Purpose: This tool is designed to guide the process of selecting students for a tutoring program, using data-driven decision-making. The following sections outline key factors to consider when selecting students for the program, along with examples of relevant data for each factor.
| Criteria | Purpose | Considerations | Examples |
| Focus Area | Select the students within the grade levels and content areas for whom tutoring will have the greatest impact on significant academic needs. | Grade Levels: Identify students who have the greatest needs in the grade levels chosen. | Grades 6 to 7 show a significant drop in math proficiency. Data Source: State Tests |
| Content Areas: Identify students who are struggling the most for the subject area chosen. | Reading comprehension as an area with widespread low performance in the school. Data Source: State Tests | ||
| Student Need: Prioritize areas with the highest concentration of students who would benefit from tutoring. | First grade students are in a critical year for developing foundational skills. Data Source: Reading Diagnostic | ||
| Student Academic Performance | Identify students who need academic support based on performance data and other indicators. | Test Scores: Identify a threshold for success on state, interim, or unit assessments. | A student scoring below the 25th percentile on state math assessments. Data Source: Standardized Test |
| Skill Deficits: Identify students who have skill gaps. | A student performing poorly in reading fluency. Data Source: Reading Diagnostic | ||
| Absenteeism: Analyze chronic absenteeism patterns to determine which students might need extra support. | A student who has missed more than 20% of school days this semester. Data Source: Attendance Records | ||
| Teacher Recommendations: Consult teachers for insights on students who may not be showing up in academic data but need support. | A student not currently failing but struggling with class participation or understanding of key concepts. Data Source: Teacher Recommendation | ||
| Equity Considerations: Prioritize students who don’t have access to additional support systems like private tutoring or after-school programs. | A student in a low-income household without access to private tutoring services. Data Source: School Counselor | ||
| Special Populations | Ensure the program supports special populations (ELLs, Special Education, etc.) without interfering with other mandated supports. | English Language Learners (ELLs): Identify language barriers and provide appropriate support. | An ELL student struggling with reading and writing in English, but has strong listening comprehension and speaking. . Data Source: WIDA ACCESS or language equivalency data |
| Special Education Needs: Ensure accommodations and support services are available for students with disabilities. | A student with a learning disability in math requires additional time and a differentiated curriculum. Data Source: Student IEP/504 | ||
| Compliance with Mandates: Ensure tutoring does not interfere with other required services (e.g., IEPs, 504 plans). | A student receiving speech therapy that cannot conflict with tutoring sessions. Data Source: Individual Student Schedules | ||
| Logistics | Ensure that students can attend tutoring sessions and that any logistical barriers are addressed | Class Schedules: Cross-reference students' schedules with available tutoring times to ensure attendance. | A student with a conflict between tutoring sessions and an advanced band class. Data Source: School Primary Schedule; Class Rosters |
| Technology Access: Ensure that students have access to necessary technology (e.g., computers, internet) if tutoring is virtual. | A student without 1:1 may need scheduling in a computer lab. Data Source: Technology distribution lists | ||
| Language Proficiency: Consider language proficiency needs when scheduling sessions. | A student who speaks Spanish as their first language may require a bilingual tutor or specific language support during sessions. Data Source: WIDA ACCESS or language equivalency data | ||
| Provider Fit | Match tutoring providers with students and schools based on their expertise, capacity, and program model. | Provider Expertise: Match tutors with appropriate subject knowledge and experience for the students' needs. | Assign a tutor with expertise in high school algebra to work with students struggling in that area. Data Source: Tutor Roster |
| Capacity: Ensure providers can meet the needs of students, such as availability of tutors and resources. | A provider with a proven track record of successfully supporting ELL students in language arts. Data Source: Tutor Evidence/Resume | ||
| Program Fit: Match the provider’s program model with the school’s specific tutoring needs (e.g., in-person vs. virtual, small group vs. one-on-one). | A provider who specializes in one-on-one, in-person math tutoring for struggling middle school students. Data Source: Tutor Evidence/Resume |