Community College Finance Simulator User Guide

Project Overview

Texas 2036 has developed an online, public community college finance simulator that will allow Texas to identify how funding to two-year community colleges are allocated and what the impacts of potential changes to current policies might be. The development of this tool coincides with the convening of the state’s Commission on Community College Finance, as established by 87(R) Senate Bill 1230. 

This tool is intended to support the Texas Commission on Community College Finance, Texas community colleges, and other stakeholders in investigating policy solutions that strengthen and sustain the state’s community college finance system while highlighting the importance of students’ outcomes. As the Commission’s discussions unfold, Texas 2036 aims to be able to be responsive to any policy adjustments discussed, and rapidly offer insight on potential financial impacts.

Simulator Tool Capabilities

The capabilities of the current version include:

  • Displays that include all funding sources—state appropriations, tuition and fee revenues*, and local tax dollars—for Texas community colleges in static and trend formats including statewide totals and individual institutional data. All current elements include these capabilities unless otherwise noted.
  • Modeling of the existing Texas community college finance formula—Core Operations, Success Points, and Contact Hours.
  • Changing the total amount of state appropriations for community colleges within existing legal and budgetary structures.
  • Changing formula components for Core Operations, Success Points and Contact Hours.
  • Two additional models that each introduce new concepts to the Texas community college finance system, including weights for Economically and Academically Disadvantaged students and the incorporation of a Local Expected Contribution, among other new concepts.

*Tuition and fee revenues are inclusive of state and local tuition waivers described in the Texas Education Code.

Navigating the Tool

The newest version of the simulator allows users to create simulations using three different models for our state’s community college finance system. All three have the same data displays and many of the same functionalities, albeit with some important differences. This guide will first focus on the elements of the simulator that are consistent across all three models, before discussing each model’s key differences and their uses below. 

State Budget Information

At the top of the simulator tool page, you can see the “bottom line,” or how any adjustments made to the state’s funding formula impacts the state budget for FY 2022. 

  • State Budget: The first figure (set to $916,653,595 by default), is the total annual amount of state funding provided to community colleges. 
    • Users can adjust the budget up and down by whole percentages by clicking the up and down arrows to the right of the state budget amount. Users can see how increasing or decreasing this amount impacts the state deficit or surplus.
  • Formula Cost: After making modifications to the formula, users can see the impact on the overall cost of the state funding formula in the middle figure (more information is below on how to make these adjustments and see their impacts). 
  • Deficit/Surplus: On the right, users can see how adjustments to the various components of the funding formula compare to the set state budget amount.

Formula Inputs

The formula inputs include the primary ways a user can modify community college funding appropriated by the state. Each model contains different inputs, which are explained in each model’s description.

Formula Output Visualizations

After adjustments are made to the Formula Inputs, users can see how that impacts individual college districts, and compare across districts, using three visualizations in the middle of the simulator tool: a scatterplot, map, and pie chart. 

Users can delete figures by clicking the three dots (𝌀) in the upper right corner of the visualization they wish to delete. Click “Delete Figure” to remove the visualization from the screen. Users can customize the visualizations they would like on the screen by clicking on the plus sign button to create a new figure. Click this button to add another data visualization. Select “Statewide” to add a scatterplot, bar graph, or map, or “District” to add a pie chart or stacked bar chart graphic.

On devices with smaller screens, such as tablets, users may only see a scatterplot and map, with a plus sign button on the right to create a new figure. Click this button to add a third data visualization and follow the same steps for customizing the visualizations on the screen.


  • The scatterplot graph allows users to show the relationship across college districts between two data sets in the tool, with an array of data from which to choose, including different sources of revenue, enrollment, and different components of the state funding formula.
  • Click the three dots (𝌀) in the upper right corner of the visualization to choose variables to show on both the x- and y-axes, categorize the districts by size and region, and have the size of the bubbles on the graph align with district size. 
  • Mouse over the bubbles to see the corresponding name of the district and its data for each of the selected axes. 


  • The map visualization allows users to see the same indicators/variables as the scatterplot, reflected so that each college district’s location in Texas is aligned with their service area. 
  • Click the three dots (𝌀) in the upper right corner of the visualization to choose variables to be reflected for each college district relative to where their service area is located in Texas, choose the desired scale (Quantiles = Equal number of districts assigned to each grouping; Quantize = Equal data intervals between minimum and maximum data points), and select the number of divisions for the selected scale.
  • Mouse over each college district to see the corresponding name of the district and its data for the selected variable.

