The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Mobile learning for science and mathematics school education: A systematic review of empirical evidence
Open accessAbstract
Abstract The ubiquity, flexibility, ease of access and diverse capabilities of mobile technologies make them valuable and a necessity in current times. However, they are under-utilized assets in mathematics and science school education. This article analyses the high quality empirical evidence on mobile learning in secondary school science and mathematics education. Our study employed a Systematic Literature Review (SLR) using well-accepted and robust guidelines. The SLR resulted in the detailed analysis of 49 studies (60 papers) published during 2003–2016. Content and thematic analyses were used to ascertain pedagogical approaches, methodological designs, foci, and intended and achieved outcomes of the studies. The apps and technologies used in these studies were further classified for domain, type and context of use. The review has highlighted gaps in existing literature on the topic and has provided insights that have implications for future research.
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Sung, Y.-T., Chang, K.-E., & Liu, T.-C. (2016) · Computers & Education · doi:10.1016/j.compedu.2015.11.008 · Cited by 1,574
Dwan, K., Gamble, C., Williamson, P. R., Kirkham, J. J., & the Reporting Bias Group (2013) · PLoS ONE · doi:10.1371/journal.pone.0066844 · Cited by 1,127
Cheon, J., Lee, S., Crooks, S. M., & Song, J. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.04.015 · Cited by 1,057
Review of trends from mobile learning studies: A meta-analysis
Wu, W.-H., Jim Wu, Y.-C., Chen, C.-Y., Kao, H.-Y., Lin, C.-H., & Huang, S.-H. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.03.016 · Cited by 946 · cited 4×
“…Hung & Zhang, 2012; G. J. Hwang & Tsai, 2011; Naismith et al., 2004; Pereira & Rodrigues, 2013; Y.-T. Sung et al., 2016; Wingkvist & Ericsson, 2011; Wu et al., 2012), or investigate only mathematics (Crompton & Burke, 2015), or only science (Crompton, Burke, et al., 2016; Zydney & Warner, 2016)…”
ResultInfluentialA Qualitative Meta-Analysis of Computer Games as Learning Tools
Ke, F. (2009) · Handbook of Research on Effective Electronic Gaming in Education · doi:10.4018/978-1-59904-808-6.ch001 · Cited by 362
Realistic Mathematics Education
Van den Heuvel-Panhuizen, M., & Drijvers, P. (2020) · Encyclopedia of Mathematics Education · doi:10.1007/978-3-030-15789-0_170 · Cited by 258
Cited by
Harnessing Generative AI (GenAI) for Automated Feedback in Higher Education: A Systematic Review
Lee, S. S., & Moore, R. L. (2024) · Online Learning · doi:10.24059/olj.v28i3.4593 · Cited by 181
Effects of digital games on student motivation in mathematics: A meta‐analysis in K‐12
Fadda, D., Pellegrini, M., Vivanet, G., & Zandonella Callegher, C. (2022) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12618 · Cited by 135
Lai, J. W. M., & Bower, M. (2020) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12412 · Cited by 92
Moderator effects of mobile users’ pedagogical role on science learning: a meta-analysis.
Shi, L., & Kopcha, T. J. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13210 · Cited by 17
Metadata
- Authors
- Bano, M., Zowghi, D., Kearney, M., Schuck, S., & Aubusson, P.
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 121
- Pages
- 30-58
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W2788874253
- Cited by
- 286
- References
- 6
- FWCI
- 7.68
- Type
- journal article
- Language
- en
- Open access
- green
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