in order to find employment, decent jobs and entrepreneurship” [31]. As digital skills form the basis for success in today’s digital society, they are, according to the European Council [32], one of the three key competences for lifelong learning, alongside civic and social competences, cultural awareness and creative competence, defined by the outcomes of safe and critical use of technology. The latter, the critical use of technology, refers to the broader concept of media literacy, an understanding of the combination of electronic media as an instrument of mass communication and digital media as an instrument of multimedia communication. And in the WEB 2.0 ecosystem, where individuals are prosumers [33], both producers and consumers of media, these skills refer to actions such as self-editing, publishing, accessing resources, interacting, searching, etc., in the interactive landscape of new, convergent media [34]: from publishing blogs and vlogs, RSS and related services, to podcasts and other content and news where users are involved in production, categorisation, dissemination, etc.
In today’s world, digital literacy is essential for active citizenship and the sustainability of democratic systems [35]. It enables individuals to think critically and solve problems creatively in order to navigate the predominantly digital media landscape and become critical consumers and producers of information.
There has been a great deal of work on defining and measuring digital skills, with an early distinction being made between digital self-efficacy, a confidence in one’s own abilities as a user and skills as separate components of digital literacy [36]. This distinction is crucial as both entities relate to different facets of using information and communication technologies (ICT). While digital self-efficacy is more associated with informal learning through trial and error, digital skills are more important for positive participation in society and can be associated with systematic development through formal education systems.
While UNESCO’s work focuses on what is known as media education, the European Union recognises the simultaneous use of media education and media literacy as an important part of the movement to promote the development of the information society and combat the digital divide. The efforts of the European Commission led to the formulation of the European Media Charter [37], which was developed to promote the development of media literacy in the European Union (EU)Member States and which identified the key competence areas related to media literacy, including digital competences.

1.3. Measuring Digital Literacy in the EU

The EU has set ambitious targets for 2030, aiming to ensure at least 80% of the population possesses basic digital skills and to have 20 million ICT specialists. These targets align with the Digital Compass for Europe’s digital decade and the European Pillar of Social Rights Action Plan. Also, digital skills for work and for life are at the top of the European Policy Agenda. The European Skills Agenda, of 1 July 2020, supports digital skills for all, supporting the objectives of the Digital Education Action Plan, which has the objectives of (i) enhancing digital skills and competences for the digital transformation while (ii) fostering the development of a high-performing digital education system [38].
To meet the set goals the European Commission defined a common set of digital competences that individuals need to possess, regardless of their level of digital expertise and it systemized them as a reference for policymakers, educators and individuals to understand and develop digital skills. The “Digital Competence Framework for Citizens”, or DigComp, is a reference framework introduced in 2013 based on a survey of experts’ views on digital competences [39]. Since then, there have been further updates and revisions of the framework to adapt to the changing digital landscape and technological advances. The DigComp 2.2 update in 2022 involved extensive consultation with various stakeholders through a dedicated community of practitioners. Open validation processes included input from key international organisations (such as International Labour Organization, UNESCO, United Nations International Children’s Emergency Fund and the World Bank) aimed at addressing citizens’ knowledge, skills and attitudes in response to evolving technological landscapes and incorporating considerations for green and sustainable interaction with digital technologies.
The framework has been put into practise at the EU level to produce the Digital Skills Indicator (DSI), which is used to set policy targets and monitor the Digital Economy and Society Indicator (DESI). It is also integrated into the Europass curriculum vitae (CV) template, which allows job seekers to assess their own digital skills and include the assessment in their respective CV.
DigComp includes five key dimensions with detailed descriptors for the competence levels (basic, intermediate, advanced and highly specialised) and examples of knowledge, skills and attitudes for each competence. The dimensions are (1) information and data literacy, (2) communication and collaboration, (3) digital content creation, (4) security and (5) problem solving.
The first dimension, information and data literacy, includes skills related to information literacy, data interpretation and critical assessment of online content. The communication and collaboration dimension deals with the skills to integrate, communicate and collaborate using digital technologies, recognising cultural and generational diversity and promoting participatory citizenship. Digital content creation is about developing and expressing ideas using digital media, understanding copyright issues and using different tools to create content. The safety dimension deals with the knowledge and skills required to navigate the digital world safely. This includes understanding online risks, privacy issues and safety measures to protect yourself and others in the digital space. Finally, the problem-solving dimension focuses on the ability to recognise and solve problems in a digital context. This includes critical thinking, creativity and adaptability in overcoming challenges related to technology and digital environments.
Driven by the observation that digitalisation is changing society and requires new digital skills, the Youth Skills (ySKILLS) project [40], funded by the European Union’s Horizon 2020 Research and Innovation Programme, investigated the potential impact of ICT use on the well-being of children and young people (aged 12–17) in Europe. Recognising the potential risks and opportunities, the project aimed to understand how children can best use information and communication technologies to achieve positive outcomes in terms of cognitive, physical, psychological and social aspects of their well-being. In addition, the project explored strategies to strengthen resilience to the negative effects of the digital divide.
To achieve this, ySKILLS brought together leading international research centres from various fields, including media studies, communication studies, youth studies, psychology, education, law, educational neuroscience and sociology. An important result of the project is the Youth Digital Skills Indicator (yDSI), a unique and comprehensively validated measurement instrument with 25 items. This instrument assesses both digital skills and knowledge in four dimensions: technical and operational skills, information navigation and processing, communication and interaction, and content creation and production. Each dimension takes into account both—the functional ability to use ICT and the critical understanding of how these technologies and their content are designed and utilised. The yDSI surpasses existing tools as it covers all four dimensions and emphasises both the functional and critical aspects of skills.
It is important to emphasise that the paper follows the conceptual guidelines of the DigComp 2.2 framework for digital competences and skills and uses selected items from the yDSI study in the research because they are appropriate and well verified for the young population. Each yDSI question covers several DigiComp skills, so it is a big challenge to clearly identify which question refers to which DigiComp skill. To our understanding, authors have mapped a specific question from the yDSI (column 2) to a specific set of skills from the DigiComp (column 4), as shown in Table 1. The first and last columns of Table 1 correspond to the number of the question that is examined in the survey. In the first column, the question numbers are listed as they appear in the survey, while in the last column they are listed in the order in which they correspond to the skill, or competence, from the DigComp framework. Given that a particular skill in the DigComp framework has a wider scope, then certain skills from the yDSI study (question codes) appear in multiple competence areas in the DigComp framework. Some skills from DigComp have quite long descriptions, so their abbreviated description is listed in column 4. To clearly link this, the corresponding original number is placed before the mention of each DigComp competence and skill, as listed in the source. In our study, we test the null hypotheses related to the yDSI skill area. If a difference is found between more than half of the associated skills for a particular competency, the null hypothesis is rejected.

