Expectancy From, and Acceptance of Augmented Reality in Dental Education Programs: a Structural Equation Model

dc.authorid Cagiltay, Nergiz Ercil/0000-0003-0875-9276
dc.authorid Toker, Sacip/0000-0003-1437-6642
dc.authorscopusid 56608927500
dc.authorscopusid 56526673700
dc.authorscopusid 57836188900
dc.authorscopusid 8885711600
dc.authorscopusid 34880569600
dc.authorscopusid 16237826800
dc.contributor.author Toker, Sacip
dc.contributor.author Akay, Canan
dc.contributor.author Basmaci, Fulya
dc.contributor.author Kilicarslan, Mehmet Ali
dc.contributor.author Mumcu, Emre
dc.contributor.author Cagiltay, Nergiz Ercil
dc.contributor.other Information Systems Engineering
dc.contributor.other Software Engineering
dc.date.accessioned 2024-07-05T15:23:13Z
dc.date.available 2024-07-05T15:23:13Z
dc.date.issued 2024
dc.department Atılım University en_US
dc.department-temp [Toker, Sacip] Atilim Univ, Informat Syst Engn Dept, Ankara, Turkiye; [Akay, Canan; Mumcu, Emre] Eskisehir Osmangazi Univ, Fac Dent, Eskisehir, Turkiye; [Basmaci, Fulya] Ankara Yildirim Beyazit Univ, Fac Dent, Ankara, Turkiye; [Kilicarslan, Mehmet Ali] Ankara Univ, Fac Dent, Ankara, Turkiye; [Cagiltay, Nergiz Ercil] Cankaya Univ, Software Engn Dept, Ankara, Turkiye en_US
dc.description Cagiltay, Nergiz Ercil/0000-0003-0875-9276; Toker, Sacip/0000-0003-1437-6642 en_US
dc.description.abstract ObjectiveDental schools need hands-on training and feedback. Augmented reality (AR) and virtual reality (VR) technologies enable remote work and training. Education programs only partially integrated these technologies. For better technology integration, infrastructure readiness, prior-knowledge readiness, expectations, and learner attitudes toward AR and VR technologies must be understood together. Thus, this study creates a structural equation model to understand how these factors affect dental students' technology use.MethodsA correlational survey was done. Four questionnaires were sent to 755 dental students from three schools. These participants were convenience-sampled. Surveys were developed using validity tests like explanatory and confirmatory factor analyses, Cronbach's alpha, and composite reliability. Ten primary research hypotheses are tested with path analysis.ResultsA total of 81.22% responded to the survey (755 out of 930). Positive AR attitude, expectancy, and acceptance were endogenous variables. Positive attitudes toward AR were significantly influenced by two exogenous variables: infrastructure readiness (B = 0.359, beta = 0.386, L = 0.305, U = 0.457, p = 0.002) and prior-knowledge readiness (B = -0.056, beta = 0.306, L = 0.305, U = 0.457, p = 0.002). Expectancy from AR was affected by infrastructure, prior knowledge, and positive and negative AR attitudes. Infrastructure, prior-knowledge readiness, and positive attitude toward AR had positive effects on expectancy from AR (B = 0.201, beta = 0.204, L = 0.140, U = 0.267, p = 0.002). Negative attitude had a negative impact (B = -0.056, beta = -0.054, L = 0.091, U = 0.182, p = 0.002). Another exogenous variable was AR acceptance, which was affected by infrastructure, prior-knowledge preparation, positive attitudes, and expectancy. Significant differences were found in infrastructure, prior-knowledge readiness, positive attitude toward AR, and expectancy from AR (B = 0.041, beta = 0.046, L = 0.026, U = 0.086, p = 0.054).ConclusionInfrastructure and prior-knowledge readiness for AR significantly affect positive AR attitudes. Together, these three criteria boost AR's potential. Infrastructure readiness, prior-knowledge readiness, positive attitudes toward AR, and AR expectations all increase AR adoption. The study provides insights that can help instructional system designers, developers, dental education institutions, and program developers better integrate these technologies into dental education programs. Integration can improve dental students' hands-on experience and program performance by providing training options anywhere and anytime. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.1002/jdd.13580
dc.identifier.issn 0022-0337
dc.identifier.issn 1930-7837
dc.identifier.pmid 38773700
dc.identifier.scopus 2-s2.0-85193687651
dc.identifier.uri https://doi.org/10.1002/jdd.13580
dc.identifier.uri https://hdl.handle.net/20.500.14411/2285
dc.identifier.wos WOS:001228239100001
dc.identifier.wosquality Q3
dc.institutionauthor Toker, Sacip
dc.institutionauthor Çağıltay, Nergiz
dc.language.iso en en_US
dc.publisher Wiley en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 2
dc.subject acceptance en_US
dc.subject augmented and virtual reality en_US
dc.subject dental education en_US
dc.subject expectancy en_US
dc.subject positive attitude en_US
dc.subject structural equation model en_US
dc.title Expectancy From, and Acceptance of Augmented Reality in Dental Education Programs: a Structural Equation Model en_US
dc.type Article en_US
dc.wos.citedbyCount 2
dspace.entity.type Publication
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