This project will study a model of pre-service teacher preparation that is designed to to increase teachers' and students' skills and confidence with computational thinking and develop teachers as designers of inclusive learning environments to promote computational thinking. The project will engage elementary (grades K-5) pre-service teachers (who are concurrently involved in school-based teacher preparation programs) as facilitators in an existing family technology program called Family Creative Learning (FCL).
Projects
This is a collaborative project to develop, test, and analyze sets of technology-supported diagnostic classroom assessments for middle school (grades 6-8) physical science. Assessments are aligned with the performance assessment and evidence-centered design methodologies suggested in the Framework for K-12 Science Education (NRC, 2012).
This is a collaborative project to develop, test, and analyze sets of technology-supported diagnostic classroom assessments for middle school (grades 6-8) physical science. Assessments are aligned with the performance assessment and evidence-centered design methodologies suggested in the Framework for K-12 Science Education (NRC, 2012).
This is a collaborative project to develop, test, and analyze sets of technology-supported diagnostic classroom assessments for middle school (grades 6-8) physical science. Assessments are aligned with the performance assessment and evidence-centered design methodologies suggested in the Framework for K-12 Science Education (NRC, 2012).
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
The focus of this project is the design of learning experiences in different high school science courses to help students gain experience in computational thinking. The project uses a partnership between two universities and school district to develop and refine the units as a collaboration between researchers, teachers, and school leaders. The goal is to help all students have opportunities to learn about computational thinking in multiple science courses.
Providing computer science (CS) education to students prior to high school is critical for catalyzing their interest in CS and closing achievement and development gaps. However, the retention rate for underrepresented group participants in middle school CS teacher preparation programs is lower than that for their peers. The resulting lack of diversity in CS teachers contributes to students’ inequitable access to quality middle school CS education. In this project will investigate effective design and implementation strategies of CS teacher preparation programs aimed to increase the number of middle school CS teachers from underrepresented groups.
This project responds to these priorities by developing and testing a place-based environmental science research and monitoring program for elementary school students and their teachers.
This project responds to these priorities by developing and testing a place-based environmental science research and monitoring program for elementary school students and their teachers.
Artificial intelligence (AI) is transforming numerous industries and catalyzing scientific discoveries and engineering innovations. To prepare for an AI-ready workforce, young people must be introduced to core AI concepts and practices early to develop fundamental understandings and productive attitudes. Neural networks, a key approach in AI development, have been introduced to secondary students using various approaches. However, more work is needed to address the interpretability of neural networks and human-machine collaboration in the development process. This exploratory project will develop and test a digital learning tool for secondary students to learn how to interpret neural networks and collaborate with the algorithm to improve AI systems. The learning tool will allow students to interact with complex concepts visually and dynamically. It will also leverage students’ knowledge and intuition of natural languages by contextualizing neural networks in natural language processing systems.
MIST is a five-year study of four large, urban districts implementing ambitious mathematics reform initiatives in the middle grades. The study uses a mixed-methods research design to investigate how changes in the school and district settings in which mathematics teachers work influence their instructional practices, students' learning opportunities, and student achievement.
This project is developing professional resources to help elementary teachers strengthen their students' writing skills, particularly writing in science notebooks. The proposed resources would include print and multi-media formats for teachers and handbooks for their professional development providers.
In this study, researchers will collaborate with Baltimore City Public Schools to collect and document teacher classroom practices prior to the implementation of an extended professional development model that targets pedagogical skills associated with the NGSS. The broad objective of the project is to characterize the benefits and limitations of utilizing controlled practice-teaching as a key component of teacher professional development for integrating NGSS aligned practices in middle school science classrooms.
This EAGER project aims to conduct a study designed to operationalize a culturally responsive computing framework, from theory to empirical application, by exploring what factors can be identified and later used to develop items for an instrument to assess youths' self-efficacy and self-perceptions in computing and technology-related fields and careers.
The goal of this project is to develop a classroom observation tool and an online professional development model to help early-elementary teachers improve science instruction among young learners by cultivating scientific discourse.
This project will support students to develop evidence-based explanations for the impact of disturbances on complex systems. The project will focus on middle school environmental science disciplinary core ideas in life, Earth, and physical sciences and serve as a starting point for supporting students to coordinate different sources of information to parse out the direct and indirect effects of disturbances on components of a system and to examine the interconnections between components to predict whether a system will return to equilibrium (resilience) or the system will change into a new state (hysteresis).
This project will study five elementary STEM schools from across the U.S. that are inclusive of students from underrepresented groups in order to determine what defines these schools and will use an iterative case study replication design to study the design and implementation of five exemplary eSTEM schools with the goal of developing a logic model that highlights the commonalities in core components and target outcomes across the schools, despite the different school contexts.
This project addresses the need to make science relevant for school students and to support student interpretation of large data sets by leveraging citizen science data about ecology and developing instruction to support student analyses of these data. This collaboration between Gulf of Maine Research Institute, Bowdoin College and Vanderbilt University engages middle-school students in building and revising models of variability and change in ecosystems and studies the learning and instruction in these classroom contexts.
This project addresses the need to make science relevant for school students and to support student interpretation of large data sets by leveraging citizen science data about ecology and developing instruction to support student analyses of these data. This collaboration between Gulf of Maine Research Institute, Bowdoin College and Vanderbilt University engages middle-school students in building and revising models of variability and change in ecosystems and studies the learning and instruction in these classroom contexts.
This project addresses the need to make science relevant for school students and to support student interpretation of large data sets by leveraging citizen science data about ecology and developing instruction to support student analyses of these data. This collaboration between Gulf of Maine Research Institute, Bowdoin College and Vanderbilt University engages middle-school students in building and revising models of variability and change in ecosystems and studies the learning and instruction in these classroom contexts.
This project contributes to advancing knowledge on STEM education focusing on societal challenges by harnessing the convergence of STEM subjects, including data science and computer science, to empower a minoritized student group—multilingual middle-school learners.
The project will design and research the Cultural Connections Process Model (CCPM), a place-based, culturally sustaining STEM educational resources and model that will engage Alaska Native and other high school students in STEM. The project approach is strongly informed by Indigenous knowledge systems (i.e., knowledge embedded in the cultural traditions of regional, Indigenous or local communities) and incorporates relevant arctic scientific research.
This project is producing a model for a Professional Learning Community (PLC) for pre-calculus teachers in secondary schools. It generates research knowledge from cycles of (1) defining, (2) studying and (3) refining the model and its components. The project leadership team are then be able to describe the support structure, group processes and tools needed to assist secondary pre-calculus teachers in providing high quality instruction for their students.
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.