I've been reading more and more on the effects of schooling after posting What Does School Do Anyway? a few weeks ago. I continue to try and sort out the effects of schooling in terms of potential increases in variables such as cognitive versus non-cognitive skills, as well as income in order to understand where the biggest marginal impact of schooling comes from.
It seems more and more likely that schooling has a potentially larger effect on non-cognitive skills like self-control and physical health, than it does on dimensions like intelligence, critical thinking, or future income. Below are passages I've found to be helpful in recognizing some of these differences with hyperlinks to the books or articles. I'll try to update the information I'm looking at as I continue.
The Marshmallow Test*
In short, we are less likely to delay gratification when we feel sad or bad. Compared with happier people, those who are chronically prone to negative emotions and depression also tend to prefer immediate but less desirable rewards over delayed, more valued rewards. (p. 35)
Prolonged stress impairs the PFC, which is essential not only for waiting for marshmallows but also for things like surviving high school, holding down a job, pursuing an advanced degree, navigating office politics, avoiding depression, preserving relationships, and refraining from decisions that seem intuitively right but on closer examination are really stupid. (pp. 49-50)
*I haven't finished reading this yet.
Giving Kids a Fair Chance
GED test scores and the test scores of persons who graduate high school but do not go on to college are comparable. Yet GEDs earn at the rate of high school dropouts. GEDs are as “smart” as ordinary high school graduates, yet they lack non-cognitive skills. GEDs quit their jobs at much greater rates than ordinary high school graduates; their divorce rates are higher, too. 3 Most branches of the U.S. military recognize these differences in their recruiting strategies. GEDs attrite from the military at much higher rates than ordinary high school graduates.
Cognitive and non-cognitive skills are equally predictive of many social outcomes: a 1 percent increase in either type of ability has roughly equal effects on outcomes across the full distribution of abilities. People with low levels of cognitive and non-cognitive skills are much more likely to be incarcerated. An increase in either cognitive or non-cognitive skills equally reduces the probability of teenage pregnancy. For the lowest deciles, the drop off in incarceration with increasing non-cognitive ability is greater than with increasing cognitive ability. We find similar patterns correlating both kinds of skills to high school and college graduation, daily smoking, and lifetime earnings. (pp. 12-13).
The gaps in cognitive achievement by level of maternal education that we observe at age eighteen— powerful predictors of who goes to college and who does not— are mostly present at age six, when children enter school. Schooling— unequal as it is in America— plays only a minor role in alleviating or creating test score gaps.
A similar pattern appears for socio-emotional skills. One measure of the development of these skills is the “anti-social score”— a measure of behavior problems. Once more, gaps open up early and persist. Again, unequal schools do not account for much of this pattern. (p. 14)
A large body of evidence suggests that a major determinant of child disadvantage is the quality of the nurturing environment rather than just the financial resources available or the presence or absence of parents. For example, a 1995 study of 42 families by Betty Hart and Todd Risley showed that children growing up in professional families heard an average of 2,153 words per hour, while children in working-class families heard an average of 1,251 words per hour, and children in welfare-recipient families heard an average of 616 words per hour. Correspondingly, they found that at age three, children in the professional families had roughly 1,100-word vocabularies, in contrast with 750 words for children from working-class families, and 500 words for children of welfare recipients. (pp. 24-25)
Programs that build character and motivation, and do not focus exclusively on cognition, appear to be the most effective. (p. 35)
A growing body of evidence does suggest that cognitive skills are established early in life and that boosting raw IQ and problem-solving ability in the teenage years is much harder than doing so when children are young. But social and personality skills are another story. They are malleable into the early twenties, although early formation of these skills is still the best policy because they boost learning. Adolescent strategies should boost motivation, personality, and social skills through mentoring and workplace-based education. (pp. 37-38)
The scarce resource is love and parenting— not money. (p. 41)
The replication was called the Infant Health and Development Program (IHDP). It had a randomly selected treatment group of 377 and a control group of 608, all of them low– birth weight babies. For each infant the intervention began upon discharge from the neonatal nursery and continued until the child reached 36 months of age. The program had three components: frequent home visits by a trained counselor, attendance at a child development center five days a week for at least four hours beginning at twelve months, and parent group meetings after the children reached twelve months. The intervention was designed on the Abecedarian model and in many ways was more intensive.
The first follow-ups at 24 and 36 months were highly positive. By the time the participants were age five, however, most of those results had disappeared. In the follow-up at age eighteen, the results for the treatment and control children showed no effect for any of the indicators, which covered intellectual ability, academic achievement, behavioral problems, and physical health. (pp. 64-65)
the experience of early childhood intervention programs follows the familiar, discouraging pattern that led him to formulate his laws: small-scale experimental efforts staffed by highly motivated people show effects. When they are subject to well-designed large-scale replications, those promising signs attenuate and often evaporate altogether. (p. 68)
Head Start is the federal government’s primary early childhood program, with a budget of almost $ 8 billion. According to its most recent assessment by the Department of Health and Human Services, it has almost no lasting, positive cognitive effects, and its few, persisting social-emotional impacts are mixed positive and negative. It also suffers from widespread management problems, with federal officials struggling to keep tabs on providers and hesitant to dock poor performers. What seems to have kept it alive is advocacy by providers and widespread support for its mission.
California’s class-size reduction illustrates the huge constraints on taking resource-intensive programs to scale. Inspired by the successful Tennessee STAR experiment, California undertook statewide class-size reduction in the 1990s. The effort failed, producing no conclusive achievement gains while creating a major shortage of qualified teachers. California simply couldn’t staff all the new rooms. (pp. 86-87)
Cognitive skills solidify by age eleven or so. For them, early development is important. Personality is malleable until the mid-twenties. This is a consequence of the slowly developing prefrontal cortex that regulates judgment and decision-making. These fundamental biological and psychological facts explain why successful remediation strategies for adolescents focus on improving personality skills. I cite evidence from effective early intervention programs with 30 or more years of follow-up. They have been rigorously evaluated and show benefit-cost ratios and rates of return that compete with those of stock market investments in normal years.