Pie Chart

  • The pie chart shows the amounts of revenue at individual college districts for each component of the “three-legged stool” for revenue: state funding, tuition and fees, and ad valorem taxes.  
  • Click the three dots (𝌀) in the upper right corner of the visualization to choose individual districts to view and switch between projected revenue and FY 2022 revenue.

Bar graph

  • The bar graph visualization allows users to see the same indicators/variables for each campus as the scatterplot, where the height of the bar correlates to the variable selected for the y-axis, and the data sorts by the variable selected for the x-axis.  
  • Click the three dots (𝌀) in the upper right corner of the visualization to choose variables to show on both the x- and y-axes and categorize the districts by size and region.
  • Mouse over the bars to see the corresponding name of the district and its data for each of the selected axes. 

Stacked Bar Chart

  • The stacked bar chart visualization allows users to see an individual college district’s property tax information compared to state averages. Available variables include district tax rates and total property tax revenues. Both the rates and revenues are separated into the two types of property taxes that can be levied by a community college district: Maintenance & Operations, which pays for operating costs, and Interesting & Sinking, which pays for capital costs.
  • Click the three dots (𝌀) in the upper right corner of the visualization to choose which variable to represent on the stacked bar charts.
  • The user has the ability to include information on each community college district’s “cap space”, which compares a district’s current tax rate or property tax revenues compared to the maximum tax rate, or cap, that a district is statutorily authorized to adopt.

Data Table

At the bottom of the simulator tool page, users can clearly see both how the current funding formula as well as any modifications impact individual schools according to all indicators available in the tool using the data table at the bottom. 

Users can select and group which indicators they would like to review by selecting them in the dropdown box, and then deselecting them by clicking the “x” next to each indicator in the dropdown box. Users can see the indicators for individual districts by selecting them in the “Filter By District” dropdown, and then deselecting them by clicking the “x” next to each district’s name in the dropdown box. Indicators available in the data table mirror those available to view in the visualizations above.

Download and Additional Resources

At the top of the screen, there are three buttons for users to access and download resources related to the tool:

  • Download allows users to download the data as currently seen on the tool for each college district in a .csv file format. In other words, any modifications made to the formula will appear for each district in the downloaded data. 
  • Sources points users to links to all publicly available data sources used in the tool.
  • Help provides a brief set of user instructions for navigating the tool. 

On smaller monitors or tablets, these buttons may appear as icons: a downward arrow for Download, a book for Sources, and question mark for Help.

Model 1 Description – Current Formula

Model 1 represents the current formula used by the Texas legislature to distribute state funds to community colleges. The funding is divided into three main segments:

Contact Hour funding is designed to aid each district based on the relative cost of providing educational services. Classes are divided across 26 different educational disciplines, and a cost study is conducted each biennium to determine the median cost of one “contact hour” in each discipline. The number of contact hours are counted for each school and then multiplied by the relevant average cost. The legislature does not fund the entire amount because the cost study is inclusive of all funding, including tuition and tax revenue. Instead, it sets the state’s portion using a rate that serves as a percentage of the total cost, based on available funds.

Success Points funding functions as an incentive to schools to emphasize movement toward certain metrics of student success. Examples include graduating students in critical fields, success in developmental education, and transfers to four-year institutions.  There are currently a total of 11 student success metrics. A weight is given to each success metric, based on the state’s priorities.  In Model 1, only the weights applied to each success metric can be modified. Modifications to the weights for each success point metric allows for simulations where available funding is reallocated to each community college based on their existing levels of student success. This is because the Success Points formula is based on available funds. The Success Points Rate determines the amount allocated to each school based on their count of success points. That rate changes automatically when weights of success metrics are changed to ensure that allocations stay within available funds.

Core Operations funding is intended to help each college cover basic operating costs in addition to the instruction and administration costs covered by the Contact Hours formula. The state does not account for a district’s characteristics, such as a district’s geographic location or size, to determine the amount of Core Operations funding for each district. Instead, the state sets a flat dollar amount, which is usually around $1 million per district for a biennium, to ensure an equal distribution for each district. 

Model 1 Formula Inputs

In Model 1, the primary way to make modifications to community college funding is by modifying the three components of the state’s existing funding formula: Contact Hours, Success Points, and Core Funding

  • Success Points: Users can adjust the amount provided to college districts for achieving certain outcomes under the Success Points formula. Users are able to adjust the weight for each of the 11 individual Success Point metrics. More information about Success Points is available here.
  • Contact Hours: The overall contact hours accumulated by community colleges are funded at varying percentages measured against total costs for those contact hours. Users can adjust this percentage, which is set at .2019 (20.19%) by default. More information about Contact Hours is available here.
  • Core Funding: The Texas Legislature provides all 50 campuses with a flat dollar appropriation through the Core Funding formula. Users can adjust this amount, which is set at $680,406 by default.

