Literacy/Language Skills

Building Insights through Observation: Researching Arts-based Methods for Teaching and Learning with Data

This project will use visualizations from an easily accessible tool from NOAA, Science On a Sphere, to help students develop critical thinking skills and practices required to effectively make meaning from authentic scientific data. The project will use arts-based pedagogies for observing, analyzing, and critiquing visual features of data visualizations to build an understanding of what the data reveal. The project will work with middle school science teachers to develop tools for STEM educators to use these data visualizations effectively.

Lead Organization(s): 
Award Number: 
2101310
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Innovations in data collection, infrastructure, and visualization play an important role in modern society. Large, complex datasets are accessible to and shared widely with the public. However, students need to learn how to interpret and reason about visualizations of scientific data. This project will use visualizations from an easily accessible tool from NOAA, Science On a Sphere, to help students develop critical thinking skills and practices required to effectively make meaning from authentic scientific data. The project will use arts-based pedagogies for observing, analyzing, and critiquing visual features of data visualizations to build an understanding of what the data reveal. The project will work with middle school science teachers to develop tools for STEM educators to use these data visualizations effectively. This project focuses on visual thinking skills that have been found to apply in both science and art: describing, wondering, recognizing uncertainty, and interpreting with evidence.

The project will conduct foundational research to understand the ways in which arts-based instructional methods and geospatial data visualization can be successfully applied by science teachers. The research will examine: (1) the ways in which arts-based instructional methods can be successfully applied by STEM teachers; (2) critical elements in the process of learning and applying these techniques to influence teachers’ content, pedagogical, and technological knowledge; and (3) for which transferable data literacy skills these approaches show most promise with children. This project will use a design-based research framework to develop data literacy teaching approaches in partnership with middle school teachers. The research process will include data about teachers’ development and students’ learning about data literacy. Data to be collected include qualitative and quantitative information from teachers and students.

Using Natural Language Processing to Inform Science Instruction (Collaborative Research: Linn)

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.

Partner Organization(s): 
Award Number: 
2101669
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Often, middle school science classes do not benefit from participation of underrepresented students because of language and cultural barriers. This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. This work continues a partnership among the University of California, Berkeley, Educational Testing Service, and science teachers and paraprofessionals from six middle schools enrolling students from diverse racial, ethnic, and language groups whose cultural experiences may be neglected in science instruction. The partnership 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. The partnership leverages a web-based platform to implement adaptive guidance designed by teachers that feature dialog and peer interaction. Further, the platform features teacher tools that can detect when a student needs additional help and alert the teacher. Teachers using the technology will be able to track and respond to individual student ideas, especially from students who would not often participate because of language and cultural barriers.

This project develops AI-based technology to help science teachers increase their impact on student science learning. The technology is aimed to provