Assessing the effectiveness of smartphones in education: A Meta-analysis of recent studies

Artur G. Ibragimov 1 * , Vagiz G. Gimaliev 2, Elena G. Khrisanova 3, Natalia S. Aleksandrova 4, Leyla B. Omarova 5, Andrey G. Bakiev 6
More Detail
1 PhD in Law, Associate Professor of the Department of Criminal Process and Criminalistics, Kazan (Volga Region) Federal University, Kazan, RUSSIA
2 Candidate of Pedagogical Sciences, Associate Professor of the Department of Foreign Languages №2, Chuvash State University, Cheboksary, RUSSIA
3 Doctor of Education, Professor, Head of the Department of Humanities, I.Y. Yakovlev Chuvash State Pedagogical University, Cheboksary, RUSSIA
4 Doctor of Education, Professor of the Department of Pedagogics and Technology of Preschool and Primary Education, Vyatka State University, Kirov, RUSSIA
5 PhD in Philosophy, Associate Professor of the Department of Humanities, Financial University under the Government of the Russian Federation, Moscow, RUSSIA
6 Candidate of Philology, Associate Professor of the Department of Linguodidactics and Translation Studies, Bashkir State University, Ufa, RUSSIA
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 13, Issue 2, Article No: e202310.
OPEN ACCESS   1143 Views   2408 Downloads   Published online: 25 Jan 2023
Download Full Text (PDF)


The usage of mobile devices is increasing in frequency and scope. The percentage of students who use smartphones is quite high, in particular among those attending institutions of higher education. Like they would with any other technology, educators are doing research on the efficacy of using smartphones in the classroom. Studies have been conducted on the efficacy of using smartphones in face-to-face education as well as in the process of distant education, which has grown more common as a direct result of COVID-19. The purpose of this study is to do a meta-analysis of the data from previous experimental studies that looked at how well smartphones have been used over the past five years. The total effect size that has been calculated is 3.73. Since p = 0.05, this effect's size is statistically important. This finding has a big effect, as can be seen. For each study, an effect size calculation was done based on Hedges' g. The size of the effect is between -8 and 25.70.


Ibragimov, A. G., Gimaliev, V. G., Khrisanova, E. G., Aleksandrova, N. S., Omarova, L. B., & Bakiev, A. G. (2023). Assessing the effectiveness of smartphones in education: A Meta-analysis of recent studies. Online Journal of Communication and Media Technologies, 13(2), e202310.


  • Ahmed, R. R., Salman, F., Malik, S. A., Streimikiene, D., Soomro, R. H., & Pahi, M. H. (2020). Smartphone use and academic performance of university students: A mediation and moderation analysis. Sustainability, 12(1), 1-28.
  • Alghazzawi, D. M., Hasan, S. H., Aldabbagh, G., Alhaddad, M., Malibari, A., Asghar, M. Z., & Aljuaid, H. (2021). Development of platform independent mobile learning tool in Saudi universities. Sustainability, 13(10).
  • Anshari, M., Almunawar, M. N., Shahrill, M., Wicaksono, D. K., & Huda, M. (2017). Smartphones usage in the classrooms: Learning aid or interference? Education and Information Technologies, 22(6), 3063-3079.
  • Arain, A. A., Hussain, Z., Rizvi, W. H., & Vighio, M. S. (2018). An analysis of the influence of a mobile learning application on the learning outcomes of higher education students. Universal Access in the Information Society, 17(2), 325-334.
  • Bell, J., Cheng, C., Klautke, H., Cain, W., Freer, D., & Hinds, T. (2018). A study of augmented reality for the development of spatial reasoning ability. 2018 ASEE Annual Conference & Exposition Proceedings.
  • Briz-Ponce, L., Juanes-Méndez, J. A., García-Peñalvo, F. J., & Pereira, A. (2016). Effects of mobile learning in medical education: A counterfactual evaluation. Journal of Medical Systems, 40(6).
  • Chang, C. Y., Kuo, S. Y., & Hwang, G. H. (2022). Chatbot-facilitated nursing education: Incorporating a knowledge based chatbot system into a nursing training program. Educational Technology and Society, 25(1), 15-27.
  • Chorosova, O. M., Aetdinova, R. R., Solomonova, G. S., & Protodyakonova, G. Y. (2020). Conceptual approaches to the identification of teachers’ digital competence: Cognitive modelling. Education and Self Development, 15(3), 189-202.
  • Chuang, Y. H., Lai, F. C., Chang, C. C., & Wan, H. T. (2018). Effects of a skill demonstration video delivered by smartphone on facilitating nursing students’ skill competencies and self-confidence: A randomized controlled trial study. Nurse Education Today, 66(July 2017), 63-68.