Click the “Refresh” button to revert any modifications back to the defaults. 

Model 2 Description – Weights and Incentive Adjustments

Model 2 has the same general structure as Model 1, with additional variable adjustments available to users. The three categories remain the same:

Academic Disadvantage and Economic Disadvantage weights have been added to both the Contact Hours and Success Points formulas. Academic disadvantage is defined as the percentage of students identified as not being college ready in reading, writing, or math, based on students’ scores measured by the Texas Success Initiative Assessment or another comparable assessment. Economic disadvantage is defined as the percentage of students receiving a federal Pell Grant. Within this tool, contact hour and success point calculations are completed before academic or economic disadvantage weights are included due to data limitation issues. Once each formula’s allocations are calculated, the relevant weight set by the user is multiplied against the formula within which the user set the weight (a weight set within the contact hours dropdown is only multiplied by the contact hours allocation amount, for example), and then multiplied by the relative percentage of students in that weight’s demographic.

Success Points also work differently within Model 2. Model 1 is meant to simulate the allocation of dollars through the Success Points formula limited only to available funding. This demonstrates a process where a budget allocation is determined before the Success Points Rate is set. Model 2 incorporates weights based on Academic Disadvantage and Economic Disadvantage. In addition, available funding is no longer defined. This allows the user to change both the Success Points Rate and the weight for each of the state’s 11 student success metrics. In comparison to Model 1, this demonstrates a process where the budget allocation for the Success Points formula is determined after the Success Points Rate and the success metrics are set.

Model 2 Formula Inputs

All modifications possible in Model 1 are available in Model 2. There are two additional variables.

First, the Success Points Rate in the Success Points formula can now be adjusted.

Second, users can include weights for Academically and Economically Disadvantaged Students

  • For both the Contact Hours and Success Points formulas, users are able to set a weight for Academically and/or Economically Disadvantaged students. Academically Disadvantaged Students are defined as “students without an exemption to the Texas Success Initiative Assessment (TSIA) and not meeting college readiness standards as measured by TSIA mathematics, reading, and writing assessments.” Economically Disadvantaged Students are defined as “students receiving a Federal Pell Grant.” 
    • Each individual college district has a designated percentage of Academically and Disadvantaged students served, which are calculated by dividing the number of credit hours taken by the respective student population by the total number of credit hours taken at each college district. 
    • The Contact Hours and/or Success Points appropriation for Academically and/or Economically Disadvantaged students is calculated by taking the total revenue from the chosen formula for a college district and multiplying it by that district’s respective percentage of Academically or Economically Disadvantaged students served, the product of which is then multiplied by the user’s desired weight for Academically or Economically Disadvantaged students. The final product is added to the total revenue from the chosen formula before the weight is applied. 
      • For example, for a district with Contact Hours revenue totalling $10 million and a 10% Economically Disadvantaged student population, assigning a 25% weight to Economically Disadvantaged students in the Contact Hour formula would result in the following calculation: 

$10 million Contact Hours revenue x 10% Economically Disadvantaged student population x 25% Economically Disadvantaged student weight = $250,000 additional Contact Hours revenue for economically disadvantaged students. The $250,000 is then added to the $10 million in Contact Hours revenue, bringing the district’s total Contact Hours revenue to $10.25 million. 

Model 3 Description – Operations with Local Contribution

Model 3 has a fundamentally different structure from Models 1 and 2, though it is important to note that additional functionalities remain to be developed over time. The prior models allocate funding based solely on state priorities and available funds without adjustments for a district’s own revenue-raising capacity. Model 3 first estimates district operating need, provides a user with the option to subtract from that need based on a district’s taxing capacity and tuition estimates to determine state aid for operating costs, and then allocates incentive funding:

The Operations Formula estimates the total funding necessary, regardless of revenue source, to meet a district’s instructional and administrative operating costs. To achieve this goal, the calculation begins with the annual cost study administered by THECB and adapted for the Contact Hours formula. The user has the option to accept the cost study results as they are (Total Operations) or decrease the total by a set percentage (Partial Operations) by adjusting the Formula Type dropdown. Demographic weights are then applied to estimate the additional costs associated with educating students with additional needs. These students are identified as either academically or economically disadvantaged using the same definitions as those in Model 2. The result is a full estimate of district operating needs. This will be the base used to identify the state’s portion of funding for operations costs.

