A thirteen-item cyberbullying sensibility scale (CSS), developed by Tanrıkulu, Kınay, and Arıcak (2013) and extensively used by researchers, was used to measure the cyberbullying sensibility levels of high school students. Unlike other similar concepts, such as cyberbullying and cyber victimization, there are no scales developed to measure the cyberbullying sensibility among university students. In this study, the data obtained from 727 university students were analyzed based on item response theory (IRT) techniques, and psychometric evidences were obtained to evaluate whether it is appropriate to use the scale on the university students. Accordingly, a parameterization of CSS items was performed by using the graded response model. Using the discrimination parameters and item fit statistics, some items were removed from the original scale and a seven-item CSS version was developed since preliminary exploratory and confirmatory factor analyses provide inadequate evidence for the validity of a one-dimensional structure of cyberbullying sensibility. However, an IRT-based item removal process yielded an acceptable improvement. In this way, despite the six items being removed from the original CSS form, the scale retained 64% of the information it provided. The reliability values computed based on the classical approach and IRT were above .8 after the item elimination process with only a minor drop. With the validation process, the CSS will be a valuable measurement tool to determine the level of cyberbullying sensibility among university students and allow academicians to conduct research with this population.
This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website (https://osf.io/mhg94/).
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