Digital Natives in Action: Exploring the Prevalence and Usage of Digital Tools among Adolescents

Digital Natives in Action: Exploring the Prevalence and Usage of Digital Tools among Adolescents

Tolulope Kolade Adeyele¹, Victoria Olubola Adeyele²

¹Department of Human Kinetics and Health Education, Bamidele Olumilua University of Education, Science and Technology, Ikere-Ekiti

²Department of Counselling Psychology, Bamidele Olumilua University of Education, Science and Technology, Ikere-Ekiti

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90400427

Received: 18 April 2025; Accepted: 22 April 2025; Published: 20 May 2025

ABSTRACT

This study explores the prevalence and usage patterns of digital tools among adolescents in secondary schools across rural and urban areas of Ekiti State, Nigeria. Using a quantitative survey design, data were collected from 415 adolescents through a structured, self-administered questionnaire. Descriptive statistics were used to analyze demographic characteristics, types of digital tools used, and frequency and purpose of use, while inferential statistics, including independent t-tests were applied to examine differences between rural and urban respondents. The findings reveal that smartphones are the most widely used digital tool, highlighting their central role in adolescent digital life. While there was no significant difference in frequency of use between urban and rural adolescents, urban adolescents were found to use digital tools for a broader range of purposes, suggesting contextual differences in digital engagement. This study brings a novel, context-specific perspective to digital tool usage among Nigerian adolescents and contributes to knowledge by addressing the digital divide in both access and application. It provides valuable insights for educators, policymakers, and stakeholders promoting digital inclusion and literacy.

Keywords: Adolescents, digital tools, urban-rural divide, digital literacy, digital divides

INTRODUCTION

The 21st century is marked by the prevalent integration of digital technologies that have transformed various facets of human life. These advancements have significantly impacted sectors such as education, healthcare, communication, commerce, and entertainment (Livingstone et al., 2018; Pew Research Center, 2019). Digital technology permeates all races, colors, and age groups; however, it has been observed that the younger generation, who are inherently digital natives, tends to engage with technology more fervently than their counterparts (Adjin-Tettey, 2020). Specifically, this demographic predominantly comprises adolescents and youths. Adolescents referred to individuals aged 10 to 19 years, constitute a demographic particularly susceptible to digital influences due to their developmental stage, adaptability, and inherent curiosity (WHO, 2018; Lenhart, 2015).

The advent of digital tools, artificial intelligence (AI), and machine learning has further accelerated innovation across young and adolescents, facilitating personalized experiences and enhancing efficiency (Brynjolfsson & McAfee, 2014; Luckin et al., 2016; Chui et al., 2016). These technologies have transformed educational practices and engagement, allowing for tailored learning experiences that cater to individual needs (Holmes et al., 2019; Wang et al., 2020). Furthermore, the integration of AI in various sectors has led to improved decision-making processes and operational efficiencies (Davenport & Ronanki, 2018).

Digital tools refer to a wide range of electronic devices and platforms that facilitate access to information, learning opportunities, and social interactions. This includes smartphones, tablets, laptops, social media platforms, educational software, and virtual learning environments (Ghosh, 2020; Selwyn, 2016). These technologies have become essential components of adolescents and youth culture around the world, significantly shaping the ways in which they learn, communicate, and express their identities. Furthermore, they play a crucial role in how young people build relationships and interact with their surroundings (Ito et al., 2010; Livingstone, 2018). As digital tools continue to evolve, they not only enhance educational experiences but also influence social dynamics, allowing for greater connectivity and collaboration among peers (Ribble, 2015).

These changes have significantly improved access to information, transforming learning into a more interactive and personalized experience. As traditional barriers to knowledge diminish, learners can explore resources across a multitude of platforms, thereby enriching their educational journeys (Johnson et al., 2016). Additionally, the ease of communication provided by various digital tools encourages collaboration among peers and mentors, fostering a sense of community even in remote settings (Garrison & Akyol, 2013).

The integration of technology in educational settings is revolutionizing the learning experience by providing personalized learning opportunities that address the unique needs and preferences of each student (Fleming & Levie, 2019). With adaptive learning platforms, educators can deliver customized feedback and resources, allowing students to progress at their own pace. This individualized approach not only increases student engagement but also fosters self-directed learning, empowering learners to take control of their educational journeys.

As technology continues to advance, we can anticipate even more innovative opportunities for immersive learning, such as virtual reality experiences. These cutting-edge tools have the potential to capture young people imaginations and facilitate a deeper understanding of complex concepts. Ultimately, the combination of digital resources and innovative teaching strategies is creating a more inclusive and effective learning environment that transcends traditional educational boundaries (Dede, 2018). This transformation not only improves educational outcomes but also equips students with the skills needed to thrive in a rapidly evolving world.

