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Using the Program for International Student Assessment (PISA) surveys (2003–2015), this chapter explores the relationship between the gender gap in math test scores and computer (digital devices) gaming, as a potential “swimming upstream” factor in the quest to close that gap. Using a decomposition based on a pooled hybrid specification, we attribute two to three points (from 13% to 29%) of the gender math gap to gender differences in the incidence and returns to intense gaming. The comparison of the negative versus positive girl-specific effects found for collaborative games versus single-player games suggest a potential role for gaming network effects.

This paper examines the effect of charter schools on student achievement in Michigan using a matched student dataset. Proponents of charter schools argue that by applying market pressure to traditional public schools, having the freedom and incentives to apply innovative curricular and instructional ideas, and offering students a choice in the schools they attend, charter schools can raise student achievement. Studies of the effect of charter schools on student achievement have been mixed, however. Methodologies vary widely depending upon the availability of data. Some studies track the same students as they transfer between charter schools and traditional schools; others rely on cross-sectional student or building-level data. We construct a dataset that matches the scores of the same student taking tests in two consecutive years. Estimating a value-added education production function, we find that charter schools are at a disadvantage to traditional public schools by an average of 0.2 standard deviations. These findings depend upon proper matching of students across school types, which in this case is accomplished by using prior test scores as a control variable and as a way to segment the sample. We also find that charter schools run by for-profit companies have an advantage over those run by not-for-profits and that charter schools improve the longer they are in operation.

The purpose of this two-part research was to investigate the effect of remote learning on student progress in elementary education. Part 2, presented in this paper, is a follow-up study to examine how student progression in the two pandemic-induced environments compared to the pre-pandemic conditions.

The authors expanded the quantitative, quasi-experimental factorial design of the authors' initial study with additional ex-post-facto standardized test score data from before the pandemic to enhance the group comparison with a control: the conventional pre-pandemic classroom environment. Thus, the authors were able to examine in which ways the two pandemic-induced learning environments (remote and hybrid) may have affected learner progress in the two subject areas: English Language (ELA) and Math. Additionally, the authors provided a grade-by-grade breakdown of analysis results.

Findings revealed significant group differences in grade levels at or below 6th grade. In the majority of analyzed comparisons, learner achievement in the hybrid group was significantly lower than those in either the remote or the classroom group, or both.

The additional findings further supported the authors' initial hypotheses: Differences in the consistency and continuity of educational approaches, as well as potential differences in learner predispositions and the availability of home support systems may have influenced observed results. Thus, this research also contributes to the general knowledge about learner needs in elementary education.

During the pandemic, remote learning became ubiquitous. However, in contrast to e-learning in postsecondary education, for which an abundance of research has been conducted, relatively little is known about the efficacy of such approaches in elementary education.

Results from international large-scale assessments, such as PISA surveys, suggest that boys do better in math and science, whereas girls do better in reading. How do gender gaps vary across subjects, when estimated simultaneously? Building on the work of Tsai, Smith, and Hauser (2017), we answer this question by applying a multilevel-MIMIC model that enables us to estimate gender gaps in two ways: gender differences in the effects of observed family and school factors on math, science, and reading scores; and the “adjusted” gender gaps in test scores across all three subjects after controlling for observables. We apply the model to 2012 PISA data of students aged 15–16 and enrolled in 9th or 10th grade in three East Asian (Japan, South Korea, and Taiwan) and three Western countries (USA, Germany, and the Czech Republic) that represent both similar and different types of school systems. Our findings indicate that the gender gap in math or science achievement in Western countries, favoring boys, does not necessarily apply to the East Asian countries examined here, while all three East Asian countries exhibit similar features of gender reading gaps in the 10th grade. There is evidence indicating that observed background and school factors impact boys’ and girls’ achievement in a similar way in USA, Japan, Korea, Taiwan, and the Czech Republic, but not in Germany. Overall, gender differences in family and school influences do not account for gender differences in academic achievement in any of the six countries.

The purpose of this paper is to examine how gender equality influences difference in cognitive skills between genders. For the closer examination of Guiso et al. (2008), restricting the sample to immigrants allows us to reduce the possibility of reverse causality.

Using PISA 2012 matched with the gender wage gap sourced from World Economic Forum’s Global Gender Index 2011, the author compares the effect of the wage gap among the areas of mathematics, science and reading.

Decreased gender wage gap leads to girls exhibiting a reduced incidence of lateness and skipping school compared with boys, which in turn improves girls’ test scores in mathematics, science and reading. The direct effect of the decreased wage gap on test scores exceeds its indirect effect on performance owing to influencing school attendance.

The findings of this paper provide evidence that higher female wage level relative to male wage level incentivizes female students to attend school, resulting in their achieving higher test scores not only for mathematics, but also for science and reading.

