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Prashant Loyalka
Journal Articles

Health, Economic, and Social Implications of COVID-19 for China's Rural Population

Huan Wang, Sarah-Eve Dill, Huan Zhou, Yue Ma, Hao Xue, Sean Sylvia, Kumi Smith, Matthew Boswell, Alexis Medina, Prashant Loyalka, Cody Abbey, Dimitris Friesen, Nathan Rose, Yian Guo, Scott Rozelle
Agricultural Economics , 2021
This study examines the effects of local and nationwide COVID‐19 disease control measures on the health and economy of China's rural population. We conducted phone surveys with 726 randomly selected village informants across seven rural Chinese provinces in February 2020. Four villages (0.55%) reported infections, and none reported deaths. Disease control measures had been universally implemented in all sample villages. About 74% of informants reported that villagers with wage‐earning jobs outside the village had stopped working due to workplace closures. A higher percentage of rural individuals could not work due to transportation, housing, and other constraints. Local governments had taken measures to reduce the impact of COVID‐19. Although schools in all surveyed villages were closed, 71% of village informants reported that students were attending classes online. Overall, measures to control COVID‐19 appear to have been successful in limiting disease transmission in rural communities outside the main epidemic area. Rural Chinese citizens, however, have experienced significant economic consequences from the disease control measures.
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Journal Articles

Skill Levels and Gains in University STEM Education in China, India, Russia, and the United States

Prashant Loyalka, Ou Lydia Liu, Guirong Li, Elena Kardanova, Igor Chirikov, Shangfeng Hu, Ningning Yu, Liping Ma, Fei Guo, Tara Beteille, Namrata Tognatta, Lin Gu, Guangming Ling, Denis Federiakin, Huan Wang, Saurabh Khanna, Ashutosh Bhuradia, Zhaolei Shi, Yanyan Li
Nature Human Behavior , 2021
Universities contribute to economic growth and national competitiveness by equipping students with higher-order thinking and academic skills. Despite large investments in university science, technology, engineering and mathematics (STEM) education, little is known about how the skills of STEM undergraduates compare across countries and by institutional selectivity. Here, we provide direct evidence on these issues by collecting and analysing longitudinal data on tens of thousands of computer science and electrical engineering students in China, India, Russia and the United States. We find stark differences in skill levels and gains among countries and by institutional selectivity. Compared with the United States, students in China, India and Russia do not gain critical thinking skills over four years. Furthermore, while students in India and Russia gain academic skills during the first two years, students in China do not. These gaps in skill levels and gains provide insights into the global competitiveness of STEM university students across nations and institutional types.
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Journal Articles

Tracking the Effects of COVID-19 in Rural China Over Time

Huan Wang, Markus Zhang, Robin Li, Oliver Zhong, Hannah Johnstone, Huan Zhou, Hao Xue, Sean Sylvia, Matthew Boswell, Prashant Loyalka, Scott Rozelle
International Journal for Equity in Health , 2021
Background: China issued strict nationwide guidelines to combat the COVID-19 outbreak in January 2020 and gradually loosened the restrictions on movement in early March. Little is known about how these disease control measures affected the 600 million people who live in rural China. The goal of this paper is to document the quarantine measures implemented in rural China outside the epicenter of Hubei Province and to assess the socioeconomic effect of the measures on rural communities over time. Methods: We conducted three rounds of interviews with informants from 726 villages in seven provinces, accounting for over 25% of China’s overall rural population. The survey collected data on rural quarantine implementation; COVID-19 infections and deaths in the survey villages; and effects of the quarantine on employment, income, education, health care, and government policies to address any negative impacts. The empirical findings of the work established that strict quarantine measures were implemented in rural villages throughout China in February. Results: There was little spread of COVID-19 in rural communities: an infection rate of 0.001% and zero deaths reported in our sample. However, there were negative social and economic outcomes, including high rates of unemployment, falling household income, rising prices, and disrupted student learning. Health care was generally accessible, but many delayed their non-COVID-19 health care due to the quarantine measures. Only 20% of villagers received any form of local government aid, and only 11% of villages received financial subsidies. There were no reports of national government aid programs that targeted rural villagers in the sample areas. Conclusions: By examining the economic and social effects of the COVID-19 restrictions in rural communities, this study will help to guide other middle- and low-income countries in their containment and restorative processes. Without consideration for economically vulnerable populations, economic hardships and poverty will likely continue to have a negative impact on the most susceptible communities.
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Journal Articles

