EmpowerK12 Data Rubric
The EmpowerK12 Data Rubric helps school teams evaluate and strengthen their data practices on the path to becoming — and sustaining — Bold schools. Bold schools significantly improve the performance of students identified as at-risk (per the OSSE definition) on state math and reading assessments compared to their peers. The rubric's criteria align with best practices from Bold Schools, emphasize data-driven decision-making, and draw from Harvard's Data Wise methodology.
Terms used in the rubric
- Data driven
- How a school uses data to make strategic decisions that impact staff, student, and/or organization improvement.
- Staff / stakeholders
- The adults charged with student support — teachers, school staff, administrators, and families.
- All students
- All students actively enrolled at the school or LEA.
- Student subgroups / subpopulations
- Students who share similar characteristics, such as gender identification, racial or ethnic identification, socioeconomic status, or disability status.
- Equity
- All students receiving the support and resources they need to be holistically well and succeed academically, based on their individual needs.
When using this rubric, keep the focus on evidence. Each domain lists potential sources of evidence you can reference to substantiate your assessment of a school's developmental stage for a specific criterion.
Each of the 22 criteria is scored 1–4 against the descriptors below. Sum the scores — 22 to 88 points — to place the school in one of four stages. What distinguishes the stages is 1) the number of people involved and/or 2) the percent of domains covered.
Score overview
Each of the 22 criteria is scored 1–4 against the descriptors below. Sum the scores — 22 to 88 points — to place the school in one of four stages. What distinguishes the stages is 1) the number of people involved and/or 2) the percent of domains covered.
The school is initiating basic data collection, often for compliance. There is an opportunity to broaden the scope of data collected and explore its impact on decision-making — gradually integrating data into the school's overall strategy, moving beyond reporting.
Foundational data processes are progressing, but the focus is on historical trends at a high level. There's room to integrate data consistently across all levels of decision-making — letting data proactively guide strategy rather than retrospective reporting.
Data use is intentional and aligned with the school's goals. The opportunity now is to fully embed data into all aspects of school operations, and to pursue ongoing professional development in data literacy.
The school has reached an advanced level of maturity, seamlessly integrating data into strategic and operational decision-making. Data is fully embedded in teaching and learning — a model of effective, comprehensive data use.
Vision and goal setting
Evaluates how a school establishes a clear vision, aligns goals with that vision, engages the community, and sets measurable, accountable objectives to achieve its vision.
Vision clarity
The school's vision is unclear, underdeveloped, or not consistently communicated. There is limited understanding of the vision among stakeholders.
The vision is somewhat unclear and lacks specificity. Some stakeholders are aware of it, but not all — including families and students. The vision is not fully integrated with the school's mission and strategic goals.
The vision is communicated and understood by most stakeholders and evident in key areas, but there may be inconsistencies in alignment with the school's mission and strategic goals.
A clearly articulated vision is prominently communicated and widely understood by all stakeholders. The vision guides decision-making and aligns with the school's mission and strategic goals.
Measurable goals and accountability
The school lacks clear, measurable goals and has no systems for holding individuals or teams accountable for meeting them.
Goals lack specificity, measurability, or clear accountability.
Goals are somewhat clear, measurable, and action-oriented, but need improvement in specificity, measurability, or accountability measures.
Clear, measurable goals and milestones track progress toward the vision, with a system of accountability for achieving them.
Vision and goal alignment and integration
The school's vision and goals for data use are not aligned with one another — and therefore not aligned with school plans, curriculum, and instructional strategies — causing a disjointed approach.
There is partial alignment between goals and the stated vision, and therefore little alignment and integration across school areas and/or a lack of consistency.
The data-driven vision and goals are directly aligned with one another.
The goal and vision are somewhat aligned with the school's structure and objectives (schedule, family engagement, school improvement plans, curriculum, instruction), but lack complete integration with all school aspects.
The school's vision and goals for data use are directly aligned with one another and with the school's objectives (schedule, family engagement, school improvement plans, curriculum, instructional strategies) — ensuring all aspects of the school support the vision and work toward the goals.
