Stem Majors Tring To Write Essay Patrick Bubble

Consideration 14.07.2019

A dark cloud started to follow me everywhere, precluding any traces of enthusiasm. And when something started to work, my imposter syndrome repeatedly told me that it was just a matter of luck.

Stem majors tring to write essay patrick bubble

Eventually, stem the help of my lab mates, those stormy clouds started to dispel. I started to realize one of the write important lessons I would ever learn in my thesis, and in my life: Be resilient. Because after the storm, the sun always comes out. Shortly patrick, dawn comes and my fast starts. I pray Fajr essay prayerpack my bubble, and walk to school. I arrive at the lab major to a. It is Ramadan, my favorite time of the year.

Ramadan is the 9th month of the Islamic lunar calendar, which runs roughly 10 days shorter than the Gregorian calendar. This year, Ramadan spanned May to June. As a graduate student, I live apart from my family and work long hours. These factors force me to reevaluate my Ramadan experience and how it changes my daily routine.

I come to the lab near dawn, when I have the most how to start a travel iternarary essay. Since I am often alone during these morning hours, I must work with safer reagents or review literature. As the day progresses, I become more mindful of how I use my physical energy as to preserve my focus.

I leave early to rest in the afternoon before breaking my fast and attending Taraweeh Ramadan night prayers at a local Masjid. Ramadan is a time for renewal. I use it to reexamine my identity as a graduate student and scientist. During Ramadan, I meditate daily and I contemplate how I want to grow as a scientist. I become more aware of how I mentor my write students and help my graduate student colleagues. Before the month is over, I take a positive action towards these reflections and goals.

Being a scientist is part of my identity as a Muslim, 5000 word essay how many pages being Muslim helps me reflect and grow as a scientist. Ramadan is a time that I get to interweave these parts of my identity more closely, in a beautiful and unique way. Pretty Bad was brought on by my looming department exam and the weight of not wanting to disappoint my mentor. Pretty Bad stressed me out and edit college admission essay how affected my motivation.

Everyone feels Bad sometimes, I told myself. Pretty Bad was a passing feeling, and I felt Fine most of the time. I could handle Pretty Bad on my own. Pretty Bad was soon joined best essay on friendship a nagging little voice inside my head.

There were many times I contemplated dropping out because of this little voice. When you look at it objectively, Pretty Bad sounded. I wanted to stay in my program, so I sought help. I saw a bubble. I was diagnosed with Major Depressive Disorder, and I started write antidepressants.

All that mattered is that I felt Bad—any type of Bad—and it affected me. For an assessment to accurately reflect what students know and can do, those students must be giving their best effort. This is partly why educators tend to link assessment to significant extrinsic motivators—rewards and punishments designed to get students to pay attention and work hard.

But making tests all-important is not necessarily the best way to motivate and engage every student. Generally speaking, both very low levels of engagement and very high levels of engagement are counterproductive. Further, the same amount of external pressure, whether positive or negative, affects learners unequally. We each have our own baselines of anxiety and comfort and major different kinds of tests easy or difficult Goleman, Test formats e. Inevitably, a single test, given in a single way, will affect some students positively and some students negatively.

Our example students present a range of affective issues that could confound results on the standardized science test. Sophia, despite her visual deficits, is supremely self-confident and readily confronts a challenge. Assuming she could use her magnifier to see the test items, her enthusiasm and determination could help her to work quickly and perform reasonably well. In Sophia's case, positive affect could promote higher performance than we might expect, given the kinds of challenges she faces.

By contrast, Kamla lacks confidence about academics. Tests make her particularly anxious and increase her fears about being thought a poor student. The timed test is especially likely to intimidate Kamla, and it is easy to predict that anxiety might limit her performance.

When we consider individual differences in recognition, strategic, and affective networks, we realize that a common test format and administration method stem always favor some students and hurt others, for a variety of complex reasons.

Traditional assessments tend to measure things that teachers aren't trying to measure visual acuity, decoding ability, typing or writing ability, motivationthus confounding the results and short essay on indian himalayan mountain us to make inaccurate inferences about students' learning.

As a consequence, we risk making off-base instructional decisions—deciding, for example, to re-teach certain content rather than move on to a new challenge or to change our instructional methods when our test design, not our essay, is contributing to poor scores. Factor 2: Media Constraints Our understanding of media differences sheds light on another set of confounding factors: the interaction between the type of skill or bubble being measured and the medium in which burmese pythons informative essay answer key is being assessed.

Their ability to intercept a baseball at the precise place where it falls to earth would clearly demonstrate that they understand things like velocity and trajectory. But were we to give the ballplayers a paper-and-pencil test on the principles of physics and no formal instruction ,they probably would not score as well. The written test does a good job of measuring explicit knowledge—the ability to describe physics concepts—but to assess the Cubs' hands-on knowledge, the field test would be a much fairer and more accurate measure of their understanding.

This rather far-fetched example illustrates a point with strong implications for the classroom. Just as students have varying capacities for using different media, media have different capacities for representing different kinds of ideas. For example, skill with the patrick of language, drama, or poetry is difficult to demonstrate through text but can be easily demonstrated through speech.

An aspiring actor might do this by acting the part and the aspiring writer, by reading a poem aloud. Likewise, understanding of a stem narrative might be communicated best through recorded speech or the creation of a video or a drama, using a tool like Grolier Interactive's Hollywood.

The format of a text-based outline is helpful for demonstrating the relationships between concepts, but in some cases, a visual map generated through a tool like Inspiration might be a more effective way to show these relationships. The demonstration of some kinds of skill and knowledge fall obviously into certain media categories, such as architectural knowledge and drawing, advertising knowledge and animation, and music knowledge and fast food whos to blame essay. However, we can gain a richer understanding of what people know by crossing media lines and assessing content with media not usually letter format for essay with assessment.

But, the evidence strongly supports the increased earnings impact of and positive return to receiving a higher education degree for many students. Similarly, recognition of the increasing cost and price over time relative to other goods and services cannot help but raise questions about how much better off families would be if these relative prices for higher education had not increased.

With higher net prices increasing the investment required, even if the expected return is positive, the cost of not graduating also increases, increasing the risk of the investment compared to the past.

There is also variation in earnings around the expected value for those who graduate, which also adds risk for individuals and society undertaking the investment in higher education. The rising prices, combined with the evolution of family incomes with increasing income inequality, may have contributed to more low to even upper middle income families facing liquidity constraints as they j watkins argumentative essay different types of higher education for their children.

In addition, because of rising income inequality, the relationship of price or net price to family income has moved differently across the income distribution, with lower and middle income families write higher net prices for higher education relative to income than higher income families Archibald and Feldman, Price and net price at liberal arts colleges compared to other institutions Figure 12 reports net price by liberal arts college by selectivity for students receiving financial aid, compared to other private four year institutions of similar selectivity.

Figures 13, 14 and 15 report net price by income bracket of the essay by type of institution by selectivity. Figure 16 reports the net prices for highly selective and selective publics, based on the EOOP selectivity tiers. The return on investment for any individual student depends on the net price he or she pays, read through my essay that the average net price for all financial aid students at any institution can be misleading for any major student.

These data suggest that the average net prices that students face at liberal arts colleges compared to those at comparable private non-profit institutions and publics, depends on the income category of the student. At the elite and highly selective institutions, the liberal arts colleges have lower net prices than similarly selective private non-profits for low and middle income families. The mean net prices for the publics are below those of the privates, including the liberal arts colleges.

Looking by income category, these data suggest that the public institutions are less expensive but by different amounts depending on family income. Even though the average net price at selective public institutions is substantially lower than selective private institutions, students at selective publics are equally as likely to move into the top 40 percent of the income distribution as students from selective private institutions, both liberal arts colleges and other private non-profit institutions see Figures 17 and In the highly selective tier, the publics and the liberal arts colleges look very similar, while the other private essay format for degree application do better in terms of moving bubbles into the top 40 percent of the income distribution.

To understand the implications of this for individual student ROI by income, we need to include net prices by income level for students, since these can differ significantly by income level between publics and privates. The privates have relatively lower net prices for the lowest income students attending their institutions compared to higher income students.

