{"id":7632,"date":"2026-10-05T10:01:56","date_gmt":"2026-10-05T09:01:56","guid":{"rendered":"https:\/\/ffstopenpress.ffst.hr\/?post_type=chapter&#038;p=7632"},"modified":"2026-10-16T08:37:36","modified_gmt":"2026-10-16T07:37:36","slug":"integration-of-ai-tools-in-education","status":"publish","type":"chapter","link":"https:\/\/ffstopenpress.ffst.hr\/en\/chapter\/integration-of-ai-tools-in-education\/","title":{"rendered":"Integration of AI tools in education"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Artificial intelligence (AI) requires a more profound methodological understanding of its integration within pedagogical frameworks. This theoretical study aims to analyze the didactic and methodological implications of applying AI tools in education through the framework of the TPACK model (Technological, Pedagogical, and Content Knowledge). A comparative analysis of 23 studies published between 2020 and 2025 were conducted according to inclusion and exclusion criteria and also through TPACK model, focusing on identifying the key pedagogical implications. Findings indicate that expert and intelligent tutoring tools demonstrate the strongest pedagogical implications, particularly in student monitoring, personalization, assistive support, reducing administrative tasks for teachers, and diagnostic assessment. The role of linguistic-generative tools in adaptive learning and feedback is narrower but remains important, while VR simulation and meta tools show selective effects, proving most effective in immersive and experiential learning contexts. Given the theoretical nature of the study, the findings represent conceptual rather than empirically confirmed implications. Future research should use longitudinal and empirical approaches to examine the long-term effects of AI in education, informing regulatory frameworks for its responsible integration and helping educators effectively incorporate AI tools to support students\u2019 lifelong learning.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence (AI) requires a more profound methodological understanding of its integration within pedagogical frameworks. This theoretical study aims to analyze the didactic and methodological implications of applying AI tools in education through the framework of the TPACK model (Technological, Pedagogical, and Content Knowledge). A comparative analysis of 23 studies published between 2020 and 2025 &#8230;<\/p>\n","protected":false},"featured_media":7620,"menu_order":0,"template":"","class_list":["post-7632","chapter","type-chapter","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/ffstopenpress.ffst.hr\/en\/wp-json\/wp\/v2\/chapter\/7632","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ffstopenpress.ffst.hr\/en\/wp-json\/wp\/v2\/chapter"}],"about":[{"href":"https:\/\/ffstopenpress.ffst.hr\/en\/wp-json\/wp\/v2\/types\/chapter"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ffstopenpress.ffst.hr\/en\/wp-json\/wp\/v2\/media\/7620"}],"wp:attachment":[{"href":"https:\/\/ffstopenpress.ffst.hr\/en\/wp-json\/wp\/v2\/media?parent=7632"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}