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Digital technologies have been increasingly embedded in students’ everyday lives. Interest-driven socio-digital participation (ISDP) involves students’ pursuit of interests mediated by computers, social media, the internet, and mobile devices’ integrated systems. ISDP is likely to intertwine closely with young people’s social networks that has been scarcely studied quantitatively. To close this gap, the present paper investigated students’ peer selection and influence effects of the intensity of their ISDP and friendship networks. We collected two-wave data by administering a peer nomination to trace students’ friendship networks with peers and a self-reported questionnaire to examine students’ ISDP. Participants were 100 students in Finland (female: 53%; mean age = 13.48, in grade 7 in the first wave). Through stochastic actor-oriented modelling, the results showed that the students’ friendship ties with peers influenced the intensity of their ISDP practices to become more similar. Yet, students did not select peers as friends based on similar intensity levels of ISDP. Utilizing influence effect found in students’ ISDP and their peer networks, we suggest that connected learning (Ito et al., 2013) should be promoted to integrate students’ informal and formal learning in order to bridge the gap between students’ informal interest-related digital practices and formal educational practices.
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Akkerman, S. F., & Bakker, A. (2011). Boundary crossing and boundary objects. Review of Educational Research, 81(2), 132–169. doi: 10.3102/0034654311404435
Altermatt, E. R., & Pomerantz, E. M. (2003). The development of competence-related and motivational beliefs: An investigation of similarity and influence among friends. Journal of Educational Psychology, 95(1), 111–123. doi: 10.1037/0022-06188.8.131.52
Amialchuk, A., & Kotalik, A. (2016). Do your school mates influence how long you game? Evidence from the US. PLoS ONE, 11(8): e0160664. doi: 10.1371/journal.pone.0160664
Bagwell, C. & Bukowski, W. (2018). Friendship in childhood and adolescence: Feature, effects and processes. In W. M., Bukowski, B. Laursen, & K. H. Rubin (Eds.), Handbook of peer interactions, relationships, and groups (2nd Ed.) (pp. 371-390). New York, NY: The Guilford Press.
Baym, N. K., & boyd, d. (2012). Socially mediated publicness: An introduction. Journal of Broadcasting & Electronic Media, 56(3), 320–329. doi: 10.1080/08838151.2012.705200
Brechwald, W. A., & Prinstein, M. J. (2011). Beyond homophily: A decade of advances in understanding peer influence processes. Journal of Research on Adolescence, 21(1), 166–179. doi: 10.1111/j.1532-7795.2010.00721.x
Bronkhorst, L. H., & Akkerman, S. F. (2016). At the boundary of school: Continuity and discontinuity in learning across contexts. Educational Research Review, 19, 18-35. doi: 10.1016/j.edurev.2016.04.001
Byrne, D. (1971). The attraction paradigm. New York, NY: Academic.
Christakis, N. A., & Fowler, J. H. (2013). Social contagion theory: Examining dynamic social networks and human behavior. Statistics in Medicine, 32(4), 556–577. doi:10.1002/sim.5408
Cillessen, A. H. N., & Borch, C. (2006). Developmental trajectories of adolescent popularity: A growth curve modelling analysis. Journal of Adolescence, 29(6), 935–959. doi: 10.1016/j.adolescence.2006.05.005
Conti, M., Passarella, A., & Das, S. K. (2017). The Internet of People (IoP): A new wave in pervasive mobile computing. Pervasive and Mobile Computing, 41, 1–27. doi:10.1016/j.pmcj.2017.07.009
Cruz, J. E., Emery, R. E., & Turkheimer, E. (2012). Peer network drinking predicts increased alcohol use from adolescence to early adulthood after controlling for genetic and shared environmental selection. Developmental Psychology, 48(5), 1390. doi:10.1037/a0027515
de la Haye, K., Green, H. D., Kennedy, D. P., Pollard, M. S., & Tucker, J. S. (2013). Selection and influence mechanisms associated with marijuana initiation and use in adolescent friendship networks. Journal of Research on Adolescence, 23(3), 474–486. doi:10.1111/jora.12018
Delay, D., Laursen, B., Kiuru, N., Salmela-Aro, K., & Nurmi, J. -E. (2013). Selecting and retaining friends on the basis of cigarette smoking similarity. Journal of Research on Adolescence, 23, 464–473. doi:10.1111/jora.12017
