STEMing the Rot: Does Relative Deprivation Explain Low STEM Graduation Rates at Top Schools?

26 Sep

The following few paragraphs are from Sociation Today:


Using the work of Elliot (et al. 1996), Gladwell compares the proportion of each class which gets a STEM degree compared to the math SAT at Hartwick College and Harvard University.  Here is what he presents for Hartwick:

Students at Hartwick College

STEM MajorsTop ThirdMiddle ThirdBottom Third
Math SAT569472407
STEM degrees55.0%27.1%17.8

So the top third of students with the Math SAT as the measure earn over half the science degrees. 

    What about Harvard?   It would be expected that Harvard students would have much higher Math SAT scores and thus the distribution would be quite different.  Here are the data for Harvard:

Students at Harvard University

STEM MajorsTop ThirdMiddle ThirdBottom Third
Math SAT753674581
STEM degrees53.4%31.2%15.4%

     Gladwell states the obvious, in italics, “Harvard has the same distribution of science degrees as Hartwick,” p. 83. 

    Using his reference theory of being a big fish in a small pond, Gladwell asked Ms. Sacks what would have happened if she had gone to the University of Maryland and not Brown. She replied, “I’d still be in science,” p. 94.


Gladwell focuses on the fact that the bottom-third at Harvard is the same as the top third at Hartwick. And points to the fact that they graduate at very different rates. It is a fine point. But there is more to the data. The top-third at Harvard have much higher SAT scores than the top-third at Hartwick. Why is it the case that they graduate with a STEM degree at the same rate as the top-third at Hartwick? One answer to that is that STEM degrees at Harvard are harder. So harder coursework at Harvard (vis-a-vis Hartwick) is another explanation for the pattern we see in the data and, in fact, fits the data better as it explains the performance of the top-third at Harvard.

Here’s another way to put the point: If preferences for graduating in STEM are solely and almost deterministically explained by Math SAT scores, like Gladwell implicitly assumes, and the major headwinds are because of relative standing, then we should see a much higher STEM graduation rate for the top-third at Harvard. We should ideally see an intercept shift across schools, which we don’t see, but a common differential between the top and the bottom third.

Self-Recommending: The Origins of Personalization

6 Jul

Recommendation systems are ubiquitous. They determine what videos and news you see, what books and products are ‘suggested’ to you, and much more. If asked about the origins of personalization, my hunch is that some of us will pin it to the advent of the Netflix Prize. Wikipedia goes further back—it puts the first use of the term ‘recommender system’ in 1990. But the history of personalization is much older. It is at least as old as heterogeneous treatment effects (though latent variable models might be a yet more apt starting point). I don’t know for how long we have known about heterogeneous treatment effects but it can be no later than 1957 (Cronbach and Goldine Gleser, 1957).  

Here’s Ed Haertel:

“I remember some years ago when NetFlix founder Reed Hastings sponsored a contest (with a cash prize) for data analysts to come up with improvements to their algorithm for suggesting movies subscribers might like, based on prior viewings. (I don’t remember the details.) A primitive version of the same problem, maybe just a seed of the idea, might be discerned in the old push in educational research to identify “aptitude-treatment interactions” (ATIs). ATI research was predicated on the notion that to make further progress in educational improvement, we needed to stop looking for uniformly better ways to teach, and instead focus on the question of what worked for whom (and under what conditions). Aptitudes were conceived as individual differences in preparation to profit from future learning (of a given sort). The largely debunked notion of “learning styles” like a visual learner, auditory learner, etc., was a naïve example. Treatments referred to alternative ways of delivering instruction. If one could find a disordinal interaction, such that one treatment was optimum for learners in one part of an aptitude continuum and a different treatment was optimum in another region of that continuum, then one would have a basis for differentiating instruction. There are risks with this logic, and there were missteps and misapplications of the idea, of course. Prescribing different courses of instruction for different students based on test scores can easily lead to a tracking system where high performing students are exposed to more content and simply get further and further ahead, for example, leading to a pernicious, self-fulfilling prophecy of failure for those starting out behind. There’s a lot of history behind these ideas. Lee Cronbach proposed the ATI research paradigm in a (to my mind) brilliant presidential address to the American Psychological Association, in 1957. In 1974, he once again addressed the American Psychological Association, on the occasion of receiving a Distinguished Contributions Award, and in effect said the ATI paradigm was worth a try but didn’t work as it had been conceived. (That address was published in 1975.)

