The 50 million dollar lie

http://garyrubinstein.teachforus.org/2013/01/09/the-50-million-dollar-lie/

by ColinWright • 13 years ago

149 152 13 years ago

garyrubinstein.teachforus.org

kenjackson4• 13 years ago

This is a surprising blog post in that I draw the complete opposite conclusion the author does. The author seems to think that the averaging hides volatility (which it does), which leads to incorrect conclusions drawn. Whereas to me it looks like it removes visual noise to show an actual trend.

In his original scatter plot, because of the big ball in the middle it's easy to handwave and say, "look a random blob" -- but even a slightly longer look seems to indicate there is a positive correlation in the data. His averaging that he does at the end, IMO, makes it clear.

cryptoz• 13 years ago

I agree 100%. A scatter plot, with a low but very obvious correlation, shown for two years only seems to me to be absolutely fantastic evidence that progress is being made.

pfortuny2• 13 years ago

Yes, that is what the people at Lehman Brothers were saying about the Mortgage market for some years.

But anyway, each one is free to reach his own conclussions.

pdonis2• 13 years ago

You're missing the point. The author agreed that there is a slight positive correlation in the data. But the averaging makes it look like there is a strong positive correlation in the data, which there isn't.

In other words: without the averaging, you are seeing the full implications of the data: slight positive correlation, but a lot of scatter--i.e., not much meat there. With the averaging, you are seeing only the positive correlation, with all other information filtered out--i.e., you are seeing only part of the picture, and it's the part that, surprise, surprise, makes the person who ordered the data collected look good.

kenjackson4• 13 years ago

Huh? The averaging doesn't give you only the positive correlation. It simply averages it. If the correlation was negative, you'd see that just as plainly. Averaging doesn't change the trend -- it just removes the volatility from the graph and makes the graph more readable (what's the density at y=x? I suspect it's a lot denser than he'd have you believe, but you can't tell from the chart at all).

Sure, you could add a volatility measure as well, but the trend is clear -- you'd rather have your child by a teacher with a high teacher score than a low one. Or are you saying that over 12 years of schooling you don't think you'd have any preference having your child taught by teachers with a score in the lowest 5%ile versus a teacher with a predicted score in the top 5%ile? Of course there's some volatility, but over time, it's seems pretty obvious to me.

FourthProtocol2• 13 years ago

The other thing the author does is to derive absolute findings when the author himself admits to making an assumption about how the numbers were obtained. To me, using the word "lie" in the title is therefore nothing more than click-baiting.

And on a separate note - there's a lot of anti-Gates sentiment flying around lately. Whether his methods are the best or not, he's using his own money. I find it really difficult to give any criticism directed at Bill Gates' foundation any credence. And that not knowing much at all about what he does.

Maybe people would like Bill more if he did a Larry Ellison and bought a yacht instead.

zasz• 13 years ago

Bill Gates's position as a famous wealthy guy means he has more of a responsibility than the rest of us to not put out misleading graphs. Even if he is spreading misinformation with his own money.

Evbn5• 13 years ago

Many would argue that Bill came by that money via illegal and unethical behavior, paid for by millions of consumers, so it is more like tax money than his own money.

Evbn5• 13 years ago

Luxury taxes crimped the yacht industry and many workers. Fiscal conservatives would appreciate some support for the yacht industry.

jacalata• 13 years ago

People are arguing that he is using his own money to actively damage society. I'm not sure if I agree with that, but to say you can't criticize someone for what they do with their money is ridiculous - as an extreme, he could use his money to poison people, or to lobby for life sentences for marijuana use.

makomk• 13 years ago

There's a lot of distrust for any billionare meddling in the education system, and with good reason - they tend to push faddish ideas with questionable evidence, like this one, and somehow manage to convince the media they've "solved" the problems with the education system. Then the state wastes a whole bunch of money on the latest fad.

Also, that's probably why the headline calls it a "lie". This is something of a pattern.

sadfaceunread• 13 years ago

+1.

The blog author saying there is no clear trend in his random blob of points is misleading. The trend is there, it is just difficult to tell the density of points in his scatter plot because of the marker size and plot size.

Alex39173• 13 years ago

"Whereas to me it looks like it removes visual noise to show an actual trend."

Except for that in this case the noise is more important than the trend. Think about it, if you're firing or sanctioning perhaps 30%+ of teachers each year for no reason, then only complete morons would go into teaching.

It's the same as airport security, where a .1% false positive rate is unacceptable, whereas a 75% false negative rate is just fine.

jellicle3• 13 years ago

Currently the number of public school teachers fired or sanctioned per year is much less than 0.1%. Which is a bit different than 30%.

So I'm thinking they're not too worried about this.

ryanmolden• 13 years ago

Did you transpose false negative and false positive in your statement about airport security? I think airport security would much rather have false positive (i.e. This guy has something suspicious, let's do further checks, oh, turns out it was nothing) vs. False negatives (i.e. This guy is clean, oh, turns out he wasn't and blew up a plane).

feral• 13 years ago

I know nothing about the domain of teacher measurement, and have no opinion on it.

But the first chart in the blog post, with the big mass of blue on it, is surely not the strong evidence of weak correlation, that the author is making it out to be?

There could still be a strong correlation in that data, even if it looks like a blob of blue - because there are so many data points on that chart, that we can no longer tell where the density of points is. Its possible that there is a dense line of points in there that still gives a strong correlation, that we just can't see.

