Science

Invisible Multilingual Black and Brown Girls: Raciolinguistic Narratives of Identity in Science Education

Black and Brown girls are underrepresented in science, technology, engineering, and math (STEM) fields. Although studies have examined the reasons for this by exploring Black and Brown girls' experiences based on culture, gender, and race, there is a need for specifically understanding how language contributes to racialized experiences in science education. This study fills this critical gap by presenting narratives of three academically talented multilingual girls from Black and Brown communities.

Author/Presenter

Akira Harper

Shakhnoza Kayumova

Year
2022
Short Description

Black and Brown girls are underrepresented in science, technology, engineering, and math (STEM) fields. Although studies have examined the reasons for this by exploring Black and Brown girls' experiences based on culture, gender, and race, there is a need for specifically understanding how language contributes to racialized experiences in science education. This study fills this critical gap by presenting narratives of three academically talented multilingual girls from Black and Brown communities.

Students Do Not Always Mean What We Think They Mean: A Questioning Strategy to Elicit the Reasoning Behind Unexpected Causal Patterns in Student System Models

An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns.

Author/Presenter

Steven Roderick

Namsoo Shin

Daniel Damelin

Lead Organization(s)
Year
2022
Short Description

An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns.

Students Do Not Always Mean What We Think They Mean: A Questioning Strategy to Elicit the Reasoning Behind Unexpected Causal Patterns in Student System Models

An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns.

Author/Presenter

Steven Roderick

Namsoo Shin

Daniel Damelin

Lead Organization(s)
Year
2022
Short Description

An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there is limited evidence of student reasoning about causal relationships that interact in diverging and converging chains, and how these affect system behavior. A chemistry unit on gas phenomena was implemented in two successive years with 73 high school students. Although the phenomena could be explained with simple linear causal reasoning, many student models included surprising and problematic causal chains and non-linear patterns.