Most existing digital literacy scales trace their lineage to the European Commission’s Digital Competence Framework for Citizens, known as DigComp. The framework, first published in 2013 and most recently updated as DigComp 2.2 in 2022, breaks digital competence into five areas covering information and data literacy, communication and collaboration, digital content creation, safety, and problem solving. The researchers argue that while these frameworks are comprehensive in many respects, they underweight the cognitive machinery that underpins effective technology use. Computational thinking, a concept popularized by computer scientist Jeannette Wing in 2006, encompasses decomposition, pattern recognition, abstraction, and algorithm design, and is increasingly viewed as a foundational literacy rather than a specialist programming skill.

The omission matters, the authors contend, because computational thinking and lifelong learning are not merely academic abstractions. They are directly linked to an individual’s prospects in the digital economy and, by extension, to overall quality of life, the central concern of the journal in which the study appears. Prior research has connected digital skills to employment quality and life satisfaction, and international bodies including the OECD and the World Bank have warned that the changing nature of work will reward those who can adapt, learn continuously, and reason systematically with digital tools. A measurement scale that ignores these capacities, the team reasoned, offers an incomplete picture of whether students are genuinely prepared for the world they will graduate into.

To construct the new instrument, the researchers combined the updated DigComp 2.2 framework with China’s own digital literacy skills and certification standards, developed by the Computer Education Research Association of Chinese Universities. This dual grounding reflects a deliberate effort to blend an internationally recognized competency model with nationally relevant policy requirements, since China has made digital literacy promotion a formal policy priority through action outlines issued by the Central Cyberspace Affairs Commission in 2021 and subsequent annual work plans. The resulting scale organizes digital literacy into four dimensions: digital knowledge and skills, computational thinking, digital social responsibility, and digital learning and collaborative innovation.

The psychometric evaluation drew on responses from 970 first-year students at a Chinese application-oriented undergraduate university, an institution type that emphasizes practical, career-focused education. The team subjected the data to rigorous statistical testing, examining reliability and validity across the four hypothesized dimensions. The analysis, which employed structural equation modeling techniques appropriate for categorical response data, demonstrated strong reliability and validity, confirming that the 18 items hang together coherently within their intended factors and that the four-dimension structure fits the observed data. The researchers also reported evidence of convergent and discriminant validity following established criteria in the measurement literature, indicating that the scale measures what it claims to measure and distinguishes digital literacy from related but distinct constructs.

With the instrument validated, the team turned to the substantive question of who scores well and where the gaps lie. On gender, the findings were nuanced. Overall digital literacy showed no significant difference between male and female students, but the dimension-level results diverged in telling ways: male students outperformed female students in computational thinking, while female students excelled in digital social responsibility, the dimension covering ethical conduct, safety, and responsible participation in digital society. These contrasting profiles suggest that aggregate scores can mask meaningful differences in the specific competencies that compose digital literacy, and that interventions targeting computational thinking may need to address gendered patterns in confidence, exposure, or encouragement.

Regional disparities emerged as a second major finding. Students from urban backgrounds demonstrated significantly higher overall digital literacy than their rural counterparts, a result consistent with earlier Chinese studies that have documented gaps in digital media literacy between urban and rural primary school students. Notably, however, computational thinking showed no significant regional differences, suggesting that the cognitive dimension of digital literacy may be more evenly distributed than access-dependent skills such as device familiarity, software fluency, or online information evaluation. The researchers also found that only-child students exhibited significantly higher digital literacy than students with siblings, while computational thinking again showed no significant difference between the two groups, a pattern that may reflect differences in household resources and parental attention rather than underlying cognitive capacity.

The scale’s designers emphasize that the instrument is intended for practical deployment, not just academic description. Universities can use it to diagnose entering students’ strengths and weaknesses, guide targeted training programs, and optimize digital education strategies across curricula. Because the scale is compact at 18 items, it can be administered efficiently to large cohorts, making it feasible for institutions to track changes over time or evaluate the effectiveness of specific interventions. Beyond the campus, the researchers suggest the tool enables scholars to examine digital literacy disparities across regions, institutions, and academic disciplines, and to explore how digital literacy correlates with outcomes such as academic satisfaction, employability confidence, and broader quality-of-life indicators.

The study arrives at a moment when measurement frameworks themselves are evolving. A fifth edition of the European framework, DigComp 3.0, has been published, and the OECD together with the European Commission released an AI literacy framework for primary and secondary education in 2026, underscoring how quickly the competency landscape is shifting. The Chinese team’s decision to integrate computational thinking anticipates this trajectory, treating the ability to reason algorithmically and learn continuously as core components of digital citizenship rather than optional extensions. As generative artificial intelligence tools spread through higher education, the boundary between using technology and understanding it is becoming a critical dividing line, and instruments that can locate students on that boundary are likely to grow in importance.