Revenues from Property Taxes and Tuition are components of a district’s potential Local Expected Contribution. This is the amount of money that a district is estimated to be able to provide for its own operations costs. Should a user choose to designate one, the Local Expected Contribution is subtracted from the base Operations Funding amount because the base includes operating costs that are being paid for by other revenue sources, including Property Tax and Tuition revenues, in addition to state funding. 

Districts are restricted from raising more than $1 per $100 in taxable property within a given district (Texas Education Code, Sec. 130.122), and no district is raising more than $0.40 based on the most recently available data. Within the Property Taxes dropdown, the user can set a contribution percentage, which is a proportion of the total tax rate allowed by state law. To ensure accuracy of simulations, this tool is designed to allow the user to modify only the state’s financing mechanisms for community colleges. The user will be limited from raising the contribution percentage higher than 5% to avoid setting a Local Expected Contribution where any district may have to raise their local tax rate to meet the Local Expected Contribution. 

To adjust tuition expectations within the Tuition dropdown, the user can choose to set a dollar per credit hour amount or use an estimate based on tuition raised in the prior year. Regardless of which option is chosen, the user also has the option to set a tuition cap, defined as a percentage of the district’s base Operations Formula. This introduces a limit on how much of a district’s full operating costs can be met through tuition and fees charged to its students.  

The total Local Expected Contribution is completed by adding the calculated expectations from Property Taxes and Tuition. It is then subtracted from the base calculated through the Operations Funding formula. The result represents how much of the base Operations Funding formula will be met by state appropriations.  

The Incentive Funding formula awards state funding to community colleges achieving outcomes based on student success metrics set by the state. The model  allows the user to set a rate that will serve as a multiplier for the amount of points a district earns through student success metrics set by the state. The model currently relies on three student success metrics that already exist in the state’s Success Points formula: successful transfer up to a four-year higher education institution; credential completion, including associate degrees; and credential completion in priority fields of study based on existing Critical Fields designated by the state. The model uses points earned by community colleges in each of those three success metrics, as used to determine Success Point allocations for the 2022-2023 Texas state budget. The user may choose to increase or decrease the assumed points earned using the Points Earned slider to simulate the costs associated with higher or lower student outcomes.

Model 3 Formula Inputs

In Model 3, there are no preset decisions within the formulas. Users must make decisions in each of the formulas before the tool will have a complete simulation. There are three formula components for users to address: Operations Formula, the Local Expected Contribution via Property Taxes and Tuition, and Incentive Funding. The Operations Formula determines the base of operations costs that the state will fund.  If users choose to incorporate a Local Expected Contribution to be subtracted from the base determined by the Operations Formula, the Property Taxes and Tuition dropdowns determine the amount of that local contribution. The Incentive Funding formula determines how much additional funding the state will contribute incentivizing schools to meet certain metrics of student success.

  • Operations Formula: Users can adjust how much of districts’ operations costs related to instruction and administration will be accounted for by the state formula. Under the Formula Type dropdown, users can choose to fund a select portion of districts’ operations costs under the Partial Operations option or to assume that all operations costs will be accounted for under the Total Operations option. For Partial Operations, the slider allows the user to set a percentage of how much of districts’ operations costs will be used by the state in its formula. Users can also manually add a weight for Economically Disadvantaged and Academically Disadvantaged students.
  • Property Taxes: Users can incorporate a Local Expected Contribution using each district’s taxable property by switching the Ad Valorem Local Contribution toggle to On. This populates a Contribution Percentage slider, which users can adjust up to 5%. 
  • Tuition: In addition to Property Taxes, users can incorporate each district’s tuition revenues into calculating a Local Expected Contribution by switching the Tuition Local Contribution toggle to On. Under Tuition Measure, users can choose to calculate the Tuition portion of the Local Expected Contribution through two options: using Cost per Credit Hour which users can designate by assigning a dollar cost per credit hour, or using Percent of Prior Year which users can designate via the accompanying slider setting a percentage. Users can leverage the separate Tuition Cap slider to designate a cap on how much of districts’ operations costs can be met by tuition revenues.
  • Incentive Funding: Users can insert a dollar amount in the Dollars per Point box, which will serve as a rate that will be multiplied by the amount of points earned by each district. The points earned are weighted based on the same respective weights that the state set for each of the three (transfer, completion, and critical field completion) student success metrics for FY 2022-2023. Through the Points Earned slider, users can set a percentage designating how much of districts’ past points earned is assumed by the model.