A heatmap with some level of binning, or a hex bin chart, or 2d histogram, would surely be more appropriate in these circumstances? Something like this: http://matplotlib.org/examples/pylab_examples/hexbin_demo.ht...

Maybe along with some direct math analysis of the correlation. Am I missing something?

drcode• 13 years ago

Exactly- It's pointless to counter a misleading graph with another misleading graph.

randomknowledge3• 13 years ago

Correlation means how well the points fit on the line. It is unfortunate that the author did not include a regression line or R^2 value but none the less one can tell there is no line which most of the points lie near. That data is absolutely not strongly correlated.

You seem to be confusing correlation and significance. Having lots of data points makes the correlation more significant, it does not make the correlation stronger.

streptomycin14• 13 years ago

one can tell there is no line which most of the points lie near

No, that's not correct. You can't conclude anything from looking at a big blob because you don't know the density of points at different places in the blob. This is the point the guy you replied to was making.

As an extreme example, imagine a billion data points that fit perfectly on a straight line. Then superimpose a million data points randomly on top of it. What does it look like? A big blob. But almost every point is highly correlated with that straight line.

cousin_it2• 13 years ago

It seems to me that the evidence of weak correlation isn't quite as weak as you imply :-) If there's a dense line in there, how come it's not sticking out of the blob even a little? Do actual phenomena often yield "deceptive" blobby scatterplots with dense lines hidden inside them? That seems apriori improbable to me, thus increasing the Bayesian probability that the blobby scatterplot is not a misleading picture after all. Though of course some more numbers would've been nice.

ak217• 13 years ago

>If there's a dense line in there, how come it's not sticking out of the blob even a little?

It is. If you look at the density in the upper right of the cloud, it is clearly clustered around the x=y line. The correlation may not be very strong, but without extra information about how strong of an effect would constitute clear evidence in favor of including the value add metric, we can't say anything more about it.

> Do actual phenomena often yield "deceptive" blobby scatterplots with dense lines hidden inside them?

Absolutely. You're looking at a misapplication of a plotting technique - a scatterplot with substantial overplotting. The author may be convinced that there's no correlation there, but by presenting this plot they provide no evidence in support of their point.

vy8vWJlco3• 13 years ago

A heatmap would be more revealing, but I'd eat my hat if it weren't a standard distribution (and I had a hat). It's nature (but hey, anything's possible). The scales are only slightly skewed, but we're not talking logarithms. The merit of the scales ("value-added") on the other hand, is very questionable.

But the relation, whatever it is describing, is pretty weak since the ellipse isn't very irregular (it's only "slightly" irregular). http://www.emeraldinsight.com/content_images/fig/08702801090... Think Kepler's laws.

Edit: The first post in the series shows a scatter of the direct (non-delta) scores, and it looks like San Fransisco in the morning: http://garyrubinstein.teachforus.org/2012/02/26/analyzing-re...

spikels7• 13 years ago

Clearly all the overlapping points in the first graph are obscuring most of what's going on. This is a warning flag that the author may be trying color the facts to suit their argument.

Not very clear what you are try to say:

(1) What "standard deviation"? Perhaps you mean the standard error of the correlation coefficient is large relative to the its estimated value. Given the large number of data points it is likely to be quite small. Another warning flag is the failure to report either the correlation coefficient or its standard error.

(2) What does "ellipse isn't irregular" mean? Given all the overlapping data points the shape of the plot is entirely driven outliers. To my eye this looks what you would get from plotting a bivariate normal distribution.

(3) Kepler? The linked graph? How is this helpful in understanding what's going on?

The first graph has a straightforward interpretation: you are making two imperfect measurements of each teacher's performance at two different times. There is noise in both measurements and teacher performance may have actually changed between measurements.

spikels7• 13 years ago

Sorry don't mean to belabor this point but I think "standard distribution" (changed from standard deviation) is still incorrect. "Standard" referers to standardized parameters (i.e. mean, variance) as in "standard normal" which has a mean of zero and variance of one (and standard deviation of one). Certainly not the case here. Maybe you mean "bivariate normal with positive correlation"?

http://en.wikipedia.org/wiki/Multivariate_normal_distributio...

Interesting thing is the (positive) means and variance seem similar which is consistent with underlying random variable being the same.

colanderman2• 13 years ago

Not to mention that he says "this is a number between -1 and +1" and the graph clearly has data points outside that range.

kevinalexbrown• 13 years ago

Edit: since ColinWright explicitly asked us to indicate experience with hard statistics: Check the link in my profile. I work with very messy data. I've also found that the more experience people have with something, the less confident they are about their expertise so I won't claim to be NotWrong, but the statistics here really aren't hard. It's linear regression with data that appears, cursorily, to be gaussian, close-ish to iid, etc. The question isn't "did Gary do the math wrong?" it's more "is he interpreting the data reasonably?"

I will make a strong claim: If doctor effectiveness were this stable, and it were the only data I had available, I would choose a doctor on this metric, ceteris paribus.

I found a scatterplot by the author that uses smaller marks so it looks a lot less blob-ish and more heat-map-ish:

http://garyrubinstein.teachforus.org/2012/02/26/analyzing-re...

I'm trying to track down the original data to verify this myself, but a couple of quick points:

There definitely seems to be good evidence of a relationship. It might be "weak" but that's not the same thing as "ineffective". Considering the number of data points, it makes it unlikely that the trend occurred by chance. This plot also makes it clear why the averaging made it look so pretty: the average in just about any percentile group in 08-09 matched 09-10 regardless of how finely it's divided (to a point).