The Impacts of Highly Resourced Vocational Schools on Student Outcomes in China

Guirong Li, Jiajia Xu, Liying Li, Zhaolei Shi, Hongmei Yi, James Chu, Elena Kardanova, Yanyan Li, Prashant Loyalka, Scott Rozelle
China & World Economy , 2020
Policymakers in developing countries have prioritized the mass expansion of vocational education and training (VET). Evidence suggests, however, that the quality of VET can be poor. One possible reason given by policymakers for this is a lack of resources per student. The goal of this study is to examine whether the quality of VET in developing countries increases by investing greater resources per student. To achieve this goal, we examine the impacts of attending model schools (which have far more resources per student) compared with non-model schools (which have fewer resources) on a range of student cognitive, non-cognitive, and behavioral outcomes. Using representative data from a survey of approximately 12,000 VET students from China, multivariate regression and propensity score matching analyses show that there are no significant benefits, in terms of student outcomes, from attending model vocational high schools, despite their substantially greater resources.
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Journal Articles

Examining Mode Effects for an Adapted Chinese Critical Thinking Assessment

Lin Gu, Guangming Ling, Ou Lydia Liu, Zhitong Yang, Guirong Li, Elena Kardanova, Prashant Loyalka
Assessment & Evaluation in Higher Education , 2020
We examine the effects of computer-based versus paper-based assessment of critical thinking skills, adapted from English (in the U.S.) to Chinese. Using data collected based on a random assignment between the two modes in multiple Chinese colleges, we investigate mode effects from multiple perspectives: mean scores, measurement precision, item functioning (i.e. item difficulty and discrimination), response behavior (i.e. test completion and item omission), and user perceptions. Our findings shed light on assessment and item properties that could be the sources of mode effects. At the test level, we find that the computer-based test is more difficult and more speeded than the paper-based test. We speculate that these differences are attributable to the test’s structure, its high demands on reading, and test-taking flexibility afforded under the paper testing mode. Item-level evaluation allows us to identify item characteristics that are prone to mode effects, including targeted cognitive skill, response type, and the amount of adaptation between modes. Implications for test design are discussed, and actionable design suggestions are offered with the goal of minimizing mode effect.
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Working Papers

Off the Epicenter: COVID-19 Quarantine Controls and Employment, Education, and Health Impacts in Rural Communities

Huan Wang, Sarah-Eve Dill, Huan Zhou, Yue Ma, Hao Xue, Prashant Loyalka, Sean Sylvia, Matthew Boswell, Jason Lin, Scott Rozelle
2020

In late January 2020, China’s government initiated its first aggressive measures to combat COVID-19 by forbidding individuals from leaving their homes, radically limiting public transportation, cancelling or postponing large public events, and closing schools across the country. The rollout of these measures coincided with China’s Lunar New Year holiday, during which more than 280 million people had returned from their places of work to their home villages in rural areas. The disease control policies remained in place until late February and early March, when they were gradually loosened to

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Journal Articles

Institutions, Implementation, and Program Effectiveness: Evidence from a Randomized Evaluation of Computer-Assisted Learning in Rural China

Di Mo, Yu Bai, Yaojiang Shi, Cody Abbey, LInxiu Zhang, Scott Rozelle, Prashant Loyalka
Journal of Development Economics , 2020
There is limited evidence on the degree to which differences in implementation among institutions matter for program effectiveness. To examine this question, we conducted an experiment in rural China in which public schools were randomly assigned to one of three treatments: a computer-assisted learning program (CAL) implemented by a government agency, the same program implemented by an NGO, and a pure control. Results show that compared to the pure control condition and unlike the NGO program, the government program did not improve student achievement. Analyzing impacts along the causal chain, we find that government officials were more likely to substitute CAL for regular instruction (contrary to protocol) and less likely to directly monitor program progress. Correlational analyses suggest that these differences in program implementation were responsible for the lack of impacts.
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Journal Articles

