School Climate Emerges as Hidden Engine of Digital Transformation in Classrooms

A massive international study of more than 35,000 teachers has revealed that the secret to getting technology genuinely used in classrooms may not lie in devices, software, or even training alone, but in something far less tangible: the social atmosphere of the school itself. Researchers Ji Liu, Emmanuel Nana Kwesi Ofori Darko, and Millicent Aziku of Shaanxi Normal University analyzed data from the OECD’s Programme for International Student Assessment (PISA) 2022 and found that a supportive school climate acts as a measurable conduit through which digital preparedness translates into real digital integration in teaching. The findings, published in the Journal of New Approaches in Educational Research, suggest that schools pouring money into laptops and connectivity may be leaving a critical ingredient out of their digital transformation strategies.

The research team set out to answer a question that has long frustrated educational technologists: why do some schools with abundant digital resources fail to see teachers actually use them, while others with modest infrastructure achieve remarkable integration? Drawing on the Technology Acceptance Model, a foundational framework in information systems research that explains how individual perceptions shape technology adoption, the authors extended the model to the institutional level. They call this adaptation the school Technology Acceptance Model, or sTAM. The central insight is that a school’s willingness to embrace digital technology is not simply the sum of individual teacher attitudes; it emerges from collective norms, collegial trust, and organizational structures that either amplify or suppress each teacher’s readiness to change.

To test this idea, the researchers constructed a school-teacher matched dataset from PISA 2022, screening an initial pool of 68,048 subjects down to 35,108 who met strict inclusion criteria: completed background questionnaires, matched teacher-to-school identification, and full responses on modules covering digital preparedness, school climate, and digital integration. The final sample included 19,853 female and 15,255 male teachers, with an average age of 43.8 years and an average of 17.6 years of work experience. Roughly 73 percent held a bachelor’s degree or below, while about 27 percent had attained a master’s degree or higher. Two-thirds of the teachers held permanent contracts, and more than three-quarters possessed full certification, painting a picture of an experienced, established professional workforce.

The three key constructs were each measured with validated scales. Digital preparedness captured whether schools prepare digital materials for remote instruction and online assessment, and whether they ensure that students and teachers have access to digital devices and resources. School climate was assessed through five items probing professional trust: whether teachers can rely on school management for support, whether principals trust their expertise, and whether colleagues depend on one another in difficult situations. Digital integration, the outcome variable, spanned fourteen items measuring how frequently teachers use tutorial software, presentation tools, learning games, information resources, simulation software, and data-logging tools in their lessons. All three scales showed excellent internal consistency, with Cronbach’s alpha values ranging from 0.858 to 0.920.

The analytical engine of the study was partial least squares structural equation modeling, or PLS-SEM, a statistical technique well suited to estimating complex models with multiple latent variables in very large datasets. Unlike covariance-based approaches, PLS-SEM does not impose strict assumptions about data normality, making it appropriate for the sprawling, cross-national PISA sample. Model fit indices provided strong support for the hypothesized structure: the standardized root mean square residual was just 0.017, far below the conventional 0.08 threshold, and the normed fit index reached 0.984, comfortably above the recommended 0.90 benchmark. Discriminant validity checks using the heterotrait-monotrait ratio and the Fornell-Larcker criterion confirmed that the three constructs were statistically distinct.

The results were striking in their consistency. Digital preparedness showed a significant positive direct effect on digital integration, with a standardized coefficient of 0.201, and a smaller but significant positive effect on school climate at 0.075. School climate, in turn, predicted digital integration with a coefficient of 0.179. Most importantly for the study’s central hypothesis, the indirect pathway from digital preparedness through school climate to digital integration was significant, with a standardized coefficient of 0.013. The total effect of digital preparedness on integration was approximately 0.214, meaning roughly six percent of that total effect flowed through the mediating channel of school climate. All four of the study’s hypotheses were supported by the data.

Skeptics might dismiss a coefficient of 0.013 as trivially small, but the authors argue that in large-scale educational systems, small effects carry substantial policy weight. When applied across thousands of schools and tens of thousands of teachers, even modest improvements in school climate linked to digital investment can accumulate into system-wide gains in teaching practice and student learning. The researchers also conducted a rigorous sensitivity analysis using Stata’s survey estimation procedures, incorporating PISA’s sampling weights, clustering, and stratification variables. The intraclass correlation coefficient of 0.279 indicated that a substantial share of the variance in digital integration occurs between schools rather than within them. Under this design-based analysis, the weighted estimates grew even stronger: digital preparedness predicted school climate at 0.096 and digital integration at 0.255, while the indirect effect through school climate remained significant at 0.013.

The theoretical implications reach into several well-established bodies of research. The finding that digitally equipped schools foster more collaborative and innovative climates aligns with community of practice theory, which holds that professional learning flourishes through shared expertise and mutual engagement, and with diffusion of innovations theory, which emphasizes how behaviors spread through social networks. When teachers witness peers successfully adopting digital tools, curiosity and emulation ripple across the school, gradually transforming the entire community into one that is digitally adept. Access to technological resources, technical support, and professional development not only builds individual confidence but nurtures a sense of professional community as educators collectively confront the challenges of integration. The study also resonates with the European Commission’s DIGCOMP framework, which positions collaboration and collegial exchange as foundations of digital competence in education.

The practical message for school leaders is a dual mandate: invest in infrastructure and invest in culture, because neither alone is sufficient. Without access to digital professional development programs, the authors warn, schools risk merely ornamenting classrooms with resources while falling short of actual integration. Structured professional learning communities and institutional support systems are essential to convert equipment into pedagogy. Policymakers are urged to embed digital preparedness indicators into school evaluation systems and to recognize that under-resourced schools may need differentiated support, such as subsidized internet access, mobile-based learning solutions, and localized training. Leadership matters at every step: principals who set clear expectations, endorse technology initiatives, and provide development opportunities bolster both teacher motivation and digital competence, creating an ecosystem in which teachers feel safe to experiment, share failures, and seek help.

The authors are candid about the study’s limitations. The cross-sectional survey design restricts causal inference, since the model is fundamentally correlational, and future longitudinal or experimental work is needed to track how digital ecosystems evolve over time. Generalizability is confined to countries participating in PISA 2022, and measurement invariance across countries was not tested, so cross-national comparisons of the latent constructs should be interpreted with caution. Self-reported data from a single survey wave also raise the possibility of common method bias and self-selection effects, as teachers more engaged with digital practices may have been more likely to respond. Even so, the study marks a meaningful shift in perspective, moving the conversation about educational technology from the individual teacher to the institution as a whole. In an era when governments worldwide are racing to digitize classrooms, the evidence suggests that the most transformative investment a school can make may be in the trust, collaboration, and shared purpose of the people who walk through its doors each morning.

Subject of Research: The mediating role of school climate in the relationship between schools' digital preparedness and teachers' digital integration, analyzed with PISA 2022 data

Article Title: Relationship between digital preparedness and digital integration: mediation evidence on the role of school climate

Article References: Liu, J., Darko, E. N. K. O., & Aziku, M. (2025). Relationship between digital preparedness and digital integration: mediation evidence on the role of school climate. Journal of New Approaches in Educational Research, 14(1), Article 18. https://doi.org/10.1007/s44322-025-00040-1

Image Credits: AI Generated

DOI: 10.1007/s44322-025-00040-1

Keywords: digital preparedness, digital integration, school climate, PISA 2022, technology acceptance model, sTAM, PLS-SEM, teacher professional development, educational technology, school leadership, OECD, mediation analysis