{"id":{"repo_id":"alverno","oai_identifier":"oai:alverno.omeka.net:959"},"canonical_url":"https://search.dev.ndltd.org/etd/alverno/oai:alverno.omeka.net:959","repository":{"repo_id":"alverno","name":"Alverno College","base_url":"https://alverno.omeka.net/oai-pmh-repository/request"},"display":{"title":"Bridging the AI literacy gap : strategies for aligning K–12 education with an AI-driven future","abstract":"Camacho, Janette The integration of artificial intelligence (AI) into society and the workplace is changing the way we live and work. As AI and advanced digital technologies become more pervasive, there is an urgent need for education systems to adapt and ensure that students develop the skills needed to succeed in an AI-driven world. This qualitative, multi-case study examines how school districts, independent schools, and state departments of education are preparing educators and modifying curricula to develop AI literacy and skills in students. The problem this research addresses is the gap between the rapid advancement of AI technologies and the slow adaptation of education systems to prepare students for a digital future. Although AI is drastically changing industries and professions, most curricula continue to focus on traditional academic content rather than 21st century digital skills. Educators themselves also often lack training in emerging technologies and how to effectively teach topics such as data literacy, algorithms, and AI ethics. This problem impacts students who graduate unprepared for the technological upheavals in higher education programs and career fields. The purpose of this study is to identify strategies, frameworks, and best practices that educational institutions are using to promote AI readiness through teacher professional development and updated, technology-enriched curricula. The theoretical framework draws on constructionism, which emphasizes learning by designing and creating, and technological pedagogical content knowledge (TPACK), which emphasizes the connections between technology, pedagogy, and content. Data will be collected through interviews with curriculum directors, technology coordinators, educators, and other leaders, observations of teacher professional development programs and classrooms where AI instruction is implemented; and analysis of curricula and technology plans. The cross-case analysis will identify common themes related to goals, strategies, challenges, and outcomes of AI education initiatives. This study is significant because the results will provide models for promising programs that other educational institutions can emulate or adapt to develop educators’ skills in teaching AI and computational thinking while updating curricula with AI skills.","abstract_html":"Camacho, Janette The integration of artificial intelligence (AI) into society and the workplace is changing the way we live and work. As AI and advanced digital technologies become more pervasive, there is an urgent need for education systems to adapt and ensure that students develop the skills needed to succeed in an AI-driven world. This qualitative, multi-case study examines how school districts, independent schools, and state departments of education are preparing educators and modifying curricula to develop AI literacy and skills in students. The problem this research addresses is the gap between the rapid advancement of AI technologies and the slow adaptation of education systems to prepare students for a digital future. Although AI is drastically changing industries and professions, most curricula continue to focus on traditional academic content rather than 21st century digital skills. Educators themselves also often lack training in emerging technologies and how to effectively teach topics such as data literacy, algorithms, and AI ethics. This problem impacts students who graduate unprepared for the technological upheavals in higher education programs and career fields. The purpose of this study is to identify strategies, frameworks, and best practices that educational institutions are using to promote AI readiness through teacher professional development and updated, technology-enriched curricula. The theoretical framework draws on constructionism, which emphasizes learning by designing and creating, and technological pedagogical content knowledge (TPACK), which emphasizes the connections between technology, pedagogy, and content. Data will be collected through interviews with curriculum directors, technology coordinators, educators, and other leaders, observations of teacher professional development programs and classrooms where AI instruction is implemented; and analysis of curricula and technology plans. The cross-case analysis will identify common themes related to goals, strategies, challenges, and outcomes of AI education initiatives. This study is significant because the results will provide models for promising programs that other educational institutions can emulate or adapt to develop educators’ skills in teaching AI and computational thinking while updating curricula with AI skills.","abstract_has_math":false,"creators":["Camacho, Janette"],"institution":"Alverno College","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025","date_published":"2025","updated_at":"2026-07-27T18:44:41Z","subjects":["Artificial intelligence--Educational applications","Information literacy"],"languages":["English"],"rights":["These materials may be used by individuals and libraries for personal use, research, teaching (including distribution to classes), or for any fair use as defined by U.S. Copyright Law."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://alverno.omeka.net/items/show/959","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Camacho, Janette"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025"]},{"key":"dc:publisher","label":"Institution","values":["Alverno College"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Artificial intelligence--Educational applications","Information literacy"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]},{"key":"dc:rights","label":"Dc Rights","values":["These materials may be used by individuals and libraries for personal use, research, teaching (including distribution to classes), or for any fair use as defined by U.S. Copyright Law."