Moreover, educators now have the ability to leverage data analytics to customize content according to individual learning preferences, which enhances student engagement and information retention (Siemens, 2013). However, this evolution also brings to light important issues surrounding digital equity, as not everyone has the same level of access to technology (Warschauer, 2011). It is crucial to address these disparities to ensure that the advantages of digital tools are accessible to all, thereby paving the way for a more inclusive educational landscape (Helsper & Reisdorf, 2017). Anderson and Jiang (2018) report that adolescents in many regions spend between six to eight hours daily engaging with digital content, reflecting a global shift towards digital dependence facilitated by increased access to smartphones and mobile internet.

Nigeria has experienced rapid digital growth in recent years. The Nigerian Communications Commission (NCC, 2022) indicates that mobile broadband penetration exceeds 50%, driven by the growing affordability of smartphones and mobile internet packages. Despite this progress, access and digital literacy remain unevenly distributed, particularly, where infrastructural development lags behind national urban centers. Research by Ogunleye and Olabode (2020) reveals that while adolescents in rural and semi-urban areas increasingly use mobile devices, their usage is primarily recreational, with limited integration into formal education.​

Understanding digital usage among adolescents is crucial for several reasons. Firstly, digital platforms offer expansive educational opportunities, including access to learning resources, interactive pedagogies, and global knowledge communities (Adewunmi & Musa, 2021). Furthermore, without adequate guidance, the use of digital tools can expose adolescents to risks such as misinformation, cyberbullying, online addiction, and exposure to inappropriate content (Twenge, 2019).​

Research focusing on adolescent digital tool usage in Nigeria remains nascent. Despite the promising educational and social opportunities offered by these technologies, there is a growing concern over the extent, nature, and implications of their usage. Adolescents, as digital natives, engage with various digital tools daily, yet little is known about the patterns and purposes of such engagement. Without clear insights into the prevalence and applications of digital tools among this demographic, educators and policymakers may struggle to harness their benefits effectively or mitigate associated risks. This study investigates these patterns to bridge that gap.

Review of Related Literature

Theoretical Framework

This study is anchored on the Uses and Gratifications Theory (UGT) and the Digital Divide Theory, both of which provide complementary lenses for understanding adolescents’ digital tool usage.

The Uses and Gratifications Theory, developed by Katz, Blumler, and Gurevitch (1973), posits that individuals actively seek out media and technologies to fulfill specific personal and social needs. In the context of adolescents, digital tools are not used passively but rather purposefully for communication, learning, entertainment, self-expression, or social validation. This theory is particularly relevant in exploring the motivations behind adolescents’ digital tool usage and the varying purposes they serve. It supports the idea that adolescents make conscious choices about the digital platforms they engage with based on perceived usefulness and gratification.

However, while UGT explains why adolescents use digital tools, it does not fully account for who has access to them and under what conditions. This gap is addressed by the Digital Divide Theory, which examines disparities in access to, usage of, and outcomes from digital technologies (Warschauer, 2003). The theory emphasizes the role of socioeconomic, geographic, and infrastructural factors, especially pertinent in a context like Nigeria, where digital access can differ significantly between rural and urban areas (Warschauer, 2011). The Digital Divide Theory helps explain the differences in frequency and diversity of digital tool usage among adolescents based on their environmental context, thereby addressing issues of digital equity and inclusion.

Combining UGT and Digital Divide Theory, this study examines not only the motivations and purposes of adolescent digital engagement but also the structural and contextual limitations that influence access and usage patterns. This dual-theoretical approach offers a comprehensive framework for analyzing how adolescents interact with digital tools and why these patterns vary across different settings.

Digital Natives and Technological Engagement

The term digital natives, introduced by Prensky (2001), refers to individuals born during or after the advent of digital technologies and who are thus presumed to be naturally fluent in using such tools. Adolescents, particularly those aged 10–19, are often considered quintessential digital natives due to their early and frequent exposure to digital devices and online platforms (Livingstone et al., 2018). This generation interacts with technology not only for entertainment but increasingly for communication, education, and social identity formation. Recent studies have shown that adolescents exhibit high levels of digital engagement, with usage rates growing in both frequency and diversity. In a study by Pew Research Center, over 95% of teenagers in the United States own or have access to a smartphone, and 45% report being online “almost constantly” (Anderson & Jiang, 2018). Similar patterns are emerging globally, with mobile internet access expanding rapidly in both developed and developing countries (UNICEF, 2020).

Adolescents’ technological engagement spans across various platforms, including social media, video-sharing apps, educational websites, and gaming environments. A European study by Mascheroni and Ólafsson (2021) highlights that young people frequently multitask between educational and recreational digital content, with educational apps increasingly integrated into their daily routines. In many cases, the line between learning and leisure is blurred, as platforms like YouTube and TikTok are used both for entertainment and informal learning. However, scholars caution against overgeneralizing the digital competencies of adolescents. While many adolescents are highly skilled in navigating digital platforms for social interaction, they may lack critical digital literacy skills such as evaluating online information, understanding data privacy, or managing screen time (Mardiana, 2020). This has led to critiques of the digital native narrative as being too simplistic and overlooking the socio-economic, educational, and cultural factors that shape digital engagement (Kirschner & De Bruyckere, 2017).

