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Describe data-driven decision making as feature of pbis


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McIntosh et al. (2021) describe data-driven decision making as a core feature of PBIS in which teams regularly collect and analyze behavior data-such as office discipline referrals, suspensions, climate surveys, and fidelity measures-to guide prevention, intervention, and progress monitoring. Using tools like "Big 5" reports and Team-Initiated Problem Solving (TIPS), schools identify specific patterns in behavior across students, settings, and times of day so supports can be proactive, targeted, and effective rather than reactive or punitive. This practice promotes equity by disaggregating data by race, ethnicity, disability, and gender to uncover hidden disparities, increase staff awareness of implicit bias, and guide culturally responsive strategies tailored to the actual problem. As shown in McIntosh et al.'s research, equity-focused, data-driven PBIS reduces racial disproportionality in discipline, improves school climate, and leads to more consistent and fair disciplinary outcomes. Need Assignment Help?

 

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