Roster Students

Before School Year

Rostering students serves as the critical on-ramp for student success systems because it transforms raw enrollment data into an actionable map detailing each student’s pathway to on-time graduation. This process requires technical and data infrastructure capable of bridging data from feeder middle schools and transfer districts to ensure each student has a profile that considers their historical holistic indicators (attendance, behavior, course grades, and well-being indicators). By leveraging the Optimal Technical and Data Infrastructure Checklist, teams can move beyond manual entry to automate workflows that enroll students and transfer their historical data, manage transfer students and new arrivals throughout the school year, and ultimately enable staff to create student profiles and plan course placement for graduation.

Technical Infrastructure Choose Plays Examples in Practice

Technical Infrastructure

Before diving into the technical configuration steps to roster incoming students, we encourage your team to ensure your technical infrastructure is ready for this effort. For the workflows illustrated below, we have identified key capabilities that are required, regardless of the tool(s) used. In the case where you aren’t sure if your system has the capabilities, this checklist will generate a set of questions you can ask the district or provider for clarity. In the case where you know the system(s) cannot do something, this checklist offers considerations for creating workaround solutions.

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Data Integrity & Governance

Is your system set up to import data from middle school/feeder school systems as soon as the school year is over (and again after summer sessions, if relevant)?

Questions for Provider:

How does the tool handle student identity management during transitions? If a duplicate record is created, what’s the process for merging the data?
Does the tool provide pre-built bridges to pull historical data from middle schools?
Does the tool enable integration of qualitative data like belonging surveys or behavioral interventions, or does the tool only ingest grades and attendance?

Questions for District:

Is the data from feeder middle schools coming from the same SIS that houses HS data?
Is there a centralized data calendar that shows when data will be updated?
Do we have access to incoming student indicator data to support our high school team review and consider intervention assignments from middle school?

Data Integrity & Governance

Is your system set up to import data from transfer students' districts using an external file or standard template?

Data Integrity & Governance

Is your system set up to automatically flag data errors, such as missing data for incoming students or duplicate student entries?

Workaround Option 1:
Export student data into Excel or a similar tool with spreadsheet capabilities. To check for duplicate data, “pivot” on a unique value (e.g., each student likely has a unique ID assigned to them). Click on “insert” and select “pivot,” enabling the ability to create a table that shows how many instances of each student ID show up in the exported data. If there are ever two or more instances, it means that there is duplicate student data, which means the district needs to have extraneous records removed. Conditional formatting, which typically appears as an option under “format,” highlights where data is missing by setting cells without data or with null data to highlight in specific colors. It’s possible to then sort the data by color to determine which data needs to be updated.
Workaround Option 2:
Once valid data values are confirmed, set up exceptions reports—within the on-track system, if possible, or in Excel or another analytics tool (e.g. Power BI or Tableau)—to query for missing or inaccurate values. Focus on the highest-priority predictive indicator data first.
Ai-enabled workaround:
If the district has a closed, secure, and approved AI tool and allows the upload of student identifying information and data, export the raw data and prompt the AI tool to visibly flag (e.g., add colors) or add a column to capture the specific issues that need to be identified and resolved. Consider including instructions for how outlier data values should be treated (e.g., if there is a null value, treat it like a zero). Prompt the AI to explain the steps taken with the data to produce the output requested and to share any inconsistencies, risks, or issues with the data and how they have been resolved or attended to in the resulting report. If any of the explanations are not clear or do not make sense, prompt the AI to alter the approach it takes to flagging the data. If the report is rerun, prompt the AI to call out the specific changes in each iteration from the prior version(s). Remember to at least spot check the data against the source data to ensure accuracy. Ensure responsible use of AI by referring to the Considerations for AI Use section of this playbook.

System Configuration & Customization

Is your system set up to provide role-appropriate dashboards that display student progress toward district-specific graduation requirements?

Workaround Option 1:
Some systems will allow administrators to create dashboards and reports for other roles in the system. Review the system FAQs and self-support materials to find instructions for duplicating administrator-facing reports and dashboards and modifying them for use by team members with other roles and more limited data access.
Workaround Option 2:
System administrators have access to the greatest amount and granularly of data. To create workaround role-specific data views, an administrator would need to start by exporting admin-level data into Excel or an analytics and reporting tool. That data would need to be scrubbed to ensure users in other roles are not inadvertantly seeing data they would not have access to generally (e.g., in an SIS or other systems). The administrator may need to remove data (e.g., specific behavior incidents that should not be shared with most teachers), anonymize data (e.g., remove student names so that user can understand trends without identifying information), and/or aggregate data (e.g., share only class-level rollups rather than student-level data to remove any risk of recognizing individual student data) to produce a report that is appropriate to share with team members in relevant roles. Given the administrative nature of this task, it would be best to focus on the highest-value data and to find one meaningful and repeatable set of data modifications so that the output is one sharable report.
AI-enabled workaround:
If the district has a closed and secure AI tool and allows the upload of student identifying information and data, export the raw data and a template of the dashboards that are needed for various roles. Prompt the AI tool to generate a dashboard for each role by specifying what the rules are for each role (note: the district might have text to this effect available or may have shared guidance when explaining how roles have been determined for other centrally-provided tools; the user may also prompt the AI to find and share what the role-based guidance is for the district and ask the district confirm the accuracy of the response). Include in the prompt information about district-specific graduation requirements, what data should be flagged, and how those flags should be visible to and usable by the end user. Consider including instructions for how outlier data values should be treated (e.g., if there is a null value, treat it like a zero). Prompt the AI to explain the steps taken with the data to create the output requested and to share any inconsistencies, risks, or issues with the data and how they have been resolved or attended to in the resulting product. If any of the explanations are not clear or do not make sense, prompt the AI to alter the approach it takes. If the request is rerun, prompt the AI to call out the specific changes in each iteration from the prior version(s). Remember to at least spot check the data against the source data to ensure accuracy. Ensure responsible use of AI by referring to the Considerations for AI Use section of this playbook.

