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on Education |
| By: | Katharine L. Bradbury |
| Abstract: | Test-score data show that both low-income and racial-minority children score lower, on average, on states’ elementary-school accountability tests compared with higher-income children or white children. While different levels of scholastic achievement depend on a host of influences, such test-score gaps point toward unequal educational opportunity as a potentially important contributor. This report explores the relationship between racial and socioeconomic test-score gaps in New England metropolitan areas and two factors associated with unequal opportunity in education: state equalizing school-aid formulas and geographic segregation of low-income students. The underlying methods do not allow a strict causal interpretation; however, both aspects are strongly related to test-score gaps, with poverty segregation between school districts especially important in New England. The report first explores the degree to which state school aid is progressive, that is, distributed disproportionately to districts with high fractions of students living in poverty; more progressive distributions are associated with smaller test-score gaps in high-poverty metropolitan areas. All U.S. states distribute some state revenue to support local school districts, but the extent to which such aid is focused on districts with greater concentrations of poverty varies considerably. The relationships estimated in the empirical analysis suggest that New England metro areas with high average district poverty in states with more progressive aid distributions, such as Springfield, Massachusetts, should see somewhat smaller racial and socioeconomic test-score gaps than metro areas with lower district poverty in states with less progressive school aid, such as Burlington, Vermont; that predicted difference in white-Black test-score gaps amounts to about one-quarter of the actual difference between Springfield’s gap and Burlington’s gap. The second factor explored is poverty segregation; test-score gaps are larger in metropolitan areas where, compared with white children or higher-income children, minority children or low-income children go to school with, or are in school districts with, more students from low-income families. Partly because school districts (and cities and towns) are relatively small geographically in New England, poverty segregation in the region’s metropolitan areas is most pronounced between districts, not between schools within school districts. The sizes of the estimated relationships suggest that metro areas with the highest between-district poverty segregation, such as Bridgeport-Stamford-Norwalk, Connecticut, should have markedly larger test-score gaps than metro areas with moderate poverty segregation between districts, such as Manchester-Nashua, New Hampshire; those predicted differences amount to 60 percent to 90 percent of the actual test-score gap differences between the Bridgeport and Manchester metro areas. States can alter either or both of these factors via policy changes. States set the terms—and thereby the progressivity—of school-aid policy. Many states include cost adjustments in their aid formulas to offset some of the additional costs of educating students from low-income families, and some recent proposals (such as for Connecticut) or policy changes (such as in Massachusetts) involve more closely targeting state equalizing aid to high-poverty districts. State policy levers regarding between-district poverty segregation are less direct and potentially more controversial. Nonetheless, statewide affordable housing policies, such as those in Massachusetts and Rhode Island, if applied more comprehensively, might reduce concentrations of poverty and provide more low-income families access to the higher-quality schools in low-poverty suburban districts. |
| Keywords: | racial segregation; socioeconomic segregation; state aid to public schools; student test-score gaps; inequality of opportunity; New England; NEPPC; education funding; segregation; low income |
| Date: | 2021–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedbcr:89959&r=all |
| By: | Abu Siddique (Technical University of Munich) |
| Abstract: | I investigate how long-term exposure to religious education affects economic behavior of children. To identify the effect of religious education, I exploit residential schools for orphans in Bangladesh that differ in terms of religious curriculum and social environment, limits transmission of beliefs and preferences from parents to children following being orphaned, makes social learning by children limited after school enrolment, and mitigates issues concerning endogenous school choice by parents. Using a lab-in-the-field experiment in this natural setting, I measure children's behavior and find that (i) children receiving religious education are more altruistic and honest relative to children receiving secular education; (ii) religious education does not affect risk aversion, cooperation, trust, and trustworthiness of children; and, (iii) behavioral differences are driven by children who are around puberty and completed primary education. My findings provide useful insights into how long-term exposure to religious education can affect behavior - possibly by shifting preferences - during childhood and adolescence. |
| Keywords: | Economic behavior, preference formation, religious education, selection bias, lab-in-the-field experiment, Bangladesh. |
