Belton ISD trustees reviewed a proposed Teacher Incentive Allotment (TIA) spending plan during their Nov. 17 meeting that would allocate 90% of earned allotment funding to teacher compensation and reserve 10% for district costs such as assessments, staffing to manage allotments and professional learning.

A district presenter explained the 90/10 model as a common approach in neighboring districts and provided examples showing how gross allotment amounts translate to take‑home pay once benefits and payroll deductions are considered. The presentation noted district obligations to include the employer cost of benefits in the compensation calculation and showed an example where $1,134,000 in generated allotment would yield a $113,400 district reserve under the 10% model. The district said the amount earmarked for individual teachers cannot exceed $5,000 and any remaining funds would be used for hiring stipends if not distributed.

On eligibility, the presenter said teachers must be reported in a designated teaching role in the winter PEIMS submission and remain in the classroom through the end of the school year to be eligible, with narrow exceptions such as mandatory military reassignment. The district explained TEA will compute allotments and notify districts; those notifications were described as expected in April 2027, with payouts to retiring designated teachers in May 2027 and other designated teachers in June 2027.

Trustees asked whether the district would be "locked in" to a chosen split; staff and trustees said state rules require a minimum of 90% to teacher compensation but the district could choose to increase (for example to 95%) though reducing below 90% is not allowed by the state. Several trustees emphasized the need for clear and early communication to teachers about expected payouts and cautioned that changing the allocation later could create morale issues.

The board asked about validation risk; staff said Belton ISD will work with data support partners to preview and validate files before submission and noted the data will be submitted to Texas Tech University in October 2026 with validation results expected back by January (year not specified in transcript).