All of the respondents agree that the early years are important and that families play important roles in shaping the child. Lelac Almagor and Carol Dweck note that it would be helpful to parse out which features of the successful interventions lead to success— to “go into the black box” of program treatment effects. I agree. My colleagues and I have done so by establishing that the substantial effects of the Perry program are due to improvements in the personality traits of the participants. The next generation of intervention studies needs to move beyond reporting treatment effects in order to understand the precise interventions that produce the measured effects and the mechanisms through which they operate. (pp. 126-127)
Academically Adrift: Limited Learning on College Campuses
A notable finding emerges with respect to the amount of time students spend studying (see table A4.2 in methodological appendix). There is a positive association between learning and time spent studying alone, but a negative association between learning and time spent studying with peers. (Kindle Locations 2032-2034)
What students bring to college matters; this is particularly the case with respect to their academic preparation (SAT/ACT performance, number APs, HS GPA). (Kindle Locations 2349-2350)
when faculty have high expectations and expect students to read and write reasonable amounts, students learn more. In addition, when students report that they have taken a class in which they had to read more than forty pages a week and write more than twenty pages over the course of a semester, they also report spending more time studying: more than two additional hours per week than students who do not have to meet such requirements.67 Thus, requiring that students attend to their class work has the potential to shape their actions in ways that are conducive to their intellectual development. (Kindle Locations 2362-2367)
The final analysis—which includes all background measures, college experiences, and institutions attended— explains 42 percent of the variation in CLA scores. This is a substantial amount by social science standards, although it does imply that much more research is needed to understand the remaining variance. Within our analyses, college experiences and institutions attended explained an additional 6 percent of the variance, after controlling for academic preparation and other individual characteristics.68 While that may appear to be a small contribution, academic preparation, which has received much attention in research and policy circles, explains only an additional 8 percent of the variance beyond students’ background characteristics.69 These estimates may seem low, but this is because of our analytic strategy: we are focusing on growth and are thus controlling for 2005 CLA scores, which, as would be expected, explain the largest portion of the variance in 2007 CLA performance. Thus, students’ college experiences and institutions attended make almost as much of a difference as prior academic preparation. If the blame for low levels of critical thinking, complex reasoning, and writing skills of college students is to be placed on academic preparation, then almost an equal amount of responsibility rests with what happens after students enter higher education. (Kindle Locations 2370-2381)
Returns to Education: The Causal Effects of Education on Earnings, Health and Smoking
Graduating high school benefits all—and especially low-ability persons. Only high-ability individuals receive substantial benefits from college graduation.
Higher ability is associated with higher earnings and more schooling. However, as shown by the grey bars in Figure 2, adjusting for family background and adolescent measures of ability attenuates, but does not eliminate, the estimated least squares estimates of the effects of education.
Disaggregating by ability, the effects are strong for high-ability people who enroll in college. They are especially strong for those who graduate college. We find little to no evidence of any benefit of graduating college for low-ability individuals.77 In fact, the point estimates are negative, albeit imprecisely estimated. Although there are wage rate benefits to low-ability people for enrolling in college (Figure 4A), the benefits in terms of the log present value of wages are minimal. For these people, the wage benefits of attending college barely offset the lost work experience and earnings from attending school.
Our findings thus support the basic insights of Becker (1964). Schooling has strong causal effects on market and non-market outcomes. Both cognitive and non-cognitive endowments affect schooling choices and outcomes. People sort into schooling based on realized incremental gains.
The Labor Market Returns to Cognitive and Noncognitive Ability: Evidence from the Swedish Enlistment
We find strong evidence that men who fare poorly in the labor market—in the sense of unemployment or low annual earnings—lack noncognitive rather than cognitive ability. However, cognitive ability is a stronger predictor of wages for skilled workers and of earnings above the median.
cognitive ability is a much stronger predictor of higher education than noncognitive ability. For example, cognitive ability is an almost four times stronger predictor of a university degree than noncognitive ability
Understanding household financial distress: The role of noncognitive abilities
Character skills are part genetics and part the influence of early childhood experience. In adulthood, these skills are hard to change. Using panel data, we find that a person's noncognitive skills are highly correlated over time. More research, however, should be devoted to whether traumatic events can alter a person’s abilities, either in the short run or even permanently.
Also targeting young children to design educational programs that develop noncognitive abilities would be highly cost-effective. Recent research shows the return on investment in education from birth to age five is 13% (Garcia et al. 2016). High-quality education should not only foster cognitive skills, such as the ability to acquire and retain knowledge (Heckman et al. 2013, Cunha et al. 2010). Character – perseverance, motivation, self-esteem, emotional stability, and conscientiousness – is important too, as this research has shown. Improved noncognitive abilities will greatly influence financial wellbeing, income, education, and health throughout the life of an individual.
Rethinking education, work and ‘employability’
However, human capital theory fails the test of realism, truncating possible knowledge about education and work, because of weaknesses in its meta-method: theorisation using a single lens, closed system modeling of social relations, the application of mathematical tools to inappropriate materials, and the multivariate analysis of interdependent variables. These weaknesses lead to numerous lacunae. For example human capital theory cannot explain status objectives, which are more important for some graduates, and in some countries, than others; or how education augments productivity; or why top-end salary inequality has increased dramatically in some countries. The limitations of human capital theory are discussed with reference to research on social stratification, work, earnings and education.