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It charts research venues, co-authorship structures, keyword evolution, and technique usage, highlighting the rising dominance of “ChatGPT” and “generative AI” after 2022. Results indicate North America and Europe lead output while collaboration networks remain fragmented. Supervised learning predominates and neural networks are the most used single technique. The article synthesizes principles linking AI use to core sustainability education competencies and discusses a dual sustainability lens, including privacy and environmental implications, and proposes assessment and capacity strategies for durable impact.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/sustainability-education-meets-artificial-intelligence-apost-2022-bibliometric-map-and-thematic-analysis/600521/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/sustainability-education-meets-artificial-intelligence-apost-2022-bibliometric-map-and-thematic-analysis/600521.png","ImageObject",300,407,{"name":92,"@type":93},"OmBimo","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-03","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the scope of this bibliometric study?","Question",{"text":112,"@type":113},"The study analyzes 417 peer reviewed publications from 2022 to 2025 focusing on the intersection of sustainability education and artificial intelligence.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"Which AI-related terms became most popular after 2022?",{"text":117,"@type":113},"“ChatGPT” and “generative AI” became the most popular terms after 2022, according to the keyword evolution results.",{"name":119,"@type":110,"acceptedAnswer":120},"What competencies and risks does the article connect AI interventions to?",{"text":121,"@type":113},"The framework links AI uses to core sustainability education competencies and addresses risks including privacy, bias, explainability, and environmental consequences related to AI energy and hardware consumption.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},600521,1792165464,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962090893581,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","Contemporary Educational Technology, 2025, 17(4), ep609  \n ISSN: 1309-517X (Online)   \n OPEN ACCESS  Review Article  \nSustainability education meets artificial intelligence: Apost-2022 bibliometric map and thematic analysis  \nAlfiya R. Masalimova 1*  \n 0000-0003-3711-2527  \nYuliya P. Kosheleva 2  \n 0000-0001-5653-2143  \nAleksandr I. Burov 3  \n 0000-0002-7909-2993  \nOlga V. Payushina 3  \n 0000-0001-8467-0623  \nNatalia L. Sokolova 4  \n 0000-0002-0667-5098  \nMaria A. Khvatova 5  \n 0000-0002-2156-8805  \n1 The Institute of Psychology and Education, Kazan Federal University, Kazan, RUSSIA  \n2 Laboratory of Differential Psychology and Psychophysiology, Federal Scientific Center of Psychological and Multidisciplinary Research, Moscow, RUSSIA  \n3 I. M. Sechenov First Moscow State Medical University, Moscow, RUSSIA  \n4 Peoples’ Friendship University of Russia (RUDN University), Moscow, RUSSIA  \n5 Bauman Moscow State Technical University, Moscow, RUSSIA  \n* Corresponding author: [alfkazan@mail. ru](alfkazan@mail. ru)  \nCitation: Masalimova, A. R., Kosheleva, Y. P., Burov, A. I., Payushina, O. V., Sokolova, N. L., & Khvatova, M. A. (2025) . Sustainability education meets artificial intelligence: A post-2022 bibliometric map and thematic analysis. Contemporary  \nEducational Technology, 17(4), ep609. [https://doi.org/10.30935/cedtech/17482](https://doi.org/10.30935/cedtech/17482)  \nARTICLE INFO ABSTRACT  \nReceived: 12 May 2025  \nAccepted: 17 Nov 2025  \nThis study maps 417 peer reviewed publications (2022-2025) at the intersection of sustainability education (SE) and artificial intelligence (AI) using bibliometric methods. We chart venues, co authorship, keyword evolution, and technique usage. The results reveal that “ChatGPT” and“generative AI” are becoming the most popular terms after 2022. Outputs are still mostly from North America and Europe, although contributions from Saudi Arabia, India, and Malaysia are growing. Institutional networks are broken, which means that institutions don’t cooperate together very often. Supervised learning predominates, and neural networks are the most used single technique. We synthesize scattered findings into three practical principles– personalization–protection, competence alignment, and multi-level synchronization–that link AI uses to core SE competencies and support course to institution coordination. The study also shows a dual sustainability lens: AI can help fight climate change, but it also has implications for privacy and the environment. This shows the need for energy reporting and bias safeguards. We suggest causal and longitudinal assessments, collaborative datasets and rubrics, and capacity enhancement for resource-limited environments. Some of the problems are a short citation window (2022-2025), a bias against English speakers, and the possibility of missing databases. Overall, the subject is growing swiftly, but it requires more proof, common standards, and more environmentally friendly ways of doing things to turn AI into lasting educational value.  \nKeywords: sustainability education, artificial intelligence, generative AI, bibliometric analysis  \nINTRODUCTION  \nSustainability education (SE) is a normative and transformative pedagogy that aims to develop learners’critical reasoning, systemic understanding, foresight, strategic action, and collaboration competencies in sustainability issue areas (Corres et al., 2020; Sandri, 2020) . On the other hand, education sustainability looks at how long an organization can last, from how it is run to how it works on campus. Even though the two subjects are typically talked about together in writing, they have different analytical focuses: We look at SE by looking at the competency outcomes of learning designs, and we look at education sustainability by looking at institutional performance metrics including energy, waste, carbon, equity, and stakeholder engagement (Rieckmann, 2012; Usak et al., 2021; Velazquez et al., 2006; Wiek et al., 2011) . Thi","cbCailoWopDLdNwR","https://ap.wps.com/l/cbCailoWopDLdNwR","pdf",485654,22,"English","# Introduction\n## Sustainability education and education sustainability\n## Post-2022 generative AI wave in sustainability education\n# Study aims and contribution\n## Systematic mapping of AI transformation in post-2022 literature","[{\"question\":\"What is the scope of this bibliometric study?\",\"answer\":\"The study analyzes 417 peer reviewed publications from 2022 to 2025 focusing on the intersection of sustainability education and artificial intelligence.\"},{\"question\":\"Which AI-related terms became most popular after 2022?\",\"answer\":\"“ChatGPT” and “generative AI” became the most popular terms after 2022, according to the keyword evolution results.\"},{\"question\":\"What competencies and risks does the article connect AI interventions to?\",\"answer\":\"The framework links AI uses to core sustainability education competencies and addresses risks including privacy, bias, explainability, and environmental consequences related to AI energy and hardware consumption.\"}]","Sustainability education meets artificial intelligence - Apost-2022 bibliometric map and thematic analysis | PDF",1792090858,55]