Inclusivity and stakeholder involvement
Decisions are made at the leadership level or in silos.
The school does not involve stakeholders in the goal-setting process, action planning, or implementation.
The school has limited stakeholder involvement in setting data-driven goals, action planning, or implementation.
Understanding of the goals and progress toward them lives with leaders or across a few departments.
The school involves stakeholders, but there could be more inclusivity and transparency in the goal-setting process, action planning, or implementation.
Most stakeholders know the goals well, but not everyone. Communication is frequent but lacks consistency and depth.
The school actively involves all stakeholders — staff, families, students, central office, board — in developing data-driven goals, action planning, and implementation.
All stakeholders know the goals well because the school communicates consistently about the goals and its progress.
Regular review and adjustment
The school lacks a process for reviewing progress and making the adjustments needed to reach goals.
There is limited review of progress, and adjustments are infrequent or inadequate.
Reviews are regularly conducted, but perhaps no more than BOY, MOY, and EOY. Adjustments are not consistently made to improve progress, or action is not taken at the highest lever of improvement.
The school reviews progress toward the vision and goals at a consistent, clearly defined cadence beyond BOY, MOY, and EOY — adjusting strategies as needed to ensure continuous improvement.
Learning mindset
Assesses how the school community fosters a trusting, growth-oriented, and adaptable environment.
Cultivating and sustaining a community of trust and vulnerability
The school community struggles to cultivate a safe environment for trust and vulnerability, hindering open communication and the willingness to take educational risks.
There are attempts to build trust and vulnerability throughout the school community and among all stakeholders, with limited success and a lack of systems and/or consistency. More than half of stakeholders are reluctant to be open or make mistakes.
There are notable, consistent efforts to establish trust and vulnerability, with some success in creating a safe environment for sharing and risk-taking — but not yet across all stakeholders.
The school actively fosters an environment where trust is encouraged and stakeholders feel safe to be vulnerable, share ideas, and take risks without fear of judgment.
Cultivating and sustaining growth mindset
The school does not actively encourage or promote a growth mindset among students, educators, and staff.
Setbacks, mistakes, and feedback cause defensiveness or are perceived as failures.
There are sporadic attempts to promote a growth mindset, with some aligned initiatives but no comprehensive strategy or integration into school culture.
Feedback exists, but only formally. The community may be unclear how they are doing between formal feedback cycles.
The school continuously works to cultivate a growth mindset, but may not succeed across all school levels (e.g., leaders have a growth mindset but not teachers, or adults do but not students).
Setbacks, mistakes, and feedback are somewhat seen as opportunities to improve, but might still be perceived in ways not conducive to learning.
The school actively promotes a growth mindset among students, educators, and staff — the belief that abilities and intelligence develop through embracing challenges and learning from failures.
The community is adaptable, specifically in the face of challenges. Setbacks, mistakes, and feedback — formal and informal — are treated as opportunities to improve rather than sources of shame or fear.
Embracing diversity and inclusion
The school does not effectively create an inclusive environment or embrace diversity in its educational approach.
The school acknowledges diversity or has some diversity initiatives, but does not consistently create an inclusive environment.
Stakeholders hold biases about students' abilities — specifically students with special needs and/or those performing below grade level.
The school promotes diversity and inclusion but needs to grow in fully embracing, celebrating, and valuing all perspectives and voices in the learning and improvement process.
The community is somewhat adaptable and open to feedback, but inconsistent in applying it.
Most stakeholders believe all students are capable of growth and grade-level proficiency, but biases about some students' abilities persist.
The school fosters an inclusive environment that celebrates diversity and different perspectives, where all voices and backgrounds are valued and respected.
All stakeholders believe all students are capable of growth and achieving grade-level proficiency.
Empowerment and accountability
There is a lack of stakeholder empowerment and ownership within the learning environment.
The school lacks accountability systems.
Ownership and empowerment are demonstrated sporadically and lack integration into the school's culture.
The school does not have strong, consistent accountability systems, and/or they are not part of the school culture.
Stakeholders take ownership in some instances, but not consistently across the school.
Some accountability systems exist, with consistent efforts across education initiatives — but not yet a school-wide practice.
Stakeholders feel empowered — they take ownership of their learning and have autonomy.
Clear accountability systems exist that stakeholders are invested in.
Data infrastructure and collection
Assesses the systems and structures used to gather, integrate, and secure high-quality data accessible to stakeholders, enabling informed decision-making based on data insights.
Data systems, collection, and integration
The school collects minimal data, primarily focused on academic performance.
Minimal effort has gone toward integrating diverse data sources.
Data collection is fragmented, with limited integration between sources.
Manual efforts predominate, leading to delays and potential inaccuracies in reporting.
Some aspects may hinder effectiveness and pose barriers to data-driven decision-making.
The school collects essential data, but it may require manual input or could be better streamlined. Integration is missing across some sources.
Integration processes are manual or semi-automated, leading to occasional delays in updates.
The system generally supports effective data-driven decision-making.
The school has a robust system for collecting diverse data types (academic, behavioral, attendance, etc.), minimizing manual effort and maximizing technology.
Data sources are integrated seamlessly, allowing a holistic view of student performance.
Automated processes deliver real-time updates and synchronization, facilitating efficient, effective data-driven decision-making.
Data quality and accuracy
Data quality is a significant concern, with frequent inaccuracies affecting the reliability of information.
Data validation processes are limited, leading to occasional inaccuracies, and rectifying errors can take time.
The school acknowledges data quality issues and has initiated some measures, but challenges with checking accuracy remain.
Data quality is a focus. Discrepancies are addressed and rectified in a timely manner, but checks are not always consistent or thorough.
There may be occasional discrepancies, but overall the data is reliable.
Rigorous processes ensure data quality and accuracy.
Regular automatic and manual checks and validation mechanisms produce exceptionally reliable data — rounds of checks pair technology with people to catch blind spots. Errors and inconsistencies are promptly identified and corrected.
Data security and privacy
The school lacks sufficient measures to secure data, posing risks to integrity and privacy.
Unauthorized access is a concern, with no clear protocols to protect sensitive information.
Urgent improvements are required to establish robust security and privacy practices.
Basic security measures exist, but notable gaps raise concerns about protecting sensitive information.
Privacy policies may be outdated or inconsistently enforced, and some personnel face challenges accessing the data they need.
Enhancements are needed for more comprehensive security and privacy protocols.
The school has security measures in place, with areas needing improvement to fully safeguard data and privacy.
Key stakeholders can access data, though with occasional challenges or limitations.
Privacy policies are established, with occasional lapses in compliance — they may not be thorough or consistently implemented.
Robust security measures protect sensitive student and staff data.
Relevant stakeholders — teachers, administrators, parents — have secure, easy access to the data they need.
Data governance is evident: policies clearly state what each stakeholder can access, align with privacy regulations, and demonstrate a strong commitment to safeguarding information.
Data tools and reporting
The school relies on default or pre-built reports without customization — one-time, non-reusable reports in tools like Excel or Google Sheets, with no standardized process for future use.
Reporting is uniform and doesn't consider the specific needs of different stakeholders.
The school relies on standardized reports with limited adjustments to meet basic requirements.
Tools generate reports regularly, but without real-time or timely updates.
Data is pulled from one or a few sources, without integrating multiple domains. There is limited differentiation in access or reporting.
Data tools create custom reports that integrate multiple sources or domains, providing a more comprehensive view.
Reports may offer limited interactivity or filtering beyond static displays.
Reports support specific meeting structures or use cases, and include some indicators or early-warning signals, though limited. Some access differentiation exists by role.
Data tools produce advanced custom reports generated automatically, with minimal intervention, designed for specific school or LEA needs.
Reports pair current data with historical trends and interactive visualizations for deeper analysis and informed decisions.
