Equity in Data Knips, Andrew; Lopez, Sonya; Savoy, Michael ...
ASCD,
2022, 2022-10-00
eBook, Book
This book helps teachers demystify and democratize data analysis, shows how data can be humanizing information, and helps educators embed equity in data work.
A substantial literature shows that U.S. early childhood interventions have important long-term economic benefits. However, there is little evidence on this question for developing countries. We ...report substantial effects on the earnings of participants in a randomized intervention conducted in 1986–1987 that gave psychosocial stimulation to growth-stunted Jamaican toddlers. The intervention consisted of weekly visits from community health workers over a 2-year period that taught parenting skills and encouraged mothers and children to interact in ways that develop cognitive and socioemotional skills. The authors reinterviewed 105 out of 129 study participants 20 years later and found that the intervention increased earnings by 25%, enough for them to catch up to the earnings of a nonstunted comparison group identified at baseline (65 out of 84 participants).
Co-published with and In this era of Big Data, institutions of higher education are challenged to make the most of the information they have to improve student learning outcomes, close equity gaps, ...keep costs down, and address the economic needs of the communities they serve at the local, regional, and national levels. This book helps readers understand and respond to this analytics revolution, examining the evolving dynamics of the institutional research (IR) function, and the many audiences that institutional researchers need to serve.Internally, there is a growing need among senior leaders, administrators, faculty, advisors, and staff for decision analytics that help craft better resource strategies and bring greater efficiencies and return-on-investment for students and families. Externally, state legislators, the federal government, and philanthropies demand more forecasting and more evidence than ever before. These demands require new and creative responses, as they are added to previous demands, rather than replacing them, nor do they come with additional resources to produce the analysis to make data into actionable improvements. Thus the IR function must become that of teacher, ensuring that data and analyses are accurate, timely, accessible, and compelling, whether produced by an IR office or some other source. Despite formidable challenges, IR functions have begun to leverage big data and unlock the power of predictive tools and techniques, contributing to improved student outcomes.
Do teachers innovate? Do they try different pedagogical approaches? Are practices within classrooms and educational organisations changing? And to what extent can change be linked to improvements? A ...measurement agenda is essential to an innovation and improvement strategy in education. Measuring Innovation in Education offers new perspectives on addressing the need for such measurement. This books first objective is informative: it gives readers new international comparative information about innovation in education compared to other sectors. And it documents change in a variety of dimensions of school practices between 1999 and 2011. Its second objective is methodological: it assesses two approaches to capturing the extent and type of innovation occurring within and across education systems. The third objective is exploratory: this book showcases a large-scale pilot that presents over 200 measures of innovation in education using existing international data. Last but not least, the fourth objective is prospective: this report proposes new approaches to measuring innovation in education in the future. This book is the beginning of a new journey: it calls for innovations in the field of measurement - and not just of education.
Atopic dermatitis (AD) is associated with mental health disorders, but its impact on global mental health symptoms is less clear.
To determine the association between pediatric AD and mental health ...impairment.
In a cross-sectional study using 2013-2017 United States National Health Interview Survey data, children with and without AD were assessed for mental disorder with impairment (MDI) using a validated behavioral screening questionnaire. Mental health services utilization was also reported.
The prevalence of any MDI was 26.7% (95% confidence interval CI, 25.1-28.3) among children with AD and 17.7% (95% CI, 17.2-18.2) among those without AD, with severe MDI being present in 10.9% (95% CI 9.9-12.1) and 6.2% (95% CI 5.9-6.5), respectively. Adjusted for sociodemographic factors, AD was associated with higher odds of MDI (odds ratio, 1.52; 95% CI, 1.39-1.67), including impairments in conduct, emotions, peer relationships, and attention. Among children with AD, 19.9% (95% CI, 16.6-23.8) and 53.5% (95% CI, 48.5-58.5) of those with mild or severe MDI, respectively, had seen a mental health professional in the last year.
Misclassification bias may arise from self-reported data.
AD is associated with clinically significant mental health symptoms, but many affected children may not seek or receive care for their symptoms.
Long-term evaluations of child health promotion programs are required to assess their sustainability and the need for reintervention.
This study sought to explore the long-term impact of a preschool ...health promotion intervention delivered in an urban low-income area of Colombia (phase 1) and to assess the effect of a new community-based intervention (phase 2).
In phase 1, a cross-sectional analysis of knowledge, attitudes, and habits (KAH) toward a healthy lifestyle and ideal cardiovascular health (ICH) scores of 1,216 children 9 to 13 years old was performed. Of the total, 596 had previously received a preschool health promotion intervention at 3 to 5 years old, whereas the remaining 620 were not previously intervened (intervention-naive group). In phase 2, all children were cluster randomized 1:1 to receive either a 4-month educational intervention (the SI! Program) to instill healthy behaviors in community centers (24 clusters, 616 children) or to control (24 clusters, 600 children). Previously intervened and intervention-naive children were not mixed in the same cluster. The primary outcomes were the change from baseline in KAH and ICH scores. Intervention effects were tested for with linear mixed-effects models.
In phase 1, ∼85% of children had nonideal cardiovascular health, and those who previously received a preschool intervention showed a negligible residual effect compared with intervention-naive children. In phase 2, the between-group (control vs. intervention) differences in the change of the overall KAH and ICH scores were 0.92 points (95% confidence interval CI: −0.28 to 2.13; p = 0.133) and −0.20 points (95% CI: −0.43 to 0.03; p = 0.089), respectively. No booster effect was detected. However, a dose-response effect was observed, with maximal benefit in children attending >75% of the scheduled intervention; the difference in the change of KAH between the high- and low-adherence groups was 3.72 points (95% CI: 1.71 to 5.73; p < 0.001).
Although overall significant differences between the intervention and control groups were not observed, high adherence rates to health promotion interventions may improve effectiveness and outcomes in children. Reintervention strategies may be required at multiple stages to induce sustained health promotion effects (Salud Integral Colombia SI! Colombia II; NCT03119792)
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Education research has experienced a methodological renaissance over the past two decades, with a new focus on large-scale randomized experiments. This wave of experiments has made education research ...an even more exciting area for statisticians, unearthing many lessons and challenges in experimental design, causal inference, and statistics more broadly. Importantly, educational research and practice almost always occur in a multilevel setting, which makes the statistics relevant to other fields with this structure, including social policy, health services research, and clinical trials in medicine. In this article we first briefly review the history that led to this new era in education research and describe the design features that dominate the modern large-scale educational experiments. We then highlight some of the key statistical challenges in this area, including endogeneity of design, heterogeneity of treatment effects, noncompliance with treatment assignment, mediation, generalizability, and spillover. Though a secondary focus, we also touch on promising trial designs that answer more nuanced questions, such as the SMART design for studying dynamic treatment regimes and factorial designs for optimizing the components of an existing treatment.
The editorial policies of several prominent educational and
psychological journals require that researchers report some measure of effect
size along with tests for statistical significance. In ...analysis of
variance contexts, this requirement might be met by using eta squared or
omega squared statistics. Current procedures for computing these
measures of effect often do not consider the effect that design features of the
study have on the size of these statistics. Because
research-design features can have a large effect on the estimated
proportion of explained variance, the use of partial eta or omega squared
can be misleading. The present article provides formulas for computing
generalized eta and omega squared statistics, which provide estimates of
effect size that are comparable across a variety of research
designs.
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