Using Data for Teacher Incentive Allotment Success

When it comes to the Teacher Incentive Allotment (TIA), using data isn’t just a requirement; it’s the foundation of reliability, equity, and success. From teacher evaluations to student growth measures, the accuracy and integrity of your data directly impact funding, morale, and trust.

Whether you’re new to TIA or a veteran refining your system, it’s essential to ensure your data collection practices are strategic and sustainable. Learn the best practices to implement effective TIA data practices in this article.

Start with a Clear Data Plan

Before collecting a single data point, develop a comprehensive data collection plan. This plan should outline:

• What data will be collected (e.g., teacher observation scores, student growth metrics, eligible teachers)?
• Who is responsible for collecting, entering, and verifying data?
• When each dataset is due (see the TEA data timelines and calendar dates).
• Where will your district’s data be stored?
• How data will be stored, reviewed, and reported–be sure to download and review the TIA Data Submission Template file.

Ensure Inter-rater Reliability in Evaluations

Observation and appraisal data are critical for teacher designations. To ensure fairness:

• Create a district calendar for teacher observations and calibration sessions with administrators and appraisers.
• Use observation rubrics consistently across campuses and grade levels.
• Regularly review data and discuss for inconsistencies or outliers.

Select Growth Models That Fit Your Context

Districts should evaluate their current instructional programs and determine which student growth measure is the best fit (e.g., Value-Added-Models–VAM, pre/post assessments, portfolios, and Student Learning Objectives–SLOs). To make the best choice:

• Align the model to the curriculum and expect learning outcomes.
• Be flexible! While some models work better for the early grades, others may be better for tested subjects and electives.
• Plan a district calendar for student growth using assessments from the district’s application weighting tab (pre/post assessments, SLOs, and portfolios).

Once your growth model is in place, focus on maintaining clean, accurate data.

Prioritize Data Accuracy Over Speed

Inaccurate or incomplete data can derail your Teacher Incentive Allotment submission. Build in checkpoints to:

• Verify teacher eligibility.
• Review the weighting tab and the eligible teachers tab from the accepted TIA system application.
  • Validate student growth measures and rosters.
• Cross-check evaluation data against district systems.

Train, Train, and Train Again

Provide ongoing training for:

• Teachers, campus administrators, and appraisers.
• Data entry personnel.
• The District Lead and the TIA team should attend the TEA TIA sessions to stay updated and informed.

Conduct Internal Audits Before Submitting to TEA

Ask the following questions before conducting internal audits:

• Have all eligible teachers been counted?
• Are growth scores calculated correctly?
• Is the teacher’s information input correctly (correct spelling of first and last name, Service IDs/Course IDs, etc.)?
• Reach out to your education service center or cohort to review and analyze data prior to submission.

Create a Culture of Data Ownership

Make data a shared responsibility, not just a compliance task. Encourage campuses to:

• Reflect on their own data trends and growth.
• Determine/develop future professional learning needs based on data.
• Celebrate successful designations resulting from data integrity.
• Own both the wins and the lessons learned.

Conclusion

Data collection for TIA isn’t just about compliance. It’s about building a fair and effective system that recognizes great teaching. By implementing these best practices, you’ll not only ensure smoother TIA submissions but also foster a culture of trust and excellence across your district. Everyone is successful when data is done right!

To learn more about TIA, visit the ESC Region 13 website. See more articles about TIA on our blog.

Additional Resources:

1. Data Capture Year FAQs
2. Data Capture Year Timeline
3. Sample TIA Implementation Calendar