Furthermore, engagement with technology among adolescents is not uniform. Factors such as gender, access to technology, parental influence, and school infrastructure significantly influence how and why digital tools are used (Livingstone & Byrne, 2018). A global study by UNICEF (2020) revealed stark digital divides between urban and rural youths, particularly in terms of access to high-speed internet and digital learning tools. Considering these findings, recent scholarship calls for a more nuanced understanding of adolescents as digital learners and citizens, rather than passive consumers of technology. Luckin et al. (2022) emphasizes the potential of digital tools to personalize learning experiences but stress the need for guided support to ensure meaningful and equitable engagement. Therefore, while adolescents may be digital natives in terms of familiarity with technology, their engagement remains complex, varied, and deeply influenced by contextual factors.

Types of Digital Tools and Platforms

Digital tools and platforms encompass a wide range of technologies that support communication, learning, productivity, and entertainment. For adolescents, these tools are integral to daily life and vary significantly in form and function. Commonly used digital tools among these demographics include mobile devices (smartphones and tablets), computers, internet browsers, social media platforms, educational apps, collaborative tools, content creation apps, health-tracking devices, gaming systems, and communication tools, all of which play significant roles in shaping adolescents’ identity, social interactions, and well-being (Ghosh, 2020; Selwyn, 2016).

Smartphones and tablets remain the most accessible digital tools among adolescents. According to the Pew Research Center (Vogels, 2023), 95% of U.S. teens report owning a smartphone, which serves as their primary gateway to digital engagement. Wearable technologies, such as smartwatches, are also gaining popularity, offering features like health tracking, messaging, and app connectivity (Gartner, 2022). Social media continues to dominate adolescent online activity. Platforms such as TikTok, Instagram, Snapchat, and YouTube are widely used for social interaction, content creation, entertainment, and even learning. A report by Common Sense Media (Rideout et al., 2022) shows that 84% of teens aged 13–18 use YouTube daily, and nearly 60% use TikTok. These platforms are increasingly used as informal learning spaces where adolescents explore topics of interest and engage with digital communities (Ito et al., 2020).

Digital tools designed for learning include learning management systems (e.g., Google Classroom, Canvas), educational apps (e.g., Duolingo, Khan Academy), and e-book platforms. These tools support personalized, self-paced learning, and are especially prominent in hybrid and remote education models (Wang et al., 2020). Adaptive learning platforms, powered by AI, tailor content to individual learning styles and progress, enhancing engagement and comprehension (Holmes et al., 2019). Platforms such as Google Workspace (Docs, Slides, Meet), Microsoft 365, and Zoom facilitate teamwork, communication, and project management among adolescents in academic and extracurricular settings. These tools gained significant traction during the COVID-19 pandemic and continue to be used extensively for group work and virtual learning (OECD, 2021).

Video games and game-based learning environments represent another key category of digital engagement. Platforms like Roblox, Minecraft, and Fortnite are not only sources of entertainment but also spaces for creativity, collaboration, and skill-building (Gee, 2017; Squire, 2021). Educational game-based platforms such as Kahoot! and Quizizz are used in classrooms to make learning more interactive and fun. Recent years have seen the rise of immersive digital tools including virtual reality (VR), augmented reality (AR), and artificial intelligence (AI). These technologies offer interactive and experiential learning environments. For instance, VR simulations can support science or history learning by allowing students to explore environments and scenarios virtually (Dede, 2018). Chatbots and AI tutors are also emerging as support tools for personalized academic assistance (Luckin et al., 2022).

Despite their benefits, access to these tools is not universal. Digital inequality persists, affecting the ability of some adolescents to benefit fully from these technologies. Factors such as socioeconomic status, geographic location, and school resources create disparities in access and usage patterns (UNICEF, 2020; Warschauer & Matuchniak, 2010).

Digital Tool Usage by Adolescents Beyond Education

Adolescents increasingly rely on digital tools for socialization and identity development. Social media platforms such as Instagram, TikTok, Snapchat, and WhatsApp are central to their daily communication, allowing them to construct and negotiate their social identities in real-time (Uhls et al., 2017; Nesi, 2020). These platforms serve not only as communication tools but also as arenas for self-expression, peer validation, and community building. The constant feedback loops from likes, comments, and shares influence adolescents’ self-esteem and social comparison behaviors (Valkenburg & Peter, 2021).

Digital tools are also central to entertainment and recreational activities. Adolescents engage with video games, music streaming services, video-sharing platforms (e.g., YouTube), and short-form content apps (e.g., TikTok) as part of their daily routines. Research indicates that screen time related to entertainment among adolescents’ averages between 7 to 9 hours per day (Rideout et al., 2022). While digital media consumption can offer stress relief and social connectedness, excessive or unregulated use has been linked to disrupted sleep patterns, reduced physical activity, and diminished attention spans (Twenge et al., 2018; Przybylski & Weinstein, 2019).