Schooling and Covid-19: Lessons from Recent Research on EdTech

Robert Fairlie, Prashant Loyalka
Nature Partner Journal: Science of Learning , 2020
The wide-scale global movement of school education to remote instruction due to Covid-19 is unprecedented. The use of educational technology (EdTech) offers an alternative to in-person learning and reinforces social distancing, but there is limited evidence on whether and how EdTech affects academic outcomes. Recently, we conducted two large-scale randomized experiments, involving ~10,000 primary school students in China and Russia, to evaluate the effectiveness of EdTech as a substitute for traditional schooling. In China, we examined whether EdTech improves academic outcomes relative to paper-and-pencil workbook exercises of identical content. We found that EdTech was a perfect substitute for traditional learning. In Russia, we further explored how much EdTech can substitute for traditional learning. We found that EdTech substitutes only to a limited extent. The findings from these large-scale trials indicate that we need to be careful about using EdTech as a full-scale substitute for the traditional instruction received by schoolchildren. The wide-scale global movement of school education to remote instruction due to Covid-19 is unprecedented. The use of educational technology (EdTech) offers an alternative to in-person learning and reinforces social distancing, but there is limited evidence on whether and how EdTech affects academic outcomes, and that limited evidence is mixed.1,2 For example, previous studies examine performance of students in online courses and generally find that they do not perform as well as in traditional courses. On the other hand, recent large-scale evaluations of supplemental computer-assisted learning programs show large positive effects on test scores. One concern, however, is that EdTech is often evaluated as a supplemental after-school program instead of as a direct substitute for traditional learning. Supplemental programs inherently have an advantage in that provide more time learning material. Recently, we conducted two large-scale randomized experiments, involving ~10,000 primary school students in China and Russia, to evaluate the effectiveness of EdTech as a substitute for traditional schooling.3,4 In both, we focused on whether and how EdTech can substitute for in-person instruction (being careful to control for time on task). In China, we examined whether EdTech improves academic outcomes relative to paper-and-pencil workbook exercises of identical content. We followed students ages 9–13 for several months over the academic year. When we examined the impacts of each supplemental program we found that EdTech and workbook exercise sessions of equal time and content outside of school hours had the same effect on standardized math test scores and grades in math classes. As such, EdTech appeared to be a perfect substitute for traditional learning. In Russia, we built on these findings by further exploring how much EdTech can substitute for traditional learning. We examined whether providing students ages 9–11 with no EdTech, a base level of EdTech (~45 min per week), and a doubling of that level of EdTech can improve standardized test scores and grades. We found that EdTech can substitute for traditional learning only to a limited extent. There is a diminishing marginal rate of substitution for traditional learning from doubling the amount of EdTech use (that is, when we double the amount of EdTech used we do not find that test scores performance doubles). We find that additional time on EdTech even decreases schoolchildren’s motivation and engagement in subject material. The findings from the large-scale trials indicate that we need to be careful about using EdTech as a full-scale substitute for the traditional instruction received by schoolchildren. There are two general takeaways: First, to a certain extent, EdTech can successfully substitute for traditional learning. Second, there are limits on how much EdTech may be beneficial. Admittedly, we need to be careful about extrapolating from the smaller amount of technology substitution in our experiments to the full-scale substitution in the face of the coronavirus pandemic. However, these studies may offer important lessons. For example, a balanced approach to learning in which schoolchildren intermingle work on electronic devices and work with traditional materials might be optimal. Schools could mail workbooks to students or recommend that students print out exercises to break up the amount of continuous time schoolchildren spend on devices. This might keep students engaged throughout the day and avoid problems associated with removing the structure of classroom schedules. Schools and families can devise creative remote learning solutions that include a combination of EdTech and more traditional forms of learning. Activities such as reading books, running at-home experiments, and art projects can also be used to break up extensive use of technology in remote instruction.
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Working Papers

Education and EdTech during COVID-19: Evidence from a Large-Scale Survey during School Closures in China

Guirong Li, Xinwu Zhang, Delei Liu, Hao Xue, Derek Hu, Oliver Lee, Chris Rilling, Yue Ma, Cody Abbey, Robert Fairlie, Prashant Loyalka, Scott Rozelle
2020
In response to the COVID-19 epidemic, many education systems have relied on distance learning and educational technologies to an unprecedented degree. However, rigorous empirical research on the impacts on learning under these conditions is still scarce. We present the first large-scale, quantitative evidence detailing how school closures affected education in China. The data set includes households and teachers of 4,360 rural and urban primary school students. We find that although the majority of students engaged in distance education, many households encountered difficulties including barriers to learning (such as access to appropriate digital devices and study spaces), curricular delays, and costs to parents equivalent to about two months of income. We also find significant disparities across rural and urban households.
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Working Papers

