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
eduCLIMBER uses Ordinary Least Squares Regression (OLSR) to calculate the likely future trend of a student’s progress over time. OLSR is a well-established method for predicting future performance based on an individual’s prior performance. OLSR calculates the line of best fit through existing data points and then extends it to future dates. While many vendors use OLSR to predict future student performance, the limitation is that it is most accurate when 9 to 12 data points have been collected.
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
- 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.