EarthX is a design-based research project that supports the integration of Earth science into high school biology, chemistry, and physics courses in Baltimore City Public Schools, while also supporting the district’s transition to three-dimensional (3D), ambitious and equitable science teaching aligned with the Next Generation Science Standards (NGSS). EarthX builds on the success of the Integrating Chemistry and Earth Science (ICE) DRK-12 project, which developed innovative chemistry course curriculum materials and PD strategies, to support Earth science integration into biology and physics course curriculum development and 3D teaching. EarthX will develop, test, and refine embedded and unit assessments for all three courses, along with providing an online system for assessment administration; real-time reporting to teachers and students; and provision of data to PD leaders, administrators, and researchers for multiple purposes. Assessments will be 3D, featuring core concepts from both Earth science and the course discipline combined with a science or engineering practice and a crosscutting concept.
Projects
The project will develop a teacher professional learning (PL) model that focuses on middle-school biological sciences in addressing real world problems. Systems thinking is central to understanding biology systems. Game design has been shown to help develop systems thinking in teachers and students. Students will participate in PL to illustrate the value of distributed expertise by sharing their knowledge of computer. Teachers will adapt their existing curriculum and will co-design games with students to experience participatory practices.
This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.
Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.
This project addresses a major educational barrier, namely that rural students are less likely to choose a major in STEM and have far less access to advanced STEM courses taught by highly qualified teachers. The LogicDataScience (LogicDS) curriculum and virtual delivery are expected to relieve the resource constraints significantly and thus reach rural students. The strategy behind this curriculum development for data science explores the utility of emphasizing how the foundations of data science in computing, mathematics, and statistics are unified by mathematical logic. The project is studying the impacts of the new curriculum on students’ learning of computing, mathematics, and statistics.
Understanding probability is essential for daily life. Probabilistic reasoning is critical in decision making not only for people but also for artificial intelligence (AI). AI sets a modern context to connect probability concepts to real-life situations. It also provides unique opportunities for reciprocal learning that can advance student understanding of both AI systems and probabilistic reasoning. This project aims to improve the current practice of high school probability education and to design AI problem-solving to connect probability and AI concepts. Set in a game-based environment, students learn and practice applying probability theory while exploring the world of probability-based AI algorithms to solve problems that are meaningful and relevant to them.
This project aims to create and study an Equitable and Interactive Mathematical Modeling (EIM2) program that positions students as decision makers in their own learning. Despite the value of connecting students’ life experiences with their mathematical learning, the practical implementation of this strategy has proven challenging in a classroom setting. EIM2 addresses this issue by supporting students to engage in equitable mathematical modeling, a process of using mathematics to analyze and quantify scenarios through a lens of equity.
In this project, we examine middle-school students’ understandings of coordinate systems and frames of reference prior to examining their graph construction and interpretation. This focus allows us to design instructional materials that can support students’ graphing understandings in ways that avoid or mitigate how persistent challenges in students’ graphing understandings identified in the research literature.
In this project, we examine middle-school students’ understandings of coordinate systems and frames of reference prior to examining their graph construction and interpretation. This focus allows us to design instructional materials that can support students’ graphing understandings in ways that avoid or mitigate how persistent challenges in students’ graphing understandings identified in the research literature.
This project will develop and study a curriculum and app that support computational thinking (CT) in a high school biology unit. The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply CT principles.
This project explores how to help teachers identify and support early elementary children’s emergent computational thinking. The project will engage researchers, professional development providers, and early elementary teachers (K-2) in a collaborative research and development process to design a scalable professional development experience for grade K-2 teachers. The project will field test and conduct research on the artifacts, facilitation strategies, and modes of interaction that effectively prepare K-2 teachers to learn about their students’ emergent use of computational thinking strategies.
Widely-adopted science education standards have expanded expectations for students to learn science research processes. To address these needs, the project will research and develop curricular materials and classroom practices that teachers can use to bring authentic science into their classes and engage students as active science researchers. The project, called MothEd, will focus on the study of moths, which are well-suited to the project’s goal of having students conduct authentic scientific investigations.
The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.
The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.
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 partnership of BSCS Science Learning, Oregon Public Broadcasting, and the National Oceanic and Atmospheric Administration advances curriculum materials development for high quality units that are intentionally designed for adaptation by teachers for their local context. The project will create a base unit on carbon cycling as a foundation for understanding how and why the Earth's climate is changing, and it will study the process of localizing the unit for teachers to implement across varied contexts to incorporate local phenomena, problems, and solutions.
This project will develop an integrated, justice-oriented curriculum and a digital platform for teaching secondary students about data science in science and social studies classrooms. The platform will help students learn about data science using real-world data sets and problems. This interdisciplinary project will also help students meaningfully analyze real-world data sets, interpret social phenomena, and engage in social change.
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 will create two curriculum units that use sophisticated simulations designed for students in secondary schools that integrate the study of the tectonic system and the rock genesis system. The project seeks to overcome the more typical approaches taken in earth science classrooms where such geologic processes are treated as discrete and highly predictable, rather than intertwined and dynamic.
This project would investigate a new model of professional development for teams of science teachers in grades K-8 who would create electronic portfolios documenting how they taught specific concepts about energy. In addition, teachers would also select evidence of student understanding of the concepts and add those materials to their portfolios. The study focuses on teaching and learning energy core ideas and science practices that are aligned with the Next Generation Science Standards (NGSS).
The goal of this project is to develop learning progressions and assessment items targeting computational thinking. The items will be used for a test of college-ready critical reasoning skills and will be integrated into an existing online assessment system, the Berkeley Assessment System Software.
The goal of this project is to study how the integration of an online curriculum, scientist mentoring of students, and professional development for both teachers and scientist mentors can improve student outcomes. In this project, teachers and scientist mentors will engage collaboratively in a professional development module which focuses on photosynthesis and cellular respiration and is an example of a student-teacher-scientist partnership. Teachers will use their training to teach the curriculum to their students with students receiving mentoring from the scientists through an online platform. Evaluation will examine whether this curriculum, professional development, and mentoring by scientists will improve student achievement on science content and attitudes toward scientists. The project will use mixed-methods approaches to explore potential factors underlying efficacy differences between in-person and online professional development. An important component of this project is comparing in-person professional development to an online delivery of professional development, which can be more cost-effective and accessible by teachers, especially those in rural and underserved areas.
This project will develop, pilot, and refine a set of coordinated and complementary activities that teacher education programs can use in both online and face-to-face settings to provide practice-based opportunities for preservice teachers to develop their ability to facilitate argumentation-focused discussions in mathematics and science.
This project will develop and research collaborative learning in biology using tablet-style computers that support simulations of biological systems and that can be used individually or linked together. The project will be implemented over 4 years in middle school life science classes, in which students will solve important socio-scientific problems, such as growing healthy plants in community gardens to address the need to grow sufficient produce to fulfill ever increasing and varying demands.
This project will develop and research collaborative learning in biology using tablet-style computers that support simulations of biological systems and that can be used individually or linked together. The project will be implemented over 4 years in middle school life science classes, in which students will solve important socio-scientific problems, such as growing healthy plants in community gardens to address the need to grow sufficient produce to fulfill ever increasing and varying demands.