Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions
Mobile learning (ML) is extremely relevant to distance teaching. Although much is known about ML usage in teacher education, less is known about crucial points in teachers’ ML adoption process under constraints such as the COVID-19 pandemic. The aim of this exploratory case study was to gain insight...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Education |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/feduc.2022.1077989/full |
| _version_ | 1811296197519867904 |
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| author | Yulia Muchnik-Rozanov Yulia Muchnik-Rozanov Rivi Frei-Landau Orit Avidov-Ungar Orit Avidov-Ungar |
| author_facet | Yulia Muchnik-Rozanov Yulia Muchnik-Rozanov Rivi Frei-Landau Orit Avidov-Ungar Orit Avidov-Ungar |
| author_sort | Yulia Muchnik-Rozanov |
| collection | DOAJ |
| description | Mobile learning (ML) is extremely relevant to distance teaching. Although much is known about ML usage in teacher education, less is known about crucial points in teachers’ ML adoption process under constraints such as the COVID-19 pandemic. The aim of this exploratory case study was to gain insight into the ML adoption process, including its critical points, by examining teachers’ emotion-related language. This study investigated the emotional response of 32 inservice teachers to Mobile Learning (ML) adoption while attending ML training during the COVID-19 pandemic. The data were collected using semi-structured interviews (10), focus groups (3), and participants’ reflections (96) at five time points. The data underwent multilevel analysis (content and linguistic analyses), revealing two critical stages during the ML adoption process and indicating several factors that may affect the quality of emotional response, thereby promoting or impeding this process. The study highlights the critical sages and their related features that must be addressed to promote optimal ML adoption in teacher education in both routine and emergency conditions. |
| first_indexed | 2024-04-13T05:45:53Z |
| format | Article |
| id | doaj.art-6478bb0cfbf74da9801dcf7f64b18ae3 |
| institution | Directory Open Access Journal |
| issn | 2504-284X |
| language | English |
| last_indexed | 2024-04-13T05:45:53Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Education |
| spelling | doaj.art-6478bb0cfbf74da9801dcf7f64b18ae32022-12-22T02:59:58ZengFrontiers Media S.A.Frontiers in Education2504-284X2022-12-01710.3389/feduc.2022.10779891077989Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotionsYulia Muchnik-Rozanov0Yulia Muchnik-Rozanov1Rivi Frei-Landau2Orit Avidov-Ungar3Orit Avidov-Ungar4The School of Education, Achva Academic College, Shikmim, IsraelThe Faculty of Education in Science and Technology, Technion - Israel Institute of Technology, Haifa, IsraelThe Faculty of Education in Science and Technology, Technion - Israel Institute of Technology, Haifa, IsraelThe School of Education, Achva Academic College, Shikmim, IsraelThe Department of Education and Psychology, Open University of Israel, Ra’anana, IsraelMobile learning (ML) is extremely relevant to distance teaching. Although much is known about ML usage in teacher education, less is known about crucial points in teachers’ ML adoption process under constraints such as the COVID-19 pandemic. The aim of this exploratory case study was to gain insight into the ML adoption process, including its critical points, by examining teachers’ emotion-related language. This study investigated the emotional response of 32 inservice teachers to Mobile Learning (ML) adoption while attending ML training during the COVID-19 pandemic. The data were collected using semi-structured interviews (10), focus groups (3), and participants’ reflections (96) at five time points. The data underwent multilevel analysis (content and linguistic analyses), revealing two critical stages during the ML adoption process and indicating several factors that may affect the quality of emotional response, thereby promoting or impeding this process. The study highlights the critical sages and their related features that must be addressed to promote optimal ML adoption in teacher education in both routine and emergency conditions.https://www.frontiersin.org/articles/10.3389/feduc.2022.1077989/fullmobile-learningteacher educationCOVID-19emotional responselinguistic analysis |
| spellingShingle | Yulia Muchnik-Rozanov Yulia Muchnik-Rozanov Rivi Frei-Landau Orit Avidov-Ungar Orit Avidov-Ungar Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions Frontiers in Education mobile-learning teacher education COVID-19 emotional response linguistic analysis |
| title | Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions |
| title_full | Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions |
| title_fullStr | Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions |
| title_full_unstemmed | Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions |
| title_short | Mobile-learning adoption in teacher education amidst COVID-19: Identifying two critical stages by exploring teachers’ emotions |
| title_sort | mobile learning adoption in teacher education amidst covid 19 identifying two critical stages by exploring teachers emotions |
| topic | mobile-learning teacher education COVID-19 emotional response linguistic analysis |
| url | https://www.frontiersin.org/articles/10.3389/feduc.2022.1077989/full |
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