16 SES 04 A, Mobile Learning
Paper/Pecha Kucha Session
Technology and electronic devices have become an increasing feature of children’s lives both within and outside educational environments. Most young people today use a variety of technologies on a daily basis (McCoy et al., 2012). Literature about children’s capacity to use digital devices involves studies on digital avatars (Liu et al., 2012) and use of game consoles (Miller and Robertson, 2011), indicating that young children are often very skilful technology users. But very little attention has focused on the impact of technology usage – particularly in terms of the academic development of children as they move into adolescence. This paper addresses this gap: to what extent do children have access to mobile phone technology at age 9 and how does this impact on their academic development? The study is based on a large scale nationally representative longitudinal study of Irish children, Growing Up in Ireland, tracking one-in-eight Irish nine-year-old children as they transition into adolescence (13 years of age).
Children’s educational attainment is strongly associated with the characteristics of their family environment, as the commanding influences of family resources (economic, cultural and social) on children’s educational attainment are evident in the strong associations between children’s attainment at school and family income, parental occupational status and parental education (Shonkoff and Philips 2000; Smyth et al. 2010). This body of research demonstrates that the resources available to families tend to be limited among some social groups and, in turn, children’s educational attainment tends to be poorer among these families. The vast body of work on children’s out-of-school activities suggests that participation in structured activities, versus free play, is positively associated with children’s academic achievement (Marsh and Kleitman 2003; Fletcher et al. 2003; Broh 2002; McCoy et al. 2012). There is much less clarity on whether and how engagement with technology, particularly mobile phone technology, can enhance cognitive development.
Some literature does examine concerns that the literacy skills of children who make substantial use of text messaging might be adversely affected. At age 9 to 12 years of age, children are still developing and consolidating their conventional reading and writing skills. This is perhaps why popular opinion suggests that frequent exposure to textese may disrupt conventional literacy development (Kemp, 2011). To date most of the research on textese in school age children has been in the UK, where mobile phones were adopted relatively early and widely. Impact on literacy skills – “almost all of the research published to date has been cross-sectional, so it has been difficult to draw casual conclusions about potential links between texting and literacy” (Kemp, 2011 - editorial, Journal of Computer Assisted Learning, 2011, 27:1-3). Overall, “the existing evidence base concerning children’s smartphone use is limited by methodological issues, lacks integration and is largely a-theoretical in nature”. (Terras and Ramsay, 2016, p.11)
Our conceptual framework assumes that mobile phone access at age 9 will be influenced by both a host of child and family factors, such as the child’s interest and engagement in other activities, as well as being influenced by other factors such as parent’s own education, family economic vulnerability, family relationships and family structure. Therefore, we take these factors into account in tracing the consequences of mobile phone usage at age 9, on academic outcomes at age 13 after the transition to secondary education. This paper examines two research questions:
(1) To what extent does access to mobile phones among children vary socio-economic groups?
(2) To what extent does mobile phone ownership at age 9 influence academic development, across reading and maths domains, at age 13?
The study is based on quantitative analysis of the Growing Up in Ireland (GUI) data. Much of the literature in the area of technology usage and impact has relied on cross-sectional data. Using longitudinal data on 9- and 13-year old children we measure the extent to which academic outcomes, in reading and maths, over the period from 9 to 13 years are shaped by children’s engagement with technology. The sampling of children within schools means that traditional multiple regression techniques are not suitable as resulting estimates of the standard errors are likely to be too small. Hence, the statistical analysis is conducted in STATA and the standard errors are adjusted to take account of weights and of clustering at the school level at age 9. Between September 2007 and May 2008, GUI interviewed 8,578 nine-year-olds, their parents and their teachers on a wide range of issues. Wave 2 of the study took place in 2011/2012 and included 7,423 of the children who had participated in Wave 1. Both GUI questionnaires at 9 and 13 collect detailed information on various aspects of children’s engagement with technology in a range of settings. Crucially the voice of the child is central – capturing important views on their use of different types of technology within and outside school and their perceptions of restrictions on their access imposed by parents and/or school personnel. Parents also report on the nature of the child’s engagement with technology – including internet accessibility, the use of a home computer and other technology and the duration of time spent on technology usage. The analysis examines the extent to which mobile phone ownership at age 9 shapes academic development at age 13. Academic ability at age 9 is based on children’s school performance on a standardised reading and mathematics tests. At 13 years, Drumcondra verbal and numeric ability tests were administered. There are a number of characteristics of the child and the family that are included in the analysis. These include family structure (whether a one- or two-parent family); mother’s education; mother’s age; parental income and education; dimensions of the parent–child relationship; parenting style; parental attendance at school meetings and assistance with homework; whether the mother has a disability.
