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To this end, 3718 articles published in the 2003\u20132022 period and indexed in the Scopus database were analyzed through machine learning-based semantic topic modeling and descriptive analysis. The findings indicate a notable upswing in studies on educational AR, particularly since 2015. The articles were categorized into eleven primary themes through topic modeling analysis. The three most prevalent topics in terms of volume are \u201cAugmented Reality in Education and Cultural Heritage\u201d, \u201cMedical Education and Patient Care\u201d, and \u201cEnhancing Safety and Information in Food Consumption\u201d. Observations across different times reveal that \u201cAugmented Reality in Electrical and Electronic Systems\u201d and \u201cGesture-Based Instruction and Maintenance\u201d were studied in the initial periods. Since 2015, there has been a notable increase in applications falling under the \u201cSerious Games\u201d category. The least voluminous and slowest-evolving topics are identified as \u201cSerious Games for Children with Autism Spectrum Disorder\u201d, \u201cAugmented Reality in Chemistry and Biology Laboratories\u201d, and \u201cAugmented Reality for Safe and Efficient Driving\u201d. Considering the recent momentum gained by these topics, it is anticipated that they will become popular topics for future studies. This study represents a significant milestone as the first and most comprehensive research using machine learning in its field, not only explaining the current state of the field but also providing valuable information for future research efforts.<\/jats:p>","DOI":"10.1007\/s10639-024-12943-1","type":"journal-article","created":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T09:05:40Z","timestamp":1722935140000},"page":"57-87","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Decoding educational augmented reality research trends: a topic modeling analysis"],"prefix":"10.1007","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8621-2335","authenticated-orcid":false,"given":"Hacer","family":"Ozyurt","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ozcan","family":"Ozyurt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,8,6]]},"reference":[{"key":"12943_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.edurev.2016.11.002","volume":"20","author":"M Ak\u00e7ay\u0131r","year":"2017","unstructured":"Ak\u00e7ay\u0131r, M., & Ak\u00e7ay\u0131r, G. 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