[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-599793-105":59,"doc-detail-599793-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","greek-pre-service-teachers-intentions-to-use-computers-as-in-service-teachers","Greek Pre-service Teachers’ Intentions to Use Computers as In-service Teachers","","The study examines factors shaping Greek pre-service teachers’ intention to use computers after they become practicing teachers. A research model extending the Technology Acceptance Model (TAM) incorporates perceived usefulness, perceived ease of use, self-efficacy, and attitude toward use, alongside behavioral intention. Data collected from 487 pre-service teachers in Greece support seven of nine hypotheses, with strong model fit. TAM plus computer self-efficacy explains 68% of behavioral intention variance, highlighting perceived usefulness and attitude as the most influential influences, with practical implications discussed.",{"@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/greek-pre-service-teachers-intentions-to-use-computers-as-in-service-teachers/599793/",{"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/greek-pre-service-teachers-intentions-to-use-computers-as-in-service-teachers/599793.png","ImageObject",300,407,{"name":92,"@type":93},"PakDamar76","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-27","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Which factors influence Greek pre-service teachers’ intention to use computers as in-service teachers?","Question",{"text":112,"@type":113},"The study uses perceived usefulness, perceived ease of use, self-efficacy, and attitude toward use, extending TAM to explain behavioral intention to use computers.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the research model tested and what data were used?",{"text":117,"@type":113},"Structural equation modeling was applied for parameter estimation and model testing, using self-reported data from 487 Greek pre-service teachers.",{"name":119,"@type":110,"acceptedAnswer":120},"What were the main findings about which variables mattered most?",{"text":121,"@type":113},"Seven of nine hypotheses were supported, and TAM with computer self-efficacy explained 68% of the variance. Perceived usefulness and attitude toward computers were the most influential factors.","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},599793,1792161198,{"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":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":46,"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":31},962090893057,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Greek Pre-service Teachers’ Intentions to Use Computers as  \nIn-service Teachers  \nEmmanuel Fokides  \nUniversity of the Aegean, Greece  \nAbstract  \nThe study examines the factors affecting Greek pre-service teachers’ intention to use computers when they become practicing teachers. Four variables (perceived usefulness, perceived ease of use, self-efficacy, and attitude toward use) as well as behavioral intention to use computers were used so as to build a research model that extended the Technology Acceptance Model (TAM) and structural equation modeling was used for parameter estimation and model testing. Self-reported data were gathered from 487 pre-service teachers studying at the Departments of Primary School Education in Greece. Results revealed a good model fit and of the nine hypotheses formulated, seven were supported.  \nOverall, the TAM, with the addition of computer self-efficacy beliefs, adequately represented the relationships among the factors. It also possesses the explanatory power to predict pre-service teachers’ intention to use computers when they become practicing teachers since a high percentage (68%) of the variance in behavioral intention to use computers was explained, while the most influential factors were perceived usefulness and attitude toward computers. Implications for practice are also discussed.  \nKeywords: Attitude toward computers; Perceived ease of use; Pre-service teachers; Selfefficacy; Structural equation modeling; Technology acceptance model  \nIntroduction  \nComputers have been introduced in education for quite a while, but despite considerable capital investments in infrastructure and training, their use is still minimal (Mueller, Wood, Willoughby, Ross, & Specht, 2008) . According to a survey conducted in all the EU's countries (Schoolnet, 2013), teachers, even though they are familiar with computers, confident in using ICT, and positive about ICT’s impact on students’ learning, they still use computers merely to prepare their teaching material. Literature suggests that teachers' views, beliefs, and attitudes are major predictors in determining if they will use computers during their teaching (e.g., Celik & Yesilyurt, 2013; Paraskeva, Bouta, & Papagianni, 2008) . So, it seems that there is a resistance to fully adopt new technologies that stems from teachers’ existing beliefs (Teo, 2009) . To influence these beliefs, in-service training is suggested (Schoolnet, 2013), but also one should start as early as possible, at the pre-service level. Thus, the universities have the responsibility to positively influence students' attitudes and adapt the curriculum so as to sufficiently prepare them to meet the challenges of using ICT at school and to instruct them on how technology intersects with pedagogical and content knowledge (Koehler & Mishra, 2009) . Consequently, the identification and understanding of the critical drivers and motivators related to students’ intentions to use computers when they become practicing teachers, are important issues, as they can provide evidence on how successful the curriculum is in shaping their attitudes and beliefs. In addition, it is theorized that positive feelings toward computers and intention to use them are closely  \nrelated to their actual use (Macharia & Pelser, 2012) . Therefore, the examination of these factors can provide useful insights regarding the extent computers are going to be used in primary schools when today's pre-service teachers become in-service teachers.  \nResearchers have proposed various and diverse models that could provide a framework that explains and predicts behavioral intention. For example, Venkatesh, Morris, Davis, and Davis (2003) argued that students’ intention to use technology could be explained by understanding their technology acceptance and, in turn, acceptance can be explained by the underlying intentions. In line with previous research, the study at hand had a two-fold purpose: (a) to propose and test a model that e","cbCaifWBveTfLnN1","https://ap.wps.com/l/cbCaifWBveTfLnN1","pdf",843841,"English","# Introduction\n## Technology Acceptance Model and Computer Self-efficacy","[{\"question\":\"Which factors influence Greek pre-service teachers’ intention to use computers as in-service teachers?\",\"answer\":\"The study uses perceived usefulness, perceived ease of use, self-efficacy, and attitude toward use, extending TAM to explain behavioral intention to use computers.\"},{\"question\":\"How was the research model tested and what data were used?\",\"answer\":\"Structural equation modeling was applied for parameter estimation and model testing, using self-reported data from 487 Greek pre-service teachers.\"},{\"question\":\"What were the main findings about which variables mattered most?\",\"answer\":\"Seven of nine hypotheses were supported, and TAM with computer self-efficacy explained 68% of the variance. Perceived usefulness and attitude toward computers were the most influential factors.\"}]","Greek Pre-service Teachers’ Intentions to Use Computers as In-service Teachers | PDF",1792089451]