JOURNAL ARTICLE
Israeli, Jordanian, and Czech Teachers' Perceptions of Using Blended Learning during COVID-19.
Published In: International Journal of Technology, Knowledge & Society: Annual Review, 2024, v. 20, n. 2. P. 47 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Shamma, Fathi; Kadrnozkova, Monika 3 of 3
Abstract
This article aimed to identify the perceptions of Israeli, Jordanian, and Czech teachers about using blended learning during COVID-19. A quantitative method was adopted in which a questionnaire was used to collect data from 509 teachers--160 from Israel, 169 from Jordan, and 180 from the Czech Republic. The questionnaire contained thirty items divided into three dimensions: teaching, learning, and educational environment. The results of this study showed a high degree of blended learning use among Israeli teachers, a moderate one among Jordanians, and a low degree of usage among Czech teachers. It also showed statistically significant differences attributed to gender and the type of school among Israeli teachers. Despite these results, all the teachers realized the potential of blended learning to improve educational outcomes. We recommend that to maximize the benefits of blended learning, challenges such as infrastructural restrictions, teacher training, and equal access to technology must be addressed. The authors concluded that the implementation of blended learning depends on two factors: the readiness of the teachers to implement it and the willingness of the system to meet their needs. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Technology, Knowledge & Society: Annual Review. 2024/12, Vol. 20, Issue 2, p47
- Document Type:Article
- Subject Area:Education
- Publication Date:2024
- ISSN:1832-3669
- DOI:10.18848/1832-3669/CGP/v20i02/47-66
- Accession Number:181706002
- Copyright Statement:Copyright of International Journal of Technology, Knowledge & Society: Annual Review is the property of Common Ground Research Networks 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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