Learning mathematics with personal mobile devices in school: a multigroup invariance analysis of acceptance among students and teachers
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Resumo
Students’ use of personal mobile devices (PMDs), including smartphones, tablets, and laptops, in mathematics classrooms globally has become feasible due to the implementation of the bring your own device (BYOD) initiatives and policies in schools. Students’ academic use of PMDs in mathematics learning has been associated with increased motivation, enjoyment, and enhanced performance. While debates continue worldwide on the bans of PMDs in schools, it is noteworthy that students in Namibian basic education are not permitted to use PMDs in schools. This study employed a comparative nonexperimental quantitative research design to assess the perceived usefulness (PU) and behavioural intention (BI) to use PMDs in mathematics classrooms among 500 Namibian students and 209 teachers. The study employed a volunteer purposeful sampling method to select participating students and teachers from government schools in the Omusati and Khomas regions. Student selection was based on self-selection from full-class mathematics groups. Similarly, the study utilised volunteer purposeful sampling to recruit grades 4–12 mathematics teachers. Utilising structural equation modelling, the findings revealed that students expressed more positive ratings for PMD usefulness and intention than did teachers. Furthermore, PU significantly predicted students’ BI to learn mathematics with PMDs in school. Multigroup confirmatory factor analysis supported configural, metric, and scalar invariance in PU and BI factor structures across both participant groups. However, when students’ latent means of PU and BI are set to 0, the teachers’ latent mean parameter estimates are negative, suggesting potential disparities. Teachers should recognise and leverage students’ positive perceptions of PMDs to enhance motivation and engagement in mathematics learning. Simultaneously, ensuring consistent assessment across participant groups is essential, while addressing teachers’ PMDs reservations through professional development and support remains crucial.
Dados da obra
- Tipo
- Artigo
- Periódico
- Frontiers in Education, v. 9
- Editora
- Frontiers Media S.A.
- Ano
- 2024 (2024-07)
- Idioma
- en
- Palavras-chave
- behavioural intentions; mathematics; measurement invariance; mathematics learning; personal mobile devices; mathematics education
- Temas
- Avaliação, Formação de Professores de Matemática
- DOI
- 10.3389/feduc.2024.1425779
- ISSN
- 2504-284X
- Acesso
- Acesso aberto
- Fontes
- DOAJ — Directory of Open Access Journals
- Na Biblioteca desde
- 01/10/2026 · verificada em 03/10/2026
Como citar
ABNT
JATILENI, Cloneria Nyambali et al.. Learning mathematics with personal mobile devices in school: a multigroup invariance analysis of acceptance among students and teachers. Frontiers in Education, v. 9, 2024. DOI: https://doi.org/10.3389/feduc.2024.1425779.
APA
Jatileni, C. N., Havu-Nuutinen, S., Pöntinen, S., & Kukkonen, J. (2024). Learning mathematics with personal mobile devices in school: a multigroup invariance analysis of acceptance among students and teachers. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1425779
BibTeX
@article{jatileni2024,
author = {Jatileni, Cloneria Nyambali and Havu-Nuutinen, Sari and Pöntinen, Susanna and Kukkonen, Jari},
title = {Learning mathematics with personal mobile devices in school: a multigroup invariance analysis of acceptance among students and teachers},
year = {2024},
journal = {Frontiers in Education},
volume = {9},
publisher = {Frontiers Media S.A.},
doi = {10.3389/feduc.2024.1425779},
language = {en}
}RIS
TY - JOUR AU - Jatileni, Cloneria Nyambali AU - Havu-Nuutinen, Sari AU - Pöntinen, Susanna AU - Kukkonen, Jari TI - Learning mathematics with personal mobile devices in school: a multigroup invariance analysis of acceptance among students and teachers PY - 2024 JO - Frontiers in Education VL - 9 DO - 10.3389/feduc.2024.1425779 LA - en ER -
Referência gerada automaticamente a partir dos metadados das fontes; confira com o documento original. Baixar BibTeX · Baixar RIS
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