2. Materials and Methods

To prepare the research area, we used the DigComp 2.2 framework, which identifies and describes the basic areas of digital competences that individuals need to be digitally competent in. As our study is aimed at young people, we used the yDSI study question from three areas: technical and operational; information navigation and processing; communication and interaction, as a framework for analysing functional digital competence. The fourth dimension of the yDSI study, which refers to content creation and production, was not included due to the scope of the research that is focused solely on the user side of consumer characteristics of subjects. This also relates to the area of problem-solving and its skills. Also, for the area of communication and interaction skills, question 9.7 was added because it was not explicitly covered in the previous questions and given that we expected a younger population of participants in the research, we considered it important to have that insight as well.
The aim of our research was therefore to investigate the relationship between attitudes towards the assumed digital competences in the selected skill areas of young people in Croatia, between genders and age groups, and to compare the obtained results with their media habits. The overall assumption of the research is that there are no differences in media habits and digital skills among young people based on age and gender. Specifically, certain media habits, such as the time spent using digital content and related activities, may result the perceived level of digital skills among young people. Given the above, ten hypotheses have been defined:
  • There is no statistically significant difference in the use of devices for internet access between generation Z and Alpha in this sample.
  • There is no statistically significant difference in the use of devices for internet access between girls and boys in this sample.
  • There is no statistically significant difference in activities carried out on the internet between generations Z and Alpha in this sample.
  • There is no statistically significant difference in activities carried out on the internet between girls and boys in this sample.
  • There is no statistically significant difference in the technical and operational skill area between generations Z and Alpha in this sample.
  • There is no statistically significant difference in the technical and operational skill area between girls and boys in this sample.
  • There is no statistically significant difference in the information navigation and processing skill area between generations Z and Alpha in this sample.
  • There is no statistically significant difference in the information navigation and processing skill area between girls and boys in this sample.
  • There is no statistically significant difference in the communication and interaction skill area between generations Z and Alpha in this sample.
  • There is no statistically significant difference in the communication and interaction skill area between girls and boys in this sample.
The data were collected in May 2023 during the three-day science and IT technology promotion fair for young people in Zagreb, Republic of Croatia. Study participants filled out the questionnaire directly at the fair after strict privacy regulations were introduced and consent was obtained for the survey adherence. For participants under the age of 15, their parents or guardians provided ethical consent and access.
The questionnaire comprises 9 questions and, apart from the demographic section, is divided into four sections. The first section refers to questions about media habits in terms of time spent, device used and internet activity. The other three sections relate to digital skills selected from the yDSI taxonomy: technical and operational; information navigation and processing; communication and interaction. Digital skills in the technical and operational and information navigation and processing sections examine six variables each, while communication and interaction examines seven. The answers to the questions on digital skills were given on a Likert scale with 6 categories (1 “Not at all applicable to me”, 2 “Not very applicable to me”, 3 “Neither applicable nor not applicable to me”, 4 “Mostly applicable to me”, 5 “Very applicable to me”) and zero (0) for the category “I do not understand what you mean”. While the original yDSI scale has 7 answer categories, it was modified to maximise understandability to younger participants and to enhance their motivation to provide accurate reports. The survey questionnaire can be found in supplementary File S1.
The answer options of media habits were also given on a Likert scale, with 5 categories (1 “Never”, 2 “Rarely”, 3 “Occasionally”, 4 “Often”, 5 “Always”). Questions and the disclaimer were also adapted to the target group in terms of text comprehensibility. When writing the disclaimer, the SMOG readability index was taken into account according to the respondents’ level of education. The questions from yDSI were translated literally into Croatian, without losing their meaning compared to the original. The Cronbach alpha coefficient (α) was used to assess the internal consistency or reliability of the ordinal measurement scales for three areas of yDSI skills. The results are between 0.6561 and 0.8318, which are considered acceptable values. According to Cohen et al. [41] (p. 506), acceptable reliability values, α-coefficient, are in the range of 0.60. Values below the cut-off value of 0.60 have unacceptable reliability, values from 0.60 to 0.69 have minimal reliability, values from 0.70 to 0.79 have good reliability, values from 0.80 to 0.90 have high reliability and very high reliability values are above 0.90. We also conducted a Kolmogorov–Smirnov significance test for the questions on digital skills, in which the Z and p-values obtained indicate a sufficient normal distribution.
