| NSF Org: |
DRL Division of Research on Learning in Formal and Informal Settings (DRL) |
| Recipient: |
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| Initial Amendment Date: | April 1, 2021 |
| Latest Amendment Date: | May 21, 2021 |
| Award Number: | 2100419 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Jessaca Spybrook
DRL Division of Research on Learning in Formal and Informal Settings (DRL) EDU Directorate for STEM Education |
| Start Date: | May 15, 2021 |
| End Date: | April 30, 2024 (Estimated) |
| Total Intended Award Amount: | $313,159.00 |
| Total Awarded Amount to Date: | $313,159.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1523 UNION RD RM 207 GAINESVILLE FL US 32611-1941 (352)392-3516 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1 UNIVERSITY OF FLORIDA GAINESVILLE FL US 32611-2002 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Discovery Research K-12 |
| Primary Program Source: |
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| Program Reference Code(s): | |
| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.076 |
ABSTRACT
The nation?s schools are growing in linguistic and cultural diversity, with students identified as English learners (ELs) comprising more than ten percent of the student population. Unfortunately, existing research suggests that ELs lag behind other students in science achievement, even in the earliest grades of school. This project will provide evidence on how school, classroom, teacher, and student factors shape elementary school science learning trajectories for ELs. The project will broaden ELs? participation in STEM learning by investigating how individual, classroom, and school level situations (inputs) such as instructional practices, learning environments, and characteristics of school personnel relate to EL elementary school science learning. Specifically, this study explores (1) a series of science inputs (time on science, content covered, availability of lab resources, and teacher training in science instruction), and (2) EL-specific inputs (classroom language use, EL instructional models, teacher certification and training, and the availability of EL support staff), in relation to ELs? science learning outcomes from a national survey.
This study provides a comprehensive analysis of English learners? (ELs) science learning in the early grades and the English learner instructional inputs and science instructional inputs that best predict early science outcomes (measured by both standardized science assessments and teacher-rated measures of science skills). The study uses the nationally representative Early Childhood Longitudinal Study (ECLS-K:2011) and employs a regression framework with latent class analysis to identify promising inputs that promote early science learning for ELs. Conceptually, rather than viewing the school-based inputs in isolation, the study explores how they combine to enhance students? science learning trajectories. The study addresses the following research questions: How do science test performance trajectories vary across and within EL student groups in elementary school? How do access to school, teacher, and classroom level science and EL inputs vary across and within EL student groups in elementary school? Which school, teacher, and classroom level science and EL inputs are predictive of greater science test performance gains and teacher-rated science skills in elementary school? Are the relationships among these school, teacher, and classroom level inputs and student test performance and teacher-rated science skills different for subgroups of EL students, particularly by race/ethnicity or by immigration status? Are there particular combinations of school, teacher, and classroom level inputs that are predictive of science learning gains (test scores and teacher-rated skills) for ELs as compared to students more broadly?
The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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PROJECT OUTCOMES REPORT
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This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Introduction
Multilingual learners (MLs) are students who come from households where a language other than English is spoken. This diverse and growing group, which includes those receiving formal English learner (EL) services at schools and many others, brings unique assets to their science learning and is important group to focus on for advancing science outcomes nationally. To date, however, there has been limited research at a national scale that looks at what school factors are most predictive of ML’s elementary school science learning. The objective of this study was to address this need by exploring the science learning trajectories of MLs in elementary school and how various science and language inputs related to their science learning outcomes.
Overview of Study Data and Methods
This study used nationally-representative data from the Early Childhood Longitudinal Study of 2010-11 (ECLS-K:2011) to examine the science learning trajectories of multilingual learners from kindergarten through fifth grade. The ECLS-K:2011 includes data on approximately 18,000 students with measures from student, parent, and teacher surveys and instruments.
MLs were defined as students from households where a non-English language was spoken and included a number of subgroups. For example, our study examined MLs who spoke Spanish and those who spoke less common non-English languages, those for whom the non-English language was the primary language used in the house and those for whom it was a secondary language, as well as those receiving formal English learner (EL) services at school and those not.
In a series of analyses, we examined the science learning trajectories of MLs and subgroups therein as measured by standardized science tests as well as teacher perceptions of science learning. Our analyses looked at how these trajectories changed over time for each subgroup and the school factors related to these changes. For example, we examined what happens to science performance when students are reclassified out of EL support services at schools. We also examined, broadly, the types of resources and inputs that ML students have in school – both related to science and related to language learning – and how these predict science outcomes.
Findings
The findings of this project show that ML students experience a range of science learning outcomes and have varied opportunities afforded to them through schools to support such learning. The results point both to places where schools appear to be successful – such as the timing of reclassification and relatively equal availability of science inputs for ML and non-ML students – as well as opportunities for improvement – such as more time on and resources for science in elementary school.
Key Finding 1: Many MLs make significant science learning gains throughout elementary school.
Students speaking languages other than English at home start elementary school with lower science scores but quickly gain ground, with some surpassing their English-only counterparts by third grade. This trend is especially pronounced for students speaking languages other than Spanish.
Finding #2: MLs and subgroups therein have similar access to science inputs as other students, but their ability to use these resources may be constrained by differences in language supports.
Of the science inputs (i.e. instructional resources, personnel support, and time and content coverage) observed in the ECLS-K:2011, ML students were in classrooms that had similar access to non-MLs. However, for many science inputs, there are opportunities for all students to receive more exposure to science learning opportunities. We also found significant differences in language supports across ML subgroups, suggesting that even if science inputs are available, ML students’ ability to access the science inputs may depend on resources such as translated materials or bilingual educators.
Finding #3 – Reclassification out of EL services did not negatively relate to ML’s science learning.
One of the most significant inputs that ML students receive are formal English learner (EL) services at school. We found that when students are reclassified out of EL services, their science test performance generally was on par with what would have been expected if they remained classified. These results suggest that schools are likely reclassifying ML students at appropriate times with regard to potential impacts on science outcomes.
Finding #4 – Inquiry and hands-on science inputs are predictive of greater science learning.
Finally, our findings demonstrate that certain science inputs are more predictive of higher science test scores than others. In particular, classrooms where MLs were exposed to more hands-on and inquiry-based science learning appeared most supportive of ML and non-ML science outcomes.
Implications and Broader Impact
This study provided some of the first nationally representative evidence on the science learning trajectories of multilingual learners in elementary school and the science and language inputs that are predictive of such learning. The exploratory findings provide a foundation for educational practice and future research that can improve science learning for MLs broadly as well as subgroups therein.
Last Modified: 07/29/2024
Modified by: Frank C Curran
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