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Article Citation - WoS: 3Citation - Scopus: 3Expectancy From, and Acceptance of Augmented Reality in Dental Education Programs: a Structural Equation Model(Wiley, 2024) Toker, Sacip; Akay, Canan; Basmaci, Fulya; Kilicarslan, Mehmet Ali; Mumcu, Emre; Cagiltay, Nergiz ErcilObjectiveDental 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.Article Citation - WoS: 10The Comparison of Trust Development in Virtual and Face-To Collaborative Learning Groups(Anadolu Univ, 2019) Baturay, Meltem Huri; Toker, SacipThe study investigates the effect of delivery types of (virtual and face-to-face) collaborative learning environments on the development of trust among group members in a graduate course. For this aim, a quasi-experimental, non-equivalent group comparison was used. It comprised a total of 64 participants 21 in the face-to-face group, and 43 in the virtual group. Study participants were comprised of students registered in a course entitled 'Web-based Education: Principles of Design and Implementation' in the spring semester as part of either a virtual or traditional face-to-face graduate program in Information Systems at an institute of higher education in Turkey in 2010. Trust levels were measured at two different occasions, namely in the beginning and end of the semester, for both study groups. The participants completed a web-based course material design project as a collaborative group activity. The results indicate that trust increases over time among virtual participants, but declines among face-to-face participants. While levels of trust among virtual course participants are lower than those of face-to-face course participants in the beginning of the semester, trust levels of virtual participants surpass those of faceto-face participants by the end of the semester. This study demonstrates that trust can develop in virtual learning environments. The initial level of trust should be taken into consideration by instructors or managers before forming groups.