  • Clavier, T., Ramen, J., Dureuil, B., Veber, B., Hanouz, J. L., Dupont, H., Lebuffe, G., Besnier, E., & Compere, V. (2019). Use of the smartphone app whatsapp as an E-learning method for medical residents: Multicenter controlled randomized trial. JMIR MHealth and UHealth, 7(4), 1-10.
  • Dabbour, E. (2016). Quantifying the effects of using online student response systems in an engineering ethics course. Journal of Professional Issues in Engineering Education and Practice, 142(2), 1-9.
  • Daliri B.O, M., M. Majd, H., & Moradi, A. (2021). Investigating a newly developed educational orthopedic application for medical interns in a before-after quasi-clinical trial study. BMC Medical Education, 21(1), 1-10.
  • Faimau, G., Tlhowe, K., & Tlhaolang, O. (2022). Smartphone use, experience of learning environment, and academic performance among university students: A descriptive appraisal. Advances in Human-Computer Interaction, 2022.
  • Field, A. P., & Gillett, R. (2010). How to do a meta-analysis. British Journal of Mathematical and Statistical Psychology, 63(3), 665-694.
  • Foen Ng, S., Syamimi Iliani Che Hassan, N., Hairunnisa Mohammad Nor, N., & Ain Abdul Malek, N. (2017). The relationship between smartphone use and academic performance: A case of students in a Malaysian tertiary institution. Malaysian Online Journal of Educational Technology, 5(4), 58-70.
  • Hedges, L. V. (1992). Meta-analysis. Journal of Educational Statistics, 17(4), 279-296.
  • Jackson, D., Kaveh, H., Victoria, J., Walker, A., & Bursztyn, N. (2019). Integrating an augmented reality sandbox challenge activity into a large-enrollment introductory geoscience lab for nonmajors produces no learning gains. Journal of Geoscience Education, 67(3), 237-248.
  • Jaramillo, A., Salinas-Cerda, J. P., & Fuentes, P. (2022). Self-regulated learning and academic performance in chilean university students in virtual mode during the pandemic: Effect of the 4Planning app. Frontiers in Psychology, 13(May).
  • Jia, J., & Chen, Z. (2020). Voluntary participation and natural grouping with smartphones: An effective and practical approach to implement a quasi-experiment. International Journal of Mobile Learning and Organisation, 14(1), 49-62.
  • Junco, R. (2012). In-class multitasking and academic performance. Computers in Human Behavior, 28(6), 2236-2243.
  • Jung, Y. (2014). What a smartphone is to me: Understanding user values in using smartphones. Information Systems Journal, 24(4), 299-321.
  • Kacetl, J., & Klímová, B. (2019). Use of smartphone applications in english language learning—A challenge for foreign language education. Education Sciences, 9(3), 1-9.
  • Kates, A. W., Wu, H., & Coryn, C. L. S. (2018). The effects of mobile phone use on academic performance: A meta-analysis. Computers and Education, 127(March), 107-112.
  • Kim, J. H., & Park, H. (2019). Effects of smartphone-based mobile learning in nursing education: A systematic review and meta-analysis. Asian Nursing Research, 13(1), 20-29.
  • Kim, S. J., Shin, H., Lee, J., Kang, S. R., & Bartlett, R. (2017). A smartphone application to educate undergraduate nursing students about providing care for infant airway obstruction. Nurse Education Today, 48, 145-152.
  • Kryukova, N. I., Chistyakov, A. A., Shulga, T. I., Omarova, L. B., Tkachenko, T. V., Malakhovsky, A. K., & Babieva N. S. (2022). Adaptation of higher education students’ digital skills survey to Russian universities. Eurasia Journal of Mathematics, Science and Technology Education, 18(11), em2183.
  • Kumar, P. R. S., Aruna, K., Kumar, A., & P., V. (2021). A smartphone use and its impact on academic performance of medical students: A cross sectional study. International Journal of Advances in Medicine, 8(10), 1582.
  • Lin, Y., Liu, Y., Fan, W., Tuunainen, V. K., & Deng, S. (2021). Revisiting the relationship between smartphone use and academic performance: A large-scale study. Computers in Human Behavior, 122(October 2020), 106835.
  • Lobos, K., Sáez-Delgado, F., Bruna, D., Cobo-Rendon, R., & Díaz-Mujica, A. (2021). Design, validity and effect of an intra-curricular program for facilitating self-regulation of learning competences in university students with the support of the 4planning app. Education Sciences, 11(8).
  • Loeffler, S. N., Bohner, A., Stumpp, J., Limberger, M. F., & Gidion, G. (2019). Investigating and fostering self-regulated learning in higher education using interactive ambulatory assessment. Learning and Individual Differences, 71(March), 43-57.
