16 SES 16 B, ICT and Learning Achievements / Assessment
A recent pioneering, cross-national European study has confirmed that from the very young age children nowadays are growing in the media-rich homes, being in a daily contact with variety of digital tools, such as smartphones, tablets, computers, and games (Chaudron et al., 2015). In line with this, the well-known term ‘digital divide’ is today in the developed countries receiving a new meaning – it no longer refers to the gap in the mere access to the technology, but to the differences in the intensity and nature of the technology use (Jackson et al., 2008). Thus, research on children’s use of technology should switch the focus on examining specific technology-based activities children choose to engage in and purposes for which children utilize digital devices (Bennett & Maton, 2010).
One of the most common uses of technology among children, especially teenagers, is for communicating via social network sites and in recent times through mobile instant messaging applications (Church & de Oliveira, 2013). However, as Ahn (2011) notes, studies on the relationship of children’s use of social media and their educational outcomes are spares, particularly when compared to studies that connect children’s social media interactions and the issues of privacy, safety, and psychological well-being. Moreover, earlier studies on children’s computer use, as well as the recent ones which explored other specific forms of digital technologies, reported mixed results on their relationship with academic performance. In line with this, the first aim of this study was to explore relationship between primary-school children’s intensity of digital communication at home and their achievement in a school domain that has recently been in the focus of educational policies worldwide – STEM (Science, Technology, Engineering, Mathematics) school domain.
From the theoretical perspective, this study is embedded in the concept of capital, which Bourdieu (1986) defined as valuable and exchangeable resources in a society that can produce forms of social advantage for those who possess these resources. Early work on the technology use in the theoretical framework of capital identified experiences with technology mainly as potential forms of cultural capital. Bourdieu (1984), for example, theorized that the development of the ICT skills within the home may be regarded as the attempt to acquire a form of cultural capital, since this is an expertise or a skill that is transformable and have a relevance for one’s future outcomes in specific domains (Facer, Sutherland, Furlong, & Furlong, 2001). However, different types of technology use nowadays may be regarded not only as a pathway in acquiring cultural but also social capital–a form of capital which refers to network ties and relations which provide shared knowledge, language, norms, and mutual support (Huysman & Wulf, 2004). Here we should note another important theoretical point – the importance of transformability of capital from one form to another – e.g., social to human capital, which is crucial for successful capital reproduction (Bourdieu, 1986). Thus, from the described theoretical perspective, we will examine the relationship between children’s digital communication and children’s academic performance as a possible form of social capital conversion. Here, we will also observe the possible moderating effects of child’s gender and family socio-economic status (SES). Namely, earlier work on capital suggested that successful capital conversion may significantly depend on these two factors (e.g., DiMaggio, 1982; Dumais, 2002).
Participants This study is part of a research project, titled "STEM career aspirations during primary schooling: A cohort-sequential longitudinal study of relations between achievement, self-competence beliefs and career interests" (JOBSTEM). In the present study we included 1205 students (580 girls), attending 5th (n = 567) and 6th grade (n = 638) of primary school (Mage = 12.15 years, SDage = 0.61 years, TRage = 10.34–15.42 years). Furthermore, in total we included data from 1148 parents (899 mothers, 219 fathers, and 30 parents with the missing data on the gender). Measures The intensity of students’ digital communication was measured with the item: “When at home, how often do you communicate via Viber, Instagram, Snapchat, and similar programs?”. Students answered on a scale that includes following points: 1 = “never”, 2 = “almost never”, 3 = “less than once a week”, 4 = “once a week”, 5 = “few times a week”, 6 = “almost every day”, 7 = “every day”. Students’ total score on the objective test of STEM achievement served as an outcome measure in this study. This test was constructed for the purposes of JOBSTEM research project and a separate form was developed for each grade in the sample. Each test form includes content that is covered by current curricular for STEM school subjects that are thought in the given grade. In the Croatian educational system, in the fifth and sixth grade these subjects are Mathematics, Biology, Geography and Technical culture. Students’ test scores were transformed into z-values and centered around corresponding grade mean. Z-scores for 5th and 6th graders were then combined into a single scale to form a dependent variable of students’ achievement in STEM school domain. Family SES was operationalized as the average level of parental education. Whenever available, we used parents’ reports as the primary measure of parental education. When parental data was not available, we utilized children' reports. Parental educational level was measured on a scale of precoded responses that included following levels: 1 = Unfinished or completed elementary school, 2 = Finished high school, 3 = University degree, 4 = Graduate Degree. Procedure In order to examine the relationship between child’s digital communication and STEM achievement, we assessed moderated moderation model (Hayes, 2013) in which intensity of the digital communication served as the independent variable and child’s gender and parental education served as the moderators. This enabled us to examine two-way and three-way interactions between these variables.
