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Unless those tests are NOT measuring performance in a meaningful way. Once we assert that those tests are not measuring performance, the claim that performance

Unless those tests are NOT measuring performance in a meaningful way. Once we assert that those tests are not measuring performance, the claim that performance is "already being measured" is just wrong and we're back to square one.

sgc 8y ago
To add to this, they need not be wrong (and really should not be to make the argument), just significantly incomplete. From what I gathered from this thread, this was already agreed upon by everyone. So in the face of a known insufficiency of objective measures, and an identified correlation between a common statistic and some identified metrics, it is legitimate to use that correlating factor to help identify better performing school systems which include the as yet unidentified measures until better measurements can be objectively identified. But one must acknowledge at the same time this is not ideal, and much more effort should be made to understand the true nature of education beyond simple test or economic results, ie, in my opinion, a better understanding of philosophy and the nature of the human being, so that we can understand what truly embodies a good education. As a tangent, may all multiple choice tests die an eternal death. They have only one redeeming quality. They are easier to grade. And even that metric is dead for many subjects in today's world. One of their more unredeeming qualities is they hide ignorance and are just too easy. All you need is a minimum of a bullshit radar to get to a 50-50 chance of being right most of the time (so if you know 70%, you will probably score 85%). Another good chunk of it, that same radar is enough for 100% accuracy due to the ridiculous alternative choices. Hell, I got bored on my PSAT and got a Mensa invitation for my score because I (intuitively) picked up on a pattern in the answers and filled it in for the last 30-40% of the test.
- darawk 8y ago
  > So in the face of a known insufficiency of objective measures, and an identified correlation between a common statistic and some identified metrics, it is legitimate to use that correlating factor to help identify better performing school systems which include the as yet unidentified measures until better measurements can be objectively identified. How do you figure that? The correlating metric only explains the variance it correlates with. But we're already measuring that variance directly.
  - thrmsforbfast 8y ago
    > But we're already measuring that variance directly. >> To add to this, they need not be wrong (and really should not be to make the argument), just significantly incomplete. From what I gathered from this thread, this was already agreed upon by everyone. ...and... >>> Unless those tests are NOT measuring performance in a meaningful way. ...and... >>>> Otherwise, it's just weighing one questionable feature more than another questionable feature. ...and... >>>>(or something)>>> I think the fundamental thesis of the article -- that we can scientifically manage a system of universal education -- is fundamentally and impossibly flawed. Especially given the current state of assessments and the incentive structures built around them. And so on... So there's a general agreement that the current tests (and/or the social system they're embedded in) are extremely flawed and at least a contest over assertions about whether good enough tests event exist. Which is to say, for the fifth(?) time, the basic problem is that standardized tests are not doing even a remotely reasonable job at "measuring that variance directly". So pretending like they are legitimate metrics (and/or any more legitimate than other fairly broken metrics like funding levels) for measuring overall educational attainment is at best flawed and at worst -- I assert very likely! -- the very source of the whole problem with K12 in this country. On that note, I would like to close out this thread by imploring you to read the essay I linked to in my first post: https://www.maa.org/external_archive/devlin/LockhartsLament.pdf https://www.maa.org/external_archive/devlin/LockhartsLament....
    - darawk 8y ago
      You didn't respond to my point at all. There is a true signal, and there is the measured signal. We're measuring, obviously, the measured signal. It is, according to you, a weak proxy for the true signal. That is, it correlates with it at some level. Secondly, we have another variable 'spending'. We can measure that this 'spending' variable correlates with the measured variable. Therefore, we know that those two variables are related in some way. Now, in terms of getting a bead on the true signal, do we care about the spending variable? The only reason we have to believe it has any relationship to the true signal is that it correlates with the measured signal! If we didn't know the measured signal directly, that might be useful. But we do. What I am saying is this: The performance tests are the best we have. There is no additive value of this 'spending' variable, as far as anyone i'm aware of can tell. If you have information to the contrary, i'm curious to hear it, though. Now, you may, perhaps even rightly, that say that the performance tests we have are so bad that they're useless. Well, i'm not going to take a position on that. The position that i'm taking is that adding 'spending' to your model does not minimize your loss function here, and there is no reason to believe that it would.
darawk 8y ago
Please re-read what I said. I addressed this objection. Saying "performance isn't being measured well" is not a reason to look at spending.