The Hidden Cost of Worker Turnover: Attributing Product Reliability to the Turnover of Factory Workers

Ken Moon, Prashant Loyalka, Patrick Bergemann, Joshua Cohen
2020
Product reliability is a key concern for manufacturers. We examine a significant but under-recognized determinant of product reliability: the rate of workers quitting from the product's assembly line, or its worker turnover. While modern manufacturers make extensive efforts to control defects and assure quality worksmanship, some quality variation in the manufactured units may be revealed only after they have been used repeatedly. If this is the case, then the disruptiveness of high turnover may directly lead to product reliability issues. To evaluate this possibility, our study collects four post-production years of field failure data covering nearly fifty million sold units of a premium mobile consumer electronics product. Each device is traced back to the assembly line and week in which it was produced, which allows us to link product reliability to production conditions including assembly lines' worker turnover, workloads, firm learning, and the quality of components. Significant effects manifest in two main ways: (1) In the high-turnover weeks immediately following paydays, eventual field failures are surprisingly 10.2% more common than for devices produced in the lowest-turnover weeks immediately before paydays. Using post-payday as an instrumental variable, we estimate that field failure incidence grows by 0.74-0.79% per 1 percentage increase in weekly turnover. (2) Even in other weeks, assembly lines experiencing higher turnover produce an estimated 2-3% more field failures. We demonstrate that staffing and retaining a stable factory workforce critically underlies product reliability and show the value of connected field data in informing manufacturing operations. Keywords: Data-driven workforce planning, Empirical operations management, Employee turnover, People 
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Journal Articles

Large-Scale International Assessments of Learning Outcomes: Balancing the Interests of Multiple Stakeholders

Guirong Li, Irina Shcheglova, Ashutosh Bhuradia, Yanyan Li, Prashant Loyalka, Olivia Zhou, Shangfeng Hu, Ningning Yu, Liping Ma, Fei Guo, Igor Chirikov
Journal of Higher Education Policy and Management , 2020
The demand for large-scale assessments in higher education, especially at an international scale, is growing. A major challenge of conducting these assessments, however, is that they require understanding and balancing the interests of multiple stakeholders (government officials, university administrators, and students) and also overcoming potential unwillingness of these stakeholders to participate. In this paper, we take the experience of the Study of Undergraduate Performance (SUPER) in conducting a large-scale international assessment as a case study. We discuss ways in which we mitigated perceived risks, built trust, and provided incentives to ensure the successful engagement of stakeholders during the study’s implementation.
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Working Papers

Isolating the "Tech" from EdTech: Experimental Evidence on Computer Assisted Learning in China

Yue Ma, Robert Fairlie, Prashant Loyalka, Scott Rozelle
The National Bureau of Economic Research , 2020
EdTech which includes online education, computer assisted learning (CAL), and remote instruction was expanding rapidly even before the current full-scale substitution for in-person learning at all levels of education around the world because of the coronavirus pandemic. Studies of CAL interventions have consistently found large positive effects, bolstering arguments for the widespread use of EdTech. However CAL programs, often held after school, provide not only computer-based instruction, but often additional non-technology based inputs such as more time on learning and instructional support by facilitators. In this paper, we develop a theoretical model to carefully explore the possible channels by which CAL programs might affect academic outcomes among schoolchildren. We isolate and test the technology-based effects of CAL and additional parameters from the theoretical model, by designing a novel multi-treatment field experiment with more than four thousand schoolchildren in rural China. Although we find evidence of positive overall CAL program effects on academic outcomes, when we isolate the technology-based effect of CAL (over and above traditional pencil-and-paper learning) we generally find small to null effects. Our empirical results suggest that, at times, the “Tech” in EdTech may have relatively small effects on academic outcomes, which has important implications for the continued, rapid expansion of technologies such as CAL throughout the world.
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Journal Articles

The Impact of Pay-for-Percentile Incentive on Low-Achieving Students in Rural China