The questionnaire was distributed to 231 trade fair visitors between the ages of 10 and 24. The gender split was 49.4% male and 50.6% female. In terms of gender, the number of respondents of both sexes is equal, as is the distribution of generations by age. Therefore, only two age groups of 10–15 and 16–24 years were selected for further discussion, corresponding to generations Alpha and Z [42]. In addition, most respondents come from primary and higher education, with the fewest from secondary education. Considering that the number of respondents from secondary education is small, only about 13%, and the age of children entering secondary education in Croatia is 15/16 years, authors believe that the categorisation into two age groups is appropriate.
Table 2 shows the characteristics of the participants.
The questionnaire was analysed according to the named areas of the yDSI taxonomy and the area of media habits with regard to the variables of age and gender. When displaying the results, a statistical test was carried out for each area and the null hypothesis that there is no difference between the two age groups or genders in terms of media habits or digital competence was tested.
The median and mean for each item were calculated for each age and gender group. Since we used the Likert scale to determine media habits and digital skills in two groups with related data, the Mann–Whitney-Wilcoxon test was applied together with Spearman correlation.

3. Results

3.1. Results of Media Habits

In the results obtained for the entire sample, respondents most frequently spent between 3 and 6 h online (54.5%) during the day, which can be considered within the normal range, taking into account school commitments and free time [43].
Of the activities for which they use the internet the most, news/conversations (84.9%) and listening to/watching music and videos (80.5%) stand out. They also use the internet mostly or often (69.7%) for further information needs, while for school needs, they often or occasionally (61.0%). The results show that the internet is never or rarely (55.8%) used to store data. It is interesting to note that there are no major differences in the frequencies of possible answers for e-mail and games.
Table 3 shows the comparison between the two age groups and genders in terms of differences in hours of internet use. The results show that there is no difference between the age and genders. For a t value of −0.18 and 6 degrees of freedom, the p-value is approximately 0.862, which suggests that in this sample there is no statistically significant difference between the two age groups in the amount of time they spend online daily.
For a t value of 0.02 and 6 degrees of freedom, the p-value is approximately 0.98, which suggests that in this sample there is no statistically significant difference between the gender in the amount of time they spend online daily.
Table 4 shows the comparison of the means and p-values for the age groups and gender in relation to the use of devices for internet access and the activities carried out. If we look at the p-values in relation to device use, we can assume that there is a difference in the use of computers, mobile phones, smart TVs and tablets between the two age groups within this sample. Generation Z uses computers and mobile phones significantly more often, while the Alphas use smart TVs and tablets more often. In terms of gender, girls show a significantly higher usage of mobile phones, whereas boys demonstrate greater usage of game consoles.
As there is a difference in p-value in most items (Table 4) when we consider age group (except for game consoles), we reject null hypothesis number 1 and conclude that there is a statistically significant difference in the use of devices for internet access between Generation Z and Alpha in this sample.
With regard to gender, we accept null hypothesis number 2 and conclude that there is no difference in the use of devices for internet access between girls and boys in this sample.
The result of the correlation showed no significant value for device use regarding age group and gender, the correlation values range from −0.115 to 0.125, and the p-values do not indicate significance (from 0.058 to 0.905).
The p-values for internet activities show differences in all items in relation to age group and only in a few items in relation to gender (searching for school information and news and entertainment in favour of girls, while boys use more for gaming activities).
Thus, within this sample, there is a statistically significant difference between generations Z and Alpha in terms of the activities they carry out on the internet, and we reject null hypothesis number 3. On the other hand, when we look at gender, there is no difference for most items; therefore, we remain with null hypothesis number 4.
The results of the correlation between activities show that e-mail has a moderately positive correlation with all other activities (storing data in the cloud 0.537; looking for information for school needs 0.464; news and conversations 0.417; listening to and watching music/videos 0.298; information about anything that interests me 0.426), except for gaming, where it is moderately negative (−0.306).

