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on Education |
| By: | Elizabeth Dhuey; A. Abigail Payne; Justin Smith |
| Abstract: | We estimate the long-term consequences of math and reading rank within an elementary school on short and long-term outcomes. We find that higher rank leads to better outcomes. Students ranked at the top in grade 7 perform up to 0.33 standard deviations higher on future school exams, are more likely to graduate high school and university, and earn significantly more at age 28. Math rank is especially predictive of high school completion and income. Reading rank is more strongly associated with university graduation. We find differences in the effect of rank on trajectories by gender for both top and bottom ranks. Our findings suggest that classroom position, even conditional on ability, has persistent effects, with implications for equity and early intervention. |
| Keywords: | post-secondary education, school rank, gender, earnings |
| JEL: | I22 I26 I21 J3 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12227 |
| By: | Teresa Baribieri (University of Bari); Vito Peragine (University of Bari); Michele Raitano (Sapienza University of Rome) |
| Keywords: | returns to education, compulsory schooling reforms, earnings mobility and volatility, lifecycle effects; earnings dynamics. |
| JEL: | J18 J24 I21 I28 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:bai:series:series_wp_03-2025 |
| By: | Duaa Abdullah; Jasem Hamoud |
| Abstract: | In this paper we provide a good overview of the problems and the background of mathematics education in Syrian schools. We aimed to study the effect of using popular mathematical puzzles on the mathematical thinking of schoolchildren, by conducting a paired experimental study (pre-test and post-test control group design) of the data we obtained through a sample taken from students of sixth-grade primary school students in Syria the Lady Mary School in Syria, in order to evaluate the extent of the impact of popular mathematical puzzles on students' ability to solve problems and mathematical skills, and then the skills were measured and the results were analyzed using a t-test as a tool for statistical analysis. |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2510.26263 |
| By: | Ham, John C. (New York University, Abu Dhabi); Khan, Saima (North South University, Bangladesh) |
| Abstract: | BRAC has over 40, 000 schools worldwide. It is widely praised for serving disadvantaged students and for matching or outperforming government schools. Using data that we collected from Dhaka’s slums, we test these claims. We find that BRAC serves the most disadvantaged students in our survey, but contrary to popular belief, BRAC students perform significantly worse than comparable students at other school types when we control for family demographics in a matching procedure. Anticipating our need to control for selection, we collected data on family demographics and the child’s fluid intelligence; since the latter affects both types of school and student performance, it unambiguously should be included in the propensity score. Once we control for fluid intelligence, the performance difference with other NGO schools disappears. The gaps between government and JAAGO schools have narrowed, but they still remain large and statistically significant. |
| Keywords: | choice-based sampling, fluid intelligence, math achievement, BRAC schools, common support, matching |
| JEL: | C21 C83 I21 J24 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18214 |
| By: | Ivan Albina (CEDLAS-IIE-FCE-UNLP); Zara Contractor (Middlebury College); Germán Reyes (Middlebury College and IZA) |
| Abstract: | Generative AI is transforming higher education, yet systematic evidence on student adoption remains limited. Using novel survey data from a selective U.S. college, we document over 80 percent of students using AI academically within two years of ChatGPT’s release. Adoption varies across disciplines, demographics, and achievement levels, highlighting AI’s potential to reshape educational inequalities. Students predominantly use AI for augmenting learning (e.g., explanations, feedback), but also to automate tasks (e.g., essay generation). Positive perceptions of AI’s educational benefits strongly predict adoption. Institutional policies can influence usage patterns but risk creating unintended disparate impacts across student groups due to uneven compliance. |
| JEL: | I21 O33 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:dls:wpaper:0359 |
| By: | Yeonha Jung; Minki Kim; Munseob Lee |
| Abstract: | This study examines the long-term impact of Hyanggyo, state-sponsored educational institutions established during the early Joseon Dynasty in Korea (1392-1592), on human capital accumulation. Although these schools largely ceased functioning as educational centers by the late 16th century, their influence has endured to the present day. Drawing on a newly constructed township-level dataset, we find a robust positive association between historical exposure to Hyanggyo and modern educational attainment. This relationship appears to be driven by enduring local demand for education, supported by three complementary findings. First, regions with greater historical exposure experienced larger gains in Japanese literacy during colonial era school expansions. Second, residents in these areas express stronger pro-education attitudes today. Third, historically exposed regions exhibited lower fertility rates, consistent with a quantity–quality tradeoff in parental investment. Together, our findings highlight the lasting legacy of early educational institutions. |
| Keywords: | Historical institutions, Human capital, Hyanggyo, Joseon, Cultural transmission |
| JEL: | I23 J24 N35 O15 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2025_707 |