JOURNAL ARTICLE
Evaluating the Mobile Learning Quality for Promoting the User Needs in Taiwanese Higher Education During COVID-19.
Published In: International Journal of Information Technology & Decision Making, 2024, v. 23, n. 2. P. 629 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Lu, Ming-Tsang; Huang, Jui-Chieh; Wang, Ming-Hui 3 of 3
Abstract
This study explores the strategic issues related to the mobile learning quality in Taiwanese higher education during the COVID-19 pandemics. While much previous study determined the factors affecting mobile learning quality, seldom research works discussed the influence weights of the elements and their interrelations in the higher education through a comprehensive view. Hence, the purpose of this research is to explore the interrelationships and feedback between the factors affecting mobile learning quality via a combined multiple attribute decision-making (MADM) method, which will include decision-making trial and evaluation laboratory (DEMATEL), and DEMATEL-based ANP (DANP) approaches. This recommended approach can offer guidance to prioritize the influence elements in the enhancement plans for mobile learning quality. This research uses the recommended approach in the higher education in Taiwan as an empirical study during COVID-19. These findings results state which service quality needs to be enhanced primarily, and learning ability is the most important factor influencing mobile learning quality during COVID-19. Furthermore, the results show that system quality perspective has the strongest impact on the relations and it also has an important effect on other perspectives. The results can provide guidance on assigning resources of limit to improve this mobile learning quality in Taiwanese higher education in the COVID-19 pandemics. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Information Technology & Decision Making. 2024/03, Vol. 23, Issue 2, p629
- Document Type:Article
- Subject Area:Education
- Publication Date:2024
- ISSN:0219-6220
- DOI:10.1142/S0219622023500232
- Accession Number:176812627
- Copyright Statement:Copyright of International Journal of Information Technology & Decision Making is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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