It's certainly the case that there's a lot of "noise". The question is how to interpret it. One might conclude that there is a lot of "measurement noise" -- that teacher evaluations are inherently messy and rather uninformative except as a larger trend. There seems to be reasonable support for this! Students aren't the same, even from year to year. Of course it could "signal noise" - maybe teachers themselves change from year to year. Perhaps one year you're more motivated, the next your not, or vice versa.

To understand the implications of this noise, we also need to ask what we're using it for. For instance, if this were a plot of the correlation between money donated to Watsi and quality-of-life, you'd probably think you were doing pretty well! You might point out that a particular quality-of-life metric is flawed or noisy, or that the quality-of-life depends on lots of things besides health, but likely you'd be happy that you're clearly causing some benefit.

So when we ask whether the data suggest the viability of value-added measurements in aggregate, to me that seems to be a yes. But if we ask whether the data suggest using these measurements to make a decision on a per-teacher basis, that depends on the context of the alternatives! If this is the only thing we have to go by, perhaps it's not so bad.

I would love to see how stable the other parts of the teacher evaluation fit in. If you combine multiple noisy signals, you often get a much better picture of what's going on! This accounts for only 1/3 of the teacher's evaluation. I would like to think that if you appeared not to be a value-added teacher, but your principals and coworkers spoke highly of you, that you'd still get that raise.

Also, I'm looking forward to multiple years of this data - if your score accounts for 35 percent of the variance from one year to the next, multiple years might look a lot better. Perhaps in deciding teacher tenure, scores over 5-10 years could be really useful.

yummyfajitas19• 13 years ago

I'm really surprised to see Gary Rubinstein continuing to post bad graphs which obscure the data. 8 months ago I wrote a blog post about why you should avoid scatterplots, and used his graphs as examples of what not to do.

http://www.chrisstucchio.com/blog/2012/dont_use_scatterplots...

He is certainly aware of my post - he even commented on it and I offered him some constructive suggestions (such as adding alpha if he wants to use scatterplots).

I'm beginning to think that maybe his goal is to make VAM look bad, rather than to actually clarify and explain the data.

(I also left a comment on his blog expressing my concerns with his plot. Strangely, I seem to be hellbanned on his blog - the post is invisible when I view the post in an incognito window.)

patio11• 13 years ago

That is common for pre-moderated comments on blogs rather than evidence of hell banning, fwiw.

tmoertel4• 13 years ago

Important expectation-calibration note: I'm not making any claims about teacher performance, the usefulness of the value-added idea, or any lofty topics in general. I'm just trying to figure out how to recreate the first graph in the initial posting and get a closer look at the data behind it.

I grabbed the data set [1], loaded it into R, and tried to recreate the first graph in the original post. Observations:

1. The value-added scores are quantized so, as some people have suggested, it's hard to see the true density relationships in the original plot. There's a lot of overlapping data points.

2. I re-plotted the data using jittering to more accurately show the density distribution. I also added a GAM smoother to show the trend. Result: https://docs.google.com/file/d/0B2Tqdso8AsFNS3lWQTdPUGpHZlk/...

3. I also plotted the change in each teacher's value-added score from one year to the next. The resulting histogram: https://docs.google.com/file/d/0B2Tqdso8AsFNeUNiM3hHUGwzdlk/...

4. If we model the relationship as next_year_value_added = this_year_value_added + random_error, here's the fitted model:

    Call:
    lm(formula = va_0910 ~ va_0809, data = ds_cmp)

    Coefficients:
                Estimate Std. Error t value Pr(>|t|)    
    (Intercept) 0.009157   0.002315   3.956 7.67e-05 ***
    va_0809     0.820085   0.017646  46.475  < 2e-16 ***
    ---
    Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

    Residual standard error: 0.2153 on 8691 degrees of freedom
    Multiple R-squared: 0.1991,	Adjusted R-squared: 0.199 
    F-statistic:  2160 on 1 and 8691 DF,  p-value: < 2.2e-16

If you want to see exactly what I did, I threw my R code and the data sets up on GitHub: https://github.com/tmoertel/nyva-cursory

[1] http://www.ny1.com/content/top_stories/156599/now-available-...

DataWorker5• 13 years ago

One question would be whether or not to match the files on subject/grade/teacher, or just the teacher.

You use subject/grade/teacher level, but you get a different answer if you use aggregated teacher level.

ColinWright5• 13 years ago

I suspect there'll be a lot of differing opinions on this, and I'm looking forward to seeing the discussion. What would be helpful would be if people could say how much experience they have in hard statistics, and how much what they say is driven a priori from the data.

I know that hackers, in particular, have real problems with "Argument from Authority", but stats is one place where it's really, really easy to go wrong, so knowing how much formal training someone has can be an important indicator.

tmoertel4• 13 years ago

Do you have a convenient link to the data set you used to generate the first plot in your article?

ColinWright5• 13 years ago

I think you're making a mistake that I see over and over again here on HN. Not my data, not my article. I just submitted it here.

absherwin5• 13 years ago

I'll bite. I won't discuss my experience in my posts since I don't want to argue from authority but will do so below. But first, I should point out that you're committing a similar sin to that which is alleged in the article. What you really care about is the correctness of an argument. You hypothesize that formal training is an important indicator of correctness. Presumably there's also noise in that scatterplot but we don't even have it. Since it's the best thing available, you are choosing to rely on it.

