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Subject: acceptance

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    Article
    Citation - WoS: 18
    Citation - Scopus: 23
    Psychological Sense of University Membership: an Adaptation Study of the Pssm Scale for Turkish University Students
    (Routledge Journals, Taylor & Francis Ltd, 2016) Alkan, Nese
    The Psychological Sense of School Membership Scale (PSSM) is a widely used instrument to assess the sense of belonging to a school among adolescents. Despite its widespread use in middle and high school students, to date no particular adaptation study has been conducted for its use among university students. For this reason, the present study conducted an adaptation of the PSSM scale for these students. Five hundred and nine students at a Turkish university voluntarily participated in the study, and the PSSM Scale's factor structure was examined by exploratory and confirmatory factor analyses, identifying three factors representing the students' sense of university membership with acceptable internal consistencies: acceptance by faculty members (.70), belonging (.75), and acceptance by students (.76). The internal consistency of the 18-item scale was calculated as .84. As hypothesized, the convergent and discriminant validity of the scale was also tested. The self-report sense of belonging and degree of satisfaction with the university were positively correlated with the three dimensions of the scale. Also, the scores regarding the students' intention to drop out of university along with loneliness were negatively correlated with all the dimension of the PSSM scale.
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    Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Expectancy 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 Ercil
    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.