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://alverno.omeka.net/items/show/959"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Camacho, Janette The integration of artificial intelligence (AI) into society and the workplace is changing the way we live and work. As AI and advanced digital technologies become more pervasive, there is an urgent need for education systems to adapt and ensure that students develop the skills needed to succeed in an AI-driven world. This qualitative, multi-case study examines how school districts, independent schools, and state departments of education are preparing educators and modifying curricula to develop AI literacy and skills in students. The problem this research addresses is the gap between the rapid advancement of AI technologies and the slow adaptation of education systems to prepare students for a digital future. Although AI is drastically changing industries and professions, most curricula continue to focus on traditional academic content rather than 21st century digital skills. Educators themselves also often lack training in emerging technologies and how to effectively teach topics such as data literacy, algorithms, and AI ethics. This problem impacts students who graduate unprepared for the technological upheavals in higher education programs and career fields. The purpose of this study is to identify strategies, frameworks, and best practices that educational institutions are using to promote AI readiness through teacher professional development and updated, technology-enriched curricula. The theoretical framework draws on constructionism, which emphasizes learning by designing and creating, and technological pedagogical content knowledge (TPACK), which emphasizes the connections between technology, pedagogy, and content. Data will be collected through interviews with curriculum directors, technology coordinators, educators, and other leaders, observations of teacher professional development programs and classrooms where AI instruction is implemented; and analysis of curricula and technology plans. The cross-case analysis will identify common themes related to goals, strategies, challenges, and outcomes of AI education initiatives. This study is significant because the results will provide models for promising programs that other educational institutions can emulate or adapt to develop educators’ skills in teaching AI and computational thinking while updating curricula with AI skills."]},{"key":"dc:format","label":"Dc Format","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Bridging the AI literacy gap : strategies for aligning K–12 education with an AI-driven future"]}]}],"canonical_facts":{"dc:creator":["Camacho, Janette"],"dc:date":["2025"],"dc:description":["Camacho, Janette The integration of artificial intelligence (AI) into society and the workplace is changing the way we live and work. As AI and advanced digital technologies become more pervasive, there is an urgent need for education systems to adapt and ensure that students develop the skills needed to succeed in an AI-driven world. This qualitative, multi-case study examines how school districts, independent schools, and state departments of education are preparing educators and modifying curricula to develop AI literacy and skills in students. The problem this research addresses is the gap between the rapid advancement of AI technologies and the slow adaptation of education systems to prepare students for a digital future. Although AI is drastically changing industries and professions, most curricula continue to focus on traditional academic content rather than 21st century digital skills. Educators themselves also often lack training in emerging technologies and how to effectively teach topics such as data literacy, algorithms, and AI ethics. This problem impacts students who graduate unprepared for the technological upheavals in higher education programs and career fields. The purpose of this study is to identify strategies, frameworks, and best practices that educational institutions are using to promote AI readiness through teacher professional development and updated, technology-enriched curricula. The theoretical framework draws on constructionism, which emphasizes learning by designing and creating, and technological pedagogical content knowledge (TPACK), which emphasizes the connections between technology, pedagogy, and content. Data will be collected through interviews with curriculum directors, technology coordinators, educators, and other leaders, observations of teacher professional development programs and classrooms where AI instruction is implemented; and analysis of curricula and technology plans. The cross-case analysis will identify common themes related to goals, strategies, challenges, and outcomes of AI education initiatives. This study is significant because the results will provide models for promising programs that other educational institutions can emulate or adapt to develop educators’ skills in teaching AI and computational thinking while updating curricula with AI skills."],"dc:format":["PDF"],"dc:identifier":["https://alverno.omeka.net/items/show/959"],"dc:language":["English"],"dc:publisher":["Alverno College"],"dc:rights":["These materials may be used by individuals and libraries for personal use, research, teaching (including distribution to classes), or for any fair use as defined by U.S. Copyright Law."],"dc:subject":["Artificial intelligence--Educational applications","Information literacy"],"dc:title":["Bridging the AI literacy gap : strategies for aligning K–12 education with an AI-driven future"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T18:44:41Z"}