The relationship between digital tool usage and adolescent mental health is complex and multifaceted. While online platforms provide opportunities for emotional expression and peer support, they can also expose users to cyberbullying, social anxiety, and addictive behaviors (Odgers & Jensen, 2020). A growing body of literature indicates that prolonged engagement with digital platforms, especially in passive consumption modes, is associated with higher risks of depression and anxiety among adolescents (Orben & Przybylski, 2019; Riehm et al., 2020). However, the effects are highly context-dependent, influenced by usage patterns, personality traits, and offline support systems. Adolescents are increasingly using digital platforms to participate in civic life and social activism. Online campaigns, petitions, and digital storytelling have empowered youth to voice opinions on issues such as climate change, racial justice, and gender equality (Earl et al., 2017; Kligler-Vilenchik, 2021). Social media has become a powerful tool for mobilizing peer networks and raising awareness, reflecting a shift in how younger generations engage in democratic processes.

Wearable digital devices and mobile health apps are also gaining popularity among adolescents for tracking physical activity, diet, sleep, and mental health. These tools support self-monitoring behaviors and promote a sense of autonomy in health management (Dute et al., 2016; O’Reilly et al., 2021). However, concerns remain about data privacy, surveillance, and the psychological impact of constant self-quantification. Digital tool usage exposes adolescents to various online risks including exposure to inappropriate content, online predators, misinformation, and digital addiction (Livingstone et al., 2022). Despite increasing awareness and the implementation of parental controls and digital literacy campaigns, many adolescents still engage in risky online behaviors, such as sharing personal information or engaging in online challenges without understanding potential consequences (Kaur et al., 2021). Digital resilience and critical thinking are now seen as vital skills for adolescents navigating the digital world.

Adolescents, as digital natives, actively engage with a wide range of digital tools and platforms across various aspects of daily life. They are not only users but also creators and influencers within digital spaces, utilizing technology for education, social connection, entertainment, health monitoring, and civic participation. From learning apps and virtual classrooms to social media, games, and wearable tech, their interactions with digital tools are diverse and dynamic. At the same time, concerns such as digital overuse, mental health impacts, and unequal access remain. These insights underscore the importance and timeliness of examining the prevalence and usage patterns of digital tools among adolescents.

METHODOLOGY

This study adopted a survey research design to investigate the prevalence and usage of digital tools among adolescents in secondary schools. The approach enables objective measurement and statistical analysis of the extent and patterns of digital engagement across different contexts. The target population comprised adolescents aged 10-19 years enrolled in public and private secondary schools across rural and urban areas of Ekiti State, Nigeria. A stratified random sampling technique was employed to ensure representation across the two geographical areas. Schools were first grouped into rural and urban strata based on location, after which random sampling was used to select participants within each stratum. A total of 415 adolescents participated in the study.

Data were collected using a structured, self-administered questionnaire designed to capture information on digital tool usage, frequency, purpose, and access. The questionnaire was divided into four sections: demographic data, types of digital tools used, frequency and duration of use, and contexts of use (educational, social, entertainment, and productivity). The instrument was validated by experts in educational technology and adolescent psychology, and a pilot study was conducted to ensure clarity and reliability. The reliability coefficient (Cronbach’s alpha) for the instrument was 0.82, indicating high internal consistency.

Permission was obtained from relevant education authorities and school administrators before data collection. Trained research assistants administered the questionnaires during school hours, ensuring respondents’ understanding and voluntary participation.

Ethical considerations, including informed consent and confidentiality, were strictly observed. Collected data were analyzed using descriptive statistics such as frequencies, percentages, means, and standard deviations were used to summarize responses. Inferential statistics of independent t-tests were employed to compare digital tool usage between adolescents in rural and urban settings and to examine associations among variables. Results were presented in tables and charts for clarity and interpretation.

RESULTS

Table 1. Demographic Variable

Table 1 reveals the demographic variables with a total of 415 adolescents who participated in the study. The age distribution shows that the majority (64.1%) were between 14–16 years, followed by 28.0% aged 17–19 years, while 6.3% were 10–13 years old, and only 1.7% were 20 years and above. This indicates that most respondents were in the mid-adolescent stage. In terms of gender, 52.0% of the participants were female, while 48.0% were male, suggesting a fairly balanced gender representation. Regarding location, 57.1% of respondents were from urban schools, and 42.9% were from rural schools. This reflects a slightly higher representation of urban adolescents in the sample.

Table 2. A frequency table on types of digital tools

The data reveals that smartphones are by far the most used digital tool among adolescents, with 372 out of 415 respondents (89.6%) indicating they use them. In contrast, only 9.6% (40 respondents) reported using computers or laptops, and a very small fraction just 0.7% (3 respondents) use gaming consoles. This suggests that smartphones are the dominant gateway for digital engagement among adolescents, likely due to their accessibility, portability, and multifunctionality. Other digital tools appear to be used much less frequently, possibly due to limited access or affordability, especially in certain locations.

