This research aims to analyze cyberslacking behavior among students in Indonesia and see if there is an influence between self-regulated learning and student academic achievement on cyberslacking behavior. The method used is a quantitative approach. Data collection using an accidental sampling technique was conducted online through Google Forms with 367 respondents. The individuals involved in this research were university students. The measuring instruments used were the adapted cyberslacking scale, the self-regulated learning scale, and the cumulative grade point average. The data was then analyzed using Jamovi 2.3.28 software with a multiple linear regression analysis model. The results showed that self-regulated learning affects cyberslacking while academic achievement does not. However, it later showed that self-regulated learning and academic achievement simultaneously affect cyber-slacking by 23 percent, with an F value of 55.8 (p less than .001). Students doing academic activities can exercise control over self-regulated learning and academic achievement to avoid cyberslacking behavior. Therefore, efforts to improve self-regulated learning and academic achievement are goals in reducing cyberslacking behavior.
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