AERA Open

“Educational equity” is universally lauded but equally ill-defined. At least five contrasting meanings of equity are in current use: equal distributions of outcomes across populations; equal outcomes for every child; equal resource allocations across students, schools, districts, states, or nations; equal experiences for each child; and equal levels of growth by each child. Furthermore, these conceptions are themselves often subsumed to concerns for benefiting the less advantaged, ensuring educational adequacy, or prioritizing short-term benefits versus long-term structural change. Researchers, educators, and policy makers alike will benefit from understanding these distinctions and trade-offs, not least in order to reimagine and restructure the unjust conditions that make some of those trade-offs unavoidable in the first place.

Meira Levinson

Tatiana Geron

Harry Brighouse

Conceptions of Educational Equity

教育公平观念

The growing visibility of autism spectrum disorder (ASD) and the trend toward inclusive classroom practices present teachers with the unique responsibility of providing an inclusive learning environment for all students. This study sought to explore how teachers may use children's picture books about autism to provide nondisabled students with experiences aimed at increasing student understandings toward autism. Researchers compiled 35 children's books for content analysis and identified significant themes presented as five assertions. Findings indicate children's picture books about autism may (a) teach readers about the core characteristics of ASD, (b) illustrate how individuals with autism may be "at risk," (c) expand on ways neurotypical children are similar and different to individuals with autism, (d) emphasize the importance of influential language, and (e) present insights about autism through the use of multiple perspectives. Findings with exemplar texts representative of each theme are presented, and practical classroom applications are discussed.

Amy Price Azano

Mary Tackett

Miranda Sigmon

Understanding the Puzzle Behind the Pictures

理解图片背后的谜团

Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a well-known framework for theorizing validity in the social sciences, this article provides both an overview of threats to validity in supervised machine learning and plausible approaches for addressing such threats. It collates a list of current best practices, brings supervised learning challenges into a unified conceptual framework, and offers a straightforward reference guide on crucial validity considerations. Finally, it proposes a novel research protocol for researchers to use during project planning and for reviewers and scholars to use when evaluating the validity of supervised machine learning applications.

Kylie Anglin

Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers

解决监督机器学习中效度威胁：教育研究者的框架与最佳实践

In 2018, a wave of educator strikes called Red for Ed swept through several states. Educators in Arizona won additional funding from the state legislature, supposedly for teacher salaries, which school boards could spend as they chose. This article quantitatively examines the participation and results of the 2018 Arizona educator strike, using this example to speak to theoretical work on types of union activity. I find that after the strike, per-pupil funding, teacher salaries, and student support staff salaries all increased. However, poststrike funding was added to Arizona’s preexisting funding formula, which advantaged the small, rural, predominantly White districts whose educators were less likely to go on strike. Educators who went on strike (often from large, urban districts with low property wealth) thus received less money for their districts and smaller raises than nonparticipating educators. This raises important concerns about how free riders can affect different types of union organizing.

Michelle Doughty

Rising Arizona: Participation and Results of the 2018 Red for Ed Strike

《崛起的亚利桑那：2018年红衣为教育罢工的参与与结果》

Multilingual learners (MLs) represent an increasing proportion of public school students. Although much attention has been given to their academic performance in English language arts and math, less research has addressed their academic performance in science, particularly in elementary school. This study leveraged nationally representative data from the Early Childhood Longitudinal Study of 2010–2011 to document the science test score trajectories of MLs from kindergarten through fifth grade. Using descriptive statistics and regression analyses, our findings document wide variation in elementary science test performance among subgroups of MLs while also documenting the rapid gains this group makes in science performance across the elementary years compared with non-MLs. Our study is among the first to use nationally representative data to examine science learning trajectories of MLs and provides a foundation for policy, practice, and future research aimed at understanding how the linguistic assets of MLs promote science learning.

F. Chris Curran

Mark B. Pacheco

Lelydeyvis Boza

Katharine Harris-Walls

Tiffany Tan

Amber Deig

Multilingual Learners and Elementary Science Achievement: Exploring Trends and Heterogeneity Across Subgroups

多语言学习者与小学科学成绩：探索各子群体间的趋势与异质性

The debate over race-conscious admissions has gained prominence, notably in cases such as Students for Fair Admissions v. Harvard. In debates on race-conscious admissions, the question is often not whether a student will go to college, but which college the student will attend. Using data from the High School Longitudinal Study of 2009, we examined racial and socioeconomic disparities in the probability of acceptance to a student’s first-choice college based on institutional selectivity. Race was a significant predictor of acceptance to a first-choice college, with Black and Asian students facing odds of acceptance that were 46% to 59% lower than those of White peers. However, at highly competitive or most selective colleges, race was no longer a significant predictor, and racial disparities in acceptance rates diminished. Socioeconomic status had no significant association with the probability of acceptance to a first-choice college.

Sooji Kim

Michael N. Bastedo

Who Gets Their First Choice? Race and Class Differences in College Admissions Outcomes

谁得到了他们的首选？大学录取结果中的种族和阶级差异

The roles of technology and education were at the forefront throughout the COVID-19 pandemic. This mixed-methods study examines the role of the three levels of the digital divide (i.e., access, capability, and outcomes) during the COVID-19 pandemic in Kentucky. We create and analyze a new multifaceted measure of district-level digital capacity to examine the role of prior investments in technological infrastructure and the relationship with student scores in reading, math, and the ACT exam. Increased investment in digital preparedness leading up to the pandemic was protective against decreases in test scores. However, nonmetropolitan and Appalachian areas did not experience the same benefits from their digital capacity investments compared with their metropolitan counterparts. Using interview data from the summer of 2021 with 16 educators predominantly from Appalachian school districts, we discuss why these efforts to bridge the digital divide were hindered by larger, systematic challenges faced by their students.

Emily E.N. Miller

Sarah Pedersen

Promises and Limitations in District Digital Capacity for Education During COVID-19

COVID-19期间教育领域区级数字化能力的潜力与局限

Abbreviation	AERA Open
Journal Impact	3.63
Quartiles(Global)	EDUCATION & EDUCATIONAL RESEARCH(Q1)

ISSN	2332-8584
h-index	41

Publication Information	Publisher: SAGE Publications Inc.，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2015，Proportion of original research papers: 98.77%，Self Citation Rate:2.90%， Gold OA Rate: 95.70%
Journal Fees	$1000Details
Average review cycle	网友分享经验：15 Weeks

AERA Open

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Conceptions of Educational Equity

Understanding the Puzzle Behind the Pictures

Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers

Rising Arizona: Participation and Results of the 2018 Red for Ed Strike

Multilingual Learners and Elementary Science Achievement: Exploring Trends and Heterogeneity Across Subgroups

Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers

Rising Arizona: Participation and Results of the 2018 Red for Ed Strike

Multilingual Learners and Elementary Science Achievement: Exploring Trends and Heterogeneity Across Subgroups

Who Gets Their First Choice? Race and Class Differences in College Admissions Outcomes

Promises and Limitations in District Digital Capacity for Education During COVID-19