3.2. Result of Digital Competence

The questionnaire was analysed with regard to selected yDSI skill areas (technical and operational; information navigation and processing; communication and interaction), which correspond to DigComp competence (protecting and managing devices and digital content; browsing, searching, filtering and evaluating data, information and digital content; collaboration, interaction and sharing with digital technologies, including netiquette) as shown in Table 1.
Technical and operational skill areas are analysed from questions 7.1 to 7.6, where the majority of respondents in this sample classify as very well known, ranging from 56% to 80%. The skill with which they are least familiar is 7.5 private browsing (15%).
In the area of Information Navigation and Processing skills, from questions 8.1 to 8.6, the respondents in this sample show slightly less knowledge than in the area of technical and operational skill. The highest percentage of answers here also indicates good knowledge, but to a lesser extent, as the percentages range from 39% to 67%. The skills that are rated as the weakest relate to 8.5 knowledge of verifying the truth of information and 8.4 use of advanced search functions.
In the last group, attitudes towards skills about the use of communication tools for different purposes are tested from questions 9.1 to 9.7. The answers indicate that the respondents in this sample believe that they have good skills in the means of communication and the desirable and undesirable forms of communication. The percentages range between 53% and 75%.
Regarding gender and age, the null hypothesis from number 5 to 10 was that there was no difference between the two groups in age and in gender for the variables within three yDSI skill areas. Further in the results, we explain the yDSI skill area through DigComp competences according to the paired characteristics shown in Table 1. If a difference was found between more than half of the corresponding skills in each of the three yDSI areas, the null hypothesis is rejected.
According to the results regarding the gender group, a statistically significant difference within this sample was only found for question 9.3 in the area of communication. Therefore, we can assume that there are no gender differences in the three yDSI skill areas regardless of the observed differences in media habits. We accept null hypothesis numbers 6, 8 and 10 that there is no statistically significant difference between the two gender groups in this sample in all three yDSI areas.
Table 5 shows the results for the age groups in relation to DigComp competence. The code number is related to question number from yDSI skills. Since DigComp competences are broader in scope than skills, they may be listed under multiple question code numbers. In accordance with the results of the Mann–Whitney U-test, the variables for which differences were found are bolded out. Looking at the mean and median, all variables show higher values at older ages (16–24), i.e., this age shows an attitude towards greater knowledge. Thus, it can be assumed that the older age group of this sample has statistically significantly better preventive skills to protect their device and privacy, by managing different attitudes to protect digital identity through data, information and content (except for question 7.6). Therefore, we reject null hypothesis number 5 and conclude that there is a statistically significant difference between the two age groups in this sample in technical and operational skills.
In Table 5, there are also statistically significant differences between the two groups on most of the variables from the information navigation and processing domain (except for variable 8.6), where the older age group has better skills in articulating information needs and searching for data, information or digital content. Therefore, we reject null hypothesis number 7 and conclude that there is a statistically significant difference between the two age groups, in this sample, in information navigation and processing.
The smallest difference between the two groups is found in the area of communication and interaction skills, where statistical significance was found in two of all questions: 9.1 and 9.7. This only indicates a possible difference in the competence of collaboration through digital technologies and in the protection of health and well-being. As there is a difference in only two of the seven questions, we attend to null hypothesis number 9 that there is no statistically significant difference between the two age groups in this sample in the area of communication and interaction.
In the assessment of attitudes towards yDSI area of technical and operational skills, all correlations are directly related, i.e., they have a positive direction and are significant at the 0.01 level (p-value is 0.000), 2-tailed (Table 6). Since the correlation values are between 0.2 and 0.6, they represent a weak to medium strength of the relationship between the individual questions in the case of behaviour and attitudes. We can see that the highest value (0.571) represents a moderately positive correlation between questions 7.4 and 7.5, which indicates a link between “managing digital identity” and “managing data, information and digital content” given the paired digital competences.
The correlations for yDSI skills in the area of information navigation and processing are positive and significant at the 0.01 level (p-value is 0.000), 2-tailed (Table 7). As the correlation values in the case of behaviour and attitudes are between 0.2 and 0.6, they represent a weak to medium strength of the relationship between the individual variables. The highest value (0.555) of a moderately positive correlation between questions 8.3 and 8.4 indicates, with regard to the paired digital competences, a relationship between the skills “Improving search results by using the advanced functions of a search engine” and “Using information presented as hyperlinks, in non-textual form and in dynamic displays”, which are characteristic of the digital competence “Browsing, searching and filtering data, information and digital content”.
In the area of communication and interaction (Table 8), all correlations have a positive direction and are significant at the 0.01 level (p-value is 0.000) 2-tailed, while the correlation values are mostly weak and between 0.2 and 0.4, with the exception of the correlation between questions 9.6 and 9.7, which has a moderate strength (0.519). The questions mentioned above indicate the connection between the digital competences “Netiquette” and “Protection of health and well-being”.