Actionable Analysis & Logic

Is your system set up to automatically flag students who are missing required courses or are otherwise off course for graduation?

Workaround Option 1:
If there is no district-provided graduation tracker, export accumulated course credits into Excel (and, if possible, credits by subject and/or core vs. elective classes) for each student. Include credits required and calculate the difference. Export any other aggregate graduation-related data available (e.g., physical education requirements, required assessments) and merge the data into the spreadsheet with credits accumulated. Sort by accumulated credits and student’s grade. Focus first on students who do not have the expected number of credits.
Workaround Option 2:
If graduation-related data is tracked (e.g., student profiles contain data such as “credits remaining” or specific courses needed), but there are no summary views or reports, export the data (by value, if there is no multi-variable table available) into an analytics and reporting tool. Sort by accumulated credits and student’s grade. Focus first on students who do not have the expected number of credits.
AI-enabled workaround:
If graduation-related data is available but in different systems (e.g., course credits are in one systems and state assessment data in another), export the data system-by-system into an analytics and reporting tool. Sort by accumulated credits and student’s grade. Focus first on students who do not have the expected number of credits. If the district has a closed and secure AI tool and allows the upload of student identifying information and data, export the raw data and prompt the AI tool to visibly flag (e.g., add colors) or add a column to capture the specific issues that need to be identified and resolved. Consider including instructions for how outlier data values should be treated (e.g., if there is a null value, treat it like a zero). Prompt the AI to explain the steps taken with the data to produce the output requested and to share any inconsistencies, risks, or issues with the data and how they have been resolved or attended to in the resulting report. If any of the explanations are not clear or do not make sense, prompt the AI to alter the approach it takes to flagging the data. If the report is rerun, prompt the AI to call out the specific changes in each iteration from the prior version(s). Remember to at least spot check the data against the source data to ensure accuracy. Ensure responsible use of AI by referring to the Considerations for AI Use section of this playbook

Responsive Communication & Alerts

Is your system set up to incorporate reminders for staff to follow up on missing data for gradebooks, rostering students, and student profiles?

Questions for Provider:

Does the platform provide push notifications to automatically send emails or reminders if data entry fields remain empty after a set number of days?
Does the platform enable staggered reminders for upcoming deadlines?
How does the platform handle data that has not yet been verified by staff? For example, does the system block teachers from entering course grades before entering assignment completion and scores?

Questions for District:

Is it possible to create a district data deadline calendar that syncs with our calendars?
Does our system support an automatic verification process for staff to validate that their entered data is accurate and complete?
Does our SIS support workflow escalation to alert appropriate staff when data entry/update deadlines have been missed?

Intuitive Insights & Dashboards

Is your system set up to provide role-based access to student profiles that aggregate holistic indicators, incorporate intervention assignments, and enable sophisticated filtering?

Workaround Option 1:
If the system has limited users and gives student profile access to administrators only, an administrator will need to run a report that captures current indicator data and intervention assignments (if available) and export it into Excel or a similar tool. A second report will need to be created (or exported, if it already exists) to match students to an adult who is part of the student success team. The second report can have any data that is useful, but must include the student success team member, student ID, student name, and student grade. It is critical that every student in the school be included in the second report and that the educators they are assigned to have permission to see their data (according to district policies). Use VLOOKUP to map this data together using the student ID. Use a macro (or sort by educator and copy/paste) to split the primary file into different spreadsheets by student success team member. Store the separate files securely; do not email the files. Note: this process will need to happen at several key points during the year.
Workaround Option 2:
If the student success team has access to the system, but only administrators and counselors can see student profiles, review the system FAQs and help materials to understand how to create and share reports or dashboards. If the administrator can create custom reports, start by creating custom groups of students and assigning them to specific student success team members (with appropriate permission to view data for those students). Then, create a dashboard or view with the highest priority indicator data for each of the groups. Finally, assign each student success team member access to the dashboard or view with their assigned students.
AI-enabled workaround:
If student success team members have access to student profiles with indicator data in one system and intervention assignments in a different system, they will need to merge the two in Excel or a separate analytics platfrom. Each team member should start by exporting intervention assignments by student; this file must contain student ID. Next, team members should export key profile/indicator data (again, including Student ID). Use VLOOKUP to map the data together by student ID. Filter out any students that do not have interventions. The file will need to be stored securely and updated intermittently when new interventions are assigned and/or there are changes to the highest priority predictive indicator data. If the district has a closed and secure AI tool and allows the upload of student identifying information and data, the AI tool may be used to pull the data from multiple systems together. Be sure to spot check the data for accuracy. Enure responsible use of AI by referring to the Considerations for AI Use section of this playbook

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