Abstract
Knowledge and abilities with social media technologies are perceived as critical premises for human development. Familiarity with different types of social media technologies has become pivotal for collaborative learning and successfully solving problems. This study examined the impact of social media technologies, compartmentalized into social media usage and students’ attitudes towards social media usage, on their collaborative problem-solving (CPS) achievement by adopting the sample from the PISA 2015 dataset across 37 countries/regions. A three-level hierarchical linear model (HLM) was adopted to identify the significant factors related to CPS achievement. Results indicated that social media usage had a significant impact on CPS achievement and they are varied in terms of different learning contexts, different social media types (e.g., e-mails, social networking sites), and different purposes of social media use (leisure or academic use). Furthermore, students who had a more positive attitude toward social media were more likely to achieve higher CPS performance.
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References
Adam, T., & Tatnall, A. (2017). The value of using ICT in the education of school students with learning difficulties. Education and Information Technologies, 22(6), 2711–2726. https://doi.org/10.1007/s10639-017-9605-2
Alalwan, N. (2022). Actual use of social media for engagement to enhance students’ learning. Education and Information Technologies, 27(7), 9767–9789. https://doi.org/10.1007/s10639-022-11014-7
Alvarez, C., Salavati, S., Nussbaum, M., & Milrad, M. (2013). Collboard: Fostering new media literacies in the classroom through collaborative problem solving supported by digital pens and interactive whiteboards. Computers & Education, 63, 368–379. https://doi.org/10.1016/j.compedu.2012.12.019
Alvarez, C., Salavati, S., Nussbaum, M., & Milrad, M. (2013). Collboard: Fostering new media literacies in the classroom through collaborative problem solving supported by digital pens and interactive whiteboards. Computers & Education, 63(4), 368–379. https://doi.org/10.1016/j.compedu.2012.12.019
Andersson, A., Hatakka, M., Gronlund, A., & Wiklund, M. (2014). Reclaiming the students-coping with social media in 1:1 schools. Learning Media and Technology, 39(1), 37–52. https://doi.org/10.1080/17439884.2012.756518
Arpaci, S., Mercan, F. A., & Arkan, S. (2021). The differential relationships between PISA 2015 science performance and, ICT availability, ICT use and attitudes toward ICT across regions: Evidence from 35 countries. Education and Information Technologies, 26(5), 6299–6318. https://doi.org/10.1007/s10639-021-10576-2
Balakrishnan, V., & Lay, G. C. (2016). Students’ learning styles and their effects on the use of social media technology for learning. Telematics and Informatics, 33(3), 808–821. https://doi.org/10.1016/j.tele.2015.12.004
Beland, L. P., & Murphy, R. (2016). Ill communication: Technology, distraction & student performance. Labour Economics, 41, 61–76. https://doi.org/10.1016/j.labeco.2016.04.004
Chang, C. J., Chang, M. H., Chiu, B. C., Liu, C. C., Chiang, S. H. F., Wen, C. T., et al. (2017). An analysis of student collaborative problem solving activities mediated by collaborative simulations. Computers & Education, 114(11), 222–235. https://doi.org/10.1016/j.compedu.2017.07.008
Chen, X., & Hu, J. (2020). ICT-related behavioral factors mediate the relationship between adolescents’ ICT interest and their ICT self-efficacy: Evidence from 30 countries. Computers & Education, 159, Article No. 104004. https://doi.org/10.1016/j.compedu.2020.104004
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Eribaum.
Comi, S. L., Argentin, G., Gui, M., Origo, F., & Pagani, L. (2017). Is it the way they use it? Teachers, ICT and student achievement. Economics of Education Review, 56, 24–39. https://doi.org/10.1016/j.econedurev.2016.11.007
Cooke, S. (2017). Social teaching: Student perspectives on the inclusion of social media in higher education. Education and Information Technologies, 22(1), 255–269. https://doi.org/10.1007/s10639-015-9444-y
DeWitt, D., Alias, N., & Siraj, S. (2015). Transforming learning: Collaborative mLearning for a problem-centered approach. Kuala Lumpur, Malaysia: University of Malaya Press.
DeWitt, D., Alias, N., Siraj, S., & Spector, J. M. (2017). Wikis for a collaborative problem-solving (CPS) module for secondary school science. Educational Technology & Society, 20(1), 144–155. Retrieved from https://www.proquest.com/docview/1874035105?accountid=15198&pq-origsite=360link
Dindar, M. (2018). An empirical study on gender, video game play, academic success and complex problem solving skills. Computers & Education, 125(10), 39–52. https://doi.org/10.1016/j.compedu.2018.05.018
Eickelmann, B., Gerick, J., & Koop, C. (2017). ICT use in mathematics lessons and the mathematics achievement of secondary school students by international comparison: Which role do school level factors play? Education & Information Technologies, 22(4), 1–25. https://doi.org/10.1007/s10639-016-9498-5
Enders, C. K. (2010). Applied missing data analysis. New York, NY, US: Guilford Press.