4. Discussion

This study highlights significant generational differences in digital competences among Croatian youth, supporting the primary assumption of this research was that differences exist in media habits and digital competences among young people based on age and gender, and that certain media habits, such as time spent using digital content and related activities, influence perceived levels of digital competence.
Older or Generation Z demonstrated significantly higher levels of digital competences in protecting devices, managing digital identity and information literacy compared to Generation Alpha. These differences are likely stemming from increased time spent online and more frequent engagement in diverse digital activities among older participants. Similar results were obtained as part of the project conducted at a national level from 2021 to 2023 by the authors [43]. The results of this project indicate an increase in the amount of time (more than 4 h per week) that children (28%) and young people (35%) spend in front of the screen in the post-pandemic period. Also, another study [44] states that the most common activities on the internet are sending messages and conversations and listening to/watching music and videos, with differences confirmed between the different age groups of children. That is, the older the children are, the more active they are, from 49.6% (messaging) and 42.5% (videos) among respondents aged 9 to 11 to 89.8% (messaging) and 61.6% (videos) among respondents aged 15 to 17. So, older participants find themselves proficient in managing digital identities, protecting devices and critically evaluating online content, while Generation Alpha, immersed in digital environments from an early age, displayed gaps in advanced skills such as verifying the credibility of information and utilising security features like private browsing.
A gender difference was found in the results of the project, with girls spending significantly more time in front of screens, between 55% and 61% depending on age. They also always or often use a mobile phone to access the internet (93.5%), while they often or occasionally (60.6%) use a computer. They also never or rarely (78.3%) use a game console or tablet. But, contrary to research assumptions, no significant gender-based differences were identified across the three skill areas. This suggests that the digital divide between male and female youth in Croatia may be narrowing, reflecting greater equality in access to and use of digital technologies. Nevertheless, nuanced differences in specific activities, such as higher engagement in messaging and educational activities among girls and gaming among boys, highlight the influence of gendered preferences on digital behaviour [28,43,44,45]. Considering the overall results of the central (median) values of this research in all covered areas of digital competences and skills, it can be concluded that the majority of the respondents consider that they have above-average (answers 4 and 5) digital skills, which corresponds to Eurostat data [45]. In fact, compared to the EU average, the results for Croatia indicate that a greater number of individuals consider themselves to have digital skills above basic ones. Thus, in the field of competences of searching, filtering and evaluating information and digital content, which can be linked to the information and data literacy skills of the Digital Skills Indicator 2.0 (DSI) [46], 97.06% of individuals in Croatia demonstrate these skills, compared to 87.40% at the EU level. In the area of competences of protection and management of devices, identity and digital content, which can be considered as yDSI technical and operational skills, these results are 77.48% and 54.51% in favour of Croatian individuals aged 16 to 24. Finally, the competences of collaboration, interaction and content sharing through digital technologies correspond to the communication and collaboration skills of yDSI, where the results are 99% in Croatia and 94.35% in the EU.
The highest rated attitude of respondents (5 “Very applicable to me”) indicates the highest digital competences (over 75%) in the area of protecting devices and digital content and around 60% in the area of managing digital identities. With the same attitude, but in a lower percentage (from 40% to 70%), respondents rate the skills in the area of competences for searching and filtering data, information and digital content. In the area of collaboration and interaction with the help of digital technologies and the exchange of information, 70% to 75% of respondents have the highest attitude rating.
So, regarding the connections between media habits and perceived digital competences the results of the study can assume that frequent use of mobile phones for communication and information retrieval can result in higher competence levels in digital communication and information literacy. However, limited engagement in advanced digital activities, such as data management and critical evaluation, can be associated with lower proficiency in these areas.
These findings emphasise the need for more tailored strategies to address generational differences in digital competences [47]. Educational programmes should focus on fostering critical information literacy and security skills among Generation Alpha, leveraging interactive tools and age-appropriate content, while for Generation Z, initiatives could prioritise advanced competences, such as data management and ethical internet use, to prepare them for the challenges of a digital society [48].
Limitations of this study, due to the randomness of sample selection, while adequate in size and participant characteristics, can introduce potential selection biases. As the sample consisted of attendees at a specific science and IT technology event, which may have attracted individuals with above-average interest in and exposure to digital technologies, the findings can be subject to limited generalisability to the broader population of Croatian youth. Additionally, the sample’s distribution across age groups that can correspond to Generation Z and Alpha, while useful for comparative analysis, may vary according to different authors’ consensus on age range for a particular generation.
Expanding the geographic scope and including participants from varied socioeconomic and educational backgrounds would enhance the study’s applicability. Furthermore, incorporating objective assessments of digital competences alongside self-reported data would mitigate the influence of potential response biases and provide a more comprehensive understanding of digital literacy levels.