This episode reminded me of the “longstanding principle in statistics, which is that, whatever you do, somebody in psychometrics already did it long before. I’ve noticed this a few times.”

Reading Cronbach today is also sobering in a way. It shows how ad hoc the investigation of theories and coming up with the right policy interventions was.

Teaching Social Science

12 Sep

Three goals: impart information, spur deeper thinking about the topic and the social world more generally, and inculcate care in thinking. As is perhaps clear, working toward achieving any one of these goals creates positive externalities that help achieve other goals. For instance, care in exposition, which is a necessary though insufficient condition for imparting correct information, is liable to produce, either through mimesis or further thought, care in how students think about questions.

Supplement such synergies by actively seeking and utilizing pertinent opportunities during both, class-wide discussions about the materials, and one-to-one discussions about research projects, to raise (and clarify) relevant points. During discussions, encourage students to seriously consider questions about epistemology, fundamental to science but also more generally to reasoning and discourse, by weaving in questions such as, “What is the claim that we are making?”, and “When can we make this claim and why?”.

Some of the epistemological questions are most naturally (and perhaps best) handled when students are engaged in working on their own research projects. Guiding students as they collect and analyze their own data provides unique opportunities to discuss issues related to research design, and logic. And it is my hunch that students are more engaged with the material (and hence learn more of it, and think more about it) when they work on their own projects than when asked to learn the materials through lectures alone. For instance, undergraduates at Stanford often excel at knowing the points made in the text, but often have yet to spend time thinking about the topic itself. My sense is (and some experience corroborates it) that thinking broadly about an issue allows students to gain new insights, and helps them contextualize their findings better. It also spurs curiosity about the social world and the broader set of questions about society. Hence, in addition to the above, ask students to discuss the topics that they are working on more generally, and think carefully and deeply about what else could be going on.

That’s Smart! What We Mean by Smartness and What We Should

16 Aug

Many people conceive of intelligence as a CPU. To them, being more intelligent means having a faster CPU. And this is despairing as the clock speed is largely fixed. (Prenatal and childhood nutrition can make a sizable difference, however. For instance, iodine deficiency in children causes mental retardation.)

But people misconceive intelligence. Intelligence is not just the clock speed of the CPU. It is also the short-term cache and the OS.

Clock speed doesn’t matter much if there isn’t a good-sized cache. The size of short-term memory matters enormously. And the good news is that we can expand it with effort.

A super fast CPU with a large cache is still only as good as the operating system. If people know little or don’t know how to reason well, they generally won’t be smart. Think of the billions of people who came before we knew how to know (science). Some of those people had really fast CPUs. But many of them weren’t able to make much progress on anything.

The chances an ignoramus who doesn’t know correlation isn’t causation will come across as stupid are also high. In fact, we often mistake being knowledgeable and possessing rules of how to reason well for being intelligent. Though it goes without saying, it is good to say it: how much we know and knowledge of how to reason better is in our control.

Lastly, people despair because they mistake skew for the variance. People believe there is a lot of variance in processing capacity. My sense is that variance in the processing capacity is low, and the skew high. In layman’s terms, most people are as smart as the other with very few very bright people. None of this is to say that the little variance that exists is not consequential.

Toward a Better OS

Ignorance of relevant facts limits how well we can reason. Thus, increasing the repository of relevant facts at hand will help you reason smarter. If you don’t know about something, that is ok. Today, the world’s information is at your fingertips. It will take you some time to go through things but you can become informed about more things than you think possible.