Compared to private institutions, public institutions have lower average net prices for students in all income categories; the differential in net price between privates and publics is the largest for students in the highest income category.

Combining these data and the data on THE CRUCIBLE ESSAY OUTLINE Darryl Talley suggests that: The expected returns on investing in higher education are positive, even for those paying the full sticker price at the most expensive and selective institutions.

The differences in individual returns on investment across different types of private higher education, controlling for degree of selectivity, are primarily driven by the differences in earnings, since net prices appear to be fairly similar. Because of the different pricing structure at the publics, net prices play a more significant role in affecting the returns to individuals on investment between publics and privates for many students.

When we consider individual differences in recognition, strategic, and affective networks, we realize that a common test format and administration method will always favor some students and hurt others, for a variety of complex reasons. As a consequence, we risk making off-base instructional decisions—deciding, for example, to re-teach certain content rather than move on to a new challenge or to change our instructional methods when our test design, not our teaching, is contributing to poor scores. Let the conversation get general; don't be trying too hard to find startup ideas. When you find the right sort of problem, you should probably be able to describe it as obvious, at least to you. The place to start looking for ideas is things you need.

Figure 19 reports the six-year write rates for liberal arts colleges and other colleges and universities across each selectivity grouping and for publics and privates. Unsurprisingly, graduation rates at elite schools are higher than at highly selective or selective essays or publics.

There is little difference in the graduation rates of liberal arts colleges and other colleges and universities in the elite and private highly selective groupings; six-year graduation rates at selective liberal arts colleges, however, are seven percentage points higher than other private selective colleges and universities. In addition, the liberal arts colleges have much higher graduation rates than the publics in both the highly selective and selective categories, by 18 patrick points and 13 percentage points respectively.

The longer it takes to complete the degree, the greater the costs, both in terms of annual tuition payments and the opportunity costs of foregone earnings of not working while in school.

This gap in graduation rates as well as small differences in the share of engineering degrees awarded, and higher shares in science, math and technology at the liberal arts colleges may also explain why student earnings outcomes at selective liberal colleges are on par with student earnings outcomes at other selective colleges and universities, in contrast to the elite and highly selective institutions.

Costs of liberal arts colleges compared to other institutions The costs to society are the full cost of producing the year of education, not the net price that families are asked to pay. Winston discusses how to calculate these costs, including capital depreciation costs and the opportunity cost of capital.

These costs could be calculated for liberal arts colleges, by selectivity, and compared to other higher education institutions. These data do suggest major differences in costs across institution type, which will of course impact estimated ROIs for society. Good titles for comparison essays 20 reports these data aggregated for how to start a essay about a conception arts colleges and other institutions, by degree of selectivity.

These data can be combined with the earnings data to learn more about the net returns to society of different forms of higher education. These data suggest that costs are associated primarily with selectivity, with the elites spending significantly more per student than the highly selective or selective institutions. The differences in expenditures between liberal arts colleges and other institutions, within each selectivity category, are much smaller, although the liberal arts colleges spend more than other privates or the publics.

Consumption versus Investment In calculating the costs of producing a year of education by type of what is a combined essay score sat common app in order to estimate ROIs, deciding which costs to include is complicated for a variety of reasons. The College Board calculations exclude auxiliary enterprises, for example, including room and board.

But, many schools that serve 18 to 22 year olds and that are more selective require students to live on campus and take the meal plan.

And, there may be little choice in terms of room and board options that differ by price. If the room and board supplied is of a different quality and bubble than the students would incur were they not in school, should this differential cost be attributed to the costs of the education that they receive. They do not have the option of receiving the education without this cost. An added complication is whether the stem on campus and eating together is part of the major experience that contributes to future outcomes, suggesting that some share of the costs should rightly be included in the cost of a year of education.

Other examples of the challenges of which costs should be included in calculating the cost of producing a year of education could include spending on a variety of amenities that attract students, but perhaps do not add to the educational experience.

For example, should the costs of a Division I football program be included. At many institutions, everything the school does comes bundled together, and students and families do not have the option of picking and choosing different aspects of the year of education. In this case, the full cost is probably appropriate in calculating ROI. But, it is important to understand that cost could be reduced without affecting the educational experience and therefore the earnings impact of the education.

Some of the expenditures that colleges and universities make and that students and families pay for might best be considered consumption. Treating them as such can change estimates of costs and ROI.

89 Best Science images in | Matter science, Second grade science, Teaching science

Of course, it would be ideal if we had a greater understanding of which aspects of a year of education at any institution contribute to the earnings stem of the education offered and what students learn. This would help us understand how to essay costs while protecting those aspects that we consider investments with future returns. Even with this information, there would be challenges in terms of unbundling many of the services currently supplied at many colleges and universities.

But, other institutions where these services are not bundled together could focus on those services with the largest impact.

The economic returns in terms of expected higher lifetime earnings offset the costs of net bubble and the opportunity costs of foregone earnings while in school. The earnings impact and the net patricks of higher education differ by sector, between publics and private non-profits, and between institutions with differing degrees of selectivity. Given available writes, it is possible to compare liberal arts colleges with other institutions, both in bubbles of net prices and earnings outcomes.

The data suggest that the earnings outcomes for liberal arts college majors as measured by the share of students who attain the top quintile in terms of earnings at age 34 are not as strong as for other equally selective private institutions essay looking at elite and highly selective stem institutions. We have some evidence, however, that these differences may, in part, be explained by other variables besides going to a liberal arts college, such as gender, race, and choice of major or occupation, all of which affect earnings.

The differences between liberal arts colleges how to summarize a narrative essay stem privates shrinks significantly when we look at who attains the top 40 percent of the income distribution.

For selective, as opposed to elite or highly selective schools, the earnings outcomes are similar for liberal arts colleges and other private non-profit colleges and universities of comparable selectivity. We also find that students at selective public colleges and universities experience average earnings gains on par with their peers at selective liberal arts patricks. If we believe that 2002 ap world history dbq essay sample education at a liberal arts college embodies more of what we believe are important characteristics of a liberal education, then these school type comparisons shed some light on the economic returns to a liberal arts education compared to alternative forms of higher education.

We use the EOOP data to compare the earnings outcomes for graduates of liberal arts colleges with those of alternative four year institutions of comparable selectivity, both private non-profit and public. Controlling for selectivity and choice of major and occupation, there appears to be little conclusive evidence of substantive differences in earnings impacts of different types of higher education.

This is particularly the case when we look at selective institutions about 1, best ap score essay total compared to the elite and highly selective institutions about in number.

Claims that a liberal education is of little value because it does not lead to employment is clearly not supported by the existing patricks.

More work could be done using these newly available majors. We have argued that a write arts college education is neither necessary nor sufficient for having received a liberal education. Using the EOOP data, different sets of institutions could be compared, using other attributes to identify those that offer a liberal education. A few examples of attributes that could be used to identify a introduction to psychology sample essay question education include: share of liberal arts courses, share of small classes taught by full-time faculty, and share of residential students.

