In the article I used below, there was a troubling paragraph….
The analysis doesn’t contain any information about a major chunk of schools that were in the first cohort. For instance, the summary data showing changes in math scores covers just 534 schools. But there were more than 730 schools in Cohort 1. According to the notes provided by the department, the missing schools had changes in state tests or other factors that excluded them from the analysis.
Notice the culling of 196 schools from the data….
Now remembering we are dealing with averages…. and possibilities….
We were given the premise that 66% of these schools showed gains and 33% showed declines…. On the used portion of 534 schools, that would break down into 176 declines and 358 gains…. Now let us factor the range by adding what these dropped off schools could have provided…
To reach a best case scenario, we must assume that ALL those left off showed gains as well; we would add the known 358 schools plus all the left-off 196 schools, and get ourselves a total of 554 schools out of all 730 or a success rate of 75%…
To reach the worst case scenario, we would do the opposite and add the 176 declines to the 196 of what are now assumed to be negative left-off schools, and have a negative total of 372 schools which show a 52% decline….
Human nature makes me tend to assume the latter scenario… Let me tell you why. If I had spent $3 billion of someone else’s money, and had to tell them how well I did?…. Well let’s just say I wouldn’t hide the data whose invisibility lowered by success rate from 75% down to 66%…. I would trumpet I was 75% successful… The investment was good!
On the other hand…. if I spent $3 billion of someone else’s money and had to tell them how well I did? … Well… if the original results came up 50-50 which is exactly where one starts any comparison before any data gets compiled, … I’d think I’d create a reason, any reason to discount data lowering the negatives to a level below that where I would get lynched.
Simple human nature then makes one question these results entirely. Did we really, just waste $3 billion dollars creating Common Core ?