5. Conclusions

In this research, it was found that there is a statistically significant difference between the two generations of digital natives in the Republic of Croatia, both in most variables on the use of internet access devices and in the activities they perform when they are online. Such differences were not found between genders, except for a small part of the variables. When examining attitudes towards the acquisition of certain digital competences and skills according to the DigiComp 2.2 framework, statistically significant differences were found between the two generations in these competence dimensions:
1.1.
Browsing, searching and filtering data, information and digital content
1.2.
Evaluating data, information and digital content
2.1.
Collaborating through digital technologies
2.6.
Managing digital identity
4.1.
Protecting devices
4.3.
Protecting health and well-being
Despite the limited sample size and scope of this research, as well as the narrow focus on the dimensions of digital literacy, this study provides valuable insights into the differences in digital skills between two different age groups of digital natives. Also, the study’s integration of the yDSI and DigComp frameworks represents a significant methodological advancement in digital competence research. By linking these tools, the study offers a nuanced understanding of digital natives’ competences and provides actionable insights for improving digital literacy education in the future. The findings contribute to understanding how media habits influence competence development, offering actionable insights for educators and policymakers aiming to equip digital natives with the skills needed to thrive in a rapidly evolving technological landscape.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/informatics12010023/s1, File S1: Survey questionnaire.

Author Contributions

Conceptualization, D.P., M.A. and B.C.; methodology, D.P., M.A. and B.C.; validation, D.P. and M.A.; formal analysis, D.P.; investigation, B.C.; resources, D.P., M.A. and B.C.; data curation, D.P.; writing—original draft preparation, D.P., M.A. and B.C.; writing—review and editing, D.P., M.A. and B.C.; visualisation, D.P.; supervision, M.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the project “Application of VR technology and neural networks in the field of computer security and digital forensics” grant number NPOO2024-1. The project is financed by the Ministry of Science, Education, and Youth through EU funding (Recovery and Resilience Facility).

Institutional Review Board Statement

An ethical review was waived for this study as the authors determined that no ethical risk was involved. The research employed a methodology specifically designed and validated for investigating the digital competences of young individuals related to the governance of DigiComp, a standardised methodology in the EU. During the collection, storage and processing of data, the authors adhered to all ethical principles respecting “good research” practises of research integrity. In the context of compliance with local or national legislation regarding conducting research with minors, the Muzza committee assessed the conditions of participation in the fair to ensure research and ethical standards. Its approval is available upon request.

Informed Consent Statement

Informed consent for participation was obtained from all subjects involved in the study. For participants under the age of 15, their parents or guardians provided consent and access. The questionnaire was completed anonymously, and data protection and confidentiality measures were followed throughout the entire process of data analysis. The conditions of consent, or voluntary participation in the research, were communicated to participants before data collection. Respondents were apprised of the research objectives and potential risks involved in their participation. Information on the data controller was clearly stated throughout the entire process.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