sgc 8y ago

To add to this, they need not be wrong (and really should not be to make the argument), just significantly incomplete. From what I gathered from this thread, this was already agreed upon by everyone. So in the face of a known insufficiency of objective measures, and an identified correlation between a common statistic and some identified metrics, it is legitimate to use that correlating factor to help identify better performing school systems which include the as yet unidentified measures until better measurements can be objectively identified. But one must acknowledge at the same time this is not ideal, and much more effort should be made to understand the true nature of education beyond simple test or economic results, ie, in my opinion, a better understanding of philosophy and the nature of the human being, so that we can understand what truly embodies a good education. As a tangent, may all multiple choice tests die an eternal death. They have only one redeeming quality. They are easier to grade. And even that metric is dead for many subjects in today's world. One of their more unredeeming qualities is they hide ignorance and are just too easy. All you need is a minimum of a bullshit radar to get to a 50-50 chance of being right most of the time (so if you know 70%, you will probably score 85%). Another good chunk of it, that same radar is enough for 100% accuracy due to the ridiculous alternative choices. Hell, I got bored on my PSAT and got a Mensa invitation for my score because I (intuitively) picked up on a pattern in the answers and filled it in for the last 30-40% of the test.

darawk 8y ago
> So in the face of a known insufficiency of objective measures, and an identified correlation between a common statistic and some identified metrics, it is legitimate to use that correlating factor to help identify better performing school systems which include the as yet unidentified measures until better measurements can be objectively identified. How do you figure that? The correlating metric only explains the variance it correlates with. But we're already measuring that variance directly.
- thrmsforbfast 8y ago
  > But we're already measuring that variance directly. >> To add to this, they need not be wrong (and really should not be to make the argument), just significantly incomplete. From what I gathered from this thread, this was already agreed upon by everyone. ...and... >>> Unless those tests are NOT measuring performance in a meaningful way. ...and... >>>> Otherwise, it's just weighing one questionable feature more than another questionable feature. ...and... >>>>(or something)>>> I think the fundamental thesis of the article -- that we can scientifically manage a system of universal education -- is fundamentally and impossibly flawed. Especially given the current state of assessments and the incentive structures built around them. And so on... So there's a general agreement that the current tests (and/or the social system they're embedded in) are extremely flawed and at least a contest over assertions about whether good enough tests event exist. Which is to say, for the fifth(?) time, the basic problem is that standardized tests are not doing even a remotely reasonable job at "measuring that variance directly". So pretending like they are legitimate metrics (and/or any more legitimate than other fairly broken metrics like funding levels) for measuring overall educational attainment is at best flawed and at worst -- I assert very likely! -- the very source of the whole problem with K12 in this country. On that note, I would like to close out this thread by imploring you to read the essay I linked to in my first post: https://www.maa.org/external_archive/devlin/LockhartsLament.pdf https://www.maa.org/external_archive/devlin/LockhartsLament....
  - darawk 8y ago
    You didn't respond to my point at all. There is a true signal, and there is the measured signal. We're measuring, obviously, the measured signal. It is, according to you, a weak proxy for the true signal. That is, it correlates with it at some level. Secondly, we have another variable 'spending'. We can measure that this 'spending' variable correlates with the measured variable. Therefore, we know that those two variables are related in some way. Now, in terms of getting a bead on the true signal, do we care about the spending variable? The only reason we have to believe it has any relationship to the true signal is that it correlates with the measured signal! If we didn't know the measured signal directly, that might be useful. But we do. What I am saying is this: The performance tests are the best we have. There is no additive value of this 'spending' variable, as far as anyone i'm aware of can tell. If you have information to the contrary, i'm curious to hear it, though. Now, you may, perhaps even rightly, that say that the performance tests we have are so bad that they're useless. Well, i'm not going to take a position on that. The position that i'm taking is that adding 'spending' to your model does not minimize your loss function here, and there is no reason to believe that it would.

darawk 8y ago

Please re-read what I said. I addressed this objection. Saying "performance isn't being measured well" is not a reason to look at spending.