Deng, L., Connelly, J., & Lau, M. (2016). Interest-driven digital practices of secondary students: Cases of connected learning. Learning, Culture and Social Interaction, 9, 45-54. doi: 10.1016/j.lcsi.2016.01.004
Escardíbul, J. O., Mora, T., & Villarroya, A. (2013). Peer effects on youth screen media consumption in Catalonia (Spain). Journal of Cultural Economics, 37(2), 185–201. doi:10.1007/s10824-012-9177-3
Farmer, T. W., Lines, M. M., & Hamm, J. V. (2011). Revealing the invisible hand: The role of teachers in children’s peer experiences. Journal of Applied Developmental Psychology, 32(5), 247–256. doi:10.1016/j.appdev.2011.04.006
Fortuin, J., Geel, M. V., & Vedder, P. (2016). Peers and academic achievement: A longitudinal study on selection and socialization effects of in-class friends. The Journal of Educational Research, 109(1), 1–6. doi:10.1080/00220671.2014.917257
Gottman, J. M. (1983). How children become friends. Monographs of the Society for Research in Child Development, 48(3), 1–86. doi:10.2307/1165860
Gremmen, M. C., Berger, C., Ryan, A. M., Steglich, C. E., Veenstra, R., & Dijkstra, J. K. (2019). Adolescents’ friendships, academic achievement, and risk behaviors: Same‐behavior and cross‐behavior selection and influence processes. Child Development, 90(2), e192-e211. doi:10.1111/cdev.13045
Hakkarainen, K., Ilomäki, L., Lipponen, L., Muukkonen, H., Rahikainen, M., Tuominen, T., . . . Lehtinen, E. (2000). Students’ skills and practices of using ICT: Results of a national assessment in Finland. Computers & Education, 34(2), 103–117. doi:10.1016/S0360-1315(00)00007-5
Hakkarainen, K., Hietajärvi, L., Alho, K., Lonka, K., & Salmela-Aro, K. (2015). Socio-digital revolution: Digital natives vs digital immigrants. In J. D. Wright (Ed.), International encyclopedia of the social and behavioral sciences (2nd ed.) (Vol. 22, pp. 918-923). Amsterdam, The Netherlands: Elsevier. doi: 10.1016/B978-0-08-097086-8.26094-7
Hamm, J. V., Farmer, T. W., Lambert, K., & Gravelle, M. (2014). Enhancing peer cultures of academic effort and achievement in early adolescence: Promotive effects of the SEALS intervention. Developmental Psychology, 50, 216–228. doi: 10.1037/a0032979
Hargittai, E. (2010). Digital na(t)ives? Variation in internet skills and uses among members of the “net generation.” Sociological Inquiry, 80(1), 92–113. doi: 10.1111/j.1475-682X.2009.00317.x
Haynie, D. L. (2001). Delinquent peers revisited: Does network structure matter? American Journal of Sociology, 106, 1013–1057. doi: 10.1086/320298
Hietajärvi, L., Salmela-Aro, K., Tuominen, H., Hakkarainen, K., & Lonka, K. (2019). Beyond screen time: Multidimensionality of socio-digital participation and relations to academic well-being in three educational phases. Computers in Human Behavior, 93, 13-24. doi: 10.1016/j.chb.2018.11.049
Hietajärvi, L., Seppä, J., & Hakkarainen, K. (2016). Dimensions of adolescents’ socio-digital participation. Qwerty, 11(2), 79–98.
Holopainen, L., & Savolainen, H. (2005). Unpublished raw data. Finland: University of Joensuu and University of Jyväskylä.
Ito, M., Baumer, S., Bittanti, M., boyd, d., Cody, R., Stephenson, B., . . . Tripp, L. (2010). Hanging out, messing around, and geeking out: Kids living and learning with new media. Cambridge, MA: MIT Press.
Ito, M., Gutiérrez, K., Livingstone, S., Penuel, B., Rhodes, J., Salen, K., ... & Watkins, S. C. (2013). Connected learning: An agenda for research and design. Irvine, CA: Digital Media and Learning Research Hub.
Juvonen, J., Espinoza, G., & Knifsend, C. (2012). The role of peer relationships in student academic and extracurricular engagement. In S. L. Christenson, A. L. Reschly & C. Wylie (Eds.), Handbook of research on student engagement (pp. 387–401). Boston, MA: Springer. doi: 10.1007/978-1-4614-2018-7_18
Kandel, D. B. (1978). Homophily, selection, and socialization in adolescent friendships. The American Journal of Sociology, 84, 427–436. doi: 10.1086/226792
Kindermann, T. A. (2016). Peer group influences on students’ academic motivation. In K.R. Wentzel, & G. B. Ramani (Eds.), Handbook of social influences in school contexts (pp. 31–47). New York, NY: Routledge.
Kiuru, N., Burk, W. J., Laursen, B., Salmela-Aro, K., & Nurmi, J. E. (2010). Pressure to drink but not to smoke: Disentangling selection and socialization in adolescent peer networks and peer groups. Journal of Adolescence, 33(6), 801–812. doi: 10.1016/j.adolescence.2010.07.006
Korhonen, T., & Lavonen, J. (2017). A new wave of learning in Finland: Get started with innovation! In S. Choo, D. Sawch, A. Villanueva, & R. Vinz (Eds.), Educating for the 21st century: Perspectives, policies and practices from around the world (pp. 447–467). Singapore: Springer. doi: 10.1007/978-981-10-1673-8_24
Kremer, M., & Levy, V. (2008). Peer effects and alcohol use among college students. Journal of Economic Perspectives, 22(3), 189–206. doi: 10.1257/jep.22.3.189
Kumpulainen, K., & Sefton-Green, J. (2012). What is connected learning and how to research it? International Journal of Learning and Media, 4(2), 7–18. doi: 10.1162/IJLM_a_00091.
Laursen, B. (2018). Peer influence. In W. M., Bukowski, B. Laursen, & K. H. Rubin (Eds.), Handbook of peer interactions, relationships, and groups (2nd Ed.) (pp.447-469). New York, NY: The Guilford Press.
Li, S., Hietajärvi, L., Palonen, T., Salmela-Aro, K., & Hakkarainen, K. (2017). Adolescents’ social networks: Exploring different patterns of socio-digital participation. Scandinavian Journal of Educational Research, 61(3), 255–274. doi: 10.1080/00313831.2015.1120236
Li, S., Palonen, T., Lehtinen, E., & Hakkarainen, K. (2018). Face-to-face contacts, Facebook connections and academic support: Adolescents’ networks between and across gender and culture in Finland. Young, 27(2), 1–17. doi: 10.1177/1103308818766773
Li, Y., Lynch, A. D., Kalvin, C., Liu, J., & Lerner, R. M. (2011). Peer relationships as a context for the development of school engagement during early adolescence. International Journal of Behavioral Development, 35, 329–342. doi: 10.1177/0165025411402578
Manski, C. (1993). Identification of endogenous social effects: The reflection problem. Review of Economic Studies, 60(3), 531–542. doi: 10.2307/2298123
Maul, A., Penuel, W. R., Dadey, N., Gallagher, L. P., Podkul, T., & Price, E. (2017). Measuring experiences of interest-related pursuits in connected learning. Educational Technology Research and Development, 65(1), 1-28. doi: 10.1007/s11423-016-9453-6
McFarlane, A. (2015). Authentic learning for the digital generation: Realising the potential of technology in the classroom. London, UK: Routledge.
McPherson, M., Smith-Lovin, L., & Cook, J. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415–444. doi: 10.1146/annurev.soc.27.1.415
Niemi, H., Kynäslahti, H., & Vahtivuori-Hänninen, S. (2013). Towards ICT in everyday life in Finnish schools: Seeking conditions for good practices. Learning, Media and Technology, 38(1), 57–71. doi: 10.1080/17439884.2011.651473
Palfrey, J., & Gasser, U. (2011). Reclaiming an awkward term: What we might learn from “digital natives”. In M. Thomas (Ed.), Deconstructing digital natives: Young people, technology, and the new literacies (pp. 186–204). London: Routledge.
Penuel, W. R., DiGiacomo, D. K., Van Horne, K., & Kirshner, B. (2016). A social practice theory of learning and becoming across contexts and time. Frontline Learning Research, 4(4), 30-38. doi: 10.14786/flr.v4i4.205
Qing, L., & Xin, M. (2010). A meta-analysis of the effects of computer technology on school students’ mathematics learning. Educational Psychology Review, 22(3), 215–243. doi: 10.1007/s10648-010-9125-8
R Development Core Team (2011). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. Retrieved from http://www.R-project.org/.
Rajala, A., Kumpulainen, K., Hilppö, J., Paananen, M., & Lipponen, L. (2016). Connecting learning across school and out-of-school contexts: A review of pedagogical approaches. In O. Erstad, K. Kumpulainen, Å. Mäkitalo, K. P. Pruulmann-Vengerfeldt, & T. Jóhannsdóttir (Eds.), Learning across contexts in the knowledge society. (pp. 15-35) Rotterdam, The Netherlands: Sense publishers.
Riikonen, S., Seitamaa-Hakkarainen, P., & Hakkarainen, K. (2018). Bringing practices of co-design and making to basic education. Presentation of the 13th International Conference on the Learning Sciences. UK: Institute of Education, University College London.
Ripley, R. M., Snijders, T. A., Boda, Z., Vörös, A., & Preciado, P. (May 2018). Manual for RSiena version 4.0. Oxford, UK: University of Oxford Department of Statistics. Retrieved from http://www.stats.ox.ac.uk/siena/.
Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York, NY: John Wiley & Sons.
Rubin, D. B. (1996). Multiple imputation after 18+ years. Journal of the American Statistical Association, 91(434), 473–489. doi: 10.1080/01621459.1996.10476908
Salmela-Aro, K., Muotka, J., Alho, K., Hakkarainen, K., & Lonka, K. (2016). School burnout and engagement profiles among digital natives in Finland: A person-oriented approach. European Journal of Developmental Psychology, 13(6), 704–718. doi: 10.1080/17405629.2015.1107542
Scott, J. (2000). Social network analysis: A handbook (2nd ed.). London: Sage.
Shin, H. (2018). The role of friends in help-seeking tendencies during early adolescence: Do classroom goal structures moderate selection and influence of friends? Contemporary Educational Psychology, 53, 135–145. doi: 10.1016/j.cedpsych.2018.03.002
Shin, H., & Ryan, A. M. (2014). Friendship networks and achievement goals: An examination of selection and influence processes and variations by gender. Journal of Youth and Adolescence, 43(9), 1453–1464. doi: 10.1007/s10964-014-0132-9
Snijders, T. A. (2005). Models for longitudinal network data. In P. Carrington, J. Scott, & S. Wasserman (Eds.), Models and methods in social network analysis (pp. 215–247). New York, NY: Cambridge University Press.
Snijders, T. A., van de Bunt, G. G., & Steglich, C. E. (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks, 32(1), 44–60. doi: 10.1016/j.socnet.2009.02.004
Steglich, C., Snijders, T. A., & Pearson, M. (2010). Dynamic networks and behavior: Separating selection from influence. Sociological Methodology, 40(1), 329–393. doi: 10.1111/j.1467-9531.2010.01225.x
Subrahmanyam, K., & Greenfield, P. (2008). Online communication and adolescent relationships. The Future of Children, 18(1), 119–146. Retrieved on January 16, 2019, from www.jstor.org/stable/20053122
Svensson, Y., Burk, W. J., Stattin, H., & Kerr, M. (2012). Peer selection and influence of delinquent behavior of immigrant and nonimmigrant youths: Does context matter? International Journal of Behavioral Development, 36(3), 178–185. doi: 10.1177/0165025411434652
van Buuren, S. (2018). Flexible imputation of missing data (2nd ed.). Boca Raton, FL: Chapman & Hall/CRC Press. Retrieved on January 16, 2019, from https://stefvanbuuren.name/fimd/
van Buuren, S., & Groothuis-Oudshoorn, K. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1–67. Retrieved on January 16, 2019, from http://www.jstatsoft.org/v45/i03/.
van Rijsewijk, L. G., Snijders, T. A., Dijkstra, J. K., Steglich, C., & Veenstra, R. (2019). The interplay between adolescents' friendships and the exchange of help: A longitudinal multiplex social network study. Journal of Research on Adolescence, 30(1), 63-77. doi: 10.1111/jora.12501
Veenstra, R., & Steglich, C. (2012). Actor-based model for network and behavior dynamics. In B. Laursen, T. D. Little, & N. A. Card (Eds.), Handbook of developmental research methods (pp. 598–618). New York, NY: The Guilford Press.
Wang, M. T., & Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review, 29(1), 119–140. doi: 10.1007/s10648-015-9355-x
Wang, M. T., Kiuru, N., Degol, J. L., & Salmela-Aro, K. (2018). Friends, academic achievement, and school engagement during adolescence: A social network approach to peer influence and selection effects. Learning and Instruction, 58, 148–160. doi: 10.1016/j.learninstruc.2018.06.003
Wernholm, M. (2018). Children’s shared experiences of participating in digital communities. Nordic Journal of Digital Literacy, 13(04), 38-55. doi: 10.18261/issn.1891-943x-2018-04-04
Witkow, M. R., & Fuligni, A. J. (2010). In-school versus out-of-school friendships and academic achievement among an ethnically diverse sample of adolescents. Journal of Research on Adolescence, 20, 631–650. doi: 10.1111/j.1532-7795.2010.00653.x