Fang Chang, Huan Wang, Yaqiong Qu, Qiang Zheng, Prashant Loyalka, Sean Sylvia, Yaojiang Shi, Sarah-Eve Dill, Scott Rozelle
Economics of Education Review , 2020
In some accountability regimes, teachers pay more attention to higher achieving students at the expense of lower achieving students. The overall goal of this study is to examine, in this type of accountability regime, the impacts of a pay-for-percentile type scheme in which incentives exist for all students but which are larger for improving the achievement of lower achieving students. Analyzing data from a large-scale randomized experiment in rural China, we find that incentives improve average achievement by 0.10 SDs and the achievement of low-achieving students by 0.15 SDs. We find parallel changes in teacher behavior and curricular coverage. Taken together, the results demonstrate that incentive schemes can effectively address teacher neglect of low-achieving students.
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Working Papers

Manufacturing Productivity with Worker Turnover

Ken Moon, Patrick Bergemann, Daniel Brown, Andrew Chen, James Chu, Ellen Eisen, Gregory Fischer, Prashant Loyalka, Sungmin Rho, Joshua Cohen
2019

We find that rapid worker turnover significantly disrupts the productivity of responsive manufacturers. Our study uses a uniquely rich dataset drawn from China-based FATP (final assembly, testing, and packaging) facilities that produce millions of units of consumer electronic goods weekly yet exhibit high worker turnover exceeding 300% annually. The data cover the firm's weekly production plans, 52,214 workers' compensations and assignments, and assembly station productivity. To study managerial prescriptions, we extend the classical production planning problem to include endogenous worker turnover as an Experience-Based Equilibrium and use advances in reinforcement learning and approximate dynamic programming to estimate and simulate our model. Our empirical analyses exploit instrumental variables, including the firm's demand forecasts as demand shifters". We find that turnover's impact on yield waste is conservatively $146-178M, and that a well-calibrated wage increase reduces the manufacturer's variable production costs (including wages) by up to 21%, or $594M for the product we study. The wage increase reduces the firm's reliance on a larger workforce and overtime to hedge against yield disruptions from turnover; it stabilizes a leaner workforce and improves both production reliability and exibility. In settings where performance depends on workers repeating known tasks in coordinated groups, our results suggest that firms responsively matching supply to demand can pay a steep price for a disruptively turnover-prone workforce.

 

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Working Papers

EdTech for Equity in China: Can Technology Improve Teaching for Millions of Rural Students?

Cody Abbey, Yue Ma, Guirong Li, Matthew Boswell, Claire Cheng, Robert Fairlie, Oliver Lee, Prashant Loyalka, Andrew Mi, Evan Peng, Scott Rozelle, Adrian Sun, Andy Zeng, Jenny Zhao
2019

Previous literature suggests subpar teaching is a primary reason why rural Chinese students lag behind academically. We initiate an investigation into the potential of educational technology (EdTech) to increase teaching quality in rural China. First, we discuss why conventional approaches of improving teaching in remote schools are infeasible in China’s context, referring to past research. We then explore the capacity of technology-assisted instruction to improve academic performance by examining previous empirical analyses. Third, we show that China is not limited by the resource constraints of other developing countries due to substantial policy support and a thriving EdTech industry. Finally, we identify potential implementation-related challenges based on the results of a preliminary qualitative survey of pilots of EdTech interventions. With this paper, we lay the foundation for a long-term research investigation into whether EdTech can narrow China’s education gap.

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Journal Articles

The Prevalence of Parent-Teacher Interaction in Developing Countries and its Effect on Student Outcomes

Guirong Li, Millie Lin, Chengfang Liu, Angela Johnson, Yanyan Li, Prashant Loyalka
Teaching and Teacher Education , 2019

Empirical evidence from developed countries supports the idea that parent-teacher interaction is high and improves student outcomes. The evidence from developing countries is, however, decidedly mixed. Using longitudinal data from nearly 6000 students and their 600 teachers in rural China, we show the prevalence of parent-teacher interaction is generally much lower than that of developed countries. We also show parent-teacher interaction, when it exists, can have positive effects on raising academic achievement and reducing learning anxiety. We demonstrate that the prevalence and effectiveness of parent-teacher interaction in a developing country context varies considerably due to both demand-side and supply-side factors.