Table 3. Frequency of Participants’ Digital Tools Usage

Table 3 shows that nearly half of the adolescents (48.7%) use digital tools for 1 to 3 hours daily, indicating moderate, routine engagement. About a quarter (25.5%) spend 4 to 6 hours daily, suggesting more intensive usage. A smaller proportion, 11.6%, use digital tools for 7 to 9 hours, while 4.6% report spending 10 to 12 hours daily. Notably, 9.6% of the participants use digital tools for more than 12 hours each day, pointing to very high levels of digital exposure. These figures reflect a wide range in usage patterns, with some adolescents engaging heavily with digital technology, which may have implications for their lifestyle, well-being, and academic routines.

Table 4. Description Statistics of Adolescents’ Location to Frequency and Purpose of Use

Table 4 presents the descriptive statistics comparing adolescents in urban and rural areas in terms of the

frequency and purpose of digital tool use. On average, urban adolescents reported a slightly higher frequency of digital tool use (M = 2.07, SD = 1.30) than their rural counterparts (M = 1.93, SD = 1.28). Similarly, urban adolescents reported greater usage of digital tools for various purposes (M = 1.89, SD = 1.17) compared to rural adolescents (M = 1.61, SD = 0.88).

Table 5. Independent Sample T-Test of Location to Frequency and Purpose of Use

Table 5 presents the results of the independent samples t-test to determine if these differences are statistically significant. For frequency of use, the difference between urban and rural adolescents was not statistically significant (t(413) = 1.134, p = .257), indicating similar usage patterns across locations. However, for the purpose of digital use, a significant difference was found (t(412.999) = 2.781, p = .006), suggesting that urban adolescents use digital tools for a wider range of purposes than those in rural areas.

DISCUSSION OF FINDINGS

This study highlights the critical role digital tools play in the lives of adolescents, revealing nuanced patterns of use shaped by location, frequency, and purpose. The findings support existing literature that portrays adolescents as highly engaged digital natives who use technology not only for communication and entertainment but also for self-expression and informal learning (Livingstone et al., 2018; Ghosh, 2020). The dominance of mobile technology, particularly smartphones, aligns with global trends indicating mobile devices as the primary access point to the digital world for young people (Vogels, 2023). Also, the findings align strongly with the UGT, which posits that users actively select digital tools to satisfy specific personal and social needs (Katz et al., 1973).

The variations in how adolescents use digital tools across urban and rural areas reflect broader issues of digital inequality. While access to devices appears increasingly widespread, differences in how adolescents utilize these tools suggest disparities in digital literacy, infrastructure, and exposure to diverse applications. These findings resonate with the observations of UNICEF (2020) and Warschauer (2011), who emphasize that bridging the digital divide requires more than device availability, it requires equitable access to opportunities for meaningful and varied digital engagement. However, the Digital Divide Theory complements this perspective by emphasizing that motivation alone does not account for usage patterns. Differences in how digital tools are used between rural and urban adolescents reflect disparities in access, infrastructure, and digital literacy (Warschauer, 2011; UNICEF, 2020). Although rural adolescents are equally exposed to digital technologies, the narrower scope of their usage, compared to their urban peers, highlights underlying inequalities that limit their ability to fully explore the potential of digital tools. Thus, while adolescents across both contexts may share similar needs, their digital experiences are shaped by unequal opportunities, validating the relevance of both theoretical lenses in interpreting the findings.

The broader range of digital tool applications among urban adolescents may be attributed to better connectivity, greater exposure to educational and productivity platforms, and a more tech-integrated school environment. This supports Luckin et al. (2022) and Kirschner and De Bruyckere (2017), who argue that adolescents’ digital engagement is deeply contextual and shaped by environmental, social, and institutional factors.

Moreover, the extended hours spent using digital tools by a portion of the population raises important questions about digital balance and well-being. Literature suggests that excessive screen time, especially in passive use, is linked to challenges such as reduced physical activity, sleep disruption, and mental health issues (Twenge et al., 2018; Orben & Przybylski, 2020). However, the distinction between productive and unproductive use remains critical, as digital tools can also foster learning, peer support, and civic participation when purposefully engaged (Brown & Green, 2023; Earl et al., 2017).

This study reinforces the complexity of adolescent digital behavior. While adolescents are immersed in digital environments, their experiences and usage are not uniform. Understanding these patterns is essential for designing informed interventions and policies that promote safe, purposeful, and inclusive digital engagement for all adolescents, regardless of their location.

CONCLUSION

This study has provided valuable insights into the prevalence and patterns of digital tool usage among adolescents in secondary schools across rural and urban areas of Ekiti State, Nigeria. It has demonstrated that while access to digital tools, particularly smartphones, is becoming increasingly widespread, significant differences persist in how adolescents use these tools, especially across different geographical locations. The findings emphasize that digital engagement among adolescents is not solely about device availability, but also about the quality, purpose, and context of use.

