Purdue University.
Department of Human Development and Family Sciences.
Dev Psychol. 2022 Oct;58(10):1947-1961. doi: 10.1037/dev0001402. Epub 2022 Jun 6.
In the present study, we investigated the relative impact of age- versus schooling-related growth in school readiness skills using four modeling approaches that leverage natural variation in longitudinal data collected within the preschool year. Our goal was to demonstrate the applicability of different analytic techniques that do not rely on assumptions inherent in commonly applied methods (e.g., the school entrance cutoff method, regression discontinuity design) that selection into subsequent grades is based on birthdate alone and that the quality of experiences between grades are not responsible for differences in outcomes. Notably, these alternative methods also do not require data collected across multiple grades. Participants included 316 children ( = 54.77 months; 47.15% male) who mostly identified as White (64%) or Latinx (20%). A little over half of the sample attended Head Start preschools (54.75%). Four modeling techniques that leverage data collected at two timepoints in preschool were used to examine schooling effects on children's preliteracy, emergent math, and executive function (EF) skills. Results replicate evidence from previous research using traditional methods. Specifically, findings across all models demonstrate a schooling effect on preliteracy skills during the preschool year, above and beyond maturation, but not on emergent math or EF. We discuss the advantages and disadvantages of each analytical tool for researchers who are interested in answering questions about the effects of schooling with diverse data collection strategies, as well as broader implications for the integrity of educational and developmental science. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
在本研究中,我们使用了四种建模方法来研究与年龄相关的和与学校教育相关的入学准备技能增长的相对影响,这些方法利用了在学前年度内收集的纵向数据中的自然变化。我们的目标是展示不同分析技术的适用性,这些技术不依赖于常见应用方法(例如,入学截止日期法、回归不连续设计)所固有的假设,即后续年级的选择仅基于出生日期,并且年级之间的经验质量不会导致结果差异。值得注意的是,这些替代方法也不需要跨多个年级收集数据。参与者包括 316 名儿童(=54.77 个月;47.15%为男性),他们主要被认定为白人(64%)或拉丁裔(20%)。略多于一半的样本参加了学前的“先普”项目(54.75%)。使用四种在学前两个时间点收集数据的建模技术来检查学校教育对儿童前读写、早期数学和执行功能(EF)技能的影响。结果复制了使用传统方法进行的先前研究的证据。具体来说,所有模型的发现都表明,在学前年度,除了成熟度之外,学校教育对前读写技能有影响,但对早期数学或 EF 没有影响。我们讨论了每种分析工具的优缺点,对于那些对使用不同的数据收集策略回答关于学校教育影响的问题以及对教育和发展科学的完整性有更广泛影响的研究人员来说,这些工具是有用的。(PsycInfo 数据库记录(c)2022 APA,保留所有权利)。