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This study examines classroom teachers’ behavioral intention to use distance education environments using the technology acceptance model framework, focusing on self-efficacy, perceived benefit, and attitude toward use. Data from 370 classroom teachers were analyzed with structural equation modeling to test measurement and structural models and to describe levels of key constructs. Results show significant effects of self-efficacy, perceived benefit, and attitudes on intention, supporting their use as predictors for future classroom adoption.",{"@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/antecedents-of-classroom-teachers-intention-to-use-distance-education-environments-a-structural-equation-modeling-approach/593140/",{"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/antecedents-of-classroom-teachers-intention-to-use-distance-education-environments-a-structural-equation-modeling-approach/593140.png","ImageObject",300,407,{"name":92,"@type":93},"Aran","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-06","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Which factors influence classroom teachers’ intention to use distance education environments?","Question",{"text":112,"@type":113},"Self-efficacy, perceived benefit, and attitudes toward use significantly influence teachers’ behavioral intention to use distance education environments.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the study conducted to test the proposed relationships?",{"text":117,"@type":113},"Data were collected from 370 classroom teachers using a self-reporting scale, and structural equation modeling was used to test measurement and structure models.",{"name":119,"@type":110,"acceptedAnswer":120},"What is the theoretical framework guiding the study?",{"text":121,"@type":113},"The study uses the technology acceptance model (TAM) to investigate predictors related to teachers’ acceptance and intention to use distance education environments.","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},593140,1792144975,{"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":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":56,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},137455076865,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","Antecedents of classroom teachers’ intention to use distance education environments: A structural equation modeling approach  \nDerya Başer  \nAbstract: Distance education’s importance has recently been understood more compared to the period prior to the COVID-19 pandemic. Teachers’ intentional use of distance education environments is considered effective in taking advantage of the distance education medium. In order to benefit from classroom teachers’ experiences during the pandemic when aiming to incorporate distance education’s advantages into formal K-12 education, factors regarding teachers’ behavioral intention to use distance education environments were investigated in this study within the framework of the technology acceptance model. The study aimed to assess classroom teachers’ self-efficacy, perceived benefit, attitude toward the use of distance education environments, as well as each of these variables’ influence on teachers’ intention to use distance education environments. Data were collected from 370 classroom teachers through a self-reporting scale. Structural equation modeling approach was then used to test the measure and structure models, with descriptive statistics applied to assess teachers’ levels for the constructs. The results indicated that classroom teachers’ self-efficacy, perceived benefit, and attitudes towards the use of distance education environments significantly influence teachers’ behavioral intention to use distance education environments. Both researchers and educational policymakers should consider these significant predictors to promote classroom teachers’ intentional use of distance education environments in their future classrooms.  \nKeywords: Classroom teachers, distance education, technology acceptance model, structural equation modeling, intention to use distance education.  \nHighlights  \nWhat is already known about this topic:  \n● Technology Acceptance Model (TAM) is a robust model that can be used to analyze how users accept and intend to use technologies and has been confirmed in numerous studies.  \n● TAM Studies in the literature have generally scrutinized learners’ acceptance of technologies for use in distance education.  \nWhat this paper contributes:  \n● The current study investigates the acceptance of distance education environments amongst classroom teachers, as they are one of the leading groups of distance education implementers at the K-12 level.  \n● The study applies SEM to provide robust quantitative evidence for the significant predictors of classroom teachers’ acceptance of distance education environments based on the TAM.  \nImplications for theory, practice and/or policy:  \n● The study offers significant predictors, namely self-efficacy, perceived benefit, and attitude toward use, of classroom teachers’ intention to use distance education environments.  \n● The study verifies the TAM model for distance education environments among Turkish classroom teachers, with multiple fit indices in the good fit ranges.  \n● The study provides evidence for the direct influence of self-efficacy which has conflicting results in existing studies.  \nIntroduction  \nFace-to-face education was almost totally replaced with distance education during the COVID-19 pandemic, resulting in distance education’s importance having since been understood much more across all levels of education. Therefore, understanding the distance education medium and teachers’use of distance education environments is crucial to being able to take advantage of its potential benefits.  \nDistance education is defined as “institution-based, formal education where the learning group is separated, and where interactive telecommunications systems are used to connect learners, resources, and instructors”(Schlosser & Simonson, 2009, p. 1) . Under the interactive telecommunications systems, technological teaching and learning platforms, as well as specialist software and tools are used by both teachers and learners in distan","cbCailRa5UklV3pe","https://ap.wps.com/l/cbCailRa5UklV3pe","pdf",519451,"English","# Abstract\n# Highlights\n## What is already known about this topic\n## What this paper contributes\n## Implications for theory, practice and/or policy\n# Introduction","[{\"question\":\"Which factors influence classroom teachers’ intention to use distance education environments?\",\"answer\":\"Self-efficacy, perceived benefit, and attitudes toward use significantly influence teachers’ behavioral intention to use distance education environments.\"},{\"question\":\"How was the study conducted to test the proposed relationships?\",\"answer\":\"Data were collected from 370 classroom teachers using a self-reporting scale, and structural equation modeling was used to test measurement and structure models.\"},{\"question\":\"What is the theoretical framework guiding the study?\",\"answer\":\"The study uses the technology acceptance model (TAM) to investigate predictors related to teachers’ acceptance and intention to use distance education environments.\"}]","Antecedents of Classroom Teachers’ Intention to Use Distance Education Environments - A Structural Equation Modeling Approach | PDF",1792076675,48]