Review Article

A meta-analysis of the effectiveness of mobile supported collaborative learning

Olga V. Sergeeva 1 , Marina R. Zheltukhina 2 * , Izida I. Ishmuradova 3 , Nataliia A. Kondakchian 4 , Natalya S. Erokhova 5 , Sergei P. Zhdanov 6 7
More Detail
1 Kuban State University, Krasnodar, RUSSIA2 Scientific and Educational Center «Person in Communication», Pyatigorsk State University, Pyatigorsk, RUSSIA3 Kazan (Volga region) Federal University, Kazan, RUSSIA4 Sechenov First Moscow State Medical University, Moscow, RUSSIA5 Peoples’ Friendship University of Russia, Moscow, RUSSIA6 National Research University “Moscow Power Engineering Institute”, Moscow, RUSSIA7 Russian University of Transport, Moscow, RUSSIA* Corresponding Author
Online Journal of Communication and Media Technologies, 15(1), January 2025, e202508, https://doi.org/10.30935/ojcmt/15948
Published: 11 February 2025
OPEN ACCESS   3316 Views   7524 Downloads
Download Full Text (PDF)

ABSTRACT

The objective of this meta-analysis study is to investigate learning results under mobile supported collaborative learning (MSCL). Robust Bayesian meta-analysis was applied to eleven studies from Scopus, Web of Science, and ERIC databases. The results reveal that MSCL has a modest but favorable effect generally (d = 0.26, 95% confidence interval [CI] [–0.34, 0.89]). Studies revealed substantial degrees of heterogeneity (τ = 0.556, 95% CI [0.305, 1.027], implying that contextual elements might influence the efficacy of MSCL. Moderator analyses showed that the MSCL was more successful at the high school level and had a greater and consistent influence especially on student motivation. Moderate publication bias was identified. These results highlight the value of MSCL as a potential improvement tool in education but suggest that its effectiveness may vary by context. Future research should examine in more detail the specific factors that increase or decrease the effectiveness of MSCL. Educators and policy makers should consider the potential benefits and limitations of this approach when implementing MSCL.

CITATION (APA)

Sergeeva, O. V., Zheltukhina, M. R., Ishmuradova, I. I., Kondakchian, N. A., Erokhova, N. S., & Zhdanov, S. P. (2025). A meta-analysis of the effectiveness of mobile supported collaborative learning. Online Journal of Communication and Media Technologies, 15(1), e202508. https://doi.org/10.30935/ojcmt/15948