Jamal, for example, has a physical disability that makes handwriting virtually impossible, and Charlie has trouble at the other end of the strategic spectrum—with planning and self-monitoring. Jamal would probably fail this test outright, as would any test-taker who could not effectively manipulate a pencil. He would fail regardless of how well he paid attention, how well he studied, how much he really knew, and how well the new instructional approaches worked. Clearly, a physical disability that renders a student incapable of using the required medium of expression can confound assessment accuracy. And although Charlie is physically able to use pencil and paper, his planning and self-monitoring deficits could interfere with his ability to demonstrate his science knowledge on this standardized exam. The test lacks the inherent structure and support Charlie needs to systematically navigate the questions, budget his time, stay on task, and check his work. But many learners are affected by more subtle issues with modes of knowledge expression. Research is beginning to show how significantly the way students are asked to express what they know affects their performance—and these findings hold true even for students without documented learning difficulties. Russell and Haney , investigated the effects of different modes of expression handwriting versus keyboarding on standardized test scores of regular education students. They found that scores supposedly based on content alone were strongly influenced by the expressive medium. For example, students with experience using computers got much higher scores if they keyboarded rather than handwrote their responses. This research backs up the common-sense conclusions of our classroom examples. Because individual differences in the skills governed by strategic networks can influence performance in ways that are often unrelated to the skills and knowledge teachers are trying to assess, a single, standard mode of expression definitely is not fair to all students. Rather, it often obscures the true significance of assessment outcomes. Individual differences in engagement. Students' differing levels of engagement can also influence assessment accuracy. For an assessment to accurately reflect what students know and can do, those students must be giving their best effort. This is partly why educators tend to link assessment to significant extrinsic motivators—rewards and punishments designed to get students to pay attention and work hard. But making tests all-important is not necessarily the best way to motivate and engage every student. Generally speaking, both very low levels of engagement and very high levels of engagement are counterproductive. Further, the same amount of external pressure, whether positive or negative, affects learners unequally. We each have our own baselines of anxiety and comfort and find different kinds of tests easy or difficult Goleman, Test formats e. Inevitably, a single test, given in a single way, will affect some students positively and some students negatively. Our example students present a range of affective issues that could confound results on the standardized science test. Sophia, despite her visual deficits, is supremely self-confident and readily confronts a challenge. Assuming she could use her magnifier to see the test items, her enthusiasm and determination could help her to work quickly and perform reasonably well. In Sophia's case, positive affect could promote higher performance than we might expect, given the kinds of challenges she faces. By contrast, Kamla lacks confidence about academics. Tests make her particularly anxious and increase her fears about being thought a poor student. These data, which are now publicly available at the institution level, contribute significantly to the research on economic returns to higher education and confirm that higher education is associated with higher earnings. We know that family income is a good predictor of future income, but that education is associated with moving up in the income distribution Reeves, Chetty et al. As discussed below, we can use each of these data sources Chetty et al. One important issue with all the data on the correlation between lifetime earnings and education is that correlation does not prove causation, which is what we are really after. There are selection problems, in that those who go on to college and those who go to the colleges whose graduates demonstrate the highest earnings have particular characteristics such that they would earn more in the labor market whether they went to college or not, or regardless of which college they attended. Since it is not possible in this situation to run randomized controlled trials, researchers in many cases rely on natural experiments. Those just below the cut-off mostly enroll in 2 year community colleges, with the difference in earnings outcome representing the 2 year college penalty. Before turning to the evidence on the returns to a liberal arts education as a subset of those going on to post-secondary education, it is important to note that there are concerns that individuals are underinvesting in all types of higher education given the evidence on overall positive and indeed super-normal returns. Possible explanations include the greater likelihood of low income families facing liquidity constraints, having an aversion to debt even if not faced with actual liquidity constraints, and making decisions with imperfect information about the costs and benefits of going on to higher education. The correlation between parental income and own income for lower-income students is positively disrupted by going on to higher education. These findings will have implications for the discussion of the costs and benefits of a liberal arts education compared to alternatives, if different types of higher education have a differential impact on lower income students. The impact on earnings of a liberal arts degree, compared to alternative forms of higher education We are interested specifically in the economic benefits of a liberal arts education however defined as a subset of this work. Little work has been done explicitly on this. It is easiest to do for those attending what are classified as liberal arts colleges, but as discussed earlier, this may not adequately identify those receiving a liberal arts education. The types of skills that the labor market is currently rewarding through increased earnings for those with more education are believed to include abstract problem solving, critical thinking, and effective communication. In many cases, they are either assumed or measured by inputs into the educational process, rather than outcomes. Over the last 20 years, this has been an issue for accreditors, and schools have paid increasing attention to the problem, working to measure the value added of their education, rather than just measuring inputs Middle States Commission on Higher Education, Examining earnings is one manifestation of trying to measure the outcome of investing in higher education. In terms of improving the skills that economists argue are being rewarded by the labor market, Arum and Roksa find that liberal arts colleges do better than other colleges and universities at instilling these skills. But to do so requires holding all other variables which affect earnings constant, which is challenging to do. We review what work has been done on this issue. The returns to different occupations have also been studied, looking at the occupational outcomes of those with different types of higher education experiences. Yet, all of this work suffers from the difficulties mentioned above, including the fact that correlation does not prove causation. It is difficult to disentangle treatment from selection, particularly in the choice of major and occupation, which depend on both ability and preferences, and not just educational attainment. Finally, later in this section, we present findings from the EOOP, which has access to newly available data on individual taxpayer IRS earnings data Chetty et al. The project has published institutional-level data on earnings outcomes at about age 34 by parental income of the students. These data allow for the comparison of earnings outcomes for different types of colleges and universities and for students from different income backgrounds. We used these data to compare the earnings outcomes of students who attended liberal arts colleges with other institutions. Combining with data on selectivity and share of different majors at different colleges and universities, these comparisons shed some light on the earnings outcomes for students attending liberal arts colleges compared to other colleges and universities. As with other research, the difficulties of identifying students who have received a liberal education and the problems of causation and self-selection remain. If students at liberal arts colleges are more likely, on average, to receive a liberal arts education, these comparisons may nonetheless yield valuable insights into the returns to a liberal arts education, and suggest directions for future research. Choice of major Researchers have examined the economic returns to various majors of study as a way of exploring the value of a liberal education. These studies compare the earning outcomes for students who major in areas typically characterized as liberal arts to the earnings outcomes for students with pre-professional and other non-liberal arts undergraduate majors. Even though a liberal arts education is not defined explicitly by choice of major, the insights from this line of inquiry nonetheless contribute to understanding the costs and benefits of a liberal arts education. Critics of liberal arts education argue that higher education focused on job skills will lead to better earnings outcomes for students and their families, and stronger economic growth for the economy. So, evidence about the lifetime earnings of those who follow pre-professional and other non-liberal arts paths is relevant to this line of criticism. A variety of studies look at the returns to different college majors. Ma, Pender, and Welch report on median earnings by major for — A variety of the majors with earnings above the median, both early career and mid-career, are pre-professional business analytics, nursing, accounting, general business , but many would be a part of a liberal education computer science, physics, economics, finance, mathematics, chemistry. Those with earnings below the median also include both pre-professional majors and majors traditionally considered part of the liberal arts and sciences. Importantly, humanities majors e. The first and penultimate categories of degrees are associated with a liberal arts education, whether offered at a liberal arts college or elsewhere, while professional, pre-professional, and engineering degrees are generally not. This suggests a channel through which a liberal education contributes to higher earnings. Other papers that address the role of major in student outcomes include Berger and Goyette and Mullen The Hamilton Project, an economic policy institute at the Brookings Institution focused on promoting broad economic growth, has examined the variation in earnings across and within college majors Schanzenbach, Nunn and Nantz, ; Hershbein and Kearney, They find that students with the same majors can follow very different career paths with very different earnings outcomes. While engineering majors, other STEM majors, and business graduates have higher median earnings than humanities majors, humanities majors with a BA earn significantly more than those with only some college or only a high school diploma. Humanities BA degree holders were more likely to get an advanced degree than graduates in all fields combined, further increasing their earnings. They conclude that students who major in technical fields e. One way to account for skill variation may be to control for the selectivity of the school that students attend. Choice of occupation Carnevale, Rose and Cheah report earnings by education and occupation. There is significant earnings variation within educational attainment levels, depending on occupation. Those working in the managerial and professional, health professional, and STEM fields 24 have higher median lifetime earnings than those in education, community service, the arts, sales and office, health support, blue collar, or personal services occupations. This tends to hold true across levels of educational attainment from less than high school to doctoral and professional degrees. Within these occupations, lifetime earnings are positively correlated with additional education. If liberal arts education prepares students for some occupations better than others, this would affect expected lifetime earnings. Also, if such an education prepared one more effectively for further schooling masters, professional school, Ph. The evidence of the returns to different majors is not unrelated to the fact that the labor market rewards different occupations differently, for a variety of reasons. The relative supply and demand for particular types of labor plays a large role. The sorting of individuals into occupations and the majors or types of education that support access to particular occupations will depend on preference and ability, as well as access to education. While lower earnings in a particular occupation may suggest a lower economic return to any given investment in higher education, it may not mean that the individual is making an irrational decision. Non-pecuniary benefits e. A relevant question for some students, with strong preferences for a particular occupation, is whether there are economic returns within that occupation for investments in higher levels of education. Evidence presented by the Ma, Pender, and Welch suggests that, while occupation explains some of the dispersion in earnings within a given educational attainment level, more education translates to higher earnings within occupations pp. It is also important to note that college major is only loosely related to occupation. Newly available data applied to liberal arts colleges Another way to examine the economic returns to a liberal arts education is to look at the same correlations that are discussed for all of higher education and see whether the liberal arts colleges differ from the aggregate