Modification of the Indonesian Academic Cyberloafing Scale (IACS): A tool for assessing online deviance in educational contexts
DOI:
https://doi.org/10.26555/humanitas.v22i1.1044Keywords:
College Students, Confirmatory Factor Analysis, Cyberloafing, Indonesian Version, PsychometryAbstract
The initial ease of internet use has led to new challenges, one of which is the phenomenon of cyberloafing. Cyberloafing refers to the activity of accessing the internet during learning processes. The aim of this study is to modify the cyberloafing scale within an educational setting in Indonesia using the dimensions of sharing, shopping, real-time updating, accessing online content, and gaming/gambling. The modifications include contextualizing the original and adding new relevant items. Data collection was conducted using purposive sampling, involving 235 university students from various higher education institutions in Indonesia. The method used to test the validity of the cyberloafing model was confirmatory factor analysis. The results showed that out of 65 items, 20 were found to be valid, with a satisfactory total Cronbach’s alpha of 0.73-0.93 and McDonald’s omega of 0.71-0.93 for measuring reliability for each dimension of cyberloafing. The practical implication of this measurement tool is that it can be used to assess the intensity of cyberloafing among higher education students in Indonesia
References
Akbulut, Y., Dursun, Ö. Ö., Dönmez, O., & Şahin, Y. L. (2016). In search of a measure to investigate cyberloafing in educational settings. Computers in Human Behavior, 55, 616–625. https://doi.org/10.1016/j.chb.2015.11.002
Alanoğlu, M., & Karabatak, S. (2021). Examining of the smartphone cyberloafing in the class: Relationship with the attitude towards learning and prevention of cyberloafing. International Journal of Technology in Education, 4(3), 351–372. https://doi.org/10.46328/ijte.84
Anandarajan, M., Devine, P., & Simmers, C. A. (2004). A multidimensional scaling approach to personal web usage in the work place. In M. Anandarajan & C.A. Sim-mers (Eds.), Personal web usage in the workplace: A guide to effective human resource management (pp. 61–79).
Blanchard, A. L., & Henle, C. A. (2008). Correlates of different forms of cyberloafing: The role of norms and external locus of control. Computers in Human Behavior, 24(3), 1067–1084. https://doi.org/10.1016/j.chb.2007.03.008
Blau, G., Yang, Y., & Ward-Cook, K. (2006). Testing a measure of cyberloafing. Journal of Allied Health, 35(1), 9–17. https://pubmed.ncbi.nlm.nih.gov/16615292/
Brown, T. A. (2006). Confirmatory factor analysis for applied research. The Guilford Press.
Choirina, V. N., Ayriza, Y., & Wibowo, Y. S. (2021). Religiosity and life satisfaction in Indonesia: Evidence from a community survey. Journal of Educational, Health and Community Psychology, 10(1), 38–47. https://doi.org/10.12928/jehcp.v10i1.19625
Cortina, J. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104. https://doi.org/10.1037/0021-9010.78.1.98
Databoks. (2018). Bappenas notes shift in public spending. Databoks. https://databoks.katadata.co.id/datapublish/2018/07/24/bappenas-catat-pergeseran-belanja-masyarakat
Desnirita, D., & Sari, A, P. (2022). The impact of workload and cyberloafing behavior on employee performance at PT Dwidaya World Wide, DKI Jakarta branch area. Journal of Indonesian Accounting Academy Padang, 2(1), 1–13. https://doi.org/10.31933/jaaip.v2i1.540
Durak, H. Y. (2020). Cyberloafing in learning environments where online social networking sites are used as learning tools: Antecedents and consequences. Journal of Educational Computing Research, 58(3), 539–569. https://doi.org/10.1177/0735633119867766
Hayes, A. F., & Coutts, J. J. (2020). Use omega rather than cronbach’s alpha for estimating reliability. But…. Communication Methods and Measures, 14(1), 1–24. https://doi.org/10.1080/19312458.2020.1718629
Kalayci, E. (2010). The investigation of relationship between cyberloafing and self regulated learning strategies among undergraduate students [Unpublished master’s thesis]. Hacettepe University.
Kemp, S. (2023). Digital 2023: Indonesia-DataReportal-Global Digital Insights. https://datareportal.com/reports/digital-2023-indonesia
Keser, H., Kavuk, M., & Numanoglu, G. (2016). The relationship between cyber-loafing and internet addiction. Cypriot Journal of Educational Sciences, 11(1), 37–42. https://doi.org/10.18844/cjes.v11i1.431
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
Kline, R. B. (2023). Principles and practice of structural equation modeling (5th ed.). The Guilford Press.
Koay, K.-Y. (2018). Assessing cyberloafing behaviour among university students: A validation of the cyberloafing scale. Pertanika Journal of Social Science and Humanities, 26(1), 409–424. http://www.pertanika.upm.edu.my/pjssh/browse/regular-issue?article=JSSH-1974-2016
Krishna, S. M., & Agrawal, S. (2023). Cyberloafing: Exploring the role of psychological wellbeing and social media learning. Behavioral Sciences, 13(8), 649. https://doi.org/10.3390/bs13080649
Li, Q., Xia, B., Zhang, H., Wang, W., & Wang, X. (2022). College students’ cyberloafing and the sense of meaning of life: The mediating role of state anxiety and the moderating role of psychological flexibility. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.905699
Lim, V. K. G. (2002). The IT way of loafing on the job: Cyberloafing, neutralizing and organizational justice. Journal of Organizational Behavior, 23(5), 675–694. https://doi.org/10.1002/job.161
Malkewitz, C. P., Schwall, P., Meesters, C., & Hardt, J. (2023). Estimating reliability: A comparison of cronbach’s α, McDonald’s ωt and the greatest lower bound. Social Sciences & Humanities Open, 7(1), 100368. https://doi.org/10.1016/j.ssaho.2022.100368
Marangoz, M., Yesildag, B., & Arikan Saltik, I. (2012). A Research on web and social network sites of e-commerce enterprises by content analysis method. Journal of Internet Applications and Management, 3(2), 53–78. https://doi.org/10.5505/iuyd.2012.87597
Mei, T. K., Mahamood, A. F., Abdullah, S., Yakob, T. K. T., & Mokhdzar, Z. A. (2021). Cyberloafing behavior and its effects towards academic achievement among students in higher education institution cyberloafing behavior and its effects towards academic achievement among students in higher education institution. Journal of Human Development and Communication, 10, 115–133. https://johdec.unimap.edu.my/index.php/volume-10-2021
Metin-Orta, I., & Demirtepe-Saygılı, D. (2023). Cyberloafing behaviors among university students: Their relationships with positive and negative affect. Current Psychology, 42(13), 11101–11114. https://doi.org/10.1007/s12144-021-02374-3
Ozdamli, F., & Ercag, E. (2021). Cyberloafing among university students. TEM Journal, 10(1), 421–426. https://doi.org/10.18421/TEM101-53
Plichta, S. B., & Kelvin, E. A. (2013). Munro’s statistical methods for health care research (6th ed.). Wolters Kluwer Health/Lippincott Williams &Wilkins.
Polat, M. (2018). The smart phone cyberloafing scale in classes (SPCSC): A scale adaptation study for university students. Social Sciences Studies Journal, 4(21), 3114–3127. https://doi.org/10.26449/sssj.733
Pratama, M. Y. A., & Satwika, Y. W. (2022). The relationship between self-regulation and cyberloafing behavior in psychology students of Surabaya state university. Character: Journal of Psychological Research, 9(1), 21–33. https://ejournal.unesa.ac.id/index.php/character/article/view/44551
Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review, 41, 71–90. https://doi.org/10.1016/j.dr.2016.06.004
Saleh, M., Daqqa, I., Rahim, M. B. A., & Sakallah, N. (2018). The effect of cyberloafing on employee productivity. International Journal of Advanced and Applied Sciences, 5(4), 87–92. https://doi.org/10.21833/ijaas.2018.04.011
Sugiyono. (2018). Quantitative Research Methods. Alfabeta.
Toker, S., & Baturay, M. H. (2021). Factors affecting cyberloafing in computer laboratory teaching settings. International Journal of Educational Technology in Higher Education, 18(1), 20. https://doi.org/10.1186/s41239-021-00250-5
Umar, J., & Nisa, Y. F. (2020). Construct validity test with CFA and reporting. Indonesian Journal of Psychology and Education Measurement, 9(2), 1–11. https://doi.org/10.15408/jp3i.v9i2.16964
Wang, J., & Wang, X. (2019). Structural Equation Modeling. Wiley. https://doi.org/10.1002/9781119422730
Widiastuti, R., & Margaretha, M. (2016). Personality factors and cyberloafing of college students in Indonesia. International Journal of Applied Business and Economic Research, 14(13), 9227–9238. https://www.serialsjournals.com/abstract/89800_30-ratna.pdf
Wu, J., Mei, W., Ugrin, J., Liu, L., & Wang, F. (2020). Curvilinear performance effects of social cyberloafing out of class: The mediating role as a recovery experience. Information Technology & People, 34(2), 581–598. https://doi.org/10.1108/ITP-03-2019-0105
Yildiz, H., & Yildiz, B. (2022). Testing the validity and reliability of a Turkish version of the social cyberloafing scale. Perspectives in Psychiatric Care, 58(4), 1291–1302. https://doi.org/10.1111/ppc.12930
Zhang, Y., Tian, Y., Yao, L., Duan, C., Sun, X., & Niu, G. (2022). Teaching presence predicts cyberloafing during online learning: From the perspective of the community of inquiry framework and social learning theory. British Journal of Educational Psychology, 92(4), 1651–1666. https://doi.org/10.1111/bjep.12531
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