Which data pattern should guide a school psychologist to implement mentoring programs for at-risk students?

Which data pattern should guide a school psychologist to implement mentoring programs for at-risk students?

• A. Higher dropout rates among specific groups like pregnant girls, certain ethnic groups, and homeless students
• B. No relationship between dropout and demographics
• C. Dropout rates decrease automatically
• D. Overall uniform dropout rate

Answer: (A)

Using data to identify which groups are most at risk guides where mentoring should be directed. When patterns show higher dropout rates for pregnant girls, students from certain ethnic groups, and homeless students, those groups are at greater risk and would likely benefit from mentoring that provides academic support, goal setting, and connections to resources. This targeted approach helps reduce barriers to staying in school and keeps students engaged. If there were no relationship between demographics and dropout, or if dropout rates were expected to decrease automatically, or if the dropout rate were uniform across all students, there would be less justification for focusing mentoring on specific groups and resources might not reach those who need them most.

Using data to identify which groups are most at risk guides where mentoring should be directed. When patterns show higher dropout rates for pregnant girls, students from certain ethnic groups, and homeless students, those groups are at greater risk and would likely benefit from mentoring that provides academic support, goal setting, and connections to resources. This targeted approach helps reduce barriers to staying in school and keeps students engaged. If there were no relationship between demographics and dropout, or if dropout rates were expected to decrease automatically, or if the dropout rate were uniform across all students, there would be less justification for focusing mentoring on specific groups and resources might not reach those who need them most.