Skew analysis is an essential component of the Teacher Incentive Allotment (TIA) validation process, ensuring that teacher designations are fairly and consistently applied across campuses and subjects. This session provides district leaders with the knowledge and tools to conduct skew analysis and use the findings to strengthen their local designation system.

Participants will:

• Define skew and understand its significance in TIA data validation.

• Review TEA requirements for skew checks and their implications for teacher designations.

• Analyze sample skew data and practice identifying patterns or discrepancies.

• Explore strategies to address skew through calibration, observation practices, and communication with stakeholders.

• Access ESC resources and supports to prepare districts for successful validation.

By the end of the session, participants will have a clear process for analyzing skew data, addressing potential concerns, and ensuring a fair and defensible TIA system.