Despite the critical importance of early elementary education, formal measurement of student learning typically does not occur until third grade when students begin participating in state assessments. In a prior report, Hiroyuki Yamada, a researcher with Curriculum Associates, developed a measure of learning growth for early grades and explored trends in mathematics outcomes for a national sample of students who entered first grade in fall 2021. Yamada found that a subset of schools included in the sample demonstrated significantly more learning growth than the average.
In this follow-up report, Yamada further examines these variations in learning growth across schools, focusing on commonly measured school attributes that may relate to learning growth. Yamada calculated measures of learning growth for students entering first grade in fall 2021 from 6,274 schools using Curriculum Associates’ i-Ready Diagnostic for Mathematics, a web-based adaptive interim assessment tool designed to measure four domains of mathematical skills. Performance data from the 2021-2022 and 2022-2023 school years were combined with school-level demographic data from the U.S. Census Bureau and the National Center of Education Statistics. The following is the E4 team’s summary of this report and its implications.
Key Finding 1: Schools’ average learning growth changes year-to-year.
- Most schools with first graders who had higher-than-average learning growth exhibited only average learning growth when those students were in second grade. Conversely, most schools with first graders who had lower-than-average learning growth improved to average learning growth when those students were in second grade.
- Additional research is needed to assess changes in learning growth longitudinally. Future studies may consider assessing schools’ growth at each grade level for the same cohort of students, observing their learning growth over time to assess the sustainability of their growth. Researchers may also consider exploring how schools’ average overall growth across all grades changes from year to year.
Key Finding 2: The relationships between schools’ average learning growth and school demographic characteristics, including location, remain unclear.
- School locations did not have a clear relationship with learning growth in terms of median household incomes and locales (i.e., suburban, city, rural, town).
- This finding may indicate that other contextual factors are important (e.g., how schools create learning environments that maximize student engagement and performance).
- Schools with higher-than-average learning growth were more likely to have a higher percentage (75%+) of White students; however, further research is needed, as there were a substantial number of schools that had higher-than-average learning growth and a lower percentage (< 25%) of White students.
Key Finding 3: Additional research is needed to understand the stability of learning growth, especially for schools that have higher-than-average learning growth.
- This study focuses on learning growth at the school level. Additional studies are needed to provide insight into teacher- or classroom-level factors that may affect growth (e.g., instructional strategies).
- Studying schools that have sustained higher-than-average learning growth may help illuminate instructional practices and leadership efforts that contribute to student growth. Qualitative methods, such as interviews with teachers or leaders, may be especially useful to better understand factors that might be driving learning growth.
- Students begin taking state assessments for grade-level learning in third grade. It may be beneficial to explore how this transition, along with other factors, affects educators and what impact, if any, this has on student mathematics learning.
- Data from i-Ready Personalized Instruction can be leveraged to help identify factors or processes that explain variations in implementation and performance across different levels of the education system to contribute to reducing undesirable variations and increasing the efficacy of learning space more reliably at scale; consequently, research efforts would be reflected in the bell curve shifting to the right.