<p>There must exist some such students, since some of them go to community college for a while, do well there, and then transfer to a good state university.</p>
<p>However, it is not necessarily the case that the state university would be able to know for those individual students from their high school records. Indeed, some such students did not become hard working until community college, sometimes after doing something else like military service between high school and community college (i.e. they were not ready to study at the college or university level right out of high school, but became committed students later).</p>
<p>Look, obviously, we’ll never know the counterfactual unless we devise a quantum engine to visit the other universe where we admitted that person and viewed just how hard-working he would be.</p>
<p>But the fact is, colleges reject plenty of people right now who might have been successful at that college had they not been rejected. Yet why aren’t my detractors concerned about them?</p>
<p>My stance is, given that the colleges have to reject somebody, they should do so based on the best statistically predictive model about future performance that they have. This is precisely the same calculus that insurance companies perform every day. Obviously no insurance company knows exactly when somebody is going to die or have a car accident or have their house struck by a hurricane. But they make statistical predictions based on when those events are likely to occur, and then charge you premiums - or reject your insurance application entirely - accordingly. A guy with numerous DWI’s and other serious moving violations and owns a sportscar isn’t easily going to find auto insurance. </p>
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<p>I have never advocated that we shut down the transfer admissions process. Schools could continue to admit transfer students…but again, based on a predictive statistical model. For example, A’s in community college creampuff classes may not be highly predictive of ability to graduate, but A’s in community college math/sci courses might be. Certain kinds of community college math courses might be more predictive than others. </p>
<p>Again, keep in mind that just as not all high school senior applicants are admitted, not all community college transfer applicants are admitted either. Indeed, many (usually most) are rejected. Since schools will need to reject plenty of applicants anyway, it should behoove them to do the best job of admitting the best ones that they can. </p>
<p>Obviously no system will ever be entirely perfect. Statistical models naturally have room for error. But it will surely be better than the current admissions system, which is clearly fraught with error. Even a 1% improvement in graduation rate would represent plenty of new graduates.</p>
<p>MisterK, no worries. I never meant to badger you. </p>
<p>The reason why I asked for evidence is because I would have then showed it to some of my colleagues, who would have then surely been surprised and intrigued. To our knowledge, any recent full-time hiring by Microsoft of non-graduates is far from usual. {We are not saying that it never happens, as it probably does, but we would just find it to be far from the norm.} </p>
<p>The fact is, Microsoft has aged to the point of becoming a mature and institutionalized company, with the employment policies of such a company. That should be unsurprising considering that Microsoft is pushing 40 years of age. Somebody without a college degree - such as a young Bill Gates - would (ironically) find it difficult to garner a job offer at Microsoft. Heck, (even more ironically), he would surely find it easier to garner an offer at a startup company who aims to disrupt Microsoft.</p>
<p>Yes, no doubt the chances for a nontraditional hire are best in a very small company or startup. In those environments, skills are all that matter, and it’s easy to part ways quickly if things aren’t working out. Some high school kids have amazing talents that can be put to use immediately, even if they’re not actually “computer science” talents.</p>
<p>Why aren’t colleges already doing this? They already rely almost entirely on grades and standardized test scores (those that place a substantial emphasis on other factors don’t have low graduation rates). Or do you really think that the type of sport someone plays is more predictive of college performance?</p>
<p>Probably because those rejected students will almost certainly apply to and get accepted at another college and thus still have the opportunity for education and success. You have been arguing on this and several other recent threads that applicants who appear to be unmotivated, or are even predicted by some model to be unmotivated, do not belong in college at all. That’s a huge difference. The former still leaves the college option open to the student. The latter does not.</p>
<p>I don’t know. Maybe, maybe not. That’s what the data could tell us. If the type of sport is not predictive, then the statistical model will surely tell us that it is not predictive. </p>
<p>But given that colleges * currently* use the type of sport that somebody plays as a factor in admissions, what’s so controversial about calculating whether that factor is correlated with graduation success? </p>
<p>Now, if you want to argue that colleges should currently not factor in the type of sports you play - or even whether any type of sports activity should play a role in admissions at all - then that’s your prerogative. But then you should be protesting the admissions policies that are currently in place. Again, given that colleges are already taking into account the type of sports you play in determining admissions decisions anyway, what’s so controversial about using that information within a predictive graduation statistical model? </p>
<p>Either that, or are you arguing that colleges - although clearly having the information within their past student databases - should not want to know? That’s quite the irony that a school - ostensibly an institution of learning and discovery - should deliberately choose not to know something for which they have the data. </p>
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<p>Nevertheless, nationwide graduation rates are conspicuously unimpressive. </p>
<p>And like I said, if colleges are already making admissions decisions based on ostensibly ‘non-academic’ criteria - such as extracurricular activities - why not do so in a statistically systematic way? </p>
<p>Let me put it to you another way. Why exactly is it so controversial to run a statistically predictive model to determine admissions, but not at all controversial to have a committee of unaccountable human beings, with all their foibles, determining admissions? Do you truly believe the latter to always be fair and just? </p>
<p>What we could do is have a ‘bake-off’ where a small cohort of (randomly selected) admissions decisions are determined through the statistical model, and the other cohort is determined by an adcom. We would then track the performance of each cohort. If the adcoms are clearly superior to the model, then evidence of that would be borne out through the superior performance of their cohort. But what if they’re not? </p>
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<p>And is that really so controversial? Would anybody like to take the opposite position: that unmotivated students should not only nevertheless still be admitted to college, but they should be admitted over other applicants who are actually motivated, even if those other applicants would go elsewhere. </p>