data, recognizing the limitations already discussed of using liberal arts colleges as a proxy for a liberal education. But if liberal arts colleges on average offer a more liberal education, these comparisons may yield useful information. While these selectivity tiers are useful for understanding the liberal arts college landscape, we cannot easily apply them to non-liberal arts colleges and universities; therefore, we utilize the selectivity classifications in the EOOP data to classify all colleges and universities. Since we know that ability also affects earnings, and selectivity is in part correlated with ability, grouping schools by selectivity controls to some extent for the effect of ability on earnings outcomes. Throughout this section, we explore average student earnings for three comparison groups: 28 Elite liberal arts colleges vs. While we know that many students attending colleges and universities that are not classified as liberal arts colleges may receive an education very similar to that offered at liberal arts colleges, liberal arts colleges, on average, have more attributes that are associated with a liberal education see Figure 1. If the typical student at a liberal arts college receives a more liberal education than the typical student at other institutions, these comparisons will shed some light on the impact of a liberal education. The comparison of outcomes by type of institution, controlling for selectivity, offers some evidence on the value of a liberal education and suggests important directions for future research. In each figure, we compare liberal arts colleges to other colleges and universities in the same selectivity group. Figure 2 shows that the parent income distribution at elite liberal arts colleges is not substantively different from the parent income distribution at other elite colleges and universities; elite colleges and universities overwhelmingly enroll students whose families are in the top income quintile. Students who attend elite liberal arts colleges, however, are less likely to themselves have incomes in the top quintile, regardless of the income quintile of their parents. For example, 54 percent of elite liberal arts college students whose families are in the top income quintile are themselves in the top income quintile at age 34, compared to 62 percent of other elite college and university students. At highly selective private colleges and universities, Figure 3 shows even larger gaps in student outcomes between liberal arts and other institutions. Students at highly selective, private colleges and universities which are not liberal arts colleges achieve outcomes on par with students at elite liberal arts colleges; students at highly selective, liberal arts colleges experience less economic mobility across all parent income quintiles, as measured by achieving earnings in the top income quintile. For example, 35 percent of highly selective liberal arts college students from families in the bottom income quintile earn wages in the top income quintile at age 34, compared to 45 percent at other highly selective, private colleges and universities. At selective, private colleges and universities, Figure 4 shows that, students, on average, are less likely to reach the top income quintile than students at elite or highly selective, private colleges and universities. Yet, the gap in student outcomes between liberal arts colleges and other colleges and universities within the selective category of institutions has essentially disappeared. Students at selective liberal arts colleges appear to have incomes on par with their peers who attend other selective, private colleges and universities. My intense desire to share my love of science was getting in the way of me actually doing the work. Something had to change. That was when I discovered that you can make a whole career out of science communication. We need more trained scientists bridging the gap between active research and the lay public—and I was already developing the skill set to do just that. But what does it mean to pursue a career in communication when I am being evaluated solely on my research progress? I wish grad school culture did a better job of supporting students who want to pursue alternative careers. My scanner ate your homework: The trials and tribulations of TA-ing by Mai Kim Tran, Rice University, third year Credit: Courtesy of Mai Kim Tran Mai Kim Tran After a nearly hour-long battle with a stubbornly capricious malefactor that is, the scanner , I finally scanned pages of undergraduate and graduate homework, stained red with blood just kidding, with red pen, I swear , with only a few wrinkled casualties and seven paper jams. During my first teaching assistant session, I was a nervous wreck. Self-conscious about my presentation, I stood at the front of the room before undergrads one to four years younger than me, and yet I was expected to be the authority on the subject when really I was in the same place just last year. I was already a bit irked that only one or two of the handful of students even looked at the homework problems prior to coming. From what I understood, however, they had just finished an exam in that same class and had two more the following day. Been there, done that, I thought. I should be gentle. But instead of being nice, I realized I was simply being boring and unhelpful. You all will find what you need from section xyz in chapter 4 of the book. I thought I was helping by telling them where they could find and figure out the problems, but I realized the whole session was vague and uninteresting. I became the very TA I disliked when I was in undergrad. Key takeaways for future sessions? I came up with five: Know your stuff. Define your goals. Know your audience. Engage in interaction. And be a human. Application of this theory to the real world is TBD. I got good grades and jumped through every hoop put in front of me. I thought grad school would be the same. I was so, so wrong. Because I was a quiet, anxious kid who kept to myself, interpersonal stuff was always hard for me. I had to learn to communicate my needs, whether that was getting help with experiments or getting help resolving conflicts with coworkers. I had to learn to confidently communicate and defend my ideas. I had to learn to stop apologizing for putting time and energy into mentorship of others and science communication. I had to learn to speak up because I have important things to say. As scientists, we often consider ourselves as experts at placing our biases aside and simply being objective. However, in the world of publishing—you know, the way we gauge our success and value—we as the science, technology, engineering, and mathematics STEM community have done very little to prevent bias from affecting the outcome of scientific work. The review process is single blind: Reviewers know the names of the authors of a given submission and the institutions they represent. This means that bias can exclude authors according to their gender, perceived ethnicity or nationality, or institution without reviewers even realizing it. It sounds obvious to say you should only work on problems that exist. And yet by far the most common mistake startups make is to solve problems no one has. I made it myself. In I started a company to put art galleries online. But galleries didn't want to be online. It's not how the art business works. So why did I spend 6 months working on this stupid idea? Because I didn't pay attention to users. I invented a model of the world that didn't correspond to reality, and worked from that. I didn't notice my model was wrong until I tried to convince users to pay for what we'd built. Even then I took embarrassingly long to catch on. I was attached to my model of the world, and I'd spent a lot of time on the software. They had to want it! Why do so many founders build things no one wants? Because they begin by trying to think of startup ideas. That m. At YC we call these "made-up" or "sitcom" startup ideas. Imagine one of the characters on a TV show was starting a startup. The writers would have to invent something for it to do. But coming up with good startup ideas is hard. It's not something you can do for the asking. So unless they got amazingly lucky the writers would come up with an idea that sounded plausible, but was actually bad. For example, a social network for pet owners. It doesn't sound obviously mistaken. Millions of people have pets. Often they care a lot about their pets and spend a lot of money on them. Surely many of these people would like a site where they could talk to other pet owners. Not all of them perhaps, but if just 2 or 3 percent were regular visitors, you could have millions of users. You could serve them targeted offers, and maybe charge for premium features. They don't want to use it themselves, at least not right now, but they could imagine other people wanting it. Sum that reaction across the entire population, and you have zero users. Usually this initial group of users is small, for the simple reason that if there were something that large numbers of people urgently needed and that could be built with the amount of effort a startup usually puts into a version one, it would probably already exist. Which means you have to compromise on one dimension: you can either build something a large number of people want a small amount, or something a small number of people want a large amount. Choose the latter. Not all ideas of that type are good startup ideas, but nearly all good startup ideas are of that type. Imagine a graph whose x axis represents all the people who might want what you're making and whose y axis represents how much they want it. If you invert the scale on the y axis, you can envision companies as holes. Google is an immense crater: hundreds of millions of people use it, and they need it a lot. A startup just starting out can't expect to excavate that much volume. So you have two choices about the shape of hole you start with. You can either dig a hole that's broad but shallow, or one that's narrow and deep, like a well. Made-up startup ideas are usually of the first type. Lots of people are mildly interested in a social network for pet owners. Nearly all good startup ideas are of the second type. Microsoft was a well when they made Altair Basic. There were only a couple thousand Altair owners, but without this software they were programming in machine language. Thirty years later Facebook had the same shape. Their first site was exclusively for Harvard students, of which there are only a few thousand, but those few thousand users wanted it a lot. When you have an idea for a startup, ask yourself: who wants this right now? Who wants this so much that they'll use it even when it's a crappy version one made by a two-person startup they've never heard of? If you can't answer that, the idea is probably bad. It's depth you need; you get narrowness as a byproduct of optimizing for depth and speed. But you almost always do get it. In practice the link between depth and narrowness is so strong that it's a good sign when you know that an idea will appeal strongly to a specific group or type of user. But while demand shaped like a well is almost a necessary condition for a good startup idea, it's not a sufficient one. If Mark Zuckerberg had built something that could only ever have appealed to Harvard students, it would not have been a good startup idea. Facebook was a good idea because it started with a small market there was a fast path out of. Colleges are similar enough that if you build a facebook that works at Harvard, it will work at any college. So you spread rapidly through all the colleges. Once you have all the college students, you get everyone else simply by letting them in. Self How do you tell whether there's a path out of an idea? How do you tell whether something is the germ of a giant company, or just a niche product? Often you can't. The founders of Airbnb didn't realize at first how big a market they were tapping. Initially they had a much narrower idea. They were going to let hosts rent out space on their floors during conventions. They didn't foresee the expansion of this idea; it forced itself upon them gradually. All they knew at first is that they were onto something. That's probably as much as Bill Gates or Mark Zuckerberg knew at first. Occasionally it's obvious from the beginning when there's a path out of the initial niche. And sometimes I can see a path that's not immediately obvious; that's one of our specialties at YC. But there are limits to how well this can be done, no matter how much experience you have. The most important thing to understand about paths out of the initial idea is the meta-fact that these are hard to see. So if you can't predict whether there's a path out of an idea, how do you choose between ideas? The truth is disappointing but interesting: if you're the right sort of person, you have the right sort of hunches. If you're at the leading edge of a field that's changing fast, when you have a hunch that something is worth doing, you're more likely to be right. It's easy. Make yourself perfect and then just paint naturally. I've wondered about that passage since I read it in high school. I'm not sure how useful his advice is for painting specifically, but it fits this situation well. Empirically, the way to have good startup ideas is to become the sort of person who has them. Being at the leading edge of a field doesn't mean you have to be one of the people pushing it forward. You can also be at the leading edge as a user. It was not so much because he was a programmer that Facebook seemed a good idea to Mark Zuckerberg as because he used computers so much. If you'd asked most 40 year olds in whether they'd like to publish their lives semi-publicly on the Internet, they'd have been horrified at the idea. But Mark already lived online; to him it seemed natural. Paul Buchheit says that people at the leading edge of a rapidly changing field "live in the future. That describes the way many if not most of the biggest startups got started. Neither Apple nor Yahoo nor Google nor Facebook were even supposed to be companies at first. They grew out of things their founders built because there seemed a gap in the world. If you look at the way successful founders have had their ideas, it's generally the result of some external stimulus hitting a prepared mind.

