Abstract
omputational study on digital maturity comprising the teaching communityand their perception towards the impact of Digital Educational Technologies (DET)and Artificial Intelligence (AI) in the learning process. The objective of this studyis to determine digital maturity profiles among teachers, pattern recognition inthe use of AI tools, and modeling their correlation with subjective assessmenttowards educational outcomes. The research that took place among 832 teachersfrom various educational organizations combines a quantitative-qualitative approach(online survey) with further advanced computational methods. PCA was applied fordetermination of latent factors within the usage of AI tools while K-Means clusteringenabled us to detect three empirical profiles concerning digital maturity. Linearregression analysis between tool usage and supposed better student outcome has beenexecuted. Findings reveal high levels of educator engagement, with traditional tools(MS Office) still topping usage and ChatGPT being the most used AI tool (80.4%). Three clusters were identified through clustering: "AI-oriented," "Basic AI," and"Interactive-traditional" that reflect digital maturity’s different aspects. A very largeproportion of teachers-84.6%-reported increased student motivation and interestthanks to DLT. The maturity profiles identified and the relationships modeledprovide an empirical basis for targeted, cluster-specific professional developmentprograms to be designed.