Virtually all parents want their children to succeed academically. How to achieve this goal, though, is far from clear. Specifically, the temporal spacing between adjacent births has been shown to affect educational outcomes. While many of these studies have produced substantial and statistically significant results, these results have been relatively narrow in their application due to data limitations. Using Colorado birth certificates matched to schooling outcomes, we investigate the relationship between birth spacing and educational attainment. We instrument birth spacing with a previous pregnancy that did not result in a live birth. We find no overall effect of spacing on either the first or second children’s grade 3–10 test scores. Stratifying by the sexes of the children, we find that when the first child is a boy and the second a girl, an extra year of spacing increases the first child’s math, reading, and writing test scores by 0.07–0.08 SD, while there is no impact on the second child. This is the first study to do such an analysis using matched large-scale birth and elementary to high school administrative data, and to leverage a very large dataset to stratify our results by the sexes of the children.

The Bryant University Mathematics Department has been collecting math placement scores and admissions data for all incoming freshmen for many years. In the past, the authors have used these data mainly for placement in first-year classes and more recently to invite the most mathematically talented students to become mathematics majors. The purpose of this paper is to use the same data source to predict persistence in declared majors for all incoming students.

In order to categorize the students, the authors use cluster analysis, one of the tools of data mining, to see if students in particular majors share similar strengths based on the available data. The authors follow up this analysis by running a multivariate analysis of variance (MANOVA) to confirm that the means of the clusters are significantly different.

The cluster analysis resulted in five distinct clusters, which were confirmed by the results of the MANOVA. The authors also found how many students in each cluster persisted in their chosen major.

These results will help to improve counseling and proper placement of incoming freshmen. They will also be helpful in long-range planning of upper-level courses. Retention of students in their majors is an important concern for colleges and universities as it relates to planning issues, such as scheduling classes, particularly for upper classmen. This could also affect departmental requirements, such as the size of the faculty.

Social psychological perspectives on educational stratification offer explanations that bridge the macro and micro social worlds. However, while ethnoracial disparities in academic achievement are evident during the earliest grade levels, most social psychological research in this area has examined high school or college student samples and has used a black–white binary to operationalize race.

We use longitudinal structural equation models to examine links between academic self-efficacy beliefs and school performance among a national sample of diverse third- through eighth-grade students in the United States.

Contrary to hypotheses derived from the student identity literature, we find no evidence that elementary and middle school students from different ethnoracial backgrounds vary in the degree to which they selectively discount evaluative feedback in their academic self-efficacy construction, nor in the extent to which they demonstrate disrupted links between academic self-efficacy and subsequent academic performance.

The study examines the extent to which race-linked social psychological processes may be driving academic achievement inequalities during the primary schooling years.

Internet use has become particularly prevalent among adolescents, prompting much thought and concern about both its potential benefits and adverse effects on adolescent learning outcomes. Much of the empirical literature on the impact of Internet use on adolescent learning outcomes is mixed, and few studies examine the causal relationship between the two in rural China. In order to bridge these gaps, we use empirical analysis to investigate the effect of Internet use on the learning outcomes of adolescents in rural China.

We use fixed effect models with samples drawn from a large nationally representative dataset (the China Family Panel Studies—CFPS) to identify the causal impacts of Internet use on the learning outcomes of three cohorts (Cohort A (N = 540), Cohort B (N = 287) and Cohort C (N = 827)) of adolescents in rural China.

The results of the descriptive analysis show a continued increase in the number of adolescents accessing the Internet and the amount of time they spend online. The results of the fixed effect models show that Internet use has positive (in many of the analyses), but mostly insignificant impacts, on the learning outcomes of adolescents. In the sets of results that find significant associations between Internet use and learning outcomes, the measured effects are moderate.

This study investigates the causal relationship between Internet use and adolescent learning outcomes in rural China. The findings claim that there is not a great need to worry about adverse effects of Internet use on adolescent learning development. Attention, however, should focus on seeking ways to improve the positive effects of the Internet use on adolescent learning outcomes. The study will provide a reference and experience for the development of education and the Internet in rural areas and promote the integrated development of urban and rural areas in China.

To combat poverty in China's rural areas, Chinese government has established an unconditional cash transfer program known as the Rural Minimum Living Standard Guarantee (Rural Dibao) Program. Interestingly, despite the importance of education in breaking cycles of poverty, little is known about Rural Dibao's impact on rural children's education. This study investigates Rural Dibao's impact on rural children's learning outcomes by first examining targeting issues within the program, exploring a causal relationship between Rural Dibao and learning outcomes, and then exploring potential mechanisms and heterogeneous effects.

Fixed effects model and propensity score weighting method and data from China Family Panel Studies (CFPS) from the years 2010 and 2014 were used.

The results suggest that the Rural Dibao program suffers from high levels of targeting error, yet is still effective (i.e., program transfers generally still go to people in need). The fixed effects and propensity score weighting models find that program participation raises rural children's standardized test scores in CFPS Chinese-language and math tests. In investigating mechanisms, increased education expenditure seems to connect Rural Dibao participation to increased learning results. The heterogeneity analysis shows that poorer, non-eastern, not left behind, younger or male children benefit from the program (while others have no effect).

These findings suggest that Rural Dibao participation boosts rural children's learning, which could indicate a long-term anti-poverty effect, and that if the program can resolve targeting problems, this effect could be even greater.