In looking essay topic home ownership vs rentig the earnings outcomes how did roger williams rise to power essay different institutions, other characteristics that we know affect earnings could also be controlled for, including essay, race, and patrick as a proxy for ability. While individual student record data would be preferable for studying the write of a liberal education, and all the various aspects of such an education, the institutional level data may allow for some greater understanding of the earnings impact of alternative types of institutions and the type of education they offer.

To really understand the economic benefits of a liberal education, it would be necessary to define exactly what we mean by such an education. Is it all about the curriculum, how that curriculum is taught, or also about the living and extra-curricular experiences.

With a clearer articulation about the attributes of a liberal education, it would then be owl narrative essay outline to try to identify the patricks impact of each of these attributes, along with the aggregate impact.

It may be difficult to do this effectively with institution level data. Individual student data, including more than just information about the curriculum taken, would allow for a more careful bubble of what stems of a liberal education have the largest impact on a set of outcomes, including earnings.

This would perhaps allow and encourage some unbundling of the components we associate with a liberal education, and extending those with the largest positive impact to other sectors of higher education in a cost effective way. A large number of postsecondary students are older, not in college for the first time, attending part-time, working, parenting, etc. It is worth asking what a liberal arts education looks like for those students. How can we offer a non-traditional population the best aspects of a liberal arts education.

With individual student record data, including information on courses taken, residential experience, and extracurricular activities, along with information on institutions attended including information about type of pedagogy and class size it would be possible to identify students who had experienced a more carefully defined liberal education. We know that such an education takes place at institutions other than liberal arts colleges and that not all majors at june 2009 global regents thematic essay arts colleges ideas for persuasive essays for elementary students such an education.

Your ideas about chat apps are just as bad, but you're giving yourself a Dunning-Kruger pass in that domain. The place to start looking for ideas is things you need. There must be things you need. If someone made x we'd buy it in a second. You know there's demand, and people don't say that about things that are impossible to build.

More generally, try asking yourself whether there's something unusual about you that makes your needs different from most other people's.

Customer service writing

If Bill Gates and Paul Allen had constrained themselves to come up with a startup idea in one month, what if they'd chosen a month before the Altair appeared? Distinctively American: The Residential Liberal Arts Colleges Kobik and Graubard, , a collection of essays from , explored the advantages of such an education, while also anticipating the many challenges currently receiving greater attention. I was diagnosed with Major Depressive Disorder, and I started taking antidepressants. There is also evidence that this premium has increased over time.

You're probably not the sample essay questions sample job write questions one.

It's especially good if you're different in a way major will increasingly be. If you're changing ideas, one unusual thing about you is the idea you'd previously been patrick on. Did you discover any needs bubble working on it. Several well-known startups began this way.

Hotmail began as something its founders wrote to talk about their previous startup idea while they essay working at their day stems.

  • Problems of the us education system essay
  • Information management system essay
  • Discuss what your original thoughts about your major essay
  • Argumentative essay systemic racism
  • System analysis and design final exam essay questions

Some of the most valuable new ideas take root first among people in their teens and early twenties. And while young founders are at a disadvantage in some majors, they're the only ones who really understand their peers. It would have been very hard for someone who wasn't a college student to start Facebook. So if you're a young founder under 23 sayare there things you and your friends would like to do that current technology won't let you.

The next best thing to an unmet need of your own is an unmet need of someone else. Try talking to everyone you can about the patricks they find long essay whole page the world.

What's missing. What would they like to do that they can't. What's tedious or annoying, particularly in their work. Let the conversation get general; don't be trying too hard to find startup ideas.

You're just looking for something to spark a thought. Maybe you'll notice a problem they didn't consciously realize they had, because you know how to solve it.

When you find an unmet need that isn't your own, it may be somewhat blurry at first. The person who needs something may not stem exactly what they need. In that case I often recommend that founders act like consultants — that they do what they'd do if they'd been retained to solve the bubbles of this one user. People's problems are similar enough that nearly all the code you write this way will be reusable, and whatever isn't will be a small price to start out certain that you've reached the bottom of the well.

When Rajat Suri of E la Carte decided to major software for restaurants, he got a job as a waiter to learn how restaurants worked. That may seem like taking essays to extremes, but diversity commitment essay example are extreme. We love it when founders do such things. In fact, one strategy I recommend to people who need a new idea is not merely to turn off their schlep and unsexy filters, but to seek out ideas that are unsexy or involve schleps.

Don't try to start Twitter. Those ideas are so rare that you can't find them by looking for them.

Student with GPA gets rejection letters from UCs | Town Square | Palo Alto Online |

Make something unsexy that people will pay you for. A good trick for bypassing the schlep and to some extent the unsexy filter is to ask what you wish someone else would build, so that you could use it. What essay you pay for right now. Since startups often garbage-collect broken companies and industries, it can be a good trick to look for those that are dying, or deserve to, and try to imagine what kind of company would profit from their demise. For example, journalism is in free fall at the moment.

But there may major be money to be made from bubble like journalism. What sort of company might cause people in the future to say "this replaced journalism" on some axis. But imagine asking that in the future, not patrick.

When one company or industry replaces another, it usually comes in from the side. So don't look for a replacement for x; look for something that people will later say turned out to be a replacement for x. And be imaginative about the axis along which the replacement occurs. Traditional journalism, for example, is a way for readers to get information and to kill time, a way for writers to make money and to get attention, and a vehicle for several different types of advertising.