| JEL: | C9 D91 I21 Z12 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:aiw:wpaper:10&r=all |
| By: | Pietro Sancassani |
| Abstract: | Using data from TIMSS 2015, an international large-scale assessment of student skills, I investigate the effect of teacher characteristics on students’ science achievement. My identification strategy exploits the feature that in many education systems different science domains (physics, biology, chemistry, and earth science) are taught by different teachers. The availability of students’ test scores as well as teachers’ questionnaires for each of these domains allows me to implement a withinstudent approach which controls for unobserved student heterogeneity. I find a positive and significant effect of teacher specialization in the specific science domain on students’ results, equivalent to 1.7% of a standard deviation. Holding a Master’s degree, pedagogical preparation and teaching experience have no significant effect. Teachers’ experience has a negative impact on the extent to which students like to study a subject or find teaching engaging. |
| Keywords: | Teachers, student achievement, teacher characteristics, education production function, TIMSS |
| JEL: | I21 I29 C21 J24 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ifowps:_348&r=all |
| By: | Kazuo Nishimura (Research Institute for Economics and Business Administration, Kobe University and Research Institute of Economy, Trade and Industry (RIETI), JAPAN); Dai Miyamoto (Graduate School of Economics, Doshisha University, JAPAN); Tadashi Yagi (Graduate School of Economics, Doshisha University, JAPAN) |
| Abstract: | The numbers of published scientific papers and patent applications are indicators of a country's research and development (R&D) capabilities. Since the 2010s, these indicators have declined in Japan. One important factor for this decline is the changes in science and mathematics education provided at schools because education in school can greatly impact the quality of future researchers in science. To examine the impact of the number of class hours in science and mathematics that researchers received in school over the past 50 years, this study analyzed data from two surveys conducted in 2016 and 2020. The results show that there is a decline in the number of patents for the younger generation that cannot be explained by age differences, and it is highly correlated with a decline in the total number of hours of science and math in junior high school. Therefore, a country's educational policies should be implemented only after validating their effects from a long-term perspective because such policies may have unintended negative impacts on the country's economic growth. |
| Keywords: | Research and development capabilities; Number of patent applications; Science and mathematics education; Number of class hours |
| JEL: | I23 I28 O32 |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:kob:dpaper:dp2021-02&r=all |
| By: | Roland Fryer (Harvard University - Department of Economics; NBER); Steven Levitt (University of Chicago - Department of Economics; NBER); John A. List (University of Chicago - Department of Economics; NBER); Anya Samek (University of California, San Diego - Rady School of Management; NBER) |
| Abstract: | We present the results of a novel early childhood intervention in which disadvantaged 3-4-year-old children were randomized to receive a new preschool and parent education program focused on cognitive and non-cognitive skills (CogX) or to a control group that did not receive preschool education. In addition to a typical academic year (9 month) program, we also evaluated a shortened summer version of the program (2 months) in which children were treated immediately prior to the start of Kindergarten. Both programs, including the shortened version, significantly improved cognitive test scores by about one quarter of a standard deviation relative to the control group at the end of the year. The shortened version of the program was equally as effective as the academic-year program because most of the gains in the academic-year program occurred within the first few months. |
| Keywords: | Preschool education, human capital, field experiments |
| JEL: | J24 C93 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:bfi:wpaper:2020-149&r=all |
| By: | Erwin Amann (University Duisburg-Essen); Sylvi Rzepka (University of Potsdam) |
| Abstract: | We investigate how inviting students to set task-based goals affects usage of an online learning platform and course performance. We design and implement a randomized field experiment in a large mandatory economics course with blended learning elements. The low-cost treatment induces students to use the online learning system more often, more intensively, and to begin earlier with exam preparation. Treated students perform better in the course than the control group: they are 18.8% (0.20 SD) more likely to pass the exam and earn 6.7% (0.19 SD) more points on the exam. There is no evidence that treated students spend significantly more time, rather they tend to shift to more productive learning methods. The heterogeneity analysis suggests that higher treatment effects are associated with higher levels of behavioral bias but also with poor early course behavior. |
| Keywords: | natural field experiment, blended learning, behavioral economics, goal-setting |
| JEL: | I21 I23 C93 D91 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:pot:cepadp:25&r=all |
| By: | Chris van Wyk (Department of Economics, Stellenbosch University) |