Firstly, girls in comparison to boys significantly more often engaged in digital communication at home (t = 6.4; p < .001). The intensity of digital communication was not related to parental education nor to the child’s STEM achievement, while STEM achievement was moderately related to parental education (r = .34; p < .001). The results of moderation testing indicated a significant three-way interaction between digital communication, gender and parental education (B = -.14; t = -2.21; p = .027). Specifically, the conditional effect of Communicating via digital applications × Gender on STEM achievement became significant when parental education reached mean-centered value of minus 0.4 (Mean-centered parental education: M = 0, SD= 0.62). This suggests that more frequent communication via digital applications among girls was associated with better STEM achievement, but only at the lower values of parental education. These findings may be explained in terms of capital resources of children who come from socially disadvantaged families with low levels of parental education. Namely, since it can be expected that these children may often lack educational support within the family, their social networks in the digital world may present a possible source of advice, information, or support in tackling their educational challenges. Furthermore, taking into account the observed gender difference in the students’ use of technologies for purposes of communication, this may present a source of transformable social capital primarily for girls from the disadvantaged social background. Future research needs to closely examine specific ways children may share information via digital technology and how are these communication behaviors connected to their educational outcomes.
Ahn, J. (2011). The effect of social network sites on adolescents' social and academic development: Current theories and controversies. Journal of the Association for Information Science and Technology, 62(8), 1435-1445. Bennett, S., & Maton, K. (2010). Beyond the ‘digital natives’ debate: Towards a more nuanced understanding of students' technology experiences. Journal of computer assisted learning, 26(5), 321-331. Bourdieu, P. (1986). Forms of capital. In J. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). NewYork: Greenwood. Chaudron, S., Beutel, M. E., Donoso Navarrete, V., Dreier, M., Fletcher-Watson, B., Heikkilä, A. S., . . . Wölfling, K. (2015). Young children (0–8) and digital technology: A qualitative exploratory study across seven countries. Technical report by the Joint Research Centre of the European Commission, Luxembourg. Luxembourg: Publications Office of the European Union. Church, K., & de Oliveira, R. (2013, August). What's up with whatsapp?: comparing mobile instant messaging behaviors with traditional SMS. In Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services (pp. 352-361). ACM. DiMaggio, P. (1982). Cultural capital and school success: The impact of status culture participation on the grades of US high school students. American sociological review, 189-201. Dumais, S. A. (2002). Cultural capital, gender, and school success: The role of habitus. Sociology of education, 44-68. Facer, K., Sutherland, R., Furlong, R., & Furlong, J. (2001). What's the point of using computers? The development of young people's computer expertise in the home. New Media & Society, 3(2), 199-219. Huysman, M., & Wulf, V. (2004). Social Capital and Information Technology: Current Debates and Research. In M. Huysman, & V. Wulf (Eds.), Social capital and information technology (pp. 1-15). Cambridge, MA: MIT Press. Jackson, L. A., Zhao, Y., Kolenic III, A., Fitzgerald, H. E., Harold, R., & Von Eye, A. (2008). Race, gender, and information technology use: The new digital divide. CyberPsychology & Behavior, 11(4), 437-442.
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