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Table 1. Youth Digital Skills Indicator (yDSI) questions and the associated DigComp competences/skills.
Table 1. Youth Digital Skills Indicator (yDSI) questions and the associated DigComp competences/skills.
yDSI—Skill Area and SkillsDigComp
Code1. Technical and
Operational		CompetenceSkillsCode
7.1I know how to adjust privacy settings4.1. Protecting devices171. Manage passwords7.3
7.2I know how to turn off the location settings on mobile devices174. Managing access to personal data7.2
7.3
7.3I know how to protect a device (e.g., with a PIN, a screen pattern, a fingerprint, facial recognition)2.6. Managing digital identity111. Verify and modify what type of metadata is included in pictures being shared to protect privacy7.1
7.4I know how to store photos, documents or other files in the cloud (e.g., Google Drive, iCloud)112. Choose strategies to control, manage or delete data collected from online systems7.4
7.5I know how to use private browsing113. Modify user configurations to enable, prevent or moderate the AI system for tracking, collecting or analysing data7.1
7.2
7.5
7.6I know how to block unwanted pop-up messages or ads4.2. Protecting personal data and privacy183. Recognise suspicious e-mail messages that attempt to obtain sensitive information or may contain malware7.6
yDSI—Skill Area and skillsDigComp
2. Navigation and processing of informationCompetenceSkills
8.1I know how to choose the best keywords for online searches1.1. Browsing, searching and filtering data, information and digital content7. Improve search results by using the advanced features of a search engine8.4
8.2I know how to find a website I have visited before8. Formulate search queries to achieve the desired result when interacting with conversational agents or smart speakers8.1
8.3I know how to find information on a website no matter how it is designed9. Use information presented as hyperlinks, in non-textual form and in dynamic displays8.3
8.4I know how to use advanced search functions in search engines10. Develop effective search methods for personal and professional purposes8.2
8.5I know how to check if the information I find online is true11. Deal with information overload and the increase in false or misleading information by adapting my personal search methods and strategies8.5
8.6I know how to figure out if a website can be trusted1.2. Evaluating data, information and digital content25. Analyse and critically evaluate search results and social media activity streams to determine their origin, distinguish fact from opinion and assess the veracity or possible limitations of the results8.5
26. Tracking down the author or source of information to verify its credibility8.6
yDSI—Skill Area and skillsDigComp
3. Communication and interactionCompetencySkills
9.1Depending on the situation, I know which medium or tool to use to communicate with someone (e.g., make a call, send a WhatsApp message, send an email)2.4. Collaborating through digital technologies84. Use digital tools in a collaborative context to plan and share tasks and responsibilities within a group9.1
9.2I know when I should mute myself or disable video in online interactions2.1. Interacting through digital technologies47. Use a variety of video conferencing functions9.2
9.3I know which images and information of me it is OK to share online49. Use digital tools for informal communication with colleagues9.3
9.4
9.4I know when it is appropriate and when it is not appropriate to use emoticons (e.g., smileys, emojis), text speak (e.g., LOL, OMG) and capital letters2.2. Sharing through digital technologies58. Sharing digital content across multiple devices9.3
9.5I know how to report negative content relating to me or a group to which I belong60. Select and restrict who the content is shared with9.3
9.4
9.6I know how to recognise when someone is being bullied online63. Label or report disinformation and misinformation9.5
9.7I know how to recognise people with bad intentions on the internet (predators)2.5. Netiquette97. Stop receiving unwanted, disturbing messages or emails9.5
9.6
99. Recognise hostile or derogatory messages or activities9.6
100. Manage interactions and conversations in different socio-cultural contexts and domain-specific situations9.5
9.6
4.3. Protect health and well-being199. Apply and follow protection strategies to fight online victimisation9.7
Table 2. Participant demographics.
Table 2. Participant demographics.
Characteristics n%
Sample size231
Gender
Female11750.6
Male11449.4
Age group
10 to 15 years (Alpha)11047.6
16 to 24 years (Z)12152.4
Educational level
Elementary education11047.6
Secondary education3113.4
Higher education9039.0
Table 3. Comparison of age groups and gender with regard to time spent using the internet.
Table 3. Comparison of age groups and gender with regard to time spent using the internet.
Hours Per Day10–1516–24FM
n%n%n%n%
1–24743.654.12823.92421.1
3–65650.07562.06555.66657.9
7–1054.63024.81815.41714.9
>1121.8119.155.186.1
N110100%121100%117100%114100%
Mean27.5 30.5 29 28.6
SD26.18 30.35 26.04 25.92
t−0.18 (df = 6)0.02 (df = 6)
Table 4. Comparison of means and p-value between age groups and gender with regard to devices with access to the internet and the activities they perform.