Besides knowledge, there are some ‘frameworks’ of how to approach a problem. For instance, management consultants have something called MECE. This ‘framework’ can help you reason better about a whole slew of problems. There are likely others.

Besides reasoning frameworks, there are simple rules that can help you reason better. You can look up books devoted to common errors in thinking, and use those to derive the rules. The rules can look as follows:

  1. Correlation is not the same as causation
  2. Don’t select on the dependent variable. What I call the ‘7 Habits of Successful People’ rule.
  3. Replace categorical thinking with continuous where possible, and be precise. For e.g., rather than claim that ‘there is a risk’, quantify the risk. Or replace the word possibility with probability where applicable.
  4. Have a better grasp of your own ignorance using some of the tricks described here.
  5. The tree of inference starts with the question. Think hard about what data you would need to answer the question well. And then what data you have. And then calibrate your assessments about the answer based on the difference between the data you would have liked to have and the data you have.

Proposal for a Program in Political Communication

4 Jun

Forces that govern people’s behavior in politics are diverse, a diversity that is not always appreciated by scientists stuck in disciplinary bunkers. While occasional interdisciplinary philandering by scientists otherwise faithful to their disciplines has contributed enormously to our understanding by fruitfully leveraging knowledge across disciplines, formalizing such interdisciplinary training may prove to be a good catalyst for increasing this salutary (though non-virtuous) behavior.

Training for academia should include logic, philosophy, methodology, writing, teaching, skill in using tools for statistics (R), typesetting (Latex), and other miscellaneous but important skills like project management, how to present, etc. In addition, a student needs training in the specific specialization.

Given the extent of training needed, a student needs both time and strong mentoring.

Here below, I expand upon three particular aspects of training –

Methods Training
Methods training in Political Science, Communication, and Psychology (the three parent disciplines of Political Communication) is generally unsatisfactory, hobbled by incompetent teaching, if not incompetence. The only compensatory aspect is that the courses are fairly applied in nature. For firmer foundations in methodology, required for scholarship, training in the statistics department is a sine-qua-non.

Courses: statistical inference, modeling and causal inference, stochastic methods, parametric and non-parametric analysis, Bayesian analysis; Applied: time series analysis, data mining, sampling, programming, and optimization.

Statistics covers one part of methodology. A separate important part of methods includes courses on measurement—what to measure and how best to measure it. Recommended courses: survey design, and psychological measurement.

A course devoted to content analysis may prove useful as well.

Content
There exist at least three fields that directly relate to Political Communication – Psychology, Communication, and Political Science.

Psychology: group psychology, social psychology, cognition, neuropsychology, evolutionary psychology.
Communication: News and Politics, Political Communication (an assimilative course), Political Economy of the Media, Media and Communication.
Political Science: historical, institutional, theoretical, and behavioral aspects of politics.

Courses in law and sociology would be useful as well.

Mentoring
Regardless of the efforts to the contrary, there is still considerable variation in the students admitted. Students vary in their level of mental maturity, specific skills that they may excel in, etc. A proper and early assessment of weaknesses and strength of a student can allow the faculty to develop a specific plan crafted to address each. Directed reading courses in the initial year(s) with one’s advisor provides an excellent opportunity for the student to learn, and for an advisor to address concerns above and beyond those discovered in reading.

Seminar series provide excellent places to learn from others – care in thinking, presentation skills, research questions, etc.

Tips for Early Stage Social Science Doctoral Students

25 Feb

I made many mistakes in my graduate career. Here are a few tips for early stage and prospective graduate students:

  • There are five tools of the trade: logic, ethics (broadly philosophy), statistics, writing, and programming (R, Python). Spend time learning the tools of the trade.
  • Everything takes time. Spend time wisely.
  • Sub-clause: Don’t waste time on projects with no real future.
  • The most important decision you will make in graduate school is who to work with. Choose productive, technically competent people.

Given time is a scarce and extremely valuable resource, deploy other resources to help you get more from your time. Some such resources include,

  • A good laptop, a backup drive, and a printer
  • Quiet, comfortable office space
  • You can’t read what you don’t have. Buy the books you want to read.

