A substantial achievement gap between K-12 English learners (ELs) and non-ELs in
science, technology, engineering, and mathematics (STEM) content areas exists, as indicated by national assessments of student outcomes. Considering the expected steady increase in students who are ELs in the U.S., determining methods for addressing this achievement gap is of immediate concern. Research has indicated this gap may be exacerbated by lack of adequate teacher preparation, specifically in STEM fields, to effectively teach students who are culturally and linguistically diverse (CLD). Founded in previous research about effective teacher preparation, the current case study pilots and reports on a model of early STEM preservice teacher training that integrates: knowledge of language development for ELs, early experiences with CLD learners, and professional development activities that guide the implementation of STEM pedagogical methods. Five STEM preservice teachers participated in a year-long supplemental training program focused on adapting STEM instruction for ELs. Components of the supplemental program included: (a) coursework extending teacher knowledge of EL language development, (b) fieldwork providing early exposure to research-based teaching experiences with EL students, and (c) professional development guiding the creation of hands-on
STEM curriculum for diverse learners. Five secondary preservice teachers experienced increases in self-efficacy, growth in STEM instructional practices, and greater motivation for teaching in high-need schools. Results will inform educational models for improving STEM-EL teaching, thereby addressing a crucial need to serve the growing national population of underserved students.
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How Fifth-Grade English Learners Engage in Systems Thinking Using Computational Models
The purpose of this study was to investigate how computational modeling promotes systems thinking for English Learners (ELs) in fifth-grade science instruction. Individual student interviews were conducted with nine ELs about computational models of landfill bottle systems they had developed as part of a physical science unit. We found evidence of student engagement in four systems thinking practices. Students used data produced by their models to investigate the landfill bottle system as a whole (Practice 1). Students identified agents and their relationships in the system (Practice 2). Students thought in levels, shuttling between the agent and aggregate levels (Practice 3). However, while students could think in levels to develop their models, they struggled to engage in this practice when presented with novel scenarios (e.g., open vs. closed system). Finally, students communicated information about the system using multiple modalities and less-than-perfect English (Practice 4). Overall, these findings suggest that integrating computational modeling into standards-aligned science instruction can provide a rich context for fostering systems thinking among linguistically diverse elementary students.
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- Award ID(s):
- 1742138
- NSF-PAR ID:
- 10376991
- Date Published:
- Journal Name:
- Systems
- Volume:
- 8
- Issue:
- 4
- ISSN:
- 2079-8954
- Page Range / eLocation ID:
- 47
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Understanding the world around us is a growing necessity for the whole public, as citizens are required to make informed decisions in their everyday lives about complex issues. Systems thinking (ST) is a promising approach for developing solutions to various problems that society faces and has been acknowledged as a crosscutting concept that should be integrated across educational science disciplines. However, studies show that engaging students in ST is challenging, especially concerning aspects like change over time and feedback. Using computational system models and a system dynamics approach can support students in overcoming these challenges when making sense of complex phenomena. In this paper, we describe an empirical study that examines how 10th grade students engage in aspects of ST through computational system modeling as part of a Next Generation Science Standards-aligned project-based learning unit on chemical kinetics. We show students’ increased capacity to explain the underlying mechanism of the phenomenon in terms of change over time that goes beyond linear causal relationships. However, student models and their accompanying explanations were limited in scope as students did not address feedback mechanisms as part of their modeling and explanations. In addition, we describe specific challenges students encountered when evaluating and revising models. In particular, we show epistemological barriers to fruitful use of real-world data for model revision. Our findings provide insights into the opportunities of a system dynamics approach and the challenges that remain in supporting students to make sense of complex phenomena and nonlinear mechanisms.
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/systems8040047