As for my formal stats training: None beyond High School. That said, I've worked with and interviewed many with far more training. One thing, I learned is that most people don't have great intuition for statistical problems and it's not terribly highly correlated with years of schooling. I've met PhD's in economics and statistics who have made basic conceptual errors as well as those with less training who were more reliable.

So while training may be correlated with accuracy, you should still demand a well-reasoned argument and think critically about it.

ColinWright5• 13 years ago

I agree almost entirely. I'm specifically not asking for people to say "I'm a PhD in statistics, and here's the answer. Accept it because I know better than you." What I'm asking for a a complete and reasoned response, along with some evidence as to how much I should listen to you in the first place.

If you have no such evidence then the onus will be on you to make your argument more complete, more coherent, and more comprehensive. If you have evidence (note: evidence, not proof) then you can be a little less rigorous in what you say, and rely on people giving you the benefit of the doubt while they work through the argument.

What I see a lot of is long, apparently good arguments, that then turn out not to be as complete or coherent. they sometimes just don't hang together.

Significant amounts of formal study in a subject is evidence that someone might just have a better understanding. After spending a lot of time on the internet I'm tired of having to wade through every single argument in detail looking for all the possible chinks.

Maybe that's just impossible. Maybe every person has to redo every analysis for every argument. Seems like a complete waste of almost everyone's time. What about "Don't Repeat Yourself" or "Don't re-invent the wheel." I guess we are doomed to reinvent the wheel in every single discussion.

Evbn5• 13 years ago

Or you could ask people to put forth coherent mathematical arguments, since research has shown, for example, that most professional PhD-holding published medical research is statistically incorrect.

DigitalJack• 13 years ago

Could you put forth a coherent mathematical argument for your statement?

btilly2• 13 years ago

Statistics, like engineering, is done with numbers. When you attempt to do it without numbers, that's called "opinion".

I have not tried to look at the numbers. Here is my opinion.

My experience of school was that a small minority of teachers are truly excellent, and a small minority were horrible. The truly excellent ones are not distinguished so much by what happened in their class as by what happened in the following classes, and what classes they left people excited about taking. The terrible ones, by contrast, showed up as poor performance all around.

The described data set has a clear correlation. Whether or not the correlation is meaningful in individual cases is much less clear. My initial approach would be to try to fit a hierarchical Bayesian model to a data set, then use the resulting model to come back with predictions about individual teachers. Teachers whom, after several measurements, are overwhelmingly identified as terrible should be removed. If you find a population of teachers who show up as superstars, they should be subjected to further study to see if we can predict the quality of incoming teachers, and to see if we can learn lessons from them that improve other teachers.

However this is a well-studied problem. I'm sure someone has tried something like this. I am sure that there are a lot of vested interests. I have not attempted to evaluate work in this area, and I have no opinion on how good it is.

kenjackson4• 13 years ago

How much formal training does the author of the blog post have? From the short bio, it doesn't sound like much.

That said, my training -- read Friedman's intro text in high school (just freetime reading on my own -- so not formal per se). Two quarters of stats as an undergrad. Two quarters in grad school. All of which at least 15 years ago -- so mostly forgotten anyways. :-)

danso• 13 years ago

I see the OP's point, that visual noise can be filtered in such a way as to create a more compelling trend, and perhaps the filtering that Gates has done has simplified the results...so, OK. Let's not look at charts, let's look at actual calculations that have the various factors accounted for...what are they?

And I guess I'll throw in my two cents into the inevitable teachers-vs-data debate. I believe teachers may be too quick to toss aside performance analysis because they are so close to the personal stories and circumstances...no line chart can seem to account for the student who was improving greatly but then missed an insurmountable number of classtime due to problems at home.

Most humans are unwilling/unable to see their lives and work measured as averages and trend lines and deterministic outcomes, and I think teachers are acutely of this belief due to the nature of their work. And unfortunately, this blinds them to the possibility that while there is no cookie-cutter solution that always works, there are surely some measures/guidelines that often work, or at least mitigate even the most extreme circumstances. As it is, there's not much incentive or opportunity to see "the bigger picture" outside of what happens in one's own classroom year after year.

That said, this is not even close to being mainly the fault of the teachers. Among the other problems is that administrators are just as prone to shortsightedness, and "the numbers" can be wielded by a petty/mediocre principal/district officer to apply pressure to a teacher. It's no wonder that teachers are quick to distrust analyses, given the possibility that they're abused for political means.

So, essentially, it's a giant crapfest with no easy solutions. From the perspective of Gates' efforts, we can only hope that he pours in so much money and advocacy that there's eventually a shift towards best practices...though it's safe to say there will still be unintended consequences that aren't all favorable.

yummyfajitas19• 13 years ago

Among the other problems is that administrators are just as prone to shortsightedness, and "the numbers" can be wielded by a petty/mediocre principal/district officer to apply pressure to a teacher.

The more we rely on objective numbers, the less a good teacher has to fear from a bad principal. The principal has no ability to make the teacher's students do worse than their statistical predictor, after all.

On the other hand, many other popular metrics (e.g. principal's opinion/coworker's opinion) can easily be tweaked by a principal who wants to put pressure on a teacher.

keithwarren• 13 years ago

Typically when someone posts a baiting title like that I know not to trust them. Scholarship and evidence don't need hyperbolic headlines.

ColinWright5• 13 years ago

I think you are mistaken. In today's attention economy even the very best scholarship and the very best evidence-based conclusions will be completely ignored unless there is a hook to get people, preferably lots of people, to read it.