Indicators and early-warning systems flag issues like dropout risk, absenteeism, and students falling behind. Reports are tailored to district administrators, school leaders, teachers, and individual students.
Data literacy and development
Assesses stakeholder data literacy and the support offered to develop that skill set.
Data understanding
Teachers and staff lack a sufficient understanding of the data relevant to their roles.
Teachers and staff have a basic understanding of the data, but gaps remain in applying various data points to their roles.
The importance of data is recognized but not fully embraced or owned.
School staff — leaders, teachers, and support staff — understand the data well, though some data points are hard to understand or connect to their work.
There is general awareness of data's importance in decision-making.
School staff demonstrate a deep understanding of the data relevant to their roles and a strong belief that data matters to the decision-making process.
Data analysis
The school lacks effective data analysis practices.
Staff — particularly instructional staff — are still developing analysis skills.
Basic analysis is conducted but inconsistently applied, with limitations in the tools and methods used.
Errors are frequent because staff struggle to analyze data or glean the right information from it.
The school conducts regular analysis, with some variability in the accuracy, nuance, and consistency of skills across the school.
Staff typically draw appropriate conclusions from the data — possibly evidenced by effective action plans and growth.
The school consistently employs thorough analysis aligned to end goals, using appropriate tools and methods to derive meaningful insights that inform instructional strategies and decision-making.
Staff draw the right conclusions — and the highest levers of action — from the data.
Student data literacy
Students have minimal understanding of their academic data, with little to no evidence of goal-setting or active engagement with relevant data.
Students have a basic understanding of their academic data, but there is limited evidence of goal setting based on it.
The integration of data into student learning is inconsistent.
Students understand their academic data well, with evidence of aligned goal setting.
Depth of data literacy may vary across student groups — visible in their ability to understand their performance or set targeted goals.
Students demonstrate a high level of data literacy: they interpret and analyze their own data, set goals based on data insights, and actively participate in their educational progress.
There is evidence of students using data to inform their learning.
Family data literacy and engagement
The school struggles to engage families in discussions about student progress.
Minimal or no resources exist for students and families to develop data literacy skills or support engagement.
Families attempt a basic understanding of academic data, but there is limited evidence of engagement in discussions about student progress. Communication about data may be inconsistent.
The school offers basic data literacy resources for students and families, but coverage and accessibility are limited, and use may be limited.
Families generally understand and use academic data to support their children's learning, with some variability in engagement — specifically among subpopulations. Communication about data is generally effective.
The school collaborates with families to set goals, address challenges, and celebrate successes based on data, but struggles to do so school-wide.
Resources for families exist, with some gaps or inconsistencies in availability or use.
Families are actively engaged in understanding and using academic data to support their children's learning. The school collaborates with families to set goals, address challenges, and celebrate successes based on data insights.
Communication between the school and families about student progress is effective.
Comprehensive, accessible resources — workshops, guides, online materials — are well-used and cover various aspects of data literacy.
Training and development
There is minimal or no provision of training and development for staff in data literacy.
Training and development opportunities exist but are limited in scope, and not all staff can access relevant training.
Training may not align well with staff needs, and there is no systematic approach to building expertise.
The school offers training and development, with gaps or inconsistencies in coverage — it may not be fully tailored to every staff member's needs.
Efforts support ongoing professional growth in data literacy.
The school provides ongoing, targeted, differentiated training that builds staff data literacy, ensuring they are well-equipped to use data in their roles.
There is a systematic approach to building and sustaining data expertise, with evidence of continuous learning and improvement.
Data use and coaching
Provides a comprehensive assessment of the school's approach to data use, commitment to data-informed instruction, and coaching support.
Consistent data meetings
Data meetings are infrequent or inconsistent, lacking structure and equity in supporting all students.
Meetings do not include elements of the data cycle beyond basic analysis.
There is limited collaboration during meetings and little evidence of problem-solving based on data.
Occasional data meetings occur but lack consistency. They do not focus on all students, or some subpopulations are left out of the conversation.