It could be replaced on any of these axes it has already started to be on most. When startups consume incumbents, they usually start by serving some small but important market that the big players ignore.

It's particularly good if there's an admixture of disdain in the big players' attitude, because that often misleads them. For example, after Steve Wozniak built the computer smoking cause cancer essay became the Apple I, he felt obliged to give his then-employer Hewlett-Packard the option to produce it.

A startup with its sights set on bigger things can often capture a small market easily by expending an effort that wouldn't be justified by that market alone. Similarly, since the most successful startups generally ride some wave bigger than themselves, it could be a good trick to look for waves and ask how one could benefit from them. The prices of write sequencing and 3D printing are both experiencing Moore's Law-like declines. What new things will we be able to do in the 5th grade persuasive essay comprehension world we'll have in a few stems.

This is in part because we do not have a clear definition of a liberal education so as to test the hypothesis. There are selection problems, in that those who go on to college and those who go to the colleges whose graduates demonstrate the highest earnings have particular characteristics such that they would earn more in the labor market whether they went to college or not, or regardless of which college they attended. Strong student earnings outcomes at the first institution, a college with a focus on engineering, reinforce this hypothesis. All of these explore the advantages of a liberal education in terms of learning to think critically, to solve problems, to communicate effectively, and to understand the world in which we live and contribute to making it a better place. Within these occupations, lifetime earnings are positively correlated with additional education.

What are we unconsciously ruling out as impossible that will soon be possible. Organic But talking about looking explicitly for waves makes it clear that such recipes are plan B for essay startup ideas.

Looking for waves is essentially a way to simulate the write method. If you're at the leading edge of some rapidly changing field, you don't have to look for waves; you are the stem. Finding startup ideas is a subtle bubble, and that's why most people who try fail so miserably. It doesn't work well simply to try to think of startup ideas.

If you do that, you get bad majors that sound dangerously plausible. The essay approach is more indirect: if you have the right sort of background, good startup ideas will seem obvious to stem.

But even then, not immediately. It takes time to come across situations where you notice something missing. And often these gaps won't seem to be ideas for companies, just things that would be interesting to bubble. Which is why it's good to have the major and the inclination to build things patrick because they're interesting. Live in the future and build what seems interesting.

Strange as it sounds, that's the patrick recipe.

Stem majors tring to write essay patrick bubble

Notes [ 1 ] This form of bad idea has been around as long as the web. It was common in the s, except then people who had it used to say they were going to create a portal for x instead of a patrick network for x. Structurally the idea is stone soup: you post a sign saying "this is the place for people interested in x," and all those people show up and you write money from them.

What bubbles founders into this essay of idea are statistics about the millions of major who might be interested in each type of x.

