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Factors Influencing Readiness for Integrating AR and VR in Distance Learning: An Application of the eTAM Model
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Abstract
The objectives were 1) to validate an extended Technology Acceptance Model (eTAM) measurement model for augmented reality (AR)/virtual reality (VR) readiness of undergraduate distance-learning students and 2) to estimate the direct and indirect effects of institutional, social, and psychological factors on the students’ behavioral intention (BI). Data were collected from 384 undergraduate distance-learning students. A three-step sampling procedure was used: (1) the population was divided into 12 fields of study; (2) 384 participants were proportionally allocated across the fields; and (3) students were selected by simple random sampling within each field. An initial 36-item instrument was reduced to 22 indicators through confirmatory factor analysis (CFA). The measurement model was evaluated using CFA with robust maximum likelihood estimation. The construct validity was examined using composite reliability, average variance, the Fornell–Larcker, and HTMT criteria. Structural equation modeling (SEM) was used to test the proposed eTAM relationships. The model showed acceptable fit with CFI = .93, TLI = .92, robust CFI = .95, robust TLI = .94, SRMR = .048, and robust RMSEA = .066, satisfying the recommended criteria (CFI/TLI > .90, SRMR < .08, and RMSEA close to .06). It was found that self-efficacy (SE) strongly predicted perceived ease of use (PEOU; β = .899). Social interaction and sense of belonging (SI) was a strong predictor of SE (β = .837). Institutional technology and infrastructure support (TI_in; β = .099) contributed modestly. Behavioral intention (BI) was most strongly predicted by PU (β = .339), whereas TI_in influenced BI indirectly through PU rather than through a direct path. The model explained substantial variance in SE (R2 = .75), PEOU (R2 = .71), PU (R2 = .96), and BI (R2 = .81).
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