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Its main objective is to identify teachers\u2019 technological profiles to design more effective AI training programs tailored to their actual needs. A mixed analytical strategy was applied to the data from a survey of 262 teachers. First,\n                    <jats:italic>Spearman correlations<\/jats:italic>\n                    were used to identify consistent constructs of behavior and attitude related to AI use, concerns, and self-training. Second,\n                    <jats:italic>K-Means clustering<\/jats:italic>\n                    was conducted on 71 variables to detect broader segments of teachers based on multivariate similarity. The results of both analyses were combined into a two-level taxonomy and mapped onto DigCompEdu competence areas. K-Means consistently produced\n                    <jats:italic>two macro groups<\/jats:italic>\n                    :\n                    <jats:italic>active adopters<\/jats:italic>\n                    and\n                    <jats:italic>cautious\/emerging adopters.<\/jats:italic>\n                    The Spearman structure refined these into five micro profiles.\n                    <jats:italic>Advanced integrators, Content and resource Builders, Data and Code, Safety first fundamentals, and Skeptics\/Context-Limited Users<\/jats:italic>\n                    . The dual approach yields a robust and actionable classification of teachers\u2019 AI readiness. The resulting macro-routes and micro-profiles support the design of targeted, scalable, and competence-aligned AI training for educators.\n                  <\/jats:p>","DOI":"10.1007\/s10209-026-01313-y","type":"journal-article","created":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T10:46:40Z","timestamp":1772448400000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Technological profiles of primary and secondary school teachers: a data-driven approach to AI training design"],"prefix":"10.1007","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5284-3401","authenticated-orcid":false,"given":"Imma","family":"Pallej\u00e0","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4554-1444","authenticated-orcid":false,"given":"Sofia","family":"Aguayo-Mauri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9471-153X","authenticated-orcid":false,"given":"David","family":"Fonseca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7513-5796","authenticated-orcid":false,"given":"Alejandro","family":"Iglesias","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9412-8827","authenticated-orcid":false,"given":"Xavi","family":"Canaleta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,2]]},"reference":[{"issue":"2","key":"1313_CR1","first-page":"343","volume":"7","author":"R Baskara","year":"2023","unstructured":"Baskara, R., Mukarto, M.: Exploring the implications of ChatGPT for language learning in higher education. 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