The results show a strongly negative relationship between mobile phone ownership at age 9 and academic performance at age 9 and 13 (measured cross-sectionally and longitudinally). Outside of the school setting, wide variation is also observed in terms of children’s access to mobile technology and the nature of that access. Some of this reflects socio-economic factors, characteristics of the child, and the parenting style adopted. Taking account of these factors, overall mobile phone ownership has a negative impact on academic development, over the period from childhood into adolescence. A range of robustness checks confirms the strongly negative results and also shows that the results hold across income and socio-economic groupings. The study proposes a range of potential underlying processes explaining the results. It may be that the technology usage is having a distraction effect in terms of children’s school- and other educational pursuits. We also hypothesise that early mobile phone usage impacts on peer relations and the development of social skills which may then impact on children’s engagement with school. Additionally we suggest that reliance on technology among children with early mobile phone access may shape the nature of interactions and communication within the home environment and this may in turn influence the nature of parent’s engagement with their child’s school activities. The potential for technology to enhance student learning is increasingly well-demonstrated, but the dangers in early mobile phone access in terms of children’s academic development is an important finding from this study.
Belo. R., Ferreira, P., and R. Telang, 2010. The effects of broadband in schools: Evidence from Portugal, Working Paper, Carnegie Mellon University. Bernicot, J., Goumi, A., A. Bert-Erboul and O. Volckaert-Legrier (2014) ‘How do skilled and less-skilled spellers write text messages? A longitudinal study’, Journal of Computer Assisted Learning, 30: 559-576. Burden et al., 2012 iPad Scotland Evaluation, University of Hull. Coe, J.E.L. and J.V. Oakhill 2010 ‘’txtN is ez f u no h2 rd’: the relation between reading ability and text-messaging behaviour’, Journal of Computer Assisted Learning, 27: 4-17. Goolsbee, A. and J. Guryan, 2006. The Impact of Internet Subsidies in Public Schools. The Review of Economics and Statistics 88(2): 336-347. https://www.ofcom.org.uk/__data/assets/pdf_file/0020/108182/children-parents-media-use-attitudes-2017.pdf Kemp, N. and C. Bushnell 2011 ‘Children’s text messaging: Abbreviations, input methods and links with literacy’, Journal of Computer Assisted Learning, 27, 18-27. Kemp, N., 2011. Editorial: Special Issue, Journal of Computer Assisted Learning, 27: 1-3. Lu, M. 2008 ‘Effectiveness of vocabulary learning via mobile phone’, Journal of Computer Assisted Learning, 24: 515-525. Male, T. and K. Burden 2014 Access Denied? Twenty-first century technology in schools, Technology, Pedagogy and education, 23(4): 423-437. O’Hara, M. 2011 Young children’s ICT experiences in the home: Some parental perspectives. Journal of Early Childhood Research, 9: 220-231. OECD 2001 Learning to Change: ICT in Schools. Paris: OECD. Ofcom 2017 Children and Parents: Media Use and Attitudes Report, Available at: Plester, B., C. Wood and P. Joshi 2009 Exploring the relationship between children’s knowledge of text message abbreviations and school literacy outcomes, British Journal of Developmental Psychology, 27: 145-161. Plester, B., M.K. Lerkkanen, L.J. Linjama, H. Rasku-Puttonen and K. Littleton 2011 ‘Finnish and UK English pre-teen children’s text message language and its relationship with literacy skills’, Journal of Computer Assisted Learning, 27, 37-48. Terras, M.M. and J. Ramsay 2016. Family Digital Literacy Practices and Children’s Mobile Phone Use’, Frontiers in Psychology, 2016, 7: 1957. Wood, C., E. Jackson, Plester and L. Wilde 2009 Children’s use of mobile phone text messaging and its impact on literacy development in primary school. British Educational Communications Technology Agency. Yoo, M. and K. Mikyung 2011 ‘The Comparative Study on Mother’s Rearing Attitude and Communication among Mother and Students Behaviour between Mobile Phone Addiction Group and non’. Korean Parent-Child Health Journal, 14(2): 76-83.
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