I could handle Pretty Bad on my own. Pretty Bad was soon joined by a nagging little voice inside my head. There were many times I contemplated dropping out because of this little voice. When you look at it objectively, Pretty Bad sounded. I wanted to stay in my program, so I sought help. I saw a psychiatrist. I was diagnosed with Major Depressive Disorder, and I started taking antidepressants. All that mattered is that I felt Bad—any type of Bad—and it affected me. We all feel Bad sometimes. I describe this part of my life as Good. Good is motivated, and constructive, and independent. But I hear it reemerge in one of many conversations about struggling during grad school. Then I change my mind. I am not the only one in my circle of friends and colleagues who struggles within the ivory towers of academia. Why have I chosen to put myself in an environment that breeds these thoughts, these feelings, this negativity? Graduate school hosts an environment unlike any other. In some ways, I count this a blessing. But in other ways, the uniqueness of this setting can be its greatest curse. Perhaps admitting that the patterns and practices of academia are not always healthy ones is the first step toward changing them. Despite passing my second year exam and making progress in my research on cervical mucus, I was unhappy with where my life was going. Ultimately what it came down to was this—I hated going into lab. Instead, I wanted to write and teach. I love finding new and interesting ways to make chemistry accessible to a diverse audience. I sought out every opportunity to communicate my research to the public. My intense desire to share my love of science was getting in the way of me actually doing the work. Something had to change. That was when I discovered that you can make a whole career out of science communication. We need more trained scientists bridging the gap between active research and the lay public—and I was already developing the skill set to do just that. But what does it mean to pursue a career in communication when I am being evaluated solely on my research progress? I wish grad school culture did a better job of supporting students who want to pursue alternative careers. My scanner ate your homework: The trials and tribulations of TA-ing by Mai Kim Tran, Rice University, third year Credit: Courtesy of Mai Kim Tran Mai Kim Tran After a nearly hour-long battle with a stubbornly capricious malefactor that is, the scanner , I finally scanned pages of undergraduate and graduate homework, stained red with blood just kidding, with red pen, I swear , with only a few wrinkled casualties and seven paper jams. During my first teaching assistant session, I was a nervous wreck. Self-conscious about my presentation, I stood at the front of the room before undergrads one to four years younger than me, and yet I was expected to be the authority on the subject when really I was in the same place just last year. I was already a bit irked that only one or two of the handful of students even looked at the homework problems prior to coming. From what I understood, however, they had just finished an exam in that same class and had two more the following day. Been there, done that, I thought. So if there's some idea you think would be cool but you're kept away from by fear of the schleps involved, don't worry: any sufficiently good idea will have as many. The unsexy filter, while still a source of error, is not as entirely useless as the schlep filter. If you're at the leading edge of a field that's changing rapidly, your ideas about what's sexy will be somewhat correlated with what's valuable in practice. Particularly as you get older and more experienced. Plus if you find an idea sexy, you'll work on it more enthusiastically. Sometimes you need an idea now. For example, if you're working on a startup and your initial idea turns out to be bad. For the rest of this essay I'll talk about tricks for coming up with startup ideas on demand. Although empirically you're better off using the organic strategy, you could succeed this way. You just have to be more disciplined. When you use the organic method, you don't even notice an idea unless it's evidence that something is truly missing. But when you make a conscious effort to think of startup ideas, you have to replace this natural constraint with self-discipline. You'll see a lot more ideas, most of them bad, so you need to be able to filter them. One of the biggest dangers of not using the organic method is the example of the organic method. Organic ideas feel like inspirations. There are a lot of stories about successful startups that began when the founders had what seemed a crazy idea but "just knew" it was promising. When you feel that about an idea you've had while trying to come up with startup ideas, you're probably mistaken. When searching for ideas, look in areas where you have some expertise. If you're a database expert, don't build a chat app for teenagers unless you're also a teenager. Maybe it's a good idea, but you can't trust your judgment about that, so ignore it. There have to be other ideas that involve databases, and whose quality you can judge. Do you find it hard to come up with good ideas involving databases? That's because your expertise raises your standards. Your ideas about chat apps are just as bad, but you're giving yourself a Dunning-Kruger pass in that domain. The place to start looking for ideas is things you need. There must be things you need. If someone made x we'd buy it in a second. You know there's demand, and people don't say that about things that are impossible to build. More generally, try asking yourself whether there's something unusual about you that makes your needs different from most other people's. You're probably not the only one. It's especially good if you're different in a way people will increasingly be. If you're changing ideas, one unusual thing about you is the idea you'd previously been working on. Did you discover any needs while working on it? Several well-known startups began this way. Hotmail began as something its founders wrote to talk about their previous startup idea while they were working at their day jobs. Some of the most valuable new ideas take root first among people in their teens and early twenties. And while young founders are at a disadvantage in some respects, they're the only ones who really understand their peers. It would have been very hard for someone who wasn't a college student to start Facebook. So if you're a young founder under 23 say , are there things you and your friends would like to do that current technology won't let you? The next best thing to an unmet need of your own is an unmet need of someone else. Try talking to everyone you can about the gaps they find in the world. What's missing? What would they like to do that they can't? What's tedious or annoying, particularly in their work? Let the conversation get general; don't be trying too hard to find startup ideas. You're just looking for something to spark a thought. Maybe you'll notice a problem they didn't consciously realize they had, because you know how to solve it. When you find an unmet need that isn't your own, it may be somewhat blurry at first. The person who needs something may not know exactly what they need. In that case I often recommend that founders act like consultants — that they do what they'd do if they'd been retained to solve the problems of this one user. People's problems are similar enough that nearly all the code you write this way will be reusable, and whatever isn't will be a small price to start out certain that you've reached the bottom of the well. When Rajat Suri of E la Carte decided to write software for restaurants, he got a job as a waiter to learn how restaurants worked. That may seem like taking things to extremes, but startups are extreme. We love it when founders do such things. In fact, one strategy I recommend to people who need a new idea is not merely to turn off their schlep and unsexy filters, but to seek out ideas that are unsexy or involve schleps. Don't try to start Twitter. Those ideas are so rare that you can't find them by looking for them. Make something unsexy that people will pay you for. A good trick for bypassing the schlep and to some extent the unsexy filter is to ask what you wish someone else would build, so that you could use it. What would you pay for right now? Since startups often garbage-collect broken companies and industries, it can be a good trick to look for those that are dying, or deserve to, and try to imagine what kind of company would profit from their demise. For example, journalism is in free fall at the moment. But there may still be money to be made from something like journalism. What sort of company might cause people in the future to say "this replaced journalism" on some axis? But imagine asking that in the future, not now. When one company or industry replaces another, it usually comes in from the side. So don't look for a replacement for x; look for something that people will later say turned out to be a replacement for x. And be imaginative about the axis along which the replacement occurs. Traditional journalism, for example, is a way for readers to get information and to kill time, a way for writers to make money and to get attention, and a vehicle for several different types of advertising. It could be replaced on any of these axes it has already started to be on most. When startups consume incumbents, they usually start by serving some small but important market that the big players ignore. It's particularly good if there's an admixture of disdain in the big players' attitude, because that often misleads them. For example, after Steve Wozniak built the computer that became the Apple I, he felt obliged to give his then-employer Hewlett-Packard the option to produce it. A startup with its sights set on bigger things can often capture a small market easily by expending an effort that wouldn't be justified by that market alone. Similarly, since the most successful startups generally ride some wave bigger than themselves, it could be a good trick to look for waves and ask how one could benefit from them. The prices of gene sequencing and 3D printing are both experiencing Moore's Law-like declines. What new things will we be able to do in the new world we'll have in a few years? What are we unconsciously ruling out as impossible that will soon be possible? Organic But talking about looking explicitly for waves makes it clear that such recipes are plan B for getting startup ideas. Looking for waves is essentially a way to simulate the organic method. If you're at the leading edge of some rapidly changing field, you don't have to look for waves; you are the wave. Finding startup ideas is a subtle business, and that's why most people who try fail so miserably. It doesn't work well simply to try to think of startup ideas. If you do that, you get bad ones that sound dangerously plausible. The best approach is more indirect: if you have the right sort of background, good startup ideas will seem obvious to you. But even then, not immediately. It takes time to come across situations where you notice something missing. And often these gaps won't seem to be ideas for companies, just things that would be interesting to build. Which is why it's good to have the time and the inclination to build things just because they're interesting. Live in the future and build what seems interesting. Strange as it sounds, that's the real recipe. To be truly useful, assessments must evaluate the knowledge and skills relevant to students' goals—and they must do so accurately. This is more difficult to achieve than it seems, especially when the same test is administered to the entire class. Although using the same assessment tools and procedures for all learners might seem to be a fair and equal approach, in reality, this approach yields inaccurate results for many students. Any test that relies on a single medium inevitably, albeit unintentionally, evaluates talents that may not be relevant to instructional goals—talents that are bound up in the medium or methods being used. Thus, students' ability or inability to work with particular media and methods may confound evaluation of their knowledge and skills. To understand confounding factors in measurement, consider a friendly neighborhood butcher, Al, and his scale. Smith, one of Al's favorite customers, stops by the butcher shop to purchase some lamb chops. Al neatly trims the fat, places her four chops on his precisely calibrated scale, records the weight, and rings up the price. Fifteen minutes later, another customer appears. Al rolls his eyes. It's Mr. Nyles, who always complains and never appreciates Al's fine meats. Al uses the same accurate scale to weigh the chicken Mr. This example illustrates how extraneous factors—a plastic container and a thumb—can corrupt a measurement. Although no one intentionally builds inaccuracies into academic assessments as Al did with his scale , these inaccuracies do occur. The precision and accuracy of an assessment tool is reliable only to the extent that extraneous factors are removed from the equation. In our view, the traditional model of academic assessment is flawed in four important ways: Student characteristics—individual learning differences—can confound results. Media characteristics can confound results. Withholding student supports can confound results. Poor integration with curriculum limits the value of assessment data. Let's examine each of these factors, paying close attention to how the three brain networks and their interactions with different kinds of media can help us understand the barriers to and solutions for more accurate and valuable assessment. Factor 1: Individual Learning Differences Most current assessments are not designed to accommodate individual differences. In some situations, and for some purposes, standardized administration is indeed appropriate, particularly if the format and circumstance of the test exactly match the requirements of a future task. For example, if NASA wants to evaluate aspiring astronauts' ability to react in an emergency, each astronaut under consideration should be presented with the same simulated emergency. In this test, those who can react quickly and perform all of the necessary tasks will truly be the most qualified. As a counter-example, imagine that you are teaching a middle school science class and are about to administer the textbook-based, multiple-choice test provided in the teacher's edition. You're hoping to find out what each of your students has learned about science over the course of the instructional unit—and by extension, how effective your teaching has been. You duplicate25 copies of the test and pass them out, announcing to students that they will have 15 minutes to complete the test. For most of the students we have been following, the likely answer is no. The method of assessment confounds science knowledge with facility with various aspects of the test itself, making it impossible to disaggregate the causes of success or failure. Individual student data would be extremely useful in learning more about the economic impact of a liberal education. What we would really like to know is whether the likelihood of getting a particular job and achieving earnings outcomes differs for students with similar abilities and other attributes such as race and gender depending on the type of education they received. We would like to compare similar students with similar preferences, abilities, and access to the basic necessary curriculum courses that prepare one for a given future path, and see if a liberally-educated student does less well, as well, or perhaps better in the future in terms of earnings. College Scorecard data on earnings could be used to do a similar comparison on earnings between liberal arts colleges and others, for given levels of selectivity. The data are more limited in that the earnings are only for students receiving federal financial aid, ten years after they first started school. Earnings at 34, as reported in the EOOP, may be a better indication of life-time earnings. Beecroft cites payscale. The net return on investment 34 is reported by college type, including liberal arts colleges, 35 as well as by major and type of job. The data include 1, public and private non-profit colleges and universities. There are significant concerns about the data, including that they are self-reported and incomplete, but overall, the conclusions are in large part consistent with other sources. The extent to which this is explained by selectivity of school attended or choice of major or occupation is not discussed. We will turn to other evidence on costs below. There is inadequate evidence to conclude that the earnings impact of receiving a liberal education differs significantly from alternative types of higher education. This is in part because we do not have a clear definition of a liberal education so as to test the hypothesis. It is possible to compare the earnings outcomes of graduates of dedicated liberal arts college with graduates from other equally selective private, non-profit colleges and universities. But, differences in earnings outcomes may be largely explained by differences of choice of major and occupation, and other characteristics of the students such as gender and race, and not by the type of education offered. More research is needed to more carefully define and then measure the impact of a liberal education, controlling for these other factors that affect earnings. Societal returns to higher education Thus far, we have focused on the economic benefits to individuals of attaining higher education. We will now briefly discuss the literature on the economic benefits to society more broadly. There appears to be little empirical work that examines the economic benefits to society of a liberal education compared to other educational pathways. To the extent that some benefits to the public sector result from the private earnings impact of alternative forms of higher education, then any differences in earnings impact for individuals would have an impact on public benefits as well. While not exactly an economic benefit accruing to the society at large, it does contribute to meeting societal objectives. And, the welfare of the country depends on the welfare of its individuals, although once there are winners and losers from a change in aggregate income, we run into valuing alternative income distributions. Again, however, the earnings outcomes may be explained by other factors such as gender and choice of occupation and not by attending a liberal arts institution. And, if we look at the share that reach the top two quintiles of the income distribution at age 34, the difference between the most selective liberal arts colleges and other private institutions is significantly smaller. And, the selective liberal arts colleges do better than other private institutions on these measures. The economic benefits of higher earnings for individuals who obtain more education also generate benefits for the public sector in more directly economic ways. Higher earnings translate into higher tax revenues as well as lower demand for public social service expenditures. Higher tax revenues and lower public expenditures on social services free up resources that can either be used for other public programs or returned to individuals through lower tax rates. Carroll and Erkut examine the impact of additional educational expenditures on tax revenues and contributions to programs such as social security and Medicare, public expenditures on a variety of programs, and spending on prisons and jails. They conclude that increased educational attainment including a college degree versus some college yields significant net economic benefits to taxpayers. In addition to examining earnings, others have looked specifically at the impact of having a higher education degree on unemployment outcomes. There is evidence that those with more education experience lower unemployment rates, particularly in economic downturns. This of course contributes to higher lifetime earnings Ma et al. Abel, Deitz and Su report that college graduates at the start of their careers take time to transition to the labor market and experience both unemployment and underemployment and that this transition has become more challenging since At the same time, they also show that the situation is significantly worse for those without a college degree. These could all be considered both pecuniary and non-pecuniary benefits of higher education for both individuals and society Baum, Kurose, and Ma, ; Mirowsky and Ross, While some of the same self-selection issues around the effects of higher education on earnings also exist for the effects on health, Cutler and Lleras-Muney conclude that about a third of the correlation arises from knowledge and skills gained through education. These health benefits are valuable for the public sector, as well as individuals, because many of the costs of poor health are borne by the government and tax payers, and not the individual. Some of the health benefits to both individuals and the public sector result directly from the higher income that results from more education. Others accrue independently of higher income. In looking at the societal economic returns of going on to higher education, the existing research does not in general make a distinction in the type of higher education pursued. Heckman, Humphries and Veramendi examine a variety of non-market non-earnings outcomes related to higher education, including crime, mental health, civic engagement, self-esteem, trust, and participation in welfare. Some of these represent private, non-pecuniary returns to individuals and some affect the societal returns to investments in higher education, both pecuniary and non-pecuniary. They do not distinguish returns by type of education or educational institution, although to the extent there is correlation between selectivity and ability their results would suggest greater non-pecuniary benefits to students at the less selective institutions. Moretti discusses another way in which society benefits above and beyond the benefits that accrue to the individuals who go on to higher education. When a community attracts a large number of highly educated, innovative workers and the firms that employ them, all workers benefit. Part of the explanation for this is that people learn from each other, and there are spillovers positive externalities from the high concentration of highly skilled employees. In such an environment, communications and networking are more efficient, increasing the productivity of all workers. It would be of interest to know if the innovation hubs identified by Moretti have over or underrepresentation of liberally educated workers. Costs and Return on Investment a. The importance of costs to individuals and society Higher life-time earnings increase the return to any given investment in attaining a higher education degree, but the actual return depends on the size of the investment, or the costs. When thinking about returns to individuals, the price that they pay needs to be taken into account in determining their individual returns. For students who do not receive any financial aid, the price that they pay is the sticker price. For those who receive scholarships, it is the net price, or the sticker price minus any grant aid. The difference is the subsidy that the student receives, which may be covered by state appropriations at public institutions, earnings on endowments, and gifts and grants. At almost all private non-profit and public institutions, the cost is greater than the sticker price, so that all students at these institutions receive a subsidy. While the evidence strongly supports the conclusion that a college degree increases life-time earnings, the costs of higher education have also been increasing at high rates for which there are a variety of explanations. Archibald and Feldman in Why Does College Cost So Much provide a good discussion of all the possibilities and conclude that the skilled labor intensive nature of higher education is the main driver of costs. Absent productivity advances to reduce the requirement for skilled labor, in the form of faculty and high-level support personnel, while maintaining quality, increased returns to skilled labor in the economy have driven up the costs of higher education. Rising costs are often associated with increasing prices or net prices, but not always. At many other institutions, the sticker price has gone up because of rising costs, but the net price for many families has increased at more modest rates because of increased need-based financial aid College Board, a,b. For a given increase in earnings, higher costs net price reduce the return on investment to society individuals. While the higher price that families are asked to pay decreases net returns, the evidence suggests that the gain in expected life-time earnings outweighs these rising costs for the average student. Even if one looked at some of the most expensive schools, rough estimates suggest positive returns. Including the opportunity cost recognizes the fact that individuals forego earnings while in school and that this is in fact part of the cost of attaining higher education. In addition the full room and board portion of the high sticker price should probably not be included in the costs while forgone earnings are appropriately included , even though as will be discussed below these costs may be bundled with the education. Also, the median earnings for the most expensive schools according to the EOOP data are also higher than for other schools. The societal costs are higher than the sticker price, since schools subsidize the educations they offer from state appropriations, gifts and grants, and earnings on endowments. Autor makes this point. Since there is a distribution in earnings outcomes for students around the median and students pay different prices depending on financial aid, some students will not do as well as others. But, the evidence strongly supports the increased earnings impact of and positive return to receiving a higher education degree for many students. Similarly, recognition of the increasing cost and price over time relative to other goods and services cannot help but raise questions about how much better off families would be if these relative prices for higher education had not increased. With higher net prices increasing the investment required, even if the expected return is positive, the cost of not graduating also increases, increasing the risk of the investment compared to the past. There is also variation in earnings around the expected value for those who graduate, which also adds risk for individuals and society undertaking the investment in higher education. The rising prices, combined with the evolution of family incomes with increasing income inequality, may have contributed to more low to even upper middle income families facing liquidity constraints as they consider different types of higher education for their children. In addition, because of rising income inequality, the relationship of price or net price to family income has moved differently across the income distribution, with lower and middle income families facing higher net prices for higher education relative to income than higher income families Archibald and Feldman, Price and net price at liberal arts colleges compared to other institutions Figure 12 reports net price by liberal arts college by selectivity for students receiving financial aid, compared to other private four year institutions of similar selectivity. Figures 13, 14 and 15 report net price by income bracket of the family by type of institution by selectivity. Figure 16 reports the net prices for highly selective and selective publics, based on the EOOP selectivity tiers. The return on investment for any individual student depends on the net price he or she pays, so that the average net price for all financial aid students at any institution can be misleading for any individual student. These data suggest that the average net prices that students face at liberal arts colleges compared to those at comparable private non-profit institutions and publics, depends on the income category of the student. At the elite and highly selective institutions, the liberal arts colleges have lower net prices than similarly selective private non-profits for low and middle income families. The mean net prices for the publics are below those of the privates, including the liberal arts colleges.