REFERENCES

  1. Aghajani, M., & Adloo, M. (2018). The effect of online cooperative learning on students’ writing skills and attitudes through telegram application. International Journal of Instruction, 11(3), 433–448. https://doi.org/10.12973/iji.2018.11330a
  2. Bartoš, F., Maier, M., Quintana, D. S., & Wagenmakers, E. J. (2022). Adjusting for publication bias in JASP and R: Selection models, PET-PEESE, and robust Bayesian meta-analysis. Advances in Methods and Practices in Psychological Science, 5(3). https://doi.org/10.1177/25152459221109259
  3. Benvenuti, M., Wright, M., Naslund, J., & Miers, A. C. (2023). How technology use is changing adolescents’ behaviors and their social, physical, and cognitive development. Current Psychology, 42(19), 16466–16469. https://doi.org/10.1007/s12144-023-04254-4
  4. Borenstein, M., Hedges, L. V, Higgins, J. P. T., & Rothstein, H. R. (2021). Introduction to meta-analysis. John Wiley & Sons. https://doi.org/10.1002/9781119558378
  5. Bringula, R. P., & Atienza, F. A. L. (2023). Mobile computer-supported collaborative learning for mathematics: A scoping review. Education and Information Technologies, 28(5), 4893–4918. https://doi.org/10.1007/s10639-022-11395-9
  6. Cerratto Pargman, T., Nouri, J., & Milrad, M. (2018). Taking an instrumental genesis lens: New insights into collaborative mobile learning. British Journal of Educational Technology, 49(2), 219–234. https://doi.org/10.1111/bjet.12585
  7. Chang, J. H., Chiu, P. S., & Huang, Y. M. (2018). A sharing mind map-oriented approach to enhance collaborative mobile learning With digital archiving systems. International Review of Research in Open and Distributed Learning, 19(1). https://doi.org/10.19173/irrodl.v19i1.3168
  8. Crompton, H., & Burke, D. (2018). The use of mobile learning in higher education: A systematic review. Computers and Education, 123, 53–64. https://doi.org/10.1016/j.compedu.2018.04.007
  9. Fabian, K., Topping, K. J., & Barron, I. G. (2018). Using mobile technologies for mathematics: Effects on student attitudes and achievement. Educational Technology Research and Development, 66(5), 1119–1139. https://doi.org/10.1007/s11423-018-9580-3
  10. Fanelli, D. (2012). Negative results are disappearing from most disciplines and countries. Scientometrics, 90(3), 891–904. https://doi.org/10.1007/s11192-011-0494-7
  11. Fu, Q. K., & Hwang, G. J. (2018). Trends in mobile technology-supported collaborative learning: A systematic review of journal publications from 2007 to 2016. Computers and Education, 119, 129–143. https://doi.org/10.1016/j.compedu.2018.01.004
  12. Gronau, Q. F., Van Erp, S., Heck, D. W., Cesario, J., Jonas, K. J., & Wagenmakers, E. J. (2017). A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: The case of felt power. Comprehensive Results in Social Psychology, 2(1), 123–138. https://doi.org/10.1080/23743603.2017.1326760
  13. Hanafi, H. F. Bin, Said, C. S., Ariffin, A. H., Zainuddin, N. A., & Samsuddin, K. (2016). Using a collaborative mobile augmented reality learning application (CoMARLA) to improve student learning. IOP Conference Series: Materials Science and Engineering, 160, Article 012111. https://doi.org/10.1088/1757-899X/160/1/012111
  14. Huang, P. Sen, Chiu, P. S., Huang, Y. M., Zhong, H. X., & Lai, C. F. (2020). Cooperative mobile learning for the investigation of natural science courses in elementary schools. Sustainability, 12(16), Article 6606. https://doi.org/10.3390/su12166606
  15. Jiang, D., & Zhang, L. J. (2020). Collaborating with ‘familiar’ strangers in mobile-assisted environments: The effect of socializing activities on learning EFL writing. Computers and Education, 150, Article 103841. https://doi.org/10.1016/j.compedu.2020.103841
  16. Johnson, D. W., & Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38(5), 365–379. https://doi.org/10.3102/0013189X09339057
  17. Johnson, D. W., & Johnson, R. T. (2014). Using technology to revolutionize cooperative learning: An opinion. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.01156
  18. Lee, W. C., & Lai, C. L. (2024). Facilitating mathematical argumentation by gamification: A gamified mobile collaborative learning approach for math courses. International Journal of Science and Mathematics Education, 22, 11–35. https://doi.org/10.1007/s10763-024-10462-6
  19. Lin, C. C., Barrett, N. E., & Liu, G. Z. (2021). English outside the academic sphere: A mobile-based context-aware comparison study on collaborative and individual learning. Journal of Computer Assisted Learning, 37(3), 657–671. https://doi.org/10.1111/jcal.12514
  20. Liu, I. F. (2024). Gamified mobile learning: Effects on English learning in technical college students. Computer Assisted Language Learning, 37(5–6), 1397–1420. https://doi.org/10.1080/09588221.2022.2080717
  21. Liu, S.-H. (2015). The perceptions of participation in a mobile collaborative learning among pre-service teachers. Journal of Education and Learning, 5(1), 87–94. https://doi.org/10.5539/jel.v5n1p87
  22. Maier, M., Bartoš, F., & Wagenmakers, E.-J. (2023). Robust Bayesian meta-analysis: Addressing publication bias with model-averaging. Psychological Methods, 28(1), 107–122. https://doi.org/10.1037/met0000405
  23. Nikou, S. A., & Economides, A. A. (2021). A framework for mobile-assisted formative assessment to promote students’ self-determination. Future Internet, 13(5), Article 116. https://doi.org/10.3390/fi13050116
  24. Rashtchi, M., & Porkar, R. (2020). Brainstorming revisited: Does technology facilitate argumentative essay writing? Language Teaching Research Quarterly, 18, 1–20. https://doi.org/10.32038/ltrq.2020.18.01
  25. Reychav, I., & Wu, D. (2016). The interplay between cognitive task complexity and user interaction in mobile collaborative training. Computers in Human Behavior, 62, 333–345. https://doi.org/10.1016/j.chb.2016.04.007
  26. Salhab, R., & Daher, W. (2023). University students’ engagement in mobile learning. European Journal of Investigation in Health, Psychology and Education, 13(1), 202–216. https://doi.org/10.3390/ejihpe13010016
  27. Sung, H. Y., Hwang, G. J., & Chang, Y. C. (2016). Development of a mobile learning system based on a collaborative problem-posing strategy. Interactive Learning Environments, 24(3), 456–471. https://doi.org/10.1080/10494820.2013.867889
  28. Sung, Y. T., Yang, J. M., & Lee, H. Y. (2017). The effects of mobile-computer-supported collaborative learning: Meta-analysis and critical synthesis. Review of Educational Research, 87(4), 768–805. https://doi.org/10.3102/0034654317704307
  29. Tiantian, Y., Razali, A. B., Zulkifli, N. N., & Jeyaraj, J. J. (2024). The effects of collaborative mobile learning approach on academic performance: The mediating role of social interaction, and learning motivation. Journal of Pedagogical Research, 8(3), 209–229. https://doi.org/10.33902/JPR.202426264
  30. Van der Linden, J., Erkens, G., Schmidt, H., & Renshaw, P. (2000). Collaborative learning. In R. J. Simons, J. van der Linden, & T. Duffy (Eds.), New learning (pp. 37–54). Springer. https://doi.org/10.1007/0-306-47614-2_3
  31. Zhang, D., & Hwang, G.-J. (2023). Effects of interaction between peer assessment and problem-solving tendencies on students’ learning achievements and collaboration in mobile technology-supported project-based learning. Journal of Educational Computing Research, 61(1), 208–234. https://doi.org/10.1177/07356331221094250
  32. Zou, W., & Li, X. (2015). Enhancing primary school students’ story writing by mobile-assisted collaborative learning: A case study. In W. Ma, A. Yuen, J. Park, W. Lau, & L. Deng (Eds.), New media, knowledge practices and multiliteracies (pp. 249–258). Springer Singapore. https://doi.org/10.1007/978-981-287-209-8_23