Even here on the allegedly rational Hacker News I've seen item after item sink without trace, whereas others with significantly fewer details and significantly worse evidence get voted up and read by thousands.

Alex Bellos recently passed on to me what his editor told him. It doesn't matter how good your article is, if no one reads it, or if no one gets to the point, it's no use and a waste of your time.

I'd like to think "Scholarship and evidence don't need hyperbolic headlines." Sadly, I think that scholarship and evidence say otherwise.

Evbn5• 13 years ago

When is HN alleged to be rational?

pfortuny2• 13 years ago

But being newsworthy does and this man wants to be newsworthy apart from trying to convey a message (which may be right, may be wrong, but he is not Bill Gates).

And really you would be amazed at the titles (and abstracts) of papers in journals of Pure Mathematics. Really. I've seen thing you people would't believe.

graeham2• 13 years ago

There are two problems with this article. First is that the "evidence" is from a scatter plot graph, with no statistical measurements attached to it. Stats really aren't something that you can rely on your eyes on. To me, it looks like a weak, positive correlation between previous year's score and current years score. The thing to look for is greater densities in the NE and SW quadrants than the NW and SE. Having a zero-mean "blob" in the data makes it tricky on the eye, but NE and SW points are the ones the model "correctly" predicts, while the NW and SE plots are the ones the models "gets wrong". I think the issue is the eye is looking for a line to process a slope of, but such data doesn't streach into a line. What it should look for is: "given a good score last year, is a good score given this year" or "given a bad score last year, is a bad score given again".

The second issue is that the author does not offer a better solution to the problem. Some information is almost always better than no informantion in decision making. Statistics in human-based samples are always tricky, and its tough to get strong correlations easily. As an aside, this is part of why clinical trials are so tricky and expensive.

(I am not a stats professional, but am a biomedical research scientist with some training in human-population based stats).

lancewiggs• 13 years ago

Exactly. Charts are useful for eyeballing, but only the use of proper statistical tools is valid for showing trends. Charts can easily be very misleading.

There seem to be a lot of comments about the charts on this page. Arguably basic statistics should be a part of every education - is that happening in the USA?

graeham2• 13 years ago

Can't comment on USA - in Canada we had an intro in high school then about a 1/2 course-credit module per year from second year until grad school in the engineering programs.

MarkMc2• 13 years ago

I don't know enough about statistics to judge the strength of Mr Rubinstein's critique, but I find this a little odd: The axes on his graph is a 'raw score' between -1 and 1, but the axes on the MET study graph is 'standard deviations'. Is that significant?

eli_awry• 13 years ago

He doesn't actually say what the positive correlation is, which I find disingenuous and suspicious. Because his scatterplot is so non-detailed, it's about as useful as the following scatterplot of SAT scores:

X|X

---

X|X

Where the axes are scores above and below 600 in math on the first and the second time taking the test. There are some individuals who do better or worse - but just because we can draw a detail-obfuscating graph of data doesn't mean there is no detail in the data, or no correlation, or that SAT scores won't help us predict future SAT scores. It just means we can draw a detail-obfuscating graph, and that there's not a perfect correlation.

One point the author does have is that these scores are not perfectly predictive, so bad performance one year shouldn't mean that the teacher gets i.e. fired. OK. He seems to be protesting using information to draw any conclusions at all. Perhaps it would be more effective to show what fallacious or irrational conclusions are being falsely drawn from this data and used to fire teachers, and then object to those specific instances of irrational actions. This value-added measure has not been shown to be intrinsically unreliable or wrongheaded but maybe some applications of it are.

ubasu• 13 years ago

This blog post linked to from the comments in the article explains the "ecological correlation fallacy"[1] being described in the article:

http://ed2worlds.blogspot.com/2013/01/gates-foundation-waste...

Key quote:

"...it has been known for more than 60 years now that correlating averages of groups grossly overstates the strength of the relationship between two variables"

Apparently, this was also used in the past to show high correlation between African-Americans and illiteracy.

[1] http://en.wikipedia.org/wiki/Ecological_fallacy

streptomycin14• 13 years ago

I'm surprised at the comments here. Seems that nearly everyone disagrees with the blog? Is Bill Gates such a saint among the HN crowd that we ignore statistics for him?

Also, see this blog for some more discussion along the same lines: http://ed2worlds.blogspot.com/2013/01/gates-foundation-waste...

Seems pretty clear that Gates' study presents the data in a very misleading manner to make a very weak correlation look like a very strong correlation.

ef4• 13 years ago

The blog post doesn't have any statistics to ignore.

Graphs are not statistics. Why doesn't he give us a correlation coefficient on his big blue blob graph?

streptomycin14• 13 years ago

You criticize a short blog post for something that is not done in the Gates publication. Do you have some bias, perhaps? Why does Gates not even give us a scatter plot, let alone a correlation coefficient? This is the critical point raised by the blog.

jhales• 13 years ago

Was thinking the same thing. I think it is: "...correlation coefficient of .35..."

Found it following the link: http://garyrubinstein.teachforus.org/2012/02/26/analyzing-re...

absherwin5• 13 years ago

Both sides are right but they seem to be concerned with different things.

Grouping data points does mask volatility. This doesn't make the effect any less real on the societal level. If we seek to improve student performance, skewing the pool of teachers towards the better ones will do that.

