Early experiences and school readiness: A within and between exploration of the Opportunity Propensity Model

• In Event: Poster Session 02
  In Poster Session: PS 02 Topic - Education, Schooling

Abstract

The Opportunity-Propensity (O-P) model was created to explain individual and group
differences in achievement and cognitive development. In this model, two conditions must be met. Opportunity factors are aspects of learning contexts at home and school that promote skill acquisition. Propensity factors are characteristics of children that make them prone to acquire skills in these contexts such as existing knowledge, motivation, and self-regulation. However, some children are more prone to these opportunities and propensities than others. Antecedent factors are variables that provide context for this, like socio-economic status, gender, race/ethnicity, and parental expectations for their children’s education. Byrnes (Byrnes, Miller-Cotto, Wang, 2018; Byrnes, Wang, Miller-Cotto, 2019) determined that propensity factors mediated the effects of opportunity variables and science, math, and reading, respectively. However, these prior OP models examined achievement outcomes at one time point and among single outcomes at a time. Considering the transactional nature of achievement and working memory over time (Miller-Cotto & Byrnes, 2019), the OP model requires additional extensions to investigate how it may explain covarying achievement relationships over time, particularly when explicitly disentangling within-person (WP) from between-person (BP) variability (e.g., Berry & Willoughby, 2017).
We propose examining the O-P model using a random-intercepts cross-lagged panel model (RI-CLPM; Hamaker et al., 2015), which helps distinguish stable, individual differences in outcomes over time from time-varying WP variability. Prior OP models have examined multiple outcomes, but to date, OP models have not examined covarying processes over time, despite the importance of transactional processes between achievement and working memory (Miller-Cotto & Byrnes, 2019). In particular, RI-CLPMs help measure the extent to which OP factors explain BP and/or WP variability in transactional models of achievement and working memory. Our proposed model is Figure 1.
We use the ECLS-K:2011 dataset for our analyses and included approximately 5,000 children in kindergarten through fifth grade. The demographic breakdown of the full sample (approximately 15,000) is: 49% female, and 54% White, 13% Black, 21% Latino, 6% Asian, and 6% “Other” race/ethnic groups. Most (86%) of the children’s home language was English. Variables of interest included parent expectations, family income, home language, time spent on math, being read to (i.e., opportunities), literacy skills, math skills, self-regulation, and executive functions (propensities).
We anticipate contributing to our understanding of what opportunities and propensities predict student outcomes and how these effects may be understood when parsing-out BP from WP variation. This allows us to more precisely examine the effects of OP factors on achievement and draw clearer conclusions for how the OP model can inform future research and practice. Specifically, we seek to understand the sources of variability within and between individuals. Schools tend to compare students’ achievement patterns to themselves as well as their peers, and our approach explicitly takes into account those different sources of variability. This study aims to highlight sources of variation across time and how the OP model may differentially explain those sources while advancing the methodology of OP analysis.

Authors

• Dana Miller-Cotto, Kent State University
  Presenting Author

• Garret Hall, Florida State University
  Non-Presenting Author

• Sophia Putzeys, Florida State University
  Non-Presenting Author