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Saturday, November 16, 2024

Students develop anti-cyberbullying plan targeting middle schools

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Chancellor Kent Syverud | Syracuse University

Chancellor Kent Syverud | Syracuse University

With nearly half of U.S. teens aged 13 to 17 reporting being targets of cyberbullying, instructional design master’s degree students Tavish Van Skoik and Jiayu “J.J.” Jiang have developed a process to help school districts address electronic aggression. According to a 2022 Pew Research Center survey, cyberbullying is a top concern for this age group.

Van Skoik and Jiang created “Cyberguard,” an anti-cyberbullying model, for their final project in the School of Education’s IDE 632: Instructional Design and Development II course. This course requires students to develop an instructional design model and appropriate accompanying implementation documentation.

Van Skoik’s and Jiang’s model proposes a process for educational institutions to follow that should help reduce the number of cyberbullying incidents. Currently under review with EDUCAUSE, they hope it will be published soon in the higher education technology journal and presented at its annual conference in November.

Having taught middle school for six years and later working as an instructional technology specialist for a school district in South Carolina, Van Skoik saw both the effects of student cyberbullying play out daily in his classroom and how his district tracked students’ use of school-issued computers. His firsthand experience sparked the idea for the model.

“I think middle schoolers are particularly vulnerable as far as emotional intelligence, behavior modification and behavior management are concerned,” says Van Skoik. He believes that interventions implemented at this age would help students learn as they grow. “Then by the time they’re in high school, which this data is from, there would be a reduction in cyberbullying cases.”

The pair used the New York State Education Department’s School Safety and Educational Climate (NYSED SSEC) incident data to identify the state high school with the highest number of self-reported cyberbullying cases. That school—which they are not disclosing—was then used as the focus of their model. The school reported 39 cyberbullying incidents over the 2021-22 school year, which they say is high compared to other schools’ average of 0.67 incidents per school.

Based on this data, Van Skoik and Jiang devised their model as steps school districts can follow to reduce incidents. The model acts as a positive feedback loop by raising awareness, identifying cyberbullying, and preventing further cases. “The point of the model is the awareness of what cyberbullying is,” stresses Van Skoik.

To counter cyberbullying, Cyberguard uses historical data, digital behavior analytics, and stakeholder feedback to facilitate targeted interventions at critical times. The model is intended for use by K-12 general administrators and IT administrators.

The Pew survey found that teens use six cyberbullying behaviors: offensive name-calling (most reported), spreading false rumors, receiving explicit images, physical threats, harassment, and having explicit images shared without consent.

Online anonymity, 24/7 connectivity, lack of supervision, and digital footprints are among causes identified by Van Skoik and Jiang. “If we can address those potential causes,” says Van Skoik, “the cases will come down.”

Regarding online anonymity, too often people can hide behind a screen creating personas that say or do things they wouldn’t face-to-face. “This model eliminates that possibility,” says Van Skoik.

The pair suggest interventions take place in both digital and real worlds. They recommend schools develop an automatic monitoring system by installing software on devices loaned out by schools.

Monitoring helps not only students but also teachers and administrators because their computers can be monitored too. According to the Pew survey three in ten teens say monitoring social media activity for bullying or harassment would help.

Software can record suspected incidents of cyberbullying; AI could also be used in monitoring programs according to Jiang. “AI can recognize if there is a risk of cyberbullying or not,” she says.

For in-person intervention schools should collect feedback from students staff parents at beginning of year including mental health evaluations when recommended followed by educational training during professional development sessions for teachers students parents finally creating avenues allowing staff students parents report incidents reviewing interventions quarterly tracking progress refining processes if needed

Both Van Skoik Jiang believe schools must provide training education about online social behavior "School's goal is learn that's why we're environment" says Van Skoik who often saw cyberbullying interrupt lessons "So if can't learn find out why"

Educational training offered multiple ways online training session mixture both "Ultimate goal educational training program address issue there's concern" says Van Skoik

Final goal Cyberguard create culture reporting online harassment software identify suspected incidents based keywords avenues self-reporting implemented Google form encouraging concerns guidance counselors staff

"I hope improve everyone's awareness skills report" says Jiang

Ultimately Cyberguard serves template evolving after initial implementation "First year formative evaluations conducted every quarter test objective" she says If decline objective met Year two objectives change greater declines Years three five evaluate effectiveness comparing hoping stark decline

"Our theory prevalence results lack awareness education training" says Van Skoik "Instructional design tells us comes lack knowledge skills attitudes"

Story by Ashley Kang ’04 G’11 (proud alumna M.S higher education program)

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