The research also carries implications for equity. If urban students systematically outperform rural students in overall digital literacy while computational thinking remains evenly distributed, then policy interventions may be most effective when they target resource-dependent skills, such as access to devices, connectivity, and structured digital instruction, rather than assuming fixed cognitive differences. Similarly, the gendered pattern across dimensions points to the value of dimension-specific diagnostics over single composite scores. The authors note that all relevant data generated or analyzed during the study are available from the corresponding author on reasonable request, and the work was funded by a Xiamen City educational science research project focused on digital literacy measurement in application-oriented undergraduate universities. For educators and policymakers wrestling with how to prepare students for a digital decade, the study offers both a sharper lens and a reminder that what we choose to measure shapes what we choose to teach.

Subject of Research: Development and psychometric validation of a digital literacy scale for college students integrating computational thinking and lifelong learning

Article Title: Developing and Validating a Digital Literacy Scale Integrating Computational Thinking and Lifelong Learning for College Students

Article References: Guo, L., Zhang, M., Hu, Y., Wang, N., Yang, J., Li, C., & Zhu, L. (2026). Developing and Validating a Digital Literacy Scale Integrating Computational Thinking and Lifelong Learning for College Students. Social Indicators Research, 184(3), Article 55. https://doi.org/10.1007/s11205-026-03931-8

Image Credits: AI Generated

DOI: 10.1007/s11205-026-03931-8

Keywords: digital literacy, computational thinking, lifelong learning, scale development, psychometrics, college students, DigComp 2.2, digital social responsibility, urban-rural gap, gender differences, digital education, quality of life

The research team surveyed professionals working in public and private social services across Spain between June and August 2023. Participants completed an online questionnaire adapted from Spain’s Digital Competence Framework, itself aligned with the European DigComp 2.2 framework. The sample had an average age of 42.9 years and was predominantly female, with women representing 82.6% of respondents. Social Work was the main area of professional training, accounting for 76.7% of the sample, followed by Social Education and Psychology. Just over half worked in the public sector, while others were employed by third-sector organisations or private entities. The survey used 63 yes-or-no items distributed across five competence areas: information and data literacy, communication and collaboration, digital content creation, safety, and problem solving. Researchers converted the responses into standardised scores from zero to 100, then used hierarchical cluster analysis with Ward’s method and squared Euclidean distance to detect groups with similar patterns of competence.

Across the sample, average performance was approximately 70% in most areas, but the overall figures concealed pronounced differences between individuals. Communication and collaboration was the strongest dimension, indicating that routine digital messaging, media sharing, online procedures and basic interaction are widely established in professional practice. Digital content creation was the weakest area overall. The distinction matters because content creation involves more than producing ordinary documents: it can include selecting tools for a particular purpose, integrating material from different sources, managing web content, understanding licensing, using artificial intelligence and producing complex resources for others. The study also found substantial variation in problem solving, the capacity to diagnose and resolve technical difficulties without immediately relying on external support. Safety scores were generally adequate, particularly for passwords, digital certificates and secure transactions, although digital well-being and misinformation protection were less consistent. Information and data literacy showed a similar pattern: basic tasks were common, while analytical and more advanced uses of information were much less widespread.

Cluster analysis produced three groups with statistically significant differences across all five dimensions. The first, comprising 283 professionals, was described as a consolidating profile. Its average digital competence score was 72.15, close to the overall sample level, and its members had an average age of 41.8 years. About one-third held postgraduate qualifications, and employment was divided relatively evenly between the public sector and other organisations. This group was capable in routine communication and collaboration and could usually resolve basic technical problems, but its performance declined when tasks required more specialised content production, advanced analysis or creative uses of technology. Only 16.3% reported using artificial intelligence tools for content creation, while 19.8% managed website content and 17.0% could debug code. In problem solving, 91.2% could resolve basic technical issues independently, but only 47.7% reported creative uses of technology. The group’s self-assessment averaged 6.72 out of 10, lower than might be expected from its measured score, suggesting caution or awareness of the complexity of digital work.

