دورية أكاديمية

Design and Analytic Features for Reducing Biases in Skill-Building Intervention Impact Forecasts

التفاصيل البيبلوغرافية
العنوان: Design and Analytic Features for Reducing Biases in Skill-Building Intervention Impact Forecasts
اللغة: English
المؤلفون: Alvarez-Vargas, Daniela (ORCID 0000-0002-4075-1154), Wan, Sirui, Fuchs, Lynn S. (ORCID 0000-0003-2099-5247), Klein, Alice, Bailey, Drew H.
المصدر: Journal of Research on Educational Effectiveness. 2023 16(2):271-299.
الإتاحة: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journalsTest
تمت مراجعته من قبل الزملاء: Y
Page Count: 29
تاريخ النشر: 2023
Sponsoring Agency: Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) (DHHS/NIH)
Institute of Education Sciences (ED)
National Science Foundation (NSF)
Contract Number: 2R01HD053714
U54HD083211
R305K050004
DGE1839285
Intended Audience: Researchers
نوع الوثيقة: Journal Articles
Reports - Research
Education Level: Early Childhood Education
Elementary Education
Grade 1
Primary Education
الواصفات: Bias, Skill Development, Intervention, Program Evaluation, Prediction, Mathematics Skills, Regression (Statistics), Program Effectiveness, Mathematics Achievement, Outcomes of Education, Grade 1, Elementary School Students, Achievement Tests
معرفات التقييم و الدراسة: Wide Range Achievement Test
DOI: 10.1080/19345747.2022.2093298
تدمد: 1934-5747
1934-5739
مستخلص: Despite policy relevance, longer-term evaluations of educational interventions are relatively rare. A common approach to this problem has been to rely on longitudinal research to determine targets for intervention by looking at the correlation between children's early skills (e.g., preschool numeracy) and medium-term outcomes (e.g., first-grade math achievement). However, this approach has sometimes over--or under--predicted the long-term effects (e.g., 5th-grade math achievement) of successfully improving early math skills. Using a within-study comparison design, we assess various approaches to forecasting medium-term impacts of early math skill-building interventions. The most accurate forecasts were obtained when including comprehensive baseline controls and using a combination of conceptually proximal and distal short-term outcomes (in the nonexperimental longitudinal data). Researchers can use our approach to establish a set of designs and analyses to predict the impacts of their interventions up to 2 years post-treatment. The approach can also be applied to power analyses, model checking, and theory revisions to understand mechanisms contributing to medium-term outcomes.
Abstractor: As Provided
ملاحظات: https://osf.io/eszauTest
IES Funded: Yes
Entry Date: 2023
رقم الانضمام: EJ1387534
قاعدة البيانات: ERIC
الوصف
تدمد:1934-5747
1934-5739
DOI:10.1080/19345747.2022.2093298