September 10, 2025Journal of Educational and Social Research

Integration of ISSM-TAM Models for Sustainable E-Learning from a Bayesian Structural Approach

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Authors

DADiego Alonso Córdova Ayala JGJorge Chue Gallardo

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Implication

Quantitative analysis reveals the ISSM-TAM e-learning model enhances academic performance in students, indicating Bayesian methods may offer superior parameter estimation.

Key Points

The Bayesian model achieved better goodness-of-fit indices compared to traditional models.
A sample of 767 undergraduate students was analyzed using a structured questionnaire with 40 items.
The study applied various statistical techniques, including PLS-SEM, CB-SEM, and B-SEM.
Exploratory and inferential analyses validated the structural relationships in the hybrid e-learning model.

Cite This Study

Ayala et al. (2025) studied this question.

synapsesocial.com/papers/68c23cf6b210217d6478c2d3 https://doi.org/10.36941/jesr-2025-0187

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Implication

Quantitative analysis reveals the ISSM-TAM e-learning model enhances academic performance in students, indicating Bayesian methods may offer superior parameter estimation.

Integration of ISSM-TAM Models for Sustainable E-Learning from a Bayesian Structural Approach

Discussion

Member takes

Implication

Key Points

Cite This Study

Integration of ISSM-TAM Models for Sustainable E-Learning from a Bayesian Structural Approach

Discussion

Member takes

Implication

Key Points

Cite This Study

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