Keywords
Socioeconomic status, Internet, academic achievement, children, math, language
Abstract
In this study, we investigate the mediating effects of children’s Internet use on the relationship between family socioeconomic status and their academic achievement, and whether the mediating effects vary across different academic subjects. We used the data from the China Family Panel Studies on the socioeconomic status of children's families, children’s Internet use, and their academic performance. In the 2014 sample, there were 2,686 participants (females=1,272). In 2016, there were 2,330 participants (females=1,069), and in 2018, there were 2,485 participants (females=1,151). The socioeconomic status and the Internet use were measured by a questionnaire. Standardized tests measured the academic performance. Our findings showed that family socioeconomic status was positively related to math performance, but not significantly related to Chinese performance. The results also indicated that Internet use did not significantly mediate the relationship between family socioeconomic status in 2014 and math performance in 2016, while the frequency of Internet use to study in 2016 partly mediated the relationship between family socioeconomic status in 2016 and math performance in 2018. Our findings suggest that Internet use can only mediate the relationship between family socioeconomic status and math performance and the mediating effects become stronger over time.
References
Anders, Y., Rossbach, H.G., Weinert, S., Ebert, S., Kuger, S., Lehrl, S., & Maurice, J.V. (2012). Home and preschool learning environments and their relations to the development of early numeracy skills. Early Childhood Research Quarterly, 27(2), 231-244. https://doi.org/10.1016/j.ecresq.2011.08.003
Link DOI | Link Google Scholar
Assari, S., Boyce, S., Bazargan, M., & Caldwell, C.H. (2020). Mathematical performance of American youth: Diminished returns of educational attainment of Asian-American parents. Education sciences, 10(2), 32. https://doi.org/10.3390/educsci10020032
Link DOI | Link Google Scholar
Baker, C.E., Kainz, K.L., & Reynolds, E.R. (2018). Family poverty, family processes and children’s preschool achievement: Understanding the unique role of fathers. Journal of Child and Family Studies, 27(4), 1242-1251. https://doi.org/10.1007/s10826-017-0947-6
Link DOI | Link Google Scholar
Bonfadelli, & Heinz. (2002). The Internet and knowledge gaps: A theoretical and empirical investigation. European Journal of Communication. https://doi.org/10.1177/0267323102017001607
Link DOI | Link Google Scholar
Bradley, R.H., & Corwyn, R.F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 21(3), 371-399. https://doi.org/10.1146/annurev.psych.53.100901.135233
Link DOI | Link Google Scholar
Brooks-Gunn, J., & Duncan, G.J. (1997). The effects of poverty on children. The Future of Children, 7(2), 55-71. https://doi.org/10.2307/1602387
Link DOI | Link Google Scholar
Camerini, A.L., Schulz, P.J., & Jeannet, A.M. (2018). The social inequalities of Internet access, its use, and the impact on children's academic performance: Evidence from a longitudinal study in Switzerland. New Media & Society, 20(7), 2489-2508. https://doi.org/10.1177/1461444817725918
Link DOI | Link Google Scholar
Cao, F.L., & Su, L.Y. (2007). Internet addiction among Chinese adolescents: Prevalence and psychological features. Child Care Health & Development, 33(3), 275-281. https://doi.org/10.1111/j.1365-2214.2006.00715.x
Link DOI | Link Google Scholar
Cheng, Y., & Wu, X. (2017). The relationship between SES and reading comprehension in Chinese: A Mediation Model. other, 8. https://doi.org/10.3389/fpsyg.2017.00672
Link DOI | Link Google Scholar
China Internet Network Information Center (Ed.) (2018). 42nd statistical report on the development of Internet in China. http://bit.ly/37Q2fj3
Link Google Scholar
DeFlorio, L., & Beliakoff, A. (2015). Socioeconomic status and preschoolers' mathematical knowledge: The contribution of home activities and parent beliefs. Early Education & Development, 26(3), 319-341. https://doi.org/10.1080/10409289.2015.968239
Link DOI | Link Google Scholar
Dijk, J.V., & Hacker, K. (2003). The digital divide as a complex and dynamic phenomenon. Information Society, 19(4), 315-326. https://doi.org/10.1080/01972240309487
Link DOI | Link Google Scholar
Duncan, G.J., Brooks-Gunn, J., & Klebanov, P.K. (1994). Economic deprivation and early childhood development. Child Dev, 65(2), 296-318. https://doi.org/10.2307/1131385
Link DOI | Link Google Scholar
Fairlie, R.W., & Robinson, J. (2013). Experimental evidence on the effects of home computers on academic achievement among schoolchildren. Social Science Electronic Publishing. https://doi.org/10.3386/w19060
Link DOI | Link Google Scholar
Farooq, M.S., Chaudhry, A.H., Shafiq, M., & Berhanu, G. (2011). Factors affecting students’ quality of academic performance: A case of secondary school level. Journal of Quality and Technology Management, 7(2), 1-14. https://bit.ly/30c1XPz
Link Google Scholar
Fergusson, D.M., Horwood, L.J., & Boden, J.M. (2008). The transmission of social inequality: Examination of the linkages between family socioeconomic status in childhood and educational achievement in young adulthood. Research in Social Stratification & Mobility, 26(3), 277-295. https://doi.org/10.1016/j.rssm.2008.05.001
Link DOI | Link Google Scholar
Ferraro, K.F., Schafer, M.H., & Wilkinson, L.R. (2016). Childhood Disadvantage and health problems in middle and later life: Early imprints on physical health? American Sociological Review, 81(1), 107-133. https://doi.org/10.1177/0003122415619617
Link DOI | Link Google Scholar
Gómez-García, M., Hossein-Mohand, H., Trujillo-Torres, J.M., Hossein-Mohand, H., & Aznar-Díaz, I. (2020). Technological Factors That Influence the Mathematics Performance of Secondary School Students. Mathematics, 8(11), 1935. https://doi.org/10.3390/math8111935
Link DOI | Link Google Scholar
Habriichuk, L., & Tulchak, L. (2017). Foreign language education and Internet? Advantages and disadvantages. https://bit.ly/2NIaHKv
Link Google Scholar
Hargittai, E. (2001). Second-level digital divide: Differences in people's online skills. First Monday, 7(4). https://doi.org/10.5210/fm.v7i4.942
Link DOI | Link Google Scholar
Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
Link DOI | Link Google Scholar
Huang, C. (2018). Social network site use and academic achievement: A meta-analysis. Computers & Education, 119, 76-83. https://doi.org/10.1016/j.compedu.2017.12.010
Link DOI | Link Google Scholar
Hunley, S.A., Evans, J.H., Delgado-Hachey, M., Krise, J., Rich, T., & Schell, C. (2005). adolescent computer use and academic achievement. Adolescence, 40(158), 307-318.
Link Google Scholar
Kim, S.Y., Kim, M.S., Park, B., Kim, J.H., & Choi, H.G. (2017). The associations between Internet use time and school performance among Korean adolescents differ according to the purpose of Internet use. PloS one, 12(4), e0174878. https://doi.org/10.1371/journal.pone.0174878
Link DOI | Link Google Scholar
Kirkorian, H.L., & Anderson, W.D.R. (2008). Media and young children's learning. Future of Children, 18(1), 39-61. https://doi.org/10.1353/foc.0.0002
Link DOI | Link Google Scholar
Kubey, R.W., Lavin, M.J., & Barrows, J.R. (2001). Internet use and collegiate academic performance decrements: Early findings. Journal of Communication, 51(2), 366-382. https://doi.org/10.1111/j.1460-2466.2001.tb02885.x
Link DOI | Link Google Scholar
Liu, A., & Xie, Y. (2015). Influences of monetary and non-monetary family resources on children's development in verbal ability in China. Research in Social Stratification & Mobility, 40, 59-70. https://doi.org/10.1016/j.rssm.2015.02.003
Link DOI | Link Google Scholar
Liu, D., Chung, K.K.H., & Mcbride, C. (2016). The role of SES in Chinese (L1) and English (L2) word reading in Chinese-speaking kindergarteners. Journal of Research in Reading, 39(3), 268-291. https://doi.org/10.1111/1467-9817.12046
Link DOI | Link Google Scholar
Livingstone, S., Mascheroni, G., & Staksrud, E. (2017). European research on children's Internet use: Assessing the past and anticipating the future. New Media & Society, 20(3), 1103-1122. https://doi.org/10.1177/1461444816685930
Link DOI | Link Google Scholar
Marks, G.N., & Pokropek, A. (2019). Family income effects on mathematics achievement: Their relative magnitude and causal pathways. Oxford Review of Education, 45(6), 769-785. https://doi.org/10.1080/03054985.2019.1620717
Link DOI | Link Google Scholar
Mascheroni, G., & Olafsson, K. (2015). The mobile Internet: Access, use, opportunities and divides among European children. New Media & Society, 18(8), 1657-1679. https://doi.org/10.1177/1461444814567986
Link DOI | Link Google Scholar
Meggiolaro, S. (2018). Information and communication technologies use, gender and mathematics achievement: Evidence from Italy. Social Psychology of Education, 21(2), 497-516. https://doi.org/10.1007/s11218-017-9425-7
Link DOI | Link Google Scholar
Mitra, S. (2019). Does collaborative use of the Internet affect reading comprehension in children. Journal of Learning for Development, 6(1), 20-36. https://bit.ly/30bH07e
Link Google Scholar
Muthén, L., & Muthén, B. (2016). Mplus. The comprehensive modelling program for applied researchers: User’s guide, 5.
Link Google Scholar
Norris, P.N. (2001). Digital divide: Civic engagement, information poverty and the internet world-wide. Info, 5(1). https://doi.org/10.1017/CBO9781139164887
Link DOI | Link Google Scholar
Park, A., & Hannum, E. (2001). Do teachers affect learning in developing countries? Evidence from matched student-teacher data from China. In Conference Rethinking Social Science Research on the Developing World in the 21st Century (pp. 1-41). http://bit.ly/3q69Kch
Link Google Scholar
Park, Y. J. (2015). My whole world's in my palm! The second-level divide of teenagers' mobile use and skill. New Media & Society, 17(6), 977-995. https://doi.org/10.1177/1461444813520302
Link DOI | Link Google Scholar
Resta, P. (1992). Organizing education for minorities: enhancing minority access and use of the new information technologies in higher education. Education & Computing, 8(1-2), 119-127. https://doi.org/10.1016/0167-9287(92)80021-3
Link DOI | Link Google Scholar
Scheerder, A., Deursen, A.V., & Dijk, J.V. (2017). Determinants of Internet skills, uses and outcomes. A Systematic review of the second- and third-level digital divide. Telematics and Informatics, 34(8), 1607-1624. https://doi.org/10.1016/j.tele.2017.07.007
Link DOI | Link Google Scholar
Stavropoulos, V., Alexandraki, K., & Motti-Stefanidi, F. (2013). Recognizing Internet addiction: Prevalence and relationship to academic achievement in adolescents enrolled in urban and rural Greek high schools. Journal of Adolescence, 36(3), 565-576. https://doi.org/10.1016/j.adolescence.2013.03.008
Link DOI | Link Google Scholar
Sutton, R.E. (1991). Equity and computers in the schools: A decade of research. Review of Educational Research, 61(4), 475-503. https://doi.org/10.3102/00346543061004475
Link DOI | Link Google Scholar
Vigdor, J.L., Ladd, H.F., & Martinez, E.G. (2014). Scaling the digital divide: Home computer technology and student achievement. In NBER Working Paper (pp. 1-47). https://doi.org/10.3386/w16078
Link DOI | Link Google Scholar
Wang, L., Li, X., & Li, N. (2014). Socio-economic status and mathematics achievement in China: A review. ZDM, 46(7), 1051-1060. https://doi.org/10.1007/s11858-014-0617-8
Link DOI | Link Google Scholar
Xie, Y. (2012). The user’ s guide of the China family panel studies (2010). Institute of Social Science Survey, Peking University.
Link Google Scholar
Zhou, D., Liu, J., & Liu, J. (2020). The effect of problematic Internet use on mathematics achievement: The mediating role of self-efficacy and the moderating role of teacher-student relationships. Children and Youth Services Review, 118, 105372. https://doi.org/10.1016/j.childyouth.2020.105372
Link DOI | Link Google Scholar
Technical information
Received: 15-12-2020
Revised: 24-01-2021
Accepted: 15-02-2021
OnlineFirst: 15-04-2021
Publication date: 01-07-2021
Article revision time: 40 days | Average time revision issue 68: 37 days
Article acceptance time: 62 days | Average time of acceptance issue 68: 78 days
Preprint editing time: 152 days | Average editing time preprint issue 68: 168 days
Article editing time: 197 days | Average editing time issue 68: 213 days
Metrics
Metrics of this article
Views: 27763
Abstract readings: 24275
PDF downloads: 3488
Full metrics of Comunicar 68
Views: 315382
Abstract readings: 273483
PDF downloads: 41899
Cited by
Cites in Web of Science
Currently there are no citations to this document
Cites in Scopus
Currently there are no citations to this document
