This project seeks to foster the science achievement of Latinx preschoolers by confronting current barriers that impact their STEM education through an integrated science-language instructional approach for preschool classrooms. The project will use everyday science experiences to engage Latinx preschoolers in learning the practices of scientists, including the practices of obtaining information and using language to communicate scientific findings.
This project will develop a set of educative resources, assessment tools and teacher professional development (PD) activities to support teachers in developing knowledge of CS standards and improving their instructional pedagogy. Teachers will learn to use formative assessments related to these standards to determine student understanding. Improved CS instruction that is responsive to the needs and challenges of the student population is particularly critical in school districts with a large population of students who are typically underserved and under-represented in computer science. The project, a partnership between SRI International and the Milwaukee Public School District, will provide professional development experiences tied to standards instead of a specific curriculum in order to support diverse teachers teaching a variety of computer science curricula using different programming languages. Teachers will receive training via a combination of virtual webinars and face-to-face instruction. Teachers will have opportunities to evaluate their own teaching and measure their students' progress towards the standards.
This project will provide evidence on how school, classroom, teacher, and student factors shape elementary school science learning trajectories for English learners (ELs). The project will broaden ELs’ participation in STEM learning by investigating how individual, classroom, and school level situations such as instructional practices, learning environments, and characteristics of school personnel relate to EL elementary school science learning.
This project will explore PK-2 teachers' content knowledge by investigating their understanding of the design and implementation of culturally relevant computer science learning activities for young children. The project team will design a replicable model of PK-2 teacher professional development to address the lack of research in early computer science education.
This project will engage middle school students in place-based coastal erosion investigations that interweave Indigenous knowledge and Western STEM perspectives. Indigenous perspectives will emphasize learning from place and community; Western STEM perspectives will focus on systems and computational thinking. The project will position middle school students in a culturally congruent epistemological stance (student-as-anthropologist), allowing them to build Earth science learning from both Indigenous knowledge as well as Western-style inquiry and promote their ability to apply integrated Earth science, mathematics, and computational thinking skills in the context of coastal erosion.
This project will develop, test, and refine a "train-the-trainer" professional development model for rural teacher-leaders. The project goal is to design and develop a professional development model that supports teachers integrating culturally relevant computer science skills and practices into their middle school social studies classrooms, thereby broadening rural students' participation in computer science.
This project is significant because it uses the community for learning science of the environment, in an approach called Citizen Science or Participatory Science Research (PSR). The project will target learning outcomes for underrepresented middle and high school students in the urban and diverse East San Francisco Bay Area, and will refine a theory of learning that makes more explicit the connections between science practices, identity, and value and relevance.
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.
This project will study the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs). The assessments target three-dimensional (3D) science learning by requiring students to integrate scientific practices, crosscutting concepts, and disciplinary core ideas to make sense of phenomena or solve complex problems.
This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. The project will conduct a comprehensive research program to develop and test technology that will empower students to use their ideas as a starting point for deepening science understanding. Researchers will use a technology that detects student ideas that go beyond a student's general knowledge level to adapt to a student's cultural and linguistic understandings of a science topic.
This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. The project will conduct a comprehensive research program to develop and test technology that will empower students to use their ideas as a starting point for deepening science understanding. Researchers will use a technology that detects student ideas that go beyond a student's general knowledge level to adapt to a student's cultural and linguistic understandings of a science topic.