Yet there is also an enormous amount of volatility which is also real. Ideally we would just create better predictors. Constraining ourself for the moment to this set, since they have high error rates on the individual level, it's also reasonable to assert that in relying on this metric, we will make unfair decisions for many teachers.

The right solution depends on how much you value optimizing student outcomes vs. optimizing fairness as well as second order effects such as driving away teachers. My bias would be to use these scores for economic incentives to attempt to ensure that retention for the best teachers is higher than for the worst. Without additional work, termination likely isn't warranted based on this data.

To those who argue that pay differentials require better evidence, I would suggest comparing the validity of performance evaluations across any other job. It's imperfect but better for society than doing nothing.

For long-term fairness, it's important that there isn't a single value-added model. Competitive pressure can do wonders to improve model quality and it's also fairer since those who don't do well on one model can move to a different rubric.

IEatShortPeople2• 13 years ago

Even if Bill Gates isn't doing the best job, every time I see one of these articles, it appears that there isn't any advice on better ways to grade teachers. Did I miss that in the article? Are there a lot of other people in the field that are doing better work? (I would really like to read if anyone can provide links to papers to other ways of analyzing teachers)

crusso2• 13 years ago

Did I miss that in the article

The blog link to this thread is a propaganda site. It conspicuously doesn't reference any of the original materials that it is attempting (weakly) to refute.

There was an article on HN last week that referenced a more source material article about the project.

Here's the link to the METProject's web site: http://www.metproject.org/

IEatShortPeople2• 13 years ago

Thanks

jellicle3• 13 years ago

So if the teacher evaluation method is alleged to be inferior, please provide a new evaluation method which is superior to it.

Can't? Won't? Then be quiet.

itg• 13 years ago

The idea would be not to waste numerous resources and money implementing a broken idea and spend some time coming up with a better one. Why put the education of our children and the careers of good teachers on the line with such a poorly thought out and half-assed idea?

jellicle3• 13 years ago

If you think that no time has been spent coming up with this idea, you are coming very late to the party. This debate is decades old, at a minimum. Dates from 1971, says Wikipedia.

http://en.wikipedia.org/wiki/Value-added_modeling

It's not something that "Bill Gates" or anyone else made up yesterday. It's a state-of-the-art approach to a difficult problem. If you have a better way, let's hear it. Otherwise, be quiet.

supercanuck• 13 years ago

Perfect shouldn't be the enemy of good. Incremental change has its benefits.

apw• 13 years ago

In mathematics and logic, showing that a proposed proof is invalid does not require that you produce a valid proof.

In science, falsifying a theory does not require that you replace it with a better theory.

dropdownmenu• 13 years ago

The author's argument for this post is rather poor. He states that the raw data plot is noisy and weakly correlated, thus no relationship can be drawn by averaging the data into sets of buckets.

While the author is correct in that averaging hides the variance of data, he does not try to answer the question of "Can a trend be found from noisy data?" or show other accepted statistical methods that show no correlation in the data.

Instead the author dismisses the report from Gates through name calling: "It seems like the point of this ‘research’ is to simply ‘prove’ that Gates was right about what he expected to be true. "

absherwin5• 13 years ago

To build intuition, let's consider a hypothetical society. We divide a group of people in two. The first group rolls a die with 100 sides labeled from 1 to 100 in even increments. The second group rolls a die with labeled 1 to 110 in even increments. The roll determines their annual ability level which is unknowable. If you were hiring, which group would you prefer? Is it fair to the second group?

Note that this isn't strictly equivalent for several reasons. The game above the error is part of the generating process instead of the measurement process. Also the distribution is district rather than continuous. The key commonality is that a weak predictor at an individual level can be a meaningful predictor at a group level.

streptomycin14• 13 years ago

To provide a contrary hypothetical...

Imagine if one group had 55% of its dice labeled up to 110 and 45% up to 100, and the other group had the opposite. So if all you use for hiring is the group membership, you're going to very arbitrarily miss out on a lot of 110s and hire a lot of 100s. And now also imagine that this process of identifying who is in what group is ridiculously expensive.

absherwin5• 13 years ago

It's not contrary at all. It's the same point. The changing mix is merely a difference of degree. The key argument you raise is that discrimination has a cost. I don't have the numbers offhand to determine whether the cost of monitoring exceeds the benefit of higher quality education. Regardless, that's a different argument that should be backed by a different set of data.

WalterBright7• 13 years ago

There is no objective way to measure teacher performance. Any evaluation method that can be written as a list of rules can and will quickly be gamed.

The thing is, it's easy to find out who the best teachers are. Simply ask the students, parents, and staff. They all know who the good ones and the bad ones are - and that can't be gamed.

colanderman2• 13 years ago

Your claim makes no sense. If the evaluation method measures what we want teachers to do, then it, by definition, can't be "gamed": if the measurement is high, then the teacher is doing what we want.

Are you claiming that there's something special about teaching that makes teacher performance much more difficult, or even impossible, to quantify? If so, what is the point of teaching if one cannot measure results?

Your solution to "ask the students, parents, and staff" is precisely a measurement method (albeit a more qualitative than quantitative one), and moreover, one that can be gamed easily by anyone who's socially shrewd. Qualitative measures like that is exactly why we have so many crappy politicians.

Evbn5• 13 years ago

Do you have any such "evaluation method measures what we want teachers to do" in mind? Point is, no one has found one.

ColinWright5• 13 years ago

I'd like to ask - how do you measure programmer productivity?

