## Understanding eduClimber Trends and FastBridge Projection Lines

The prediction lines seen in eduClimber and FastBridge progress monitoring graphs are calculated in different ways. These lines are intended to help educators predict future student performance on progress monitoring measures, thereby enabling them to make informed decisions regarding the next steps.

## eduCLIMBER Trend Line

The FastBridge trend line (also referred to as the Total Trend in PM reports) uses **Ordinary Least Squares Regression (OLSR)** to compute a line the fits the student’s progress monitoring scores. The line requires a minimum of 3 data points and is updated with each successive PM score. The line is extended to the goal date to provide an estimate of where the student will be by the goal date assuming her/his growth remains constant. Research shows that by around the 12^{th} week with at least 9 data points, the projected score based on the trend line is fairly accurate as long as the intervention remains the same.

Above is an example of an **eduCLIMBER** progress graph with a **trendline that extends beyond existing data points** to predict future performance. This line is shown in **blue**, and in this example, the line is predicting that the student will perform **above the goal line**, thus showing **on-track** performance.

## FAST Projection Line

**FastBridge uses Bayesian** analysis to calculate the FAST Projection Line that displays on progress graphs once a student has **six or more** **data points**. Bayesian analysis uses **conditional probability** from prior data trends as a way of predicting what data trend is likely for an individual student. By using prior data from large numbers of other students to predict future performance, the amount of time needed to calculate a trend line is shortened. In this way, future student performance can be accurately predicted after only **six weeks** of progress monitoring.

In FastBridge progress monitoring reports, the Bayesian analysis is referred to as the FAST Projection Line. Due to the necessity of a sufficient amount of prior data in order to calculate predicted scores, the FAST Projection Line is available for the most commonly-used progress monitoring measures, including:

- CBMmath Automaticity
- CBMreading English
- CBMreading Spanish
- earlyMath
- Decomposing DC-1
- Numeral Identification NI-1

- earlyReading English
- Decodable Words
- Letter Names
- Letter Sounds
- Nonsense Words
- Onset Sounds
- Word Segmenting
- Sight Words-150

## Progress Monitoring Reports with FAST Projection Line

Above is an example of a Progress Monitoring Report with the **FAST Projection Line** shown. In this example, there are **six data** points. The student’s **goal** is shown with a **dashed line**, and the student’s **trend** based on existing scores is shown with a **solid blue line**. The** FAST Projection Line** is shown as a **dotted line** that extends after the date of the last data point.

In this case, the **solid blue line** suggests that the student is **not on track** to reach the goal, but the **FAST Projection Line** indicates that the **student will reach the goal**. Using the FAST Projection Line, the teacher and team are able to decide to maintain the current intervention and continue to review the data to confirm that the student remains on track to reach the goal.