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Research Worth Reading

Computer Modeling, Computational Thinking, and Community-Driven Science Practices

By The NSTA Research Committee

Posted on 2024-10-08

Computer Modeling, Computational Thinking, and Community-Driven Science Practices

“Research” can refer to a wide range of activities: It can describe when students in science classes may investigate a topic, gather evidence, and analyze data to develop their own ideas and present them to others. Or it might refer to investigations conducted by scientists. The NSTA Research Division focuses on another kind of research: the systematic study of how people learn science, including investigations into teaching methods, curriculum design, student understanding of scientific concepts, and factors that influence science learning, with the goal of improving science education practices and student outcomes across various levels of learning. The NSTA Research Committee is here to help keep you updated on the latest research in science education. Watch for our quarterly blog posts, or subscribe to NSTA’s Research listserv.

The following studies, published in the Journal of Research in Science Teachinghave been recognized as Research Worth Reading by NSTA Affiliate NARST (the National Association for Research in Science Teaching), a global organization dedicated to improving science teaching and learning through research. In addition to the summaries given below, the entire articles are available through Open Access via the links provided and include the corresponding author’s e-mail contact. 

Computer Modeling Helps Multilingual Learners Participate Meaningfully in Science

It’s commonly assumed that students learning English as an additional language—sometimes called multilingual learners—require a “basics first” approach. After all, these students are faced with the daunting task of learning school subjects, such as science, at the same time they are developing English proficiency. But this assumption is rooted in a deficit view of multilingual learners as lacking the relevant knowledge and language to engage in authentic science, including cutting-edge technologies used in STEM disciplines. A 2023 study suggests that this assumption may unfairly limit what multilingual learners can do in the science classroom.

Researchers from the University of Miami, New York University, Massachusetts Institute of Technology, and The Ohio State University designed a yearlong curriculum that integrates computer modeling into elementary science instruction. In each unit in the curriculum, students engage with a visual programming environment to explain a science phenomenon, such as why an organism mysteriously disappeared from an ecosystem. When the technology-integrated curriculum was implemented in linguistically diverse fifth-grade classrooms, the researchers found that computer modeling enabled multilingual learners to participate meaningfully in science practices and communicate their science ideas. For example, multilingual learners leveraged resources in the programming environment, including code blocks and dynamic visualization, to construct explanations of science phenomena.

Based on their findings, the researchers suggest that “rather than viewing educational innovations as yet another challenge for [multilingual learners] to overcome,” teachers can consider the benefits of “innovations for harnessing [multilingual learners’] expansive sensemaking and meaning-making potential.” So the next time you wonder whether multilingual learners will be able to handle a new curriculum or technology, think twice. Perhaps the more apt question is this: How can innovation harness the assets that multilingual learners bring?

Task Analysis Tool Helps Teachers Make Lessons More Student-Centered and Integrate Computational Thinking

Analyzing lessons to find ideal points for integrating new ideas, such as science and engineering practices, can be a vague process for classroom teachers. However, research on the use of the Task Analysis Tool (TAT) has shown promise in helping teachers locate precise points where computational thinking can support student thinking about data. As a bonus, the TAT also helped teachers determine if their lesson was more teacher-centered or student-centered.

This 2023 study by researchers at George Mason University, Rutgers University, and Brigham Young University examined lesson plans and interviewed nine biology teachers in a professional learning experience focused on integrating computational thinking into science data practices. The teachers in the study were able to successfully analyze their lessons and find points of integration to support their students’ learning about data practices in science by implementing the TAT.

The teachers credited the TAT for their success. Teacher use of the TAT led to three lesson improvements. Teachers (1) noticed that in the original plan, they were taking responsibility for doing the data practices rather than having the students do them, and then altered their lesson to be more student-centered; (2) filled in gaps where they might have missed data practices that were needed; and (3) more clearly integrated computational thinking into each data practice. 

Teaching Health Justice and Reimagining Narrative of Place Through Community-Driven Science Practices

Racial, environmental, and science educational injustices are highly intertwined with direct implications for the health and well-being of communities of color. Furthermore, racial disparities in access to high-quality science learning experiences in K–12 schooling result in the persistent underrepresentation of Black, Latinx, Indigenous, and other students of color in college science majors and professions. Some important questions for science teachers and practitioners are these: How can we address systemic disparities in our classrooms and support youth of color as learners, doers, and change agents in science? How would discussions of race, place, and power take shape in science class?

This 2023 study examined how a biology teacher engaged high school students of color in a three-week science unit exploring community health. The researcher, a former high school science teacher, explored how the teacher’s positioning as a Black woman scientist shaped her goals and vision and the instructional and pedagogical resources she made available during the unit. The findings demonstrate how engaging community health at the intersection of history, race, place, and power shaped meaningful engagement in science practices, expanding how they are typically addressed through the Next Generation Science Standards. The teacher’s approach supported student sensemaking in ways that surfaced challenges, tensions, and opportunities to disrupt and reimagine community narratives—using science to better their communities. 

The study provides the following insights for engaging history, race, place, and power as it relates to science and your school community.

  • Foster safe, inclusive classroom learning communities that challenge dominant forms of individuality in society and illustrate that communities thrive through collective care and action;
  • Foster critical data analysis when using resources such as graphs, tables, and other data representations of community-relevant statistics and outcomes and cultivate sensemaking based on dimensions including race, gender, and socioeconomic status;
  • Engage students authentically in science practices by viewing youths’ lived experiences and analytical observations as central to the “doing” of science; and

Promote asset-based approaches to science learning by eliciting students’ cultural practices and traditions as relevant community resources.

Note: This blog post is part of the new blog series Research Worth Reading, which features the latest highlights of recent research in science education with practical applications for your classroom.


The mission of NSTA is to transform science education to benefit all through professional learning, partnerships, and advocacy.

Research

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