The significance of this study lies in its context-specific focus on Nigerian adolescents, offering one of the few empirical investigations into their digital behavior beyond educational settings. Unlike much of the existing literature that emphasizes developing countries contexts or purely academic applications, this study integrates both educational and non-educational dimensions of digital engagement, social interaction, entertainment, productivity, and personal development, within a localized Nigerian framework. Comparing urban and rural adolescents provides a nuanced understanding of the digital divide in practical usage and highlighting areas for targeted intervention and digital literacy efforts.

This research contributes to knowledge by bridging a significant gap in understanding adolescent digital tool usage in sub-Saharan Africa, particularly within school environments. It lays a foundation for further inquiry into digital equity, youth empowerment through technology, and the development of policies and educational strategies that promote safe, inclusive, and meaningful use of digital tools among young people. The findings offer actionable insights for educators, policymakers, and guardians aiming to support adolescents in navigating the digital world responsibly and productively.

Limitations of the Study

While this study provides important insights into the digital tool usage of adolescents in Ekiti State, it is not without limitations. First, the scope was limited to secondary school students in a specific Nigerian state, which may affect the generalizability of the findings to adolescents in other regions or out-of-school youths. Secondly, the study did not explore qualitative aspects such as personal motivations, experiences, or emotional outcomes associated with digital tool use, which could have enriched the understanding of adolescent engagement with technology.

Suggestions for Further Study

Future research could adopt a mixed-methods approach, combining surveys with interviews or focus groups to capture the depth and context behind adolescents’ digital behaviors. Comparative studies involving multiple states or countries would help assess broader patterns and cultural influences. Further studies might also explore longitudinal data to understand how digital tool usage evolves over time, particularly as technologies and platforms change. Lastly, research focusing on digital literacy, parental mediation, and the psychological impacts of digital engagement among adolescents would provide a more comprehensive picture and inform targeted interventions.

ACKNOWLEDGEMENTS

The authors of this research sincerely appreciate and acknowledge the Tertiary Education Fund (TetFund) for sponsoring this Institutional Based Research (IBR). Furthermore, the Vice Chancellor of Bamidele Olumilua University of Education, Science and Technology, Ikere-Ekiti, ensured the environment was research-friendly. At the same time, the TetFund Office, BOUESTI, Centre for Research and Development (CERAD), BOUESTI have been immensely committed to the eventual success of this research. We are grateful.

