All four sectors in K–12 education compete for the support of their customers—that is, the parents of their prospective students. Those parents have more choices today than in decades past: they may send their children to the public school automatically assigned to them by their school district, or opt for a private school, charter school, or district-run school of choice. These choices include a range of cost and convenience—and, not surprisingly, a range of customer satisfaction levels.
Since No Child Left Behind (NCLB) was enacted into federal law in 2002, states have been required to test students in grades 3 through 8 and again in high school to assess math and reading achievement. The federal law also asks states to establish the performance level students must reach on the exams in order to be identified as “proficient.” According to NCLB, each school was expected to increase the percentage of proficient students at a rate that would ensure that all students were proficient by the year 2014.
Do teachers and the public disagree on education reform? We use data from a nationally representative survey conducted in 2011 to identify the extent of the differences between the opinion of teachers and the general public on a wide range of education policies. The overall cleavage between teachers and the general public is wider than the cleavages between other relevant groups, including that between Democrats and Republicans.
Neither holding a college major in education nor acquiring a master's degree is correlated with elementary and middle school teaching effectiveness, regardless of the university at which the degree was earned. Teachers generally do become more effective with a few years of teaching experience, but we also find evidence that teachers may become less effective with experience, particularly later in their careers.
State-mandated systems of comprehensive examinations to be taken prior to high school graduation would focus the attention of students in high school, motivate them to higher levels of performance, provide guidance to teachers as to the appropriate material to be covered, and reduce antieducational pressures within peer groups, all of whose members would share a common objective.
Targeted stigma and school voucher threats under a revised 2002 Florida accountability law have positive impacts on school performance as measured by the test score gains of their students. In contrast, stigma and public school choice threats under the US federal accountability law, No Child Left Behind, do not have similar effects in Florida. Estimation relies upon individual-level data and is based upon regression analyses that exploit discontinuities within the accountability regimes.
We use data from a sample of applicants to a national means-tested school voucher program and a national sample of the population eligible for the program to evaluate the factors leading families to use school vouchers. Our analysis divides the process of voucher usage into two distinct stages: initial application and subsequent take-up. Using a nested logit model, we find that some factors, like religious affiliation and religious service attendance, affect both stages. Others, like mother's education, affect only one (application).
By design, randomized field trials (RFTs) avoid many of the problems that plague observational studies, foremost among them being the introduction of selection biases. In practice, however, RFTs regularly confront other difficulties, such as chance differences between treatment and control groups and attrition from the study. To address these issues, baseline data on the variable of primary interest are essential. Theory also aids the analytic process, identifying ways in which data should be disaggregated and determining the generalizability of the findings uncovered.
When estimating voucher impacts on test scores in the New York City randomized field trial (RFT) for African Americans (defined either by mother’s ethnicity, parental caretaker, mother and father’s ethnicity, or mother or father’s ethnicity), results remain significantly positive, even when models include students for whom no baseline test scores are available. These results obtain as long as one estimates impacts precisely by controlling for baseline test scores for those students who have them.