Meetings do not use a research-based data protocol or improvement process, but have a consistent structure. They include some — but not all — elements of the data cycle: analyzing data, identifying the problem of practice, action planning, practice, progress monitoring.
Some collaboration occurs, with attempts at data-based problem-solving, but participants do not always reach informed decisions.
Regular, consistent data meetings occur, with evidence of a clear schedule and commitment.
Meetings attempt a research-based data protocol or improvement process that includes analyzing observation and instructional data, but not across subjects or all school staff.
Where meetings happen, collaborative problem-solving is a key feature, with evidence of effective teamwork and data-driven decision-making.
Highly regular, well-structured data meetings are held consistently across staff — leadership, coaches, teachers — using a variety of data and focusing on the success of all students. A robust schedule is evident, and meetings are a vital part of school culture.
Meetings leverage a research-based data protocol or improvement process: analyzing observation and instructional data, identifying the problem of practice, action planning, practicing, and progress monitoring.
Highly effective collaborative problem-solving is evident, demonstrating a strong commitment to data-driven decision-making and continuous improvement.
Data informed instruction
Instructional practices have limited alignment with available data.
There is limited evidence of adjustments based on data analysis.
There are attempts to align instruction with data, but the connection is inconsistent or not effectively implemented.
Some differentiation and personalization are attempted, but lack consistency, effective implementation, or alignment to data takeaways.
There is limited integration or alignment with interventions, MTSS, or RTI.
Instructional practices are consistently aligned with data insights. Adjustments are made based on analysis, and teaching strategies are tailored to student needs.
Differentiation is consistently applied based on data, with evidence of addressing individual student strengths and weaknesses — though inconsistent documentation or tracking creates challenges for intervention, MTSS, or RTI.
Instruction is highly effectively aligned with data insights. Data is seamlessly integrated into daily instruction, with clear evidence of continual adjustment and improvement.
Targeted differentiation, grounded in thorough analysis, produces personalized instructional strategies that address each student's unique needs and feed easily into interventions, MTSS, or RTI.
Action-focused data decision making
There is limited evidence of data influencing decision-making.
The school may rely more on intuition or tradition than on systematically incorporating data into decisions.
Data is occasionally referenced in decision-making, but the connection between analysis and strategic decisions is unclear or inconsistently applied.
There is room for a more systematic approach to data-informed decision-making.
The school has a data-driven decision-making culture, but it may not apply consistently across teaching, school wellbeing, and administration.
The link between data analysis and specific decisions may not be consistently documented or transparent.
The school has a strong data-driven decision-making culture: data is regularly used by the appropriate stakeholder to strategically inform school-wide practices, assess school wellness, and guide improvement efforts.
There is a clear, documented connection between data analysis and the decision-making process.
Targeted coaching cadence
There is limited use of data to set coaching goals; goals may be vague or unrelated to identified needs.
The school shows little evidence of monitoring or tailoring coaching to individual strengths and weaknesses.
Feedback may lack specificity or be generic.
The school demonstrates some use of data in goal setting, but goals may lack specificity or a clear connection to data analysis.
Some attempts are made to monitor progress and customize coaching strategies, but the differentiation lacks depth or may not align with data or identified staff needs.
Feedback may lack depth or a clear connection to analysis, and may be received as punitive rather than supportive.
The school demonstrates clear evidence of using data to set specific, measurable coaching goals tied directly to identified needs and priorities.
Progress is monitored regularly, with evidence of data-driven adjustments to coaching strategies — though with some inconsistency.
Feedback is targeted, actionable, and linked to coaching goals, but may not be framed in a way that intentionally values the staff member and builds trust.
The school effectively uses data to set targeted, measurable coaching goals that align with individual staff needs and broader school objectives.
The school is highly effective at monitoring progress and adjusting coaching strategies in real time — a dynamic, responsive approach to individual needs.
Staff receive targeted, actionable, evidence-based feedback that directly supports adult growth and contributes to trust and growth-mindset building.