How Are Academic Disciplines Divided?

18 Jul

The social sciences are split into disciplines like Psychology, Political Science, Sociology, Anthropology, Economics, etc. There is a certain anarchy to the way they are split. For example, while Psychology is devoted to understanding how the individual mind works, and sociology to the study of groups, Political science is devoted merely to an aspect of groups—group decision making.

One of the primary reasons the social sciences are divided so is because of the history of how social sciences developed. As major figures postulated important variables that constrain the social world, fields took shape around them. The other pertinent variables that explain some of the new disciplines in social sciences are changes in technology, and more broadly changing social problems. For example, the discipline of Communication took shape around the time mass media became popular.

The way the social sciences are currently divided has left them with a host of inefficiencies which leave them largely inefficacious in a variety of scenarios where they can offer substantive help. Firstly, The containerized way of understanding the social world provide inadequate ways of understanding complex social systems that are imposed upon by a variety of variables that range from the individual to the institutional. And secondly, the largely discipline-specific theoretical motivations lead academic to concoct elaborate theories that often misstate their applicability in complex ecosystems. We all know how economics never met common sense till of recently. It isn’t that disciplines haven’t tried to bridge the inter-disciplinary divide, they certainly have by creating sub-disciplines ranging from social-psychology (in psychology) to political psychology (in Political Science), and in fact that is exactly where some of the most exciting research is taking place right now, the problem is that we have been slow to question the larger restructuring of the social sciences. The question then arises as to what should we put at the center of our focus of our disciplines? The answer is by no means clear to me though I think it would be useful to develop competencies around primary organizing social structures/institutions.

Role of Social Science

Let me assume away the fact that most social science knowledge will end up in the society either through Capitalism or selective uptake by policymakers. Next, we need to evaluate how social science can meaningfully contribute to society. One intuitive way would be to create social engineering departments that are focused on specific social problems. The advice is by no means radical— certainly Education as a discipline has been around for some time, and relatively recently departments (or schools) devoted to Public Health, Environmental Policy have opened up across college campuses. Secondly, social science should create social engineering departments that help offer solutions for real-life problems, much the same way engineering departments affiliated with natural sciences do and try experimenting with how for example different institutional structures would affect decision making. Lastly, social scientists have a lot more to offer to third world countries which have yet to be overrun by brute Capitalism. What social science departments need to do is lead more data collection efforts in third world countries and offer solutions.

Advice on Studying in the US: Why, Why Not, and How

8 Nov

The number of foreign students studying in the US increased for the first time in four years buoyed by a 32% increase in the number of Indians joining graduate programs. Graduate education in the US has become increasingly popular for Indians meanwhile undergraduate population of Indian students in the US is still far behind (about a sixth of the graduate population) and for good reason. Here below I try to come up with a guide to issues that an incoming undergraduate applicant may want to think about before coming to the US.

Why not?

Finances: Undergraduate education in the US is extremely expensive, especially at top-tier private schools, and given the income disparity (in dollar terms) between India and US. In addition, the chances that an international student will get hired right away after graduation with a top-notch salary are slim given visa issues. A prospective undergraduate applicant may also want to factor in the pressure that s/he is likely to come under (or feel) if his/her parents are taking a large loan to finance their education. There is also a good chance that the undergraduate will probably have to work 20 hours per week (or more illegally) to supplement his or her income, which in turn will cut into the study time.

Age and associated factors: Add to the above the fact the relative immaturity and youth that make it harder to adjust to a completely new culture. It is not merely adjusting to a new culture but adapting to it to such a degree, and with enough rapidity, so as not distract you from studies for a significant time.

Why?

Going to a liberal arts college in the US allows one a lot of choices in sampling different courses. This kind of choice is relatively absent in colleges in Asia or even Europe. Then there are top-tier facilities, labs, faculty etc. which may make the expense seem worthwhile. In addition, doing an undergraduate degree will almost certainly improve your chances of doing graduate school here.

