Exploring Preservice STEM Teachers’ Smartphone Addiction

Alfiya R. Masalimova; Elmira R. Khairullina; Natalya I. Lapidus; Natalia A. Orekhovskaya; Marina R. Zheltukhina; Ekaterina A. Baranova

doi:10.30935/cedtech/11916

Alfiya R. Masalimova ¹ ^* , Elmira R. Khairullina ², Natalya I. Lapidus ³, Natalia A. Orekhovskaya ⁴, Marina R. Zheltukhina ⁵, Ekaterina A. Baranova ⁶

More Detail

CONT ED TECHNOLOGY, Volume 14, Issue 3, Article No: ep371

https://doi.org/10.30935/cedtech/11916

Submitted: 30 December 2021, Published Online: 24 March 2022

OPEN ACCESS 2032 Views 1216 Downloads

Download Full Text (PDF)

Abstract

Smartphones are mobile technology cutting-edge. Daily, the amount of time spent on a phone increases. Excessive smartphone use and addiction have developed into big social issues. Addiction to smartphones is a negative and pathological concept that is assessed by a set of subjective and behavioral symptoms including fixation, loss of control, and withdrawal symptoms. Teachers in STEM fields have a higher degree of involvement with their students in the use of digital tools. STEM teacher candidates must demonstrate an understanding of how to incorporate technology successfully into classroom activities. Determine the incidence of smartphone addiction among prospective STEM educators to justify future awareness training. The association between pre-service STEM instructors’ smartphone addiction was studied. The research included 242 persons, 180 of whom were females and 62 males. The SAI is self-administered and scored independently for each dimension. Data is analyzed using machine learning techniques. Cluster analysis is used to analyze the inventory’s dimensions. The k-means technique is used for cluster analysis. The library’s SHAP (SHapley additive explanations) approach was used to evaluate the classification result and assess the impact of attributes on the classification result. According to the findings, the highest level was judged to be 30 participants. Approximately 3%4 participants are deemed moderate (high and very high). Also, 48 people are at a low level. In terms of the overall group, it is modest. Being in the lowest cluster is linked to 100+ uses, whereas being in the highest cluster is linked to 6-10 uses. The exact degree of smartphone use linked to smartphone addiction is unknown. Females inversely correlate with the highest and lowest clusters.

Keywords: smartphone addiction, pre-service teachers, machine learning algorithm, cluster analysis

References

Abubakar Ismaila, A., Kadage Tukur, A., & Amoson Gambari, I. (2019). Ease and level of use of smartphone for learning amongst pre-service teachers colleges of education in North-West, Nigeria. International Journal on Research in STEM Education, 1(1), 40-49. https://doi.org/10.31098/ijrse.v1i1.60
Alkhunaizan, A. S. (2019). An empirical study on smartphone addiction of the university students. International Journal of Interactive Mobile Technologies, 13(2), 184-195. https://doi.org/10.3991/ijim.v13i12.11120
Arnavut, A., Nuri, C., & Direktor, C. (2018). Examination of the relationship between phone usage and smartphone addiction based on certain variables. Anales de Psicologia [Annals of Psychology], 34(3), 446-450. https://doi.org/10.6018/analesps.34.3.321351
ASAM. (2019). ASAM definition of addiction. American Society of Addiction Medicine. https://www.asam.org/Quality-Science/definition-of-addiction
Awofala, A. O. (2020). Investigating nomophobia as a predictor of smartphone addiction among Nigerian pre-service mathematics teachers. Indonesian Journal of Informatics Education, 4(2), 43-50. https://doi.org/10.20961/ijie.v4i2.40021
Bauer, M., Glenn, T., Geddes, J., Gitlin, M., Grof, P., Kessing, L. V., Monteith, S., Faurholt-Jepsen, M., Severus, E., & Whybrow, P. C. (2020). Smartphones in mental health: A critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders, 8(1), 1-19. https://doi.org/10.1186/s40345-019-0164-x
Bayanova, A. R., Chistyakov, A. A., Timofeeva, M. O., Nasonkin, V. V., Shulga, T. I., & Vasyukov, V. F. (2022). Psychometric properties of smartphone addiction inventory (SPAI) in Russian context. Contemporary Educational Technology, 14(1), ep342. https://doi.org/10.30935/cedtech/11478
Caliskan, S., Guney, Z., Sakhieva, R. G., Vasbieva, D. G., & Zaitseva, N. A. (2019). Teachers’ views on the availability of Web 2.0 tools in education. International Journal of Emerging Technologies in Learning, 14(22), 70-81. https://doi.org/10.3991/ijet.v14i22.11752
Carbonell, X., Chamarro, A., Oberst, U., Rodrigo, B., & Prades, M. (2018). Problematic use of the internet and smartphones in university students: 2006-2017. International Journal of Environmental Research and Public Health, 15(3), 475. https://doi.org/10.3390/ijerph15030475
Celik, O. T., & Konan, N. (2019). The mediator role of interaction anxiety in the relationship between social support perception and smartphone addiction. Journal of Education and Future, 15, 63-75. https://doi.org/10.30786/jef.397445
Ching, S. M., Yee, A., Ramachandran, V., Lim, S. M. S., Sulaiman, W. A. W., Foo, Y. L., & Hoo, F. K. (2015). Validation of a Malay version of the smartphone addiction scale among medical students in Malaysia. PLoS ONE, 10(10), 1-11. https://doi.org/10.1371/journal.pone.0139337
Criollo-C, S., Guerrero-Arias, A., Jaramillo-Alcázar, Á., & Luján-Mora, S. (2021). Mobile learning technologies for education: Benefits and pending issues. Applied Sciences, 11(9), 4111. https://doi.org/10.3390/app11094111
Demirci, K., Akgonul, M., & Akpinar, A. (2015). Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. Journal of Behavioral Addictions, 4(2), 85-92. https://doi.org/10.1556/2006.4.2015.010
Ekaterina, S., Dmitry, I., Muratova, A., Islam, R., Mitrofanova, E., & Ignatov, D. I. (2019). Searching for interpretable demographic patterns. https://mpra.ub.uni-muenchen.de/97305/1/paper2.pdf
Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 207, 251-259. https://doi.org/10.1016/j.jad.2016.08.030
Felisoni, D. D., & Godoi, A. S. (2018). Cell phone usage and academic performance: An experiment. Computers and Education, 117, 175-187. https://doi.org/10.1016/j.compedu.2017.10.006
Gecgel, H. (2020). Investigation of smartphone addiction levels of Turkish pre-service teachers with regards to various variables. Journal of Language and Linguistic Studies, 16(3), 1415-1442. https://doi.org/10.17263/jlls.803828
Gezgin, D. M. (2018). Understanding patterns for smartphone addiction: Age, sleep duration, social network use and fear of missing out. Cypriot Journal of Educational Sciences, 13(2), 166-177. https://doi.org/10.18844/cjes.v13i2.2938
Gokcearslan, S., & Oberst, U. (2018). stress and social support among university students: A path analysis. Stress and Health, 33(5), 624-630.
Harris, B., Regan, T., Schueler, J., & Fields, S. A. (2020). Problematic mobile phone and smartphone use scales: A systematic review. Frontiers in Psychology, 11, 672. https://doi.org/10.3389/fpsyg.2020.00672
Haug, S., Paz Castro, R., Kwon, M., Filler, A., Kowatsch, T., & Schaub, M. P. (2015). Smartphone use and smartphone addiction among young people in Switzerland. Journal of Behavioral Addictions, 4(4), 299-307. https://doi.org/10.1556/2006.4.2015.037
Kim, H.-Y. (2013). Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness and kurtosis. Restorative Dentistry & Endodontics, 38(1), 52. https://doi.org/10.5395/rde.2013.38.1.52
Konan, N., Durmus, E., Turkoglu, D., & Bakir, A. A. (2018). How is smartphone addiction related to interaction anxiety of prospective teachers? Education Sciences, 8(4), 186. https://doi.org/10.3390/educsci8040186
Kwon, M., Kim, D. J., Cho, H., & Yang, S. (2013). The smartphone addiction scale: Development and validation of a short version for adolescents. PLoS ONE, 8(12), 1-7. https://doi.org/10.1371/journal.pone.0083558
Lee, E. B. (2015). Too much information: Heavy smartphone and Facebook utilization by African American young adults. Journal of Black Studies, 46(1), 44-61. https://doi.org/10.1177/0021934714557034
Lepp, A., Barkley, J. E., & Karpinski, A. C. (2014). The relationship between cell phone use, academic performance, anxiety, and satisfaction with life in college students. Computers in Human Behavior, 31(1), 343-350. https://doi.org/10.1016/j.chb.2013.10.049
Lin, Y. H., Chang, L. R., Lee, Y. H., Tseng, H. W., Kuo, T. B. J., & Chen, S. H. (2014). Development and validation of the smartphone addiction inventory (SPAI). PLoS ONE, 9(6), e98312. https://doi.org/10.1371/journalpone.0098312
Lin, Y. H., Chiang, C. L., Lin, P. H., Chang, L. R., Ko, C. H., Lee, Y. H., & Lin, S. H. (2016). Proposed diagnostic criteria for smartphone addiction. PLoS ONE, 11(11), 1-11. https://doi.org/10.1371/journal.pone.0163010
Lin, Y. H., Lin, Y. C., Lee, Y. H., Lin, P. H., Lin, S. H., Chang, L. R., Tseng, H. W., Yen, L. Y., Yang, C. C. H., & Kuo, T. B. J. (2015). Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App). Journal of Psychiatric Research, 65, 139-145. https://doi.org/10.1016/j.jpsychires.2015.04.003
Matar Boumosleh, J., & Jaalouk, D. (2017). Depression, anxiety, and smartphone addiction in university students-A cross sectional study. PLoS ONE, 12(8), e0182239. https://doi.org/10.1371/journal.pone.0182239
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), 417. https://doi.org/10.3390/educsci11080417
Mok, J.-Y., Choi, S.-W., Kim³, D.-J., & Choi, J.-S. (2014). Neuropsychiatric disease and treatment dovepress latent class analysis on internet and smartphone addiction in college students. Journal of Neuropsychiatric Disease and Treatment, 10, 817-828. https://doi.org/10.2147/NDT.S59293
Panova, T., & Carbonell, X. (2018). Is smartphone addiction really an addiction? Journal of Behavioral Addictions, 7(2), 252-259. https://doi.org/10.1556/2006.7.2018.49
Randler, C., Wolfgang, L., Matt, K., Demirhan, E., Horzum, M. B., & Beşoluk, S. (2016). Smartphone addiction proneness in relation to sleep and morningness-eveningness in German adolescents. Journal of Behavioral Addictions, 5(3), 465-473. https://doi.org/10.1556/2006.5.2016.056
Razumovskaya, M., Zaitseva, N. A., Larionova, A. A., Chudnovskiy, A. D., & Breusova, E. A. (2018). Prospects for applying various forms of organizational integration to improve the quality of education. Astra Salvensis, 6(2), 348.
Romero-Rodríguez, J. M., Rodríguez-Jiménez, C., Navas-Parejo, M. R., Marín-Marín, J. A., & Gómez-García, G. (2020). Use of Instagram by pre-service teacher education: Smartphone habits and dependency factors. International Journal of Environmental Research and Public Health, 17(11), 1-10. https://doi.org/10.3390/ijerph17114097
Scikit-Learn. (2021). Scikit-learn: Machine learning in Python—Scikit-learn 1.0.1 documentation. https://scikitlearn.org/stable/
Shan, Z., Deng, G., Li, J., Li, Y., Zhang, Y., & Zhao, Q. (2013). Correlational analysis of neck/shoulder pain and low back pain with the use of digital products, physical activity and psychological status among adolescents in Shanghai. PLoS ONE, 8(10), e78109. https://doi.org/10.1371/journal.pone.0078109
Shrikumar, A., Greenside, P., & Kundaje, A. (2017). Learning important features through propagating activation differences. In Proceedings of the 34^th International Conference on Machine Learning (pp. 4844-4866).
Soomro, K. A., Zai, S. A. Y., Nasrullah, & Hina, Q. A. (2019). Investigating the impact of university students’ smartphone addiction on their satisfaction with classroom connectedness. Education and Information Technologies, 24(6), 3523-3535. https://doi.org/10.1007/s10639-019-09947-7
Syakur, M. A., Khotimah, B. K., Rochman, E. M. S., & Satoto, B. D. (2018). Integration k-means clustering method and elbow method for identification of the best customer profile cluster. IOP Conference Series: Materials Science and Engineering, 336(1). https://doi.org/10.1088/1757-899X/336/1/012017
Tugun, V., Bayanova, A. R., Erdyneeva, K. G., Mashkin, N. A., Sakhipova, Z. M., & Zasova, L. V. (2020). The opinions of technology supported education of university students. International Journal of Emerging Technologies in Learning, 15(23), 4-14. https://doi.org/10.3991/ijet.v15i23.18779
Vezzoli, M., Colombo, A., Marano, A., Zoccatelli, G., & Zogmaister, C. (2021). Test for mobile phone dependence: Psychometric properties and confirmatory factor analysis. Current Psychology. https://doi.org/10.1007/s12144-021-01449-5
XGBoost Developers. (2021). XGBoost documentation—XGBoost 1.5.1 documentation. https://xgboost.readthedocs.io/en/stable/#
Yuan, C., & Yang, H. (2019). Research on k-value selection method of k-means clustering algorithm. Multidisciplinary Scientific Journal, 2(2), 226-235. https://doi.org/10.3390/j2020016

Citation

Masalimova, A. R., Khairullina, E. R., Lapidus, N. I., Orekhovskaya, N. A., Zheltukhina, M. R., & Baranova, E. A. (2022). Exploring Preservice STEM Teachers’ Smartphone Addiction. Contemporary Educational Technology, 14(3), ep371. https://doi.org/10.30935/cedtech/11916

Masalimova, A. R., Khairullina, E. R., Lapidus, N. I., Orekhovskaya, N. A., Zheltukhina, M. R., and Baranova, E. A. (2022). Exploring Preservice STEM Teachers’ Smartphone Addiction. Contemporary Educational Technology, 14(3), ep371. https://doi.org/10.30935/cedtech/11916

Masalimova AR, Khairullina ER, Lapidus NI, Orekhovskaya NA, Zheltukhina MR, Baranova EA. Exploring Preservice STEM Teachers’ Smartphone Addiction. CONT ED TECHNOLOGY. 2022;14(3), ep371. https://doi.org/10.30935/cedtech/11916

Masalimova, Alfiya R., Elmira R. Khairullina, Natalya I. Lapidus, Natalia A. Orekhovskaya, Marina R. Zheltukhina, and Ekaterina A. Baranova. "Exploring Preservice STEM Teachers’ Smartphone Addiction". Contemporary Educational Technology 2022 14 no. 3 (2022): ep371. https://doi.org/10.30935/cedtech/11916

Masalimova, Alfiya R. et al. "Exploring Preservice STEM Teachers’ Smartphone Addiction". Contemporary Educational Technology, vol. 14, no. 3, 2022, ep371. https://doi.org/10.30935/cedtech/11916

Masalimova AR, Khairullina ER, Lapidus NI, Orekhovskaya NA, Zheltukhina MR, Baranova EA. Exploring Preservice STEM Teachers’ Smartphone Addiction. CONT ED TECHNOLOGY. 2022;14(3):ep371. https://doi.org/10.30935/cedtech/11916