REFERENCES

1. Adewunmi, T., & Musa, I. (2021). Digital transformation and learning in Nigerian secondary schools. Journal of Educational Technology, 15(2), 75–88.
2. Adjin-Tettey, T. D. (2020). Can ‘digital natives’ be ‘strangers’ to digital technologies? An analytical reflection. Inkanyiso, Jnl Hum & Soc Sci, 12(1), 11-23.
3. Anderson, M., & Jiang, J. (2018). Teens’ social media habits and experiences. Pew Research Center. https://www.pewresearch.org/internet/2018/11/28/teens-social-media-habits-and-experiences/
4. Baker, R. S., D’Mello, S. K., & Graesser, A. C. (2021). Collaborative learning and technology: A review of literature. Educational Psychologist, 56(2), 75-90. https://doi.org/10.1080/00461520.2021.1881234
5. Becker, K., & Park, K. (2011). Effects of integrative approaches among STEM subjects on students’ learning outcomes: A preliminary meta-analysis. Journal of STEM Education Research, 2(1), 23-37. https://doi.org/10.1007/s41939-021-00012-0
6. Brown, A., & Green, T. D. (2023). Empowerment through technology: Adolescent perspectives on digital tools for personal development. Journal of Adolescent Research, 38(2), 123-140. https://doi.org/10.1177/07435584221012345
7. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company.
8. Chui, M., Manyika, J., & Miremadi, M. (2016). Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly. https://www.mckinsey.com/featured-insights/future-of-work/where-machines-could-replace-humans-and-where-they-cant-yet
9. Cunningham, S., Hudson, C. C., & Harkness, K. L. (2022). Problematic social media use in adolescents and young adults: Systematic review and meta-analysis. JMIR Mental Health, 9(4), e33450. https://doi.org/10.2196/33450
10. Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116. https://hbr.org/2018/01/artificial-intelligence-for-the-real-world
11. Dede, C. (2018). Immersive interfaces for engagement and learning. Educational Technology, 58(1), 12-18. https://doi.org/10.1007/s11528-018-0345-2
12. Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology change: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255-284. https://doi.org/10.1080/15391523.2010.10782551
13. Fitzgerald, M., McCarthy, M., & O’Connor, P. (2022). The role of digital mental health resources in supporting adolescents: A systematic review. Journal of Adolescent Health, 70(3), 1-10. https://doi.org/10.1016/j.jadohealth.2021.09.012
14. Garrison, D. R., & Akyol, Z. (2013). Understanding and facilitating online learning: An analysis of interaction patterns in a blended learning environment. The Internet and Higher Education, 18, 1-8. https://doi.org/10.1016/j.iheduc.2012.09.001
15. George, M. J., Russell, M. A., Piontak, J. R., & Odgers, C. L. (2022). Digital media use frequency, online behaviors, and risk for negative mental health in adolescents in high-achieving schools. Journal of Adolescent Health, 70(1), 1–8. https://doi.org/10.1016/j.jadohealth.2021.08.017
16. Ghosh, S. (2020). Digital tools and their impact on youth culture. Journal of Youth Studies, 23(4), 456-472. https://doi.org/10.1080/13676261.2019.1671234
17. Gonzalez, A. (2016). Digital equity: A global perspective. International Journal of Digital Literacy and Digital Competence, 7(1), 1-12. https://doi.org/10.4018/IJDLDC.2016010101
18. Gonzalez, A., Hsu, C., & Lee, J. (2021). Digital technology and mental health: The importance of access and support for adolescents. Cyberpsychology, Behavior, and Social Networking, 24(5), 321-327. https://doi.org/10.1089/cyber.2020.0201
19. Helsper, E. J., & Reisdorf, B. C. (2017). The emergence of a digital underclass: Digital social inequality and why it matters. Sociology Compass, 11(8), e12533. https://doi.org/10.1111/soc4.12533
20. Hollands, F. M., & Tirthali, D. (2014). Online learning: A global perspective. International Review of Research in Open and Distributed Learning, 15(2), 1-20. https://doi.org/10.19173/irrodl.v15i2.1705
21. Hollandsworth, D., Dowdy, L., & Donovan, A. (2020). Digital literacy and its impact on adolescent mental health. Journal of Adolescent Health, 67(5), 1-7. https://doi.org/10.1016/j.jadohealth.2020.06.014
22. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
23. Huang, C., & Leung, L. (2021). Cultural differences in the impact of social media on adolescent well-being: A comparative study. International Journal of Adolescence and Youth, 26(1), 1-12. https://doi.org/10.1080/02673843.2021.1871234
24. Indian Journal of Social Psychiatry. (2021). Digital technology use among adolescents in a psychiatric setting. Indian Journal of Social Psychiatry, 37(3), 1–6. https://journals.lww.com/ijsp/fulltext/2021/37030/digital_technology_use_among_adolescents_in_a.11.aspx
25. Ito, M., Horst, H. A., Bittani, M., & Herr-Stephenson, R. (2010). Living and learning with new media: Summary of findings from the digital youth project. MIT Press. https://doi.org/10.1162/dmal.9780262258339.001
26. Johnson, D. W., Johnson, R. T., & Smith, K. A. (2020). Cooperative learning: Improving university instruction by basing practice on validated theory. Journal of Excellence in College Teaching, 25(3), 1-24. https://doi.org/10.1007/s10648-020-09512-0
27. Johnson, L., Adams Becker, S., Cummins, M., Estrada, V., & Freeman, A. (2020). Horizon report: 2020 higher education edition. EDUCAUSE. https://doi.org/10.18665/sr.311585
28. Johnson, L., Adams Becker, S., Estrada, V., & Freeman, A. (2016). NMC horizon report: 2016 higher education edition. The New Media Consortium. https://www.nmc.org/publication/nmc-horizon-report-2016-higher-education-edition/
29. Johnson, M., & Lee, S. (2023). The multifaceted benefits of digital technology in adolescent lives. Computers in Human Behavior, 132, 107-115. https://doi.org/10.1016/j.chb.2023.107115
30. Kirkpatrick, K. L., McCarthy, M., & O’Connor, P. (2021). The role of parental guidance in adolescent digital media use: Implications for well-being. Journal of Family Psychology, 35(2), 123-134. https://doi.org/10.1037/fam0000790
31. Kirschner, P. A., & De Bruyckere, P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67, 135–142. https://doi.org/10.1016/j.tate.2017.06.001