If you have considered the above arguments and still want to apply for getting an undergraduate degree in the US, then here is the drill –

Decided? Then Prepare

The preparation should ideally start at least about a year and a half before you want to join the school. An international student needs to give TOEFL (Test for English as a foreign language), SAT and generally SAT 2s in at least one or more subjects – especially if you are applying to top universities. English, of course, would be the main challenge. Given that SAT now has a writing section; it is of paramount importance that students develop good writing skills. You may want to engage a tutor to understand “expository” writing techniques. A preparation program can be really helpful especially because you will get to meet people who are in the same boat. Preparation center staff can also provide you helpful pointers on admission essays etc.

Schools: It is foolhardy to limit your choices to Harvard or MIT or two other top universities that you may have heard of in India. There are a lot of top-tier universities in the US including Princeton, Stanford, Dartmouth, Yale, UC Berkeley, Cornell, Georgetown etc. It is imperative that you apply to at least 8 -10 universities. There may also be an argument for applying to mid-ranked private schools like Boston University or NYU for typically they have the dollars to fund top international students. One type of university you don’t want to apply to is – large state universities that never fund international students at undergraduate level and typically won’t do much for your career prospects.

Funding: A lot of top universities engage in what is called “need-blind admission”. Chances are that once you are admitted into Harvard or Yale and don’t have the money to pay for their tuition, they will pony up the rest. On the other hand, chances are that your family will still need to contribute a good 10-15 grand a year. It is also a mistake to imagine that all the “aid” from universities will be in the form of grants, a majority of the aid is in the form of subsidized loans.

Application: The art of getting into a US university is self-aggrandizement and careful positioning. It is expected that your application will include records of volunteer activity, membership to various clubs and other “leadership” experience. The other important thing in application is how you place yourself academically – here’s what I mean – say, if you are great in Chemistry – give a SAT II exam for Chemistry and get a 750 plus score on it and then write how much you want to get a Chemistry degree in your “Statement of Purpose”. Given the way universities in US work, one can change fields on the first day of the school so you can still do engineering or English literature.

Reforming the College Application Process

1 Aug

College application process in the US is overrun by blatant self-serving marketing and cronyism. We must reform the application process to change the way students look at education.

The Graduate Application Process

While US-based schools uniformly ask for a “Statement of Purpose” and occasionally a personal biography to mention things which “may not have been covered otherwise,” UK based schools like LSE only ask for a formal thesis proposal from their Ph.D. applicants. The subjectivity introduced by essays like the “Statement of Purpose” gives the admissions committee enough elbow room to fit in candidates whose backgrounds may otherwise be suspect. LSE’s demands only a formal thesis proposal, which includes research design and bibliography, and gives a better understanding of a student’s intellectual ability to handle research than say 3-4 pages of carefully crafted spiel to please the head honcho of the department or to whoever holds the key to your admission.

On to undergraduate application process

Today an application to a top-echelon school passes through many rounds of editing before it reaches the desk of the admissions officer. There are numerous websites and books dedicated to the craft of writing a successful admissions essay. The key to a successful admissions essay is to have “an angle” around which you weave your life story and tell the admissions officer why your life has led you to ‘this’ particular program at this college. Of course, the logic and events are sham or nip-tucked to give them the exaggerated appearance that is needed for the storyline. The sham stories give admissions officers a poor idea of student’s interests and capabilities especially because they can so easily be spun around to sound and say what is wanted. In writing dishonest essays, students also fail to analyze if they really want to join a particular school or a program. Still, by far the more insidious effect of the growing importance of the extra-curricular activities in the college application process is that today high-school students are hustling to get into multiple extracurricular activities at the expense of studying. It may also be argued that the admissions essays unfairly favor the rich students who can carefully tend to the admissions essay with the help of online services. It is this thing, which is, in fact, unique to the US, that it rewards entrepreneurship and salesmanship over scholarship.

Cure?

The application process at undergraduate level should highlight the importance of academic achievement in schools and pay little or scant attention to frivolities like admission essays.