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Journal Articles

Stuck in Place? A Field Experiment on the Effects of Reputational Information on Student Evaluations

James Chu, Guirong Li, Prashant Loyalka, Chengfang Liu, Leonardo Rosa, Yanyan Li
Social Forces , 2019

Studies suggest that students’ prior performance can shape subsequent teacher evaluations, but the magnitude of reputational effects and their implications for educational inequality remain unclear. Existing scholarship presents two major perspectives that exist in tension: do teachers primarily use reputational information as a temporary signal that is subsequently updated in response to actual student performance? Or do teachers primarily use reputational information as a filter that biases perception of subsequent evidence, thus crystallizing student reputations and keeping previously poor-performing students stuck in place? In a field experiment, we recruited a random sample of 832 junior high school teachers from the second-most populous province of China to grade a sequence of four essays written by the same student, and we randomly assign both the academic reputation of the student and the quality of the essays produced. We find that (1) reputational information influences how teachers grade, (2) teachers rely on negative information more heavily than positive information, and (3) negative reputations are crystallized by a single behavioral confirmation. These results suggest that students can escape their prior reputations, but to do so, they must contradict them immediately, with a single confirmation sufficient to crystallize a negative reputation.

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Journal Articles

Does Teacher Training Actually Work? Evidence from a Large-Scare Randomized Evaluation of a National Teacher Training Program

Prashant Loyalka, Anna Popova, Guirong Li, Zhaolei Shi
American Economic Journal: Applied Economics , 2019
Despite massive investments in teacher professional development (PD) programs in developing countries, there is little evidence on their effectiveness. We present results of a large-scale, randomized evaluation of a national PD program in China in which teachers were randomized to receive PD; PD plus follow-up; PD plus evaluation of the command of PD content; or no PD. Precise estimates indicate PD and associated interventions failed to improve teacher and student outcomes after one year. A detailed analysis of the causal chain shows teachers find PD content to be overly theoretical, and PD delivery too rote and passive, to be useful.
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Journal Articles

The Impact of Teacher Professional Development Programs on Student Achievement in Rural China: Evidence from Shaanxi Province

Meichen Lu, Prashant Loyalka , Yaojiang Shi, Fang Chang, Chengfang Liu, Scott Rozelle
Journal of Development Effectiveness , 2019

There is a significant gap in academic achievement between rural and urban students in China. Policymakers have sought to close this gap by improving the quality of teaching in rural areas through teacher professional development (PD) programs. However, there is limited evidence on the effectiveness of such programs. In this paper, we evaluate the impact of a PD program-National Teacher Training Program (NTTP)  and find that the NTTP has no effect on math achievement. We also find that while the program has a positive effect on math teaching knowledge of teachers, it has no significant effect on teaching practices in the classroom. Taken together, these results indicate that teachers may have improved their knowledge for teaching from NTTP, but did not apply what they learned to improve teaching practices or student learning.

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Journal Articles

Pay by Design: Teacher Performance Pay Design and the Distribution of Student Achievement

Prashant Loyalka, Sean Sylvia, Chengfang Liu, James Chu, Yaojiang Shi
Journal of Labor Economics , 2019

Abstract: We present results of a randomized trial testing alternative approaches of mapping student achievement into rewards for teachers. Teachers in 216 schools in western China were assigned to performance pay schemes where teacher performance was assessed by one of three different methods. We find that teachers offered “pay-for-percentile” incentives (Barlevy and Neal 2012) outperform teachers offered simpler schemes based on class average achievement or average gains over a school year. Moreover, pay-for-percentile incentives produced broad-based gains across students within classes. That teachers respond to relatively intricate features of incentive schemes highlights the importance of close attention to performance pay design. 

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Journal Articles

Computer Science Skills Across China, India, Russia, and the United States

Prashant Loyalka, Ou Lydina Liu, Guirong Li, Igor Chirikov, Elena Kardanova, Lin Gu, Guangming Ling, Ningning Yu, Fei Guo, Liping Ma, Shangfeng Hu, Angela Sun Johnson, Ashutosh Bhuradia, Saurabh Khanna, Isak Froumin, Jinghuan Shi, Pradeep Kumar Choudhury, Tara Beteille, Francisco Marmolejo, Namrata Tognatta
Proceedings of the National Academy of Sciences of the United States of America , 2019

We assess and compare computer science skills among final-year computer science undergraduates (seniors) in four major economic and political powers that produce approximately half of the science, technology, engineering, and mathematics graduates in the world. We find that seniors in the United States substantially outperform seniors in China, India, and Russia by 0.76–0.88 SDs and score comparably with seniors in elite institutions in these countries. Seniors in elite institutions in the United States further outperform seniors in elite institutions in China, India, and Russia by ∼0.85 SDs. The skills advantage of the United States is not because it has a large proportion of high-scoring international students. Finally, males score consistently but only moderately higher (0.16–0.41 SDs) than females within all four countries.