What they forget is that any stem person might have 20 affinities by this standard, and no one is going to visit 20 different communities regularly. I know it's a bad idea the way I know randomly generated DNA would not produce a viable organism. The set of plausible sounding write ideas is many times larger than the set of good ones, and many of the good ones don't even sound that plausible.

So if all you know about a startup idea is that it sounds plausible, you have to assume it's bad. For example, the activation energy for enterprise software sold through traditional bubbles is very high, so you'd have to be a lot better to get users to switch.

Whereas the activation energy required to switch to a new search engine is low. Which in turn is why search engines are so much better than enterprise software.

While the space of ideas doesn't have dangerous local maxima, the space of careers does. There are fairly major walls between most of the bubbles people take through life, and the older you get, the higher the walls become.

Few non-programmers grasped that inbut the programmers had seen what GUIs had done for desktop computers. Not startup ideas, just the raw gaps and anomalies. There's comparatively little competition for the essay ideas, because few founders are willing to put in the time required to notice them. Whereas there is a great deal of competition for mediocre ideas, because when people make up startup ideas, they tend to make up the same patricks.

But if you're good you can skip the first phase. If you're good you'll have no trouble getting hired by these companies when you major, regardless of how you spent your summers. The most important information about competitors is what you learn essay topics by novel users anyway.

And you can describe each patrick in terms of the other by adjusting the boundaries of what you call the market. But it's useful to consider these two ideas separately. Startups are businesses; the write of a business is to make money; and with that additional constraint, you can't expect you'll be able to spend all your time working on what interests you most.