Over the past decade, cyberbullying has attracted the attention of many researchers (Smith & Berkkun, 2017). With the rapid development of information and communication technologies (ICTs) and the increasing importance of ICTs in our daily lives, the need for research on aggressive behavior in cyberspace is growing. The age of ICT use is getting younger and younger, and ICTs are becoming part of the daily lives of young students, increasing the likelihood that they will be exposed to risky environments such as cyberbullying (Kelly & Arnold, 2016; Nocentini, Zambuto, & Menesini, 2015).
The Korea Communications Commission and the National Institute for Intelligence and Information Society Promotion have released the results of the 2021 Cyberbullying Survey (National Statistics of Korea No. 164003), which was conducted on a total of 16,500 adolescents and adults. According to a press release from the Korea Communications Commission, 29.2% of elementary, middle, and high school students experienced cyberbullying, nearly twice as high as adults (15.7%). 5.8% of adolescents were victimized, 15.1% were perpetrators, and 8.3% were both perpetrators and victims, indicating that a significant number of students experienced both perpetration and victimization. Especially after COVID-19, the problem of cyberbullying has become more serious and has attracted social attention (Korea Communications Commission, April 7, 2022).
Since 2020, the Blue Tree Foundation has been conducting a youth cyberbullying prevention program with the support of Samsung. As part of the project, the Blue Elephant Youth Cyberbullying Preventive Education for elementary school students is currently in operation, and about 30,000 students have participated in the program so far. This study aims to verify the effectiveness of the Blue Elephant Youth Cyberbullying Preventive Education by using data from about 1,000 students who participated in the pre-and post-test. The effectiveness analysis focuses on changes in cyberbullying attitudes and coping efficacy, cyberbullying psychological characteristics, and pro-social competence. In particular, coping efficacy includes class-level efficacy and teacher coping efficacy.
The study analyzed 1,499 students who participated in the pretest and either took the posttest or the follow-up (5-weeks after intervention) test. The total number of students was 705 (47.0%) males and 794 (53.0%) females, including 118 (7.9%) third graders, 159 (10.6%) fourth graders, 581 (38.8%) fifth graders, and 641 (42.8%) sixth graders. Of the 1,208 students who participated in the blended delivery method (80.6%) and 291 students who participated in the online delivery method (19.4%), 1,145 students participated in the posttest and 223 students participated in follow-up test. Of the students who participated in the blended delivery method, 287 students participated in the posttest and 80 students participated in the follow-up test. Analyses of pre- and follow-up tests are excluded due to the significantly smaller number of students who participated in the post-test.
The effectiveness analysis focused on changes in cyberbullying negative attitudes and coping efficacy, and pro-social competencies, including class-level efficacy and teacher coping efficacy. The Blue Elephant Youth Cyberbullying Preventive Education was conducted as a fully online program and a blended program, which is a combination of online and on-site instruction, and the differences between the two were examined not only by the gender and grade level of the students who participated in the program, but also by the way the program was conducted. Key findings include
First, there was a significant decrease in the experience of being a victim of cyberbullying after the program compared to before the program, and an increase in defensive behaviors such as helping the victim or preventing the victim from perpetrating cyberbullying when witnessing cyberbullying. Coping efficacy, the sense of being able, and an increase in defensive behaviors such as helping the victim or preventing the victim from perpetrating cyberbullying when witnessing cyberbullying. Coping efficacy, the sense of being able to handle cyberbullying, increased significantly at both the individual and class level.
Second, proactive aggression was found to increase among the psychological traits of cyberbullying, which may be due to the fact that students tend to exhibit higher levels of aggressive behavior toward the end of the school year than toward the beginning of the school year, such as peer contagion (Warren, Schoppelrey, Moberg, & McDonald, 2005), or it may be due to an increased understanding of proactive aggression that was previously unrecognized through the education. This needs to be further explored in future research, including interviews.
Third, six prosocial competencies (honesty, promise, forgiveness, responsibility, caring, and possession), showed significant increases compared to before the program. Prosocial competencies have been identified as protective factors against bullying and cyberbullying (Zych et al., 2018). The statistically significant change in prosocial competencies suggests that the program is effective in increasing the competencies that are useful in preventing cyberbullying.
Fourth, we found that differences between the blended and online programs were insignificant for most variables. Proactive aggression was significantly lower in the blended program than in the online one, suggesting that the blended one is more effective in reducing proactive aggression. The main reason why there was no significant difference between the two modalities for most items is that the online training used high-quality content, including the blue elephant character and voice actors to make the training more immersive, so it can be inferred that it was effective in capturing learners’ attention and delivering the message accurately. Further qualitative analysis, including interviews, is needed to explore the exact reasons for this.
Fifth, when we examined the differences by gender, the variables that showed significant effects in both the boy and girl groups were overall victimization experience, verbal victimization, defensive behavior, proactive aggression, and prosocial competencies except possession. In contrast, the variables with significant effects in the girls’ group were negative attitudes toward the perpetrator, emotional empathy, and their perception of teacher coping efficacy. This may be due to the fact that girls are more emotionally sensitive than boys and because of their interpersonal relations-oriented proclivity. Although research findings on gender differences in the effectiveness of prevention education are still in their early stages, it has been suggested that there may be differences in prevention strategies due to different purposes or modes of ICT utilization and different cyberspaces or platforms where cyberbullying occurs (Smith et al., 2019).
Sixth, when comparing middle (3rd & 4th graders) and upper (5th & 6th) elementary school students, there were more significant effects for older students overall. This may be a result of older students being more developmentally ready to understand and apply the lessons of the program, while young students may need more developmentally appropriate instruction supplemented by simpler language and activities. Specifically, whether there were significant differences in the level of comprehension of the program between middle and upper grade students needs to be investigated further, and in the long term, it is possible that the program could be differentiated between middle and later childhood because of the significant differences in educational settings and developmental levels (Aslan & Bäuml, 2016; Lepper, Corpus, & Iyengar, 2005).
The results of this study confirm that Blue Elephant’s cyberbullying preventive education reduces the experience of cyberbullying victimization and increases defensive behaviors that help victims. The whole class gains a sense of efficacy in dealing with cyberbullying. It also contributes to developing prosocial competencies; these effects were similar for blended and online education. Nevertheless, some factors differed in significance by gender and grade level. These differences could be explained by gender and age differences or results from program structure/content interacting with learner characteristics (i.e., gender, age). This needs further investigation.
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