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Journal Articles

Parental Migration, Educational Achievement, and Mental Health of Junior High School Students in Rural China

Fang Chang, Yuxi Jiang, Prashant Loyalka, James Chu, Yaojiang Shi, Annie Osborn, Scott Rozelle
China Economic Review , 2019
China's rapid development has led to an unprecedented increase in migration rates as an evergrowing number of rural residents migrate to urban areas to seek better job opportunities an help alleviate family poverty. Economic pressures and structural restrictions force many of these migrant workers to leave their children behind in their rural homes, which has led to the emergence and expansion of a new subpopulation in China: left-behind children (LBCs). This study examines the impacts of parental migration on the educational outcomes (specifically math achievement) and mental health (specifically anxiety) of LBCs using data covering 7495 children in a prefecture of Shaanxi Province (from three surveys conducted between 2012 and 2014). We distinguish between “both parents migrating,” “one parent migrating,” “only a father migrating,” and “only a mother migrating.” We also explore the impacts on male versus female LBCs. We find no significant impact of parental migration on the math achievement of LBCs. In terms of mental health, however, our results indicate that left-behind girls were negatively affected by one parent migrating, especially if the migrating parent was the father. The findings suggest that it may not be necessary for policy makers to design special programs to improve educational outcomes of LBCs in general. However, local committees, schools, and parents should pay particular attention to left-behind girls living with only one parent, as they may be more vulnerable to mental health problems than their peers.
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Journal Articles

Stereotype Threat and Educational Tracking: A Field Experiment in Chinese Vocational High Schools

James Chu, Prashant Loyalka, Guirong Li, Liya Gao, Yao Song
Socius , 2018

Educational tracks create differential expectations of student ability, raising concerns that the negative stereotypes associated with lower tracks might threaten student performance. The authors test this concern by drawing on a field experiment enrolling 11,624 Chinese vocational high school students, half of whom were randomly primed about their tracks before taking technical skill and math exams. As in almost all countries, Chinese students are sorted between vocational and academic tracks, and vocational students are stereotyped as having poor academic abilities. Priming had no effect on technical skills and, contrary to hypotheses, modestly improved math performance. In exploring multiple interpretations, the authors highlight how vocational tracking may crystallize stereotypes but simultaneously diminishes stereotype threat by removing academic performance as a central measure of merit. Taken together, the study implies that reminding students about their vocational or academic identities is unlikely to further contribute to achievement gaps by educational track.

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Journal Articles

Ability Tracking and Social Trust in China's Rural Secondary School System

Fan Li, Prashant Loyalka, Hongmei Yi, Yaojiang Shi, Natalie Johnson, Scott Rozelle
School Effectiveness and School Improvement , 2018

The goal of this paper is to describe and analyze the relationship between ability tracking and student social trust, in the context of low-income students in developing countries. Drawing on the results from a longitudinal study among 1,436 low-income students across 132 schools in rural China, we found a significant lack of interpersonal trust and confidence in public institutions among poor rural young adults. We also found that slow-tracked students have a significantly lower level of social trust, comprised of interpersonal trust and confidence in public institutions, relative to their fast-tracked peers. This disparity might further widen the gap between relatively privileged students who stay in school and less privileged students who drop out of school. These results suggest that making high school accessible to more students may improve social trust among rural low-income young adults.

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Journal Articles

Unequal Access to College in China: How Far Have Poor, Rural Students Been Left Behind?

Hongbin Li, Prashant Loyalka, Binzhen Wu, Jieyu Xie, Scott Rozelle
The China Quarterly , 2018

In the 1990s, rural youth from poor counties in China had limited access to college. After mass college expansion started in 1998, however, it was unclear whether rural youth from poor counties would gain greater access. The aim of this paper is to examine the gap in college and elite college access between rural youth from poor counties and other students after expansion. We estimate the gaps in access by using data on all students who took the college entrance exam in 2003. Our results show that gaps in access remained high even after expansion.

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