- PMD: 1,6
- Cost: Included in Registration
- Skill Level: Intermediate
- Poster Session 3: Promoting Safe and Positive Schools
Learner Objectives
This session will help participants…
- learn about the power of machine learning algorithms in detecting potential victims and how they can be integrated into comprehensive prevention strategies, enabling school psychologists to intervene early and provide targeted support to vulnerable students;
- gain a deeper understanding of the various risk factors associated with cyberbullying, including psychological issues and internet addiction, and become better equipped to identify warning signs and implement proactive measures to prevent cyberbullying among middle school students; and
- gain knowledge about strategies for creating a safe and inclusive school environment that mitigates the impact of cyberbullying, which may include implementing digital citizenship programs, establishing reporting mechanisms, and fostering positive online behaviors.
Description
Cyberbullying among middle school students: Learn how machine learning techniques can identify students at risk of cyberbullying and how to enable targeted interventions and create a safer school environment.
Presenter(s)
Anqi Zhang, Fordham University
Yifan Wang, Graduate Student Fordham University
Yena Li, Graduate Student Fordham University
Contributor(s)
Jelena K. Sanchez, Isabel C. Itzkowitz