Table 4. Comparison of means and p-value between age groups and gender with regard to devices with access to the internet and the activities they perform.
Device Used for Accessing the InternetMeanAgeMeanGender
10–1516–24pFMp
Computer 3.08 3.75 0.000 3.32 3.55 0.114
Mobile phone 4.24 4.74 0.000 4.61 4.39 0.009
Gaming console 1.85 1.63 0.090 1.52 1.96 0.008
Smart TV 3.04 2.41 0.000 2.82 2.60 0.175
Tablet 1.94 1.63 0.024 1.91 1.64 0.059
Activities on the Internet
Saving data to the cloud 2.07 2.85 0.000 2.55 2.41 0.296
e-mail 2.42 3.71 0.000 3.24 2.95 0.094
Searching for information for school needs 3.45 3.86 0.002 3.88 3.44 0.001
Messages and conversations 4.05 4.65 0.000 4.52 4.21 0.002
Listening to and watching music/videos 3.93 4.44 0.000 4.30 4.09 0.079
For playing 3.62 2.73 0.000 2.84 3.47 0.000
Information about anything and everything that interests me 3.62 4.25 0.000 3.97 3.93 0.863
Table 5. Obtained results and p-values for age groups with respect to the DigComp Competency in three yDSI taxonomy areas.
Table 5. Obtained results and p-values for age groups with respect to the DigComp Competency in three yDSI taxonomy areas.
CodeDigComp Competency MeanMedianMann–Whitney U Test
10–1516–2410–1516–24(p)
7.1 Managing digital identity 3.89 4.59 4 5 0.000
7.2 Managing digital identity
Protecting devices		4.34 4.73 5 5 0.000
7.3 Protecting devices 4.39 4.55 5 5 0.049
7.4 Managing digital identity 3.72 4.54 4 5 0.000
7.5 3.25 4.38 4 5 0.000
7.6 Protecting personal data and privacy4.06 4.38 5 5 0.094
8.1 Browsing, searching and filtering data, information and digital content 4.02 4.39 4 5 0.005
8.2 4.38 4.64 5 5 0.023
8.3 3.75 4.36 4 5 0.000
8.4 3.40 4.21 4 5 0.000
8.5 Evaluating data, information and digital content 3.72 4.08 4 4 0.026
8.6 Evaluating data, information and digital content 3.83 4.16 4 5 0.081
9.1Collaborating through digital technologies
Sharing information and content 		4.35 4.60 5 5 0.004
9.2 Interacting through digital technologies 4.39 4.61 5 5 0.053
9.3 Interacting through digital technologies4.62 4.66 5 5 0.859
9.4 Sharing information and content 4.49 4.60 5 5 0.203
9.5 Sharing information and content
Netiquette 		4.19 4.48 5 5 0.106
9.6 Netiquette 4.45 4.40 5 5 0.469
9.7 Protecting health and well-being 4.15 4.36 4 5 0.023
Table 6. Correlation of skills in the technical and operational area.
Table 6. Correlation of skills in the technical and operational area.
7.17.27.37.47.57.6
7.11 7.1Adjust privacy settings
7.20.3081 7.2Turn off the location settings on mobile devices
7.30.2590.3951 7.3Protect my device
7.40.4110.450.4441 7.4Store photos, documents or other files in the cloud
7.50.3560.3040.2990.5711 7.5Use private browsing
7.60.3220.370.320.470.39217.6Block unwanted pop-up messages or ads
Conditional formatting has been applied to the values, depending on the strength of the correlation.
Table 7. Correlation of skills in the navigation and processing of information area.
Table 7. Correlation of skills in the navigation and processing of information area.
8.18.28.38.48.58.6
8.11 8.1Choose the best keywords for online searches
8.20.2691 8.2Find a website that I have already visited
8.30.3720.4131 8.3Find information on a website no matter how it is designed
8.40.3270.3250.5551 8.4Use of advanced search functions in search engines
8.50.360.2880.4720.4861 8.5Check whether the information I find on the internet is true
8.60.3330.3170.5140.4050.53818.6Figure out if a website can be trusted
Conditional formatting has been applied to the values, depending on the strength of the correlation.
Table 8. Correlation of skills in the communication and interaction area.
Table 8. Correlation of skills in the communication and interaction area.
9.19.29.39.49.59.69.7
9.11 9.1Which medium or tool to use to communicate with someone
9.20.3551 9.2Mute myself or disable videos in online interactions
9.30.2710.2391 9.3Which images and information of me it is OK to share online
9.40.2860.2960.3631 9.4When it is and is not appropriate to use emoticons, spoken text
9.50.360.3240.2560.2861 9.5Report negative content relating to me or a group where I belong
9.60.3020.3090.2360.3050.3551 9.6Recognise when someone is being bullied online
9.70.3050.330.2560.2670.3830.51919.7Recognise people with bad intentions on the internet
Conditional formatting has been applied to the values, depending on the strength of the correlation.
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Pongrac, D.; Alić, M.; Cafuta, B. Digital Competences of Digital Natives: Measuring Skills in the Modern Technology Environment. Informatics 2025, 12, 23. https://doi.org/10.3390/informatics12010023

AMA Style

Pongrac D, Alić M, Cafuta B. Digital Competences of Digital Natives: Measuring Skills in the Modern Technology Environment. Informatics. 2025; 12(1):23. https://doi.org/10.3390/informatics12010023

Chicago/Turabian Style

Pongrac, Danijela, Marta Alić, and Brigitta Cafuta. 2025. "Digital Competences of Digital Natives: Measuring Skills in the Modern Technology Environment" Informatics 12, no. 1: 23. https://doi.org/10.3390/informatics12010023

APA Style

Pongrac, D., Alić, M., & Cafuta, B. (2025). Digital Competences of Digital Natives: Measuring Skills in the Modern Technology Environment. Informatics, 12(1), 23. https://doi.org/10.3390/informatics12010023

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