<p>Put another way, if you’re a motivated student, and your dream is to go to the University of Michigan, only to be rejected because they for some reason would rather admit a bunch of unmotivated students who are far more interested in partying and socializing than in studying, how much consolation will you derive from the fact that you can still go to Michigan State, and that those students, had they not be admitted to UM, might not be admitted anywhere at all? For most people, probably no consolation whatsoever. All you’ll care about is that while you would have studied hard at UM, they didn’t even give you the chance because they offered the seat to somebody who is partying away. </p>
<p>I would also argue that motivation is highly socially contingent. I suspect that many currently unmotivated college students would actually become motivated had they been put into a different environment. Hence, any statistical model would be specific to that school: one for UM would predict lack of motivation at UM, but may have little predictive power to determine motivation at another school. Each school ideally would run their own model. Students would then be efficiently sorted by only being admitted to the schools at which they are the most likely to be motivated if they choose to go. Keep in mind that, under the new system, while you might be rejected from certain schools which you would currently be admitted to, you would likely also be admitted to other schools which you would currently be rejected from, as schools would be freeing up spots that were formerly being given to unmotivated students.</p>
<p>Nevertheless, it is still probably true that there will be some students who will not be motivated no matter where they go. But to them, I would ask, what’s so controversial about not admitting them? Why should competitive colleges provide a scarce admissions seat to those universally unmotivated students over somebody who is actually likely to be motivated? Those unmotivated students are free to attend an open-admissions community college - where they would not be taking any admissions seats from anybody - where they could then demonstrate their latent motivation and reapply as a transfer student.</p>
<p>Yet I continue to ask the question, why exactly should a college with a limited number of admissions seats reject somebody who is predicted to be clearly motivated in favor of somebody else who is predicted to be clearly unmotivated? Would anybody like to volunteer to defend that practice?</p>
<p>Put another way, if you’re a motivated student, and your dream is to go to the University of Michigan, only to be rejected from that and every other college because some mathematical model had “predicted,” based on social factors and which high school you had the misfortune to attend, that you would be unmotivated. For most people, that “prediction” is probably no consolation whatsoever. All you’ll care about is that while you had academic stats aligned with what UM otherwise regularly accepts, and you would have studied hard at UM, they didn’t even give you the chance because they offered the seat to somebody with okay stats, but not quite as good as yours, who went a school with a better motivation prediction profile.</p>
<p>The entire premise of this counterargument is flawed - the presumption is that the UM motivation statistical model is indeed reliable, or at least, more reliable than the current human-based adcom system is. Now, if your argument is that the predictive model may be faulty, that’s a worthy debate which ultimately revolves around the technical reliability of the model itself. Obviously if the model is faulty, then it shouldn’t be used, just as if an insurance actuarial model is found to be faulty, then it also shouldn’t be used. Here I am implicitly assuming that the predictive model was properly designed and tested using validation data such that it was found to be reliable. </p>
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<p>But like I said, that’s surely happening now under the current system, as presumably right now the UM adcom is using the imputed difficulty and prestige of the high school you attended, as well as a number of other social factors, to determine admissions decisions. </p>
<p>For example, right now, somebody who earned top grades at Bloomfield Hills’ International Academy, arguably the best public high school in the country, surely enjoys a substantial admissions advantage at UM over somebody with the same grades but who went to a terrible high school. All I am proposing is that since admissions decisions are already incorporating the quality of your high school anyway, why not do so in a statistically rigorous manner? The same could be said for social factors: right now, the human-based adcom is attempting to ‘weigh’ your social factors that will determine motivation, and probably not doing so in a rigorous way. </p>
<p>Now, if your proposal is that the predictive model should not incorporate the quality of the high school under the notion that it isn’t the students’ fault if they attend a bad one, fair enough. Then the human-based adcom should not be allowed to incorporate that information either by the exact same argument. Adcoms should then be blinded from information that would allow them to deduce where an applicant went to high school. But if certain types of information are going to be used no matter what, what’s so controversial about using that information rigorously? </p>
<p>If anything, I would argue that the consolation one would receive by being rejected by a statistical model is better, or at least, no worse, than the consolation one would receive under the current system. If you’re rejected under a statistical model despite having the same stats as other admittees, at least you can tell yourself that the model didn’t properly calibrate and capture your “unexplained residual” value, which all statistical models inherently are unable to explain. But it’s no personal insult. However, under the current system, you would know that actual human beings looked at your application and made a decision that you were not worthy. Frankly, there’s no way to take that as anything but a personal insult. </p>
<p>The bottom line is that whatever criticisms one might have of a statistical model are surely even more applicable to the current human-based adcom model. Let’s face it, the status quo ain’t that great. What matters is not whether the new system would be perfect, but whether it whether it would be better than the current system.</p>
<p>Frankly, I detect a strong whiff of social engineering and fear of ‘elitism’ emanating from the arguments of my detractors. I suspect that the real fear is that poor students from poor school districts would not be admitted under the statistically predictive model. I’m not sure that fear is valid, because I suspect that the model would be just as likely to reject lazy rich students. But even if the fear is valid, again, how is that different from the admissions decisions being made by the human-based adcoms right now? Let’s face it, right now, the student population at UM tends to skew towards the rich. Right now, there’s not exactly a lot of students from the most poverty-stricken swaths of Detroit admitted to UM. </p>
<p>Hence, I must ask the question: why would it be such a terrible thing for a statistical model to admit a student profile that may skew rich when it is perfectly fine for human-based adcoms to currently be admitting a student profile that also skews rich? What’s the difference? </p>