WalterBright7• 13 years ago

You can't specify everything in the rules. For example, I know a case where management decided to hand out bonuses to the staff for minimizing inventory, because inventory costs money. The staff minimized inventory, all right, and got their bonuses. Meanwhile, the production line would regularly get halted because they'd run out of things like 5 cent resistors. It was a disaster.

The same company decided to rate programmers based on the bug list. A big chart was posted on the wall that showed the daily bug count. It wasn't a week before huge fights erupted over the bug count - over what was and was not a bug. The programmers quickly gamed it. They'd hide bugs, they'd refuse to fix one bug if that fix would produce some other minor bugs (e.g. if the bug was "feature X missing", then feature X is added, but had a couple issues with it, then X would not get fixed). They'd even add "bugs" blamed on other programmers and then "fix" them to get the credit.

Management gave up on that after two weeks and pulled the banner down.

WalterBright7• 13 years ago

I don't think it's so easy to manipulate a classroom full of students into thinking you're a great teacher when you're not. Remember, you're in front of them several hours a day, 5 days a week.

DataWorker5• 13 years ago

Which is why we have objective measures for programmers.

thedufer• 13 years ago

I'm confused as to why the "‘raw’ score (for value added, this is a number between -1 and +1)" goes up to ~1.6 in 2009-2010 and up to ~1.1 in 2008-2009. Why does the data go outside the ranges he states? I find it hard to believe someone who can't read something so simple off his own graph.

carbocation3• 13 years ago

The author incorrectly stated that "value added" is a score between -1 and +1. In fact, "value added" scores are z scores, which can in theory range from (-∞,∞).

keithpeter3• 13 years ago

"In New York City, the value-added score is actually not based on comparing the scores of a group of students from one year to the next, but on comparing the ‘predicted’ scores of a group of students to what those students actually get. The formula to generate this prediction is quite complicated, but the main piece of data it uses is the actual scores that the group of students got in the previous year."

http://garyrubinstein.teachforus.org/2012/03/06/analyzing-re...

Some qualitative comments (from the UK)

An experienced and resourceful teacher may be allocated more 'problem' students than a relatively new teacher as a matter of policy. Teaching students at the extremes of the ability range is harder than the median as the reasons for (say) severe under achievement can be very diverse (learning difficulties, home situation, undiagnosed medical issues - diabetes in my recent experience with one student - and so on) and each student may need a different approach.

I have taught in a few settings over the years. The best teaching happens in my experience in settings where people work together. Performance related pay based on dodgy statistics in an atmosphere of public ridicule does not seem the best way to encourage sharing of practice and teamwork!

"Good luck with that" as I believe the late Mr Jobbs used to say to competitors.

spikels7• 13 years ago

You are correct that if students were assigned in some biased manner it could invalidate any relationship between teacher quality and subsequent student performance.

That is exactly what makes this study interesting. All the students were assigned randomly! Much like in a randomized medical study this allows the establishment of a causal relationship.

keithpeter3• 13 years ago

"All the students were assigned randomly! Much like in a randomized medical study this allows the establishment of a causal relationship."

Two thoughts...

1) Ethics: You put some children with dyslexia or with challenging behaviour with newly trained teachers with little experience? Did their parents have any say in this? Was there an ethics process? Was there support available for newly trained teachers meeting major needs in their randomly allocated classes? Amazing.

2) Correlation does not imply a causal relationship. You need a theory. Theory in this area is not positivist, it is fuzzier.

As I said before, 'good luck with that'.

MarkMc2• 13 years ago

If you want to crunch the numbers yourself, here's the raw data: http://www.ny1.com/content/top_stories/156599/now-available-...

tokenadult• 13 years ago

More weekends than not, Colin shares here on HN an interesting link about education policy. I see from Colin's own top level comment that this one is shared for methodological discussion. I'm still mulling over what I think about this link after reading it, but I'm not sure I can agree that the Gates Foundation research group is engaged in a "lie" about anything. Education policy is the issue that drew me to participate on Hacker News,

http://news.ycombinator.com/item?id=4728123

and I'm glad to see that so many participants, from the founder on to the newest member, enjoy thinking about and checking facts on education issues.

There is other research on the issue of teacher quality and value-added measures to assess teacher quality,

http://hanushek.stanford.edu/publications/teacher-quality

and I encourage Hacker News participants to dig through some of the other publications to figure out what the best available current data show.

The other comments here suggest that the blog author of the submitted blog post is overstating his own case at least as much as he accuses the Gates Foundation supporters of overstating their case. If people who oppose the kind of teacher ratings proposed by the Gates Foundation really had courage of their convictions, they might try to let learners have full power to shop for teachers, on the grounds that teacher quality measures miss many dimensions of teacher performance that are important to individual learners. In fact, very few states even have as easy and time-proven a policy reform as statewide open enrollment (which my state has had for almost a generation now)

http://education.state.mn.us/MDE/StuSuc/EnrollChoice/index.h...

and no state yet lets learners shop for schools on an equal per-capita funding basis whether the school is state-operated or not (as the Netherlands has for more than a century). Teachers will have plenty of deserved professional respect and regard from their clients if their clients have power to shop. But if policy proposals for learner power to shop are rejected, hand in hand with rejecting proposals for evaluating teachers for their effectiveness in publicly subsidized instruction, I wonder what the true agenda is. What assurance do we (we parents, we taxpayers, we members of the general public) have that all schools are staffed with the best available teachers unless someone is checking on how the teachers are doing their work?

carbocation3• 13 years ago

I'm working on reproducing the graph with the data available from the NYT, but I'm not sure on one or two details of the author's method. If someone sees it, please let me know! Things I can't tell so far:

1) How is a "teacher" defined? Just(hash firstname lastname)? If so...

