Here is an example of the kind of challenge faced by a district evaluating the effectiveness of a 4th grade teacher.
Districts often base teacher evaluations on a point system. In our example, we assume that the maximum teacher evaluation score is 1000 points. We then divide ranges of points into evaluation categories as follows:
- 750-1000 Highly Effective
- 500-750 Effective
- 250-500 Developing
- 000-250 Ineffective
Teachers earn their points based on the following criteria. The teacher rating scale (observation rubric) is worth 100 points. State test growth percentile is worth 100 points. ATI Galileo DL scores or other district determined student growth measures are also factored into the teacher score. In order to get the teacher rating, the administrator multiplies the total points the teacher earned on the rating scale by 5. Then the administrator adds up the state test growth percentiles in math, reading, and science. The administrator then computes the average DL score changes on all benchmarks and adds the DL score changes to the total score. The teacher is then rated based on predetermined categories listed above.
Ask yourself how long will it take the administrator to be able to evaluate, calculate, and determine the appropriate rating for all of the teachers being evaluated.
The answer to this question is likely to be a long time even in a relatively small district. ATI has a simple, efficient and accurate solution to this challenge. It is a score compiler. The compiler will take data from various sources and calculate a rating for each teacher. ATI enters staff rating scales including (evaluation rubrics) into Galileo. Administers then can electronically complete scoring observations online. For example, scoring may occur during a scheduled teacher observation. The results of the evaluation are calculated immediately and pulled into the compiler. State test data can be uploaded into Galileo and pulled into the compiler. Finally, ATI pre/posttest data provides information about whether each teacher and/or school has met expected growth, not met expected growth, or exceeded expected growth. This data is also retrieved and placed into the compiler. All of the information as well as any other required information (e.g., other assessment data, surveys, informal observation, school-wide data) is then compiled to provide a rating for each staff member without the administrator needing to complete any of the calculations.