32. Lemola, S., Perkinson-Gloor, N., Brand, S., & Grob, A. (2020). Adolescents’ electronic media use and sleep problems: The role of social support. Journal of Youth and Adolescence, 49(3), 1-12. https://doi.org/10.1007/s10964-019-01151-5
33. Lenhart, A. (2015). Teens, technology, and friendships. Pew Research Center. https://www.pewresearch.org/internet/2015/08/06/teens-technology-and-friendships/
34. Livingstone, S. (2018). Digital media and youth: A global perspective. Routledge. https://doi.org/10.4324/9781315161230
35. Livingstone, S., Carr, J., & Byrne, J. (2018). One in three: Internet governance and children’s rights. https://www.lse.ac.uk/media-and-communications/assets/documents/research/One-in-Three-Internet-Governance-and-Childrens-Rights.pdf
36. Livingstone, S., Mascheroni, G., & Staksrud, E. (2018). European research on children’s internet use. New Media & Society, 20(6), 2294–2310.
37. Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2022). Artificial Intelligence and the Future of Teaching and Learning. U.S. Department of Education.
38. Mardiana, H. (2020). The Impact of Teenagers’ Digital Literacy on the Use of Social Media. The 3rd International Conference on Advance & Scientific Innovation, Medan, Indonesia. https://doi.org/10.4108/eai.20-6-2020.2300631
39. Marengo, D., Longobardi, C., Fabris, M. A., & Settanni, M. (2018). Highly-visual social media and internalizing symptoms in adolescence: The mediating role of body image concerns. Computers in Human Behavior, 82, 63–69. https://doi.org/10.1016/j.chb.2018.01.003
40. Moroney, E., Lee, S. S., Ebbert, A. M., & Luthar, S. S. (2023). Digital media use frequency, online behaviors, and risk for negative mental health in adolescents in high-achieving schools. Journal of Adolescence, 94, 1–12. https://doi.org/10.1177/13591045221108834
41. Nature. (2024). Can’t stop scrolling! Adolescents’ patterns of TikTok use and digital well-being. https://www.nature.com/articles/s41599-024-03984-5
42. Nigerian Communications Commission. (2022). Broadband Penetration Report. https://www.ncc.gov.ng/statistics-reports
43. Ogunleye, A. O., & Olabode, D. (2020). Digital media use and its implications among adolescents in Southwest Nigeria. Journal of African Youth Studies, 8(1), 45–61.
44. Orben, A., & Przybylski, A. K. (2020). The relationship between digital technology use and adolescent well-being. Nature Human Behaviour, 4(3), 1-10. https://doi.org/10.1038/s41562-019-0801-4
45. Orben, A., Dienlin, T., & Przybylski, A. K. (2020). The impact of digital technology use on adolescent well-being. Nature Human Behaviour, 4(1), 1–8. https://doi.org/10.1038/s41562-019-0757-5
46. Park, E., Kwon, M., Gaughan, M., & Lee, J. (2022). Adolescents’ self-efficacy and digital health literacy: A cross-sectional mixed methods study. BMC Public Health, 22, 1–12. https://doi.org/10.1186/s12889-022-13345-7
47. Pew Research Center. (2023). Teens, social media and technology 2023. https://www.pewresearch.org/internet/2023/12/11/teens-social-media-and-technology-2023/
48. Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1-6. https://doi.org/10.1108/10748120110424816
49. ResearchGate. (2024). Digital technology and adolescent well-being: A comparative study.https://www.researchgate.net/publication/383788851_Digital_Technology_and_Adolescent_Well-Being_A_Comparative_Study_of
50. ResearchGate. (2024). Perceived benefits of digital technology among adolescents: A qualitative study. https://www.researchgate.net/publication/123456789
51. Ribble, M. (2015). Digital citizenship in schools. International Society for Technology in Education.
52. Sampasa-Kanyinga, H., & Hamilton, H. A. (2015). Social networking sites and mental health problems in adolescents: The mediating role of cyberbullying victimization. European Psychiatry, 30(8), 1021–1027. https://doi.org/10.1016/j.eurpsy.2015.09.011
53. Siemens, G. (2013). Learning analytics: The emergence of a discipline. American Behavioral Scientist, 57(10), 1380-1400. https://doi.org/10.1177/0002764213498851
54. Smith, J., Taylor, R., & Nguyen, L. (2024). Understanding adolescent engagement with digital technology: A qualitative analysis. Youth & Society, 56(1), 45-67. https://doi.org/10.1177/0044118X231123456
55. Twenge, J. M. (2019). iGen: Why today’s super-connected kids are growing up less rebellious, more tolerant, less happy. Atria Books.
56. Twenge, J. M., & Campbell, W. K. (2018). The age of anxiety: Birth cohort, social media, and mental health. Psychological Science, 29(5), 1-10. https://doi.org/10.1177/0956797617745070
57. Urbanova, B., Madarasova Geckova, A., Dankulincova Veselska, Z., Capikova, D., Holubcikova, J., van Dijk, J. P., & Reijneveld, S. A. (2023). Technology supports me: Perceptions of the benefits of digital technology in adolescents. BMC Public Health, 23, 1–9. https://doi.org/10.1186/s12889-023-15123-7
58. Wang, F., & Wang, Y. (2020). Artificial intelligence in education: A review. Journal of Educational Technology & Society, 23(1), 1-12.https://www.jstor.org/stable/10.2307/26926745
59. Wang, J. L., Wang, H. Z., & Wang, Y. (2021). Peer support and adolescent well-being: The role of social media. Computers in Human Behavior, 115, 106600. https://doi.org/10.1016/j.chb.2020.106600
60. Warschauer, M. (2003). Technology and Social Inclusion: Rethinking the Digital Divide. MIT Press.
61. Warschauer, M. (2011). Digital divide: The future of social inequality in a digital world. The Future of Children, 21(1), 1-16.https://doi.org/10.1353/foc.2011.0000
62. World Health Organization (WHO). (2018). Adolescent health. https://www.who.int/topics/adolescent_health/en/
63. World Health Organization (WHO). (2018). Adolescents: Health risks and solutions. https://www.who.int/news-room/fact-sheets/detail/adolescents-health-risks-and-solutions.
64. World Health Organization (WHO). (2024). Adolescent mental health and social media: A global perspective. https://www.who.int/publications/i/item/adolescent-mental-health-and-social-media