Rebuttal Response 1

Rebuttal response 1
Name
Institution

Rebuttal Response 1
In most instances, the data that can be provided by program evaluators cannot be of right quality. The quality compromise could be due to some issues that were closely related to the quality of data presented. Oaks school data analysis on English Language Arts has been evaluated by two tests the CRCT and the milestone. At first, CRCT provided information rating the school correctly in the English language, but later Milestone performed experiments that gave contrary results. The information provided is contradicting and need some severe sort of evaluation to confirm the truth of the tests and give Oaks the real picture. The following is a discussion to respond to the data provided by Milestone and CRCT on the Oak’s school performance on the English language.
Completeness of the data
The database used by Milestone did not meet completeness measures since their data was consistent for over three years meaning hence the information was fooled (Henson, 2016. The data on current English performance could have been omitted hence bases in the computer programmes. The data provided by milestone did not give an accurate picture of the administrative data since the database was incomplete.
Data timing
The data that was made available to evaluators was not up to date and violate some of the historical data backgrounds.
An accurate representation of a program
There was a possibility that validity of the data on the Oaks programs was an abstract (Henson, 2016.

A different field was taken and assumed to represent the data of the Oaks school on language performance.
Consistency of data
Inconsistency in data sometimes does not represent a problem in the data, but probably it renders the information useless to some extent (Henson, 2016). The program was extensive, and hence the data was not sufficient for evaluators to give an actual performance of the programme.
In conclusion, data analysis by evaluators determines the outcome of a program where in most cases do not match the standards. Hence it is essential to use different models and tools to evaluate data to avoid biases.
 

Reference
Henson, H. (2016). Data quality evaluation for program evaluators. Canadian Journal of Program Evaluation, 21(1), 99–108. doi:10.3138/cjpe.261