Broadening Participation

As part of the STEP UP project, a national initiative to empower high school teachers to inspire young women to pursue physics degrees in college, we developed two lessons for high school physics classes that are intended to facilitate the physics identity development of female students. One discusses physics careers and links to students' own values and goals; the other focuses on a discussion of underrepresentation of women in physics with the intention of having students elicit and examine stereotypes in physics.

As part of the STEP UP project, a national initiative to empower high school teachers to inspire young women to pursue physics degrees in college, we developed two lessons for high school physics classes that are intended to facilitate the physics identity development of female students. One discusses physics careers and links to students' own values and goals; the other focuses on a discussion of underrepresentation of women in physics with the intention of having students elicit and examine stereotypes in physics.

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. Supporting Computational Algorithmic Thinking (SCAT) is a longitudinal project that explores the development of CAT capabilities by guiding African American middle-school girls through the iterative game design cycle, resulting in a set of complex games around broad themes.

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that the solution solves the problem, and evaluating the solution based on some set of criteria.

Much of the research in science education that explores the influence of a racial and gendered identity on science, technology, engineering, and mathematics (STEM) engagement for Black women situate their identities primarily as responses to the oppression and struggles they face in STEM. In this study, we use Phenomenological Variant Ecological Systems Theory as a strengths‐based approach to investigate 10 undergraduate Black women’s perceptions of race and gender on their STEM identity development and engagement.

Computational algorithmic thinking (CAT) is the ability to design, implement, and assess the implementation of algorithms to solve a range of problems. It involves identifying and understanding a problem, articulating an algorithm or set of algorithms in the form of a solution to the problem, implementing that solution in such a way that it solves the problem, and evaluating the solution based on some set of criteria. CAT has roots in Mathematics, through problem solving and algorithmic thinking. CAT lies at the heart of Computer Science, which is defined as the study of algorithms.

The purpose of this study was to develop and validate a survey of opportunities to participate (OtP) in science that will allow educators and researchers to closely approximate the types of learning opportunities students have in science classrooms. Additionally, we examined whether and how opportunity gaps in science learning may exist across schools with different socioeconomic levels. The OtP in science survey consists of four dimensions that include acquiring foundational knowledge, planning an investigation, conducting an investigation, and using evidence to communicate findings.

Making sense of fractions can be challenging for students with learning disabilities. Dr. Jessica Hunt of North Carolina State University studies how these children think and learn and is developing novel teaching methods that facilitate mathematics learning for this underserved population.