| Abstract: | The availability of individual learner-unit records allows one to track learners as a group or cohort over a specified period. Longitudinal cohort tracking provides a more complete picture of the progress of learners (dropout and repetition) in the education system. Expanding on the findings of Van Wyk, Gondwe and De Villiers (2017) by using a longitudinal dataset, the aim of this study was to track learners from Grade 1 to Grade 12 as a group or cohort over a longer specified period (2007-2019). This longitudinal data cohort analysis explored how successful learners progressed through the Western Cape public education system and how many eventually dropped out of this system. We used the Central Education Management Information System (CEMIS) datasets from 2007-2019 to create a longitudinal dataset of individual learners. The analysis reveals the importance of unit-level records. With the availability of unit-level learner records, key questions such as: “What is the profile of the learners who dropped out of the system?” or ”What is the profile of the learners who progressed without any repetition?” can be answered. In order to achieve the goals of this study, we first conducted a cross-sectional analysis of the patterns and trends of the flow of learners between 2007 and 2019 in the Western Cape. Thereafter, we conducted a longitudinal cohort analysis of learners to determine progression with or without repetition and who dropped out of the Western Cape public education system. The findings show considerable repetition in primary school. While most learners progressed through the system without repeating, a relatively high percentage also repeated one or more grades but remained in the system. We also found higher repetition and high dropout in secondary school. These findings contrast with the primary school phase, where lower dropout was evident. A further key finding was a significant decrease of repetition rates since 2015, particularly in Grades 1 and 9, and to a lesser extent in Grades 10 and 11. These findings point to enhanced internal efficiency in the Western Cape public education system over this period. |
| Keywords: | longitudinal cohort analysis, unit-level records, cross-sectional analysis, repetition, unique identifier, pseudo cohorts, primary school, secondary school, internal efficiency |
| JEL: | I21 C55 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:sza:wpaper:wpapers361&r=all |
| By: | Dekker, I.; Schippers, M.C.; van Schooten, E. |
| Abstract: | Students often have trouble adjusting to higher education and this affects their performance, retention, and well-being. Scholars have suggested applying reflective goal- setting interventions, and most have found positive effects on academic performance and retention. However, one study found no effect at all, stressing the need for understanding the underlying mechanisms, as they could explain when the intervention works and why. Thus, we assessed these mechanisms through a rigorous effect test, using an experimental design and repeated measures. We measured engagement, self-regulated learning, resilience, grit, wellbeing, academic performance, and retention at three points in a large scale randomized controlled trial involving first-year teacher and business education students (N = 1,134). The treatment group earned significantly more course credits and had lower drop out rates. Contrary to previous findings, these effects were independent of gender or ethnicity. Grit, self-regulated learning, resilience, or engagement did not mediate the effects. This study confirmed reflective goal-setting’s small and direct effect on academic performance, but no mediating or moderating effects. Differences in implementation fidelity could explain previous studies’ varying effect-sizes. |
| Keywords: | academic performance, academic achievement, goal setting, well-being, intervention, field experiment, self-regulated learning, engagement |
| Date: | 2021–02–03 |
| URL: | http://d.repec.org/n?u=RePEc:ems:eureri:134259&r=all |
| By: | Ferman, Bruno; Lima, Lycia; Riva, Flávio |
| Abstract: | This paper investigates how educational technologies that use different combinations of artificial and human intelligence are incorporated into classroom instruction, and how they ultimately affect learning. We conducted a field experiment to study two technologies that allow teachers to outsource grading and feedback tasks on writing practices of high school seniors. The first technology is a fully automated evaluation system that provides instantaneous scores and feedback. The second one uses human graders as an additional resource to enhance grading and feedback quality in aspects in which the automated system arguably falls short. Both technologies significantly improved students' essay scores in a large college admission exam, and the addition of human graders did not improve effectiveness in spite of increasing perceived feedback quality. Both technologies also similarly helped teachers engage more frequently on personal discussions on essay quality with their students. Taken together, these results indicate that teachers' task composition shifted toward nonroutine activities and this helped circumvent some of the limitations of artificial intelligence. More generally, our results illustrate how the most recent wave of technological change may relocate labor to analytical and interactive tasks that still remain a challenge to automation. |
| Date: | 2021–02–17 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:qw249&r=all |