  • Mella-Norambuena, J., Cobo-Rendon, R., Lobos, K., Sáez-Delgado, F., & Maldonado-Trapp, A. (2021). Smartphone use among undergraduate stem students during COVID-19: An opportunity for higher education? Education Sciences, 11(8).
  • Normand, S. T. (1999). Meta-analysis: formulating, evaluating, combining, and reporting. Statistics in Medicine, 18(3), 321-359.<321::AID-SIM28>3.0.CO;2-P
  • Oschepkov, A. A., Kidinov, A. V., Babieva, N. S., Vrublevskiy, A. S., Egorova, E. V., & Zhdanov, S. P. (2022). STEM technology-based model helps create an educational environment for developing students' technical and creative thinking. Eurasia Journal of Mathematics, Science and Technology Education, 18(5), em2110.
  • Park, K. Y., & Kim, M. S. (2018). Outcomes of a drug dosage calculation training smartphone app on learning achievement, metacognition, and flow state according to prior knowledge. Eurasia Journal of Mathematics, Science and Technology Education, 14(7), 2867-2876.
  • Pesha, A. (2022). The development of digital competencies and digital literacy in the 21st century: A survey of studies. Education and Self Development, 17(1), 201-220.
  • Platonova, R. I., Khuziakhmetov, A. N., Prokopyev, A. I., Rastorgueva, N. E., Rushina, M. A., & Chistyakov, A. A. (2022). Knowledge in digital environments: A systematic review of literature. Frontiers in Education, 7, 1060455.
  • Qarkaxhja, Y., Kryukova, N. I., Cherezova, Y. A., Rozhnov, S. N., Khairullina, E. R., & Bayanova, A. R. (2021). Digital transformation in education: Teacher candidate views on mobile learning. International Journal of Emerging Technologies in Learning, 16(19), 81-93.
  • Rosenthal, R., & DiMatteo, M. R. (2001). Meta-analysis: Recent developments in quantitative methods for literature reviews. Annual Review of Psychology, 52(1), 59-82.
  • Sarker, I. H. (2019). Context-aware rule learning from smartphone data: survey, challenges and future directions. Journal of Big Data, 6(1), 1-25.
  • Schmidt, F. (2008). Meta-analysis. Organizational Research Methods, 11(1), 96-113.
  • Shakoor, F., Fakhar, A., & Abbas, J. (2021). Impact of smartphones usage on the learning behaviour and academic performance of students: Empirical evidence from Pakistan. International Journal of Academic Research in Business and Social Sciences, 11(2).
  • Shen, Z. (2021). An empirical study on adult students’ English mobile learning based on frame model. E3S Web of Conferences, 275, 2019-2022.
  • Singh, M. K. K., & Samah, N. A. (2018). Impact of smartphone: A review on positive and negative effects on students. Asian Social Science, 14(11), 83.
  • Sorakin, Y., Akarturk, H., Oznacar, B., Prokopyev, A. I., Burkhanova, I. Y., Musin, O. A., Shaleeva, E. F., & Krivonozhkina, E. G. (2022). Educational reflections on the coronavirus pandemic in three different countries. Eurasia Journal of Mathematics, Science and Technology Education, 18(11), em2180.
  • Sultan, L., Abuznadah, W., Al-Jifree, H., Khan, M. A., Alsaywid, B., & Ashour, F. (2020). An experimental study on usefulness of virtual reality 360° in undergraduate medical education. Advances in Medical Education and Practice, 10, 1103-1104.
  • Sumathi, K., Selva Lakshmi, N., & Kundhavai, S. (2018). Reviewing the impact of smartphone usage on academic performance among students of higher learning. International Journal of Pure and Applied Mathematics, 118(8), 1-7.
  • Tao, Z., Yang, X., Lai, I. K., & Chau, K. (2018). A research on the effect of smartphone use, student engagement and self-directed learning on individual impact: China empirical study. 2018 International Symposium on Educational Technology (ISET), 221-225.
  • The Jamovi project. (2022). jamovi ((Version 2.3.12)).
  • Wang, C. Y., Lu, C. Y., Yang, S. Y., Tsai, S. C., & Huang, T. W. (2022). 3D virtual reality smartphone training for chemotherapy drug administration by non-oncology nurses: A randomized controlled trial. Frontiers in Medicine, 9(June), 1-9.
  • Zakian, M., Xodabande, I., Valizadeh, M., & Yousefvand, M. (2022). Out-of-the-classroom learning of English vocabulary by EFL learners: Investigating the effectiveness of mobile assisted learning with digital flashcards. Asian-Pacific Journal of Second and Foreign Language Education, 7(1).
  • Zhdanov, S. P., Baranova, K. M., Udina, N., Terpugov, A. E., Lobanova, E. V., & Zakharova, O. V. (2022). Analysis of learning losses of students during the COVID-19 pandemic. Contemporary Educational Technology, 14(3), ep369.