Modeling Development and Validation of Metaverse Attitude Scale
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Abstract
This study is an attempt to develop a reliable and valid measurement tool to measure secondary school students' attitudes towards metaverse use. Therefore, the study reported the analyses related to metaverse attitude scale (MVAS). The content validity of the scale was ensured by an expert’s view, and Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) designed according to the Technology Adaptation Model (TAM) were employed to ensure its construct validity. . The structural equation model was used to reveal the relationship across the variables. EFA was carried out with the data obtained from 251 5th, 6th, 7th, and 8th-grade secondary school students enrolled in public schools in a city in northwest Turkey. The results of EFA confirmed a 22-item three-factor model. Then, the three-factor model obtained from EFA was cross-validated through the use of CFA that proposed a 21-item 3-factor model. The fit indices for CFA were found as .05 for RMSEA, .049 for SRMR, .889 for GFI, .871 for AGFI, .9146 for NFI, .965 for CFI, and .916 for RFI. Besides, the results affirmed the proposed 21-item three-factor model theoretically and statistically. Structural equation modeling was used to determine the relationship across variables. Accordingly, secondary school students were identified to have positive responses towards cognitive and affective fields related to the metaverse. However, they could not transform these responses into behavioral field. As a result, the metaverse may be used in education since it is likely to observe the independent variables such as perceived usefulness, perceived ease of use and attitude towards use regarding the metaverse in secondary school students.
Keywords
Metaverse, Attitude, Validity, Reliability, Scale development
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Kirbas, O. & Dogan, F. (2023). Modeling Development and validation of Metaverse Attitude Scale. International Journal of Technology in Education (IJTE), 6(2), 155-186. https://doi.org/10.46328/ijte.363
DOI: https://doi.org/10.46328/ijte.363
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Abstracting/Indexing
International Journal of Technology in Education (IJTE) - ISSN:2689-2758
affiliated with
International Society for Technology, Education and Science (ISTES)
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.