The second group, containing 152 professionals, showed the strongest performance. This advanced profile had a mean competence score of 89.77 and was the youngest of the three groups, with an average age of 40.2 years. More than half held master’s or doctoral qualifications, and the group had a lower representation in the public sector than the other profiles. Its members performed strongly in every competence area, particularly in digital content creation and problem solving. Their mean score for content creation was 81.47, and their problem-solving score reached 93.26. Nearly all could address routine technical problems, while 97.4% reported responding proactively to their own digital needs and 99.3% to the needs of others. The group also showed the highest engagement with training or self-directed learning, reported by 90.8% of its members. Advanced capabilities were not limited to personal use: participants commonly helped colleagues search for and verify information, selected tools according to content needs, produced complex content for third parties and used digital resources for creative or civic purposes. Their self-perceived competence, 7.82 out of 10, was still below the level indicated by the broader assessment.

The third group, comprising 106 professionals, had the lowest measured competence, with a mean score of 52.62. Its members were older on average, at 49.5 years, had the longest average tenure in their current organisations, at approximately 15 years, and were predominantly employed in public administration. Only 20.6% held postgraduate qualifications. The largest gaps appeared in digital content creation and problem solving, where mean scores were 38.05 and 32.23, respectively. Fewer than half could solve a simple video-call problem or independently search online for a solution, and only 9.4% used technology creatively. Use of artificial intelligence tools for content creation was reported by 7.5%, while only 8.5% reported debugging programmes and 16.0% using smart-home technologies. Communication skills were also limited when tasks moved beyond essential functions: 16.0% co-edited documents and 21.7% could explain collaborative digital services to others. Safety was a relative strength, but weaknesses remained in app-permission management and protection against misinformation. This group rated its own competence at 5.93 out of 10, slightly higher than its measured performance, a mismatch that could reduce motivation to seek training.

Differences between the profiles were not merely statistical. The researchers calculated partial eta-squared values to estimate how much variation in each competence dimension was associated with cluster membership. The values ranged from 0.237 for safety to 0.619 for problem solving, with particularly strong separation in problem solving, content creation and communication. The results therefore point to distinct patterns of capability rather than a simple continuum in which every skill rises at the same rate. The advanced group was consistently above the sample average, while the constrained group was below it in all five dimensions. The consolidating group occupied an intermediate position, with notable competence in communication and collaboration but less confidence or experience with complex tasks. Item-level results also revealed that basic digital activity is not equivalent to digital maturity. For example, many professionals could organise files, exchange messages or use secure transactions, yet far fewer could analyse data, manage online content, apply artificial intelligence or create sophisticated solutions for colleagues and clients.

The findings have direct implications for social services, where professionals handle sensitive information about people’s finances, family circumstances, health, legal situations and use of support. Digital case-management platforms and interconnected regional systems can improve continuity and coordination, but they also raise demands for privacy, cybersecurity, ethical decision-making and careful communication. The authors argue that digital competence should therefore be treated as a professional requirement linked to service quality and the protection of users’ rights, not as an optional technical extra. They recommend strengthening foundational skills and learning networks for the constrained profile, helping the consolidating group progress toward advanced competence, and supporting advanced professionals as digital mentors or agents of organisational change. Training should also address digital well-being. The intermediate group reported particular difficulties with posture and screen-time control, illustrating how frequent technology use can coexist with occupational vulnerability and technostress. Sustainable digital transformation will require organisational investment, protected time for learning and policies that treat continuous development as a professional right rather than a one-time response to new software.

The study’s conclusions should be interpreted alongside its limitations. Because participation relied on an online questionnaire, the sample may overrepresent professionals already comfortable with digital tools. The instrument measured self-reported competence rather than performance observed in practical tasks, leaving room for self-efficacy and social-desirability bias. Spain’s decentralised social services system also varies across autonomous communities in administration, resources, infrastructure and organisational culture, but the available data did not allow those regional differences to be analysed in detail. Even so, the three-profile structure provides a useful framework for planning more precise interventions. The researchers call for regular competence assessments, longitudinal studies and evaluations conducted before and after training. Such work could show whether targeted programmes improve practical ability, reduce digital stress and strengthen service delivery without widening inequalities between organisations. As social services continue to adopt digital records, remote communication, automated processes and emerging artificial-intelligence tools, the central challenge will be ensuring that technological change expands professional capacity and client access rather than reproducing existing divisions inside the system.

Subject of Research: Digital competence profiles among social services professionals in Spain

Article Title: Assessment of digital competences: characterisation of professional profiles in Spanish social services

Article References: Gómez-Rasco, T., Fernández-Borrero, M. A., Muñoz-Moreno, R., & Ferri-Fuentevilla, E. (2026). Assessment of digital competences: characterisation of professional profiles in Spanish social services. SN Social Sciences, 6(9), Article 390. https://doi.org/10.1007/s43545-026-01666-4

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01666-4

Keywords: digital competence, social services, Spain, DigComp 2.2, digital skills, professional training, digital resilience, problem solving, digital well-being, Assessment, digital, competences