Erdogdu, F. (2022). ICT, learning environment and student characteristics as potential cross-country predictors of academic achievement. Education and Information Technologies, 27(5), 7135–7159. https://doi.org/10.1007/s10639-021-10848-x
Ertmer, P. A., Newby, T. J., Liu, W., Tomory, A., Yu, J. H., & Lee, Y. M. (2011). Students’ confidence and perceived value for participating in cross-cultural wiki-based collaborations. Educational Technology Research and Development, 59, 213–228. https://doi.org/10.1007/s11423-011-9187-4
Feng, S. H., Wong, Y. K., Wong, L. Y., & Hossain, L. (2019). The internet and Facebook usage on academic distraction of college students. Computers & Education, 134, 41–49. https://doi.org/10.1016/j.compedu.2019.02.005
Field, A. (2009). Discovering statistics using SPSS (3rd ed.). Thousand Oaks, CA, US: Sage publications.
Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. Internet and Higher Education Mobile, 19, 18–26. https://doi.org/10.1016/j.iheduc.2013.06.002
Goldhammer, F., Gniewosz, G., & Zylka, J. (2016). ICT engagement in learning environments. In S. Kuger, E. Klieme, N. Jude, & D. Kaplan (Eds.), Assessing contexts of learning: An international perspective (pp. 331–351). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-45357-6_13
Greiff, S., & Neubert, J. C. (2014). On the relation of complex problem solving, personality, fluid intelligence, and academic achievement. Learning & Individual Differences, 36, 37–48. https://doi.org/10.1016/j.lindif.2014.08.003
Hammond, M. (2020). What is an ecological approach and how can it assist in understanding ICT take-up? British Journal of Educational Technology, 51(3), 853–866. https://doi.org/10.1111/bjet.12889
Herborn, K., Stadler, M., Mustafić, M., & Greiff, S. (2020). The assessment of collaborative problem solving in PISA 2015: Can computer agents replace humans? Computers in Human Behavior, 104, Article No.105624. https://doi.org/10.1016/j.chb.2018.07.035
Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research & Development, 55(3), 223–252. https://doi.org/10.1007/s11423-006-9022-5
Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY, US: Routledge.
Hu, J., & Yu, R. (2021). The effects of ICT-based social media on adolescents’ digital reading performance: A longitudinal study of PISA 2009, PISA 2012, PISA 2015 and PISA 2018. Computers & Education, 175, Article No. 104342. https://doi.org/10.1016/j.compedu.2021.104342
Junco, R. (2012). The relationship between frequency of Facebook use, participation in Facebook activities, and student engagement. Computers & Education, 58(1), 162–171. https://doi.org/10.1016/j.compedu.2011.08.004
Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! the challenges and opportunities of social media. Business Horizons, 53(1), 59–68. https://doi.org/10.1016/j.bushor.2009.09.003
Lambic, D. (2016). Correlation between Facebook use for educational purposes and academic performance of students. Computers in Human Behavior, 61, 313–320. https://doi.org/10.1016/j.chb.2016.03.052
Li, K., Huang, L., & Song, Z. (2020). Understanding the emergence of collaborative problem-solving practices in enterprise social media: The roles of social factors. Ieee Access : Practical Innovations, Open Solutions, 8, 210066–210080. https://doi.org/10.1109/ACCESS.2020.3039239
Lin, C. H., Zhang, Y., & Zheng, B. (2017). The roles of learning strategies and motivation in online language learning: A structural equation modeling analysis. Computers & Education, 113, 75–85. https://doi.org/10.1016/j.compedu.2017.05.014
Manca, S., & Ranieri, M. (2016). Is Facebook still a suitable technology-enhanced learning environment? An updated critical review of the literature from 2012 to 2015. Journal of Computer Assisted Learning, 32(6), 503–528. https://doi.org/10.1111/jcal.12154
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
Mora, T., Escardíbul, J. O., & Di Pietro, G. (2018). Computers and students’ achievement: An analysis of the one laptop per child program in Catalonia. International Journal of Educational Research, 92, 145–157. https://doi.org/10.1016/j.ijer.2018.09.013
OECD. (2017). PISA 2015 results (volume V). Paris: OECD Publishing. https://doi.org/10.1787/19963777
Petko, D., Cantieni, A., & Prasse, D. (2017). Perceived quality of educational technology matters: A secondary analysis of students’ ICT use, ICT-related attitudes, and PISA 2012 scores. Journal of Educational Computing Research, 54(8), 1070–1091. https://doi.org/10.1177/0735633116649373
Ratitch, B. (2014). Multiple imputation. John Wiley & Sons, Ltd.
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models. Sage.
Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., & Congdon, R. (2019). HLM 8 for Windows [Computer software]. Skokie, IL: Scientific Software International, Inc.
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available online at https://www.R-project.org/
Reinhardt, J. (2019). Social media in second and foreign language teaching and learning: Blogs, wikis, and social networking. Language Teaching, 52(1), 1–39. https://doi.org/10.1017/s0261444818000356
Rojas, M., Nussbaum, M., Chiuminatto, P., Guerrero, O., Greiff, S., Kriegerc, F., & Westhuizenc, L. V. D. (2021). Assessing collaborative problem-solving skills among elementary school students. Computers & Education. https://doi.org/10.1016/j.compedu.2021.104313., 175, Article No. 104313.