2) When a teacher teaches multiple subjects per year, which one is chosen? Or are they both represented, so that "teacher" actually means (hash firstname lastname subject)?

tmoertel4• 13 years ago

If you want to see how I recreated the OP's graph, just fork my GitHub repo. It has R code and the data sets, too:

https://github.com/tmoertel/nyva-cursory

Anyway, here are the variables I used to identify comparable observations:

    ## these variables identify comparable teacher observations
    id_vars <- c("subject", "grade", "dbn",
                 "teacher_name_first_1", "teacher_name_last_1")

So I used subject, grade, school (identified by dbn) and the teacher's first and last names.

carbocation3• 13 years ago

Nice, thanks for sharing. I used the same variables with the exception of dbn; my code is here https://gist.github.com/4652968 (I later started applying filters such as 4th-grade teachers only, etc., which is reflected in the gist.)

I was pretty curious how the author specifically munged his data, since then we could put to rest the speculation about the degree of correlation.

derpmaster• 13 years ago

This is the corporatist way. Everything is measured so it can be 'tweaked' by managers and technocrats because school is a business now.

Having a bad teacher to me doesn't matter when any kid can turn on his phone or laptop and watch free MIT lectures, free Stanford lectures, free Khanacademy lectures, free Android and iOS developer courses all over youtube, ect.

Gates obsession with teacher metrics would be better spent on building an entirely free university with worldwide standardized credits, so somebody in Pakistan can have their education credentials accepted should they start working overseas instead of being forced to drive a cab around Montreal while spending thousands to retake what he/she already learned.

crusso2• 13 years ago

Having a bad teacher to me doesn't matter when any kid can turn on his phone or laptop and watch free MIT lectures

Alternative self-study education is small compensation for having your child literally waste a school year in a teacher's class who has no clue how to keep control of the kids or desire to go over the material in class vs assigning everything for homework. In my daughter's case, her fourth grade teacher was too busy using that vaunted Internet access to check her facebook page.

Also, your "doesn't matter" argument would hold a lot more water if I didn't have to pay significant taxes to support such a lame public education system.

lifeisstillgood• 13 years ago

Isn't the point that before starting a measurement exercise one should have defined how one was going to interpret the results - and the whole is or is not successful if it meets its own success criteria

acslater00• 13 years ago

As far as I can tell, the author breaks the universe of teachers into 5% groups and then proceeds to show that the percentile groups are ordinally stable between these two years. In other words, the top scoring group in year 1 beat all other groups in year 2, and so forth, with perhaps some slight shuffling in the absolute middle of the distribution [hard to see on the graph].

This is supposed to be evidence that the correlation is weak??

saosebastiao• 13 years ago

Never trust anybody who tries to explain statistics using Excel.

bramcohen• 13 years ago

Looking at the correlation in students between year to year makes clear what's going on - http://garyrubinstein.teachforus.org/2012/03/06/analyzing-re...

There's such a high correlation between an individual student's score from one year to the next, and the number of data points is so small, that trying to tweeze out the teacher's contribution in a statistically meaningful way is fairly hopeless.

What I'd like to see are correlates with a teacher's own scores on the tests of the material they're supposed to be teaching (oh you think they all can get perfect scores easily? Hah!) and whether teachers banned from giving homework do any worse, and whether dumping the enforced curriculum in favor of letting students study at their own pace makes any difference. Given how little what the teachers actually do seems to make, it would be logical to at least dump the things which make school dull and unpleasant.

DataWorker5• 13 years ago

Using LOC to hire or fire programmers ignores important contextual factors, just as using test scores of students to hire or fire teachers ignores important contextual factors. What language is being used? How large is the project? Existing code? Platform? Bug count? Does the person contribute to the team in other ways?

In teacher evaluation you also have critically important contextual factors. What course is being taught? Are the students motivated? What's the classroom like? A lot of ELL kids in the class; does the teacher speak their language?

Many people see some amount of value in these imperfect metrics because they a) seek to measure the critical output (programmers are paid to make code and teachers are paid to make kids learn), and b) simple numeric metrics aren't biased by human fallibility. Popularity amongst peers won't have any impact on LOC or student test scores.

The author feels they shouldn't be used as 33% of the overall evaluation, which is the suggestion made by Gates.

In terms the specific points the author made about Gates' evidence in favor of their suggestion of 33%, I think he's basically right. I haven't read the original study and so I'm assuming for sake of discussion that he's conveying it correctly.

Over saturated scatterplots are not very useful, and in the hands of someone with no training or knowledge of basic statistics they may be dangerous, but they're not wrong. A trained consumer of research, seeing a plot like the author's first, will only be able to conclude that the correlation is not perfect. That rules out only a subset, and a subset that's fairly uncommon outside of the physical sciences, of the possible relationships between two variables. Not very useful, but not misleading unless there's an assumption that the number of data points is relatively small (which may be the case in some research contexts).

Averaging points and then taking the fake aggregated points and plotting those is wrong. It's using a tool to show variability in the wrong way. Averaging hides the variability that is supposed to be shown in a scatterplot. Why not average down to 2 points and draw the line then? Because that's wrong.

I'm thankful that one or two other people here understand, but a bit dismayed at the kneejerk groupthink.

The 50 million dollar lie

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