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Exploring the acceptance of e-learning in health professions education in Iran based on the technology acceptance model (TAM).

作者信息

Mastour Haniye, Yousefi Razieh, Niroumand Shabnam

机构信息

Department of Medical Education, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

School of Medical Education and Learning Technologies, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Sci Rep. 2025 Mar 10;15(1):8178. doi: 10.1038/s41598-025-90742-5.


DOI:10.1038/s41598-025-90742-5
PMID:40065055
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11894139/
Abstract

The COVID-19 pandemic has rapidly accelerated the adoption of e-learning across educational institutions worldwide, especially in health professions education. This study explored the factors influencing e-learning acceptance among health professions students and faculty members in Iran using an extended Technology Acceptance Model (TAM). A descriptive cross-sectional study was conducted among 932 participants, including faculty members, postgraduates, and undergraduates at Mashhad University of Medical Sciences, one of the top five universities in Iran. Data were collected through an online survey from August 1 to August 31, 2020. The TAM was extended by incorporating innovation, social, and organizational characteristics. Partial least squares structural equation modeling was used to analyze the relationships between constructs, including perceived ease of use (PEU), perceived usefulness (PU), and intention to use e-learning. The findings revealed that PEU and PU were pivotal in shaping e-learning acceptance, underscoring the need for user-friendly and effective platforms. Attitude toward e-learning significantly influenced participants' intention to use e-learning platforms, with PEU emerging as the most influential factor. PU had a more substantial impact on faculty members and undergraduate students, while postgraduates placed less emphasis on usefulness. Organizational factors only indirectly affected e-learning acceptance, mediated by individual characteristics. This study underscores the importance of usability, technological infrastructure, and digital literacy training in promoting e-learning acceptance among health professions students and faculty members. These findings significantly impact policymakers, educators, and administrators in designing more user-centered e-learning platforms. Future research should explore the longitudinal effects of technological advancements and institutional policies on e-learning adoption.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/a11ba8a75172/41598_2025_90742_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/158f267e0b59/41598_2025_90742_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/087250eedeea/41598_2025_90742_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/a11ba8a75172/41598_2025_90742_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/158f267e0b59/41598_2025_90742_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/087250eedeea/41598_2025_90742_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a183/11894139/a11ba8a75172/41598_2025_90742_Fig3_HTML.jpg

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Exploring the acceptance of e-learning in health professions education in Iran based on the technology acceptance model (TAM).

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本文引用的文献

[1]
Virtual Dissection: an Educational Technology to Enrich Medical Students' Learning Environment in Gastrointestinal Anatomy Course.

Med Sci Educ. 2023-9-2

[2]
Early prediction of medical students' performance in high-stakes examinations using machine learning approaches.

Heliyon. 2023-7-13

[3]
Drivers of iPad use by undergraduate medical students: the Technology Acceptance Model perspective.

BMC Med Educ. 2022-2-8

[4]
Using virtual reality for dynamic learning: an extended technology acceptance model.

Virtual Real. 2022

[5]
The COVID-19 pandemic and E-learning: challenges and opportunities from the perspective of students and instructors.

J Comput High Educ. 2022

[6]
The acceptance and impact of Google Classroom integrating into a clinical pathology course for nursing students: A technology acceptance model approach.

PLoS One. 2021

[7]
Measuring Students' Use of Zoom Application in Language Course Based on the Technology Acceptance Model (TAM).

J Psycholinguist Res. 2021-8

[8]
A systematic review of the factors - enablers and barriers - affecting e-learning in health sciences education.

BMC Med Educ. 2020-3-30

[9]
An Analysis of the World Health Organization Disability Assessment Schedule 2.0 Measurement Model Using Partial Least Squares-Structural Equation Modeling.

Assessment. 2020-12

[10]
An Empirical Assessment of a Technology Acceptance Model for Apps in Medical Education.

J Med Syst. 2015-9-28

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