Rutherford, C. (2010). Using online social media to support preservice student engagement. MERLOT Journal of Online Learning and Teaching, 6(4), 703–711. Retrieved from http://jolt.merlot.org/vol6no4/rutherford_1210.pdf
Sarwar, B., Zulfiqar, S., Aziz, S., & Ejaz Chandia, K. (2019). Usage of social media tools for collaborative learning: The effect on learning success with the moderating role of cyberbullying. Journal of Educational Computing Research, 57(1), 246–279. https://doi.org/10.1177/0735633117748415
Schafer, J. L., & Olsen, M. K. (1998). Multiple imputation for multivariate missing-data problems: A data analyst’s perspective. Multivariate Behavioral Research, 33(4), 545–571. https://doi.org/10.1207/s15327906mbr3304_5
Shute, V. J., Ventura, M., & Ke, F. F. (2015). The power of play: The effects of Portal 2 and lumosity on cognitive and noncognitive skills. Computers & Education, 80, 58–67. https://doi.org/10.1016/j.compedu.2014.08.013
Skryabin, M., Zhang, J., Liu, L., & Zhang, D. (2015). How the ICT development level and usage influence student achievement in reading, mathematics, and science. Computers & Education, 85, 49–58. https://doi.org/10.1016/j.compedu.2015.02.004
Smith, E. E. (2016). A real double-edged sword”: Undergraduate perceptions of social media in their learning. Computers & Education, 103, 44–58. https://doi.org/10.1016/j.compedu.2016.09.009
Srijamdee, K., & Pholphirul, P. (2020). Does ICT familiarity always help promote educational outcomes? Empirical evidence from PISA-Thailand. Education and Information Technologies, 25(6), 1–38. https://doi.org/10.1007/s10639-019-10089-z
Stadler, M., Herborn, K., Mustafi, M., & Greiff, S. (2019). Computer-based collaborative problem solving in PISA 2015 and the role of personality. Journal of intelligence, 7(3), https://doi.org/10.3390/jintelligence7030015. Article No.15.
Stadler, M., Herborn, K., Mustafi, M., & Greiff, S. (2020). The assessment of collaborative problem solving in PISA 2015: An investigation of the validity of the PISA 2015 CPS tasks. Computers & Education, 157(2), 103964. https://doi.org/10.1016/j.compedu.2020.103964
Unal, E., & Cakir, H. (2021). The effect of technology-supported collaborative problem solving method on students’ achievement and engagement. Education and Information Technologies, 26(4), 4127–4150. https://doi.org/10.1007/s10639-021-10463-w
Vaughan, N. D. (2010). A blended community of inquiry approach: Linking student engagement and course redesign. The Internet and Higher Education, 13, 60–65. https://doi.org/10.1016/j.iheduc.2009.10.007
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151. https://doi.org/10.1126/science.aap9559
Wang, M., & Hu, J. (2022). Perceived teacher autonomy support for adolescents’ reading achievement: The mediation roles of control-value appraisals and emotions. Frontiers in Psychology, 13, 959461. https://doi.org/10.3389/fpsyg.2022.959461
Wu, J. Y., & Nian, M. W. (2021). The dynamics of an online learning community in a hybrid statistics classroom over time: Implications for the question-oriented problem-solving course design with the social network analysis approach. Computers & Education, 166, Article No. 104120. https://doi.org/10.1016/j.compedu.2020.104120
Wu, S. Y. (2019). Incorporation of collaborative problem solving and cognitive tools to improve higher cognitive processing in online discussion environments. Journal of Educational Computing Research, 58(1), 249–272. https://doi.org/10.1177/0735633119828044
Yu, R., Wang, M., & Hu, J. (2023). The relationship between ICT perceived competence and adolescents’ digital reading performance: A multilevel mediation study. Journal of Educational Computing Research. Advance online publication. https://doi.org/10.1177/07356331221137107
Zhang, D., & Liu, L. (2016). How does ICT use influence students’ achievements in math and science over time? Evidence from PISA 2000 to 2012. Eurasia Journal of Mathematics Science and Technology Education, 12(9), 2431–2449. https://doi.org/10.12973/eurasia.2016.1297a
Zheng, Y., Bao, H., Shen, J., & Zhai, X. (2020). Investigating sequence patterns of collaborative problem-solving behavior in online collaborative discussion activity. Sustainability, 12(20), 8522. https://doi.org/10.3390/su1220852
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This research was supported by the Zhejiang Provincial Philosophy and Social Sciences Programme of Leading Talents Cultivation Project for Distinguished Young Scholars, China “A study on the influencing factors and mechanism of digital reading literacy in the digital intelligence era” (grant number 23QNYC04ZD).
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Wang, M., Yu, R. & Hu, J. The relationship between social media-related factors and student collaborative problem-solving achievement: an HLM analysis of 37 countries. Educ Inf Technol 28, 14071–14089 (2023). https://doi.org/10.1007/s10639-023-11763-z
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DOI: https://doi.org/10.1007/s10639-023-11763-z