Measuring Cyberbullying Levels among Adolescents in Integrated Islamic Junior High Schools in Jambi City: An Implementation of the Rasch Model
DOI:
https://doi.org/10.12928/jehcp.v13i1.27366Abstract
The incidence of cyberbullying in adolescents is increasing. This is, in part, attributed to the progress of Science and Technology (IPTEK), which is inseparable from the negative impact of cyberbullying. The latter has become central to adolescent communication. Consequently, cyberbullying, especially among adolescents, demands serious attention for early intervention. The purpose of this study was to measure the level of cyberbullying among students at SMP IT Jambi City by implementing the Rasch Model, a modern theoretical approach enhancing the accuracy of measuring latent variables. The research included 91 students from classes VII and VIII, selected through proportional random sampling. Data collection employed the Cyber Victim and Bullying Scale (CVBS) with 28 questions. The Rasch Model analysis revealed a high level of cyberbullying among adolescents at SMP IT Jambi City, with 52.2% categorized as high and 47.8% as low. The results demonstrated high accuracy, evident in validity and reliability coefficients of 0.87 and 0.71, respectively. This research provides valuable information for stakeholders aiming to maintain a cyberbullying-free climate.
References
Andrich, D., & Marais, I. (2019). A course in Rasch measurement theory. Measuring in the educational, social, and health sciences, 41-53
Baldry AC, Farrington DP, Sorrentino A. “Am I at risk of cyberbullying”? A narrative review and conceptual framework for research on the risk of cyberbullying and cyber victimization: the risk and needs assessment approach. Aggress Violent Behav. (2015) 23:36–51. doi: 10.1016/j.avb.2015.05.014
Bond, T.G., & Fox, C.M. (2013). Applying the Rasch model: Fundamental measurement in the human sciences. Psychology Press.
Brennan, R.L. (2000). Performance assessments from the perspective of generalizability theory. Applied Psychological Measurement, 24 (4), 339-353.
Del Rey, R., Casas, J. A., & Ortega, R. (2016). Impact of the ConRed program on different cyberbullying roles. Aggressive Behavior, 42, 123–135. https://doi.org/10.1002/ab.21608
Dooley JJ, Pyzalski J, Cross D. Cyberbullying versus face-to-face bullying: a theoretical and conceptual review. J Psychol. (2009) 217:182–8. doi: 10.1027/0044-3409.217.4.182
Falani, I., Akbar, M., & Naga, DS (2020). The Precision of Students' Ability Estimation on Combinations of Item Response Theory Models. International Journal of Instruction, 13 (4), 545-558.
Falani, I., Iriyadi, D., Ice, YW, Susanti, H., & Nasuition, RA (2022). A Rasch Analysis of Perceived Stigma of COVID-19 among Nurses in Indonesia Questionnaire. Psychological Thought, 15(1), 12.
Fitriana, NS (2018). Positive Thinking Training to Reduce Public Speaking Anxiety in Students (Doctoral dissertation, Mercu Buana University Yogyakarta).
Ferrara P, Ianniello F, Villani A, Corsello G. Cyberbullying a modern form of bullying: let's talk about this health and social problem. Ital J Pediatr. 2018;44(1):14. doi:10.1186/s13052-018-0446-4
Gradinger, P., Yanagida, T., Strohmeier, D., & Spiel, C. (2015). Prevention of cyberbullying and cybervictimization: Evaluation of the ViSC Social Competence Program. Journal of School Violence, 14(1), 87–110. https://doi.org/10.1080/15388220. 2014.963231
Jadambaa A, Thomas HJ, Scott JG, Graves N, Brain D, Pacella R. Prevalence of traditional bullying and cyberbullying among children and adolescents in Australia: a systematic review and meta-analysis. Aust NZJ Psychiatry. (2019) 53:878–88. doi: 10.1177/0004867419846393
Mardapi, D. (2012). Educational measurement, assessment, and evaluation. Yogyakarta: Nuha Medika , 45 .
Olweus D. Bullying at School: What We Know and What We Can Do. Oxford; Cambridge, MA: Blackwell (1993).
O'Brien, E. J., & Albrecht, J. E. (1992). Comprehension strategies in the development of a mental model. Journal of experimental psychology: learning, memory, and cognition, 18(4), 777.
Pengpid, S.; Peltzer, K. Bullying victimization and externalizing and internalizing symptoms among in-school adolescents from five ASEAN countries. Child. Youth Serv. Rev. 2019, 106, 104473
Pereira F, Matos M. Cyber-stalking victimization: what predicts fear among Portuguese adolescents? Eur J Crim Policy Res. (2016) 22:253–70. doi: 10.1007/s10610-015-9285-7
Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Danish Institute for Educational Research.
Reed LA, Ward LM, Tolman RM, Lippman JR, Seabrook RC. The association between stereotypical gender and dating beliefs and digital dating abuse perpetration in adolescent dating relationships. J Interpers Violence. (2018). doi: 10.1177/0886260518801933
Smith PK, Mahdavi J, Carvalho M, Fisher S, Russell S, Tippett N. Cyberbullying: its nature and impact in secondary school pupils. J Child Psychol Psychiatry. (2008) 49:376–85. doi: 10.1111/j.1469-7610.2007.01846.x
Sumintono, B. (2015). Rasch modeling in educational assessment: An introduction.
Supriyati, Y., Falani, I., & Maulana, S. (2021, March). The information function of mixed-format test of physics learning outcomes measurement. In AIP Conference Proceedings (Vol. 2320, No. 1). AIP Publishing.
Thomas HJ, Connor JP, Scott JG. Integrating traditional bullying and cyberbullying: challenges of definition and measurement in adolescents - a review. Educ Psychol Rev. (2015) 27:135–52. doi: 10.1007/s10648-014-9261-7
UNICEF ed. Children in a Digital World. New York, NY: UNICEF (2017).
Wright, B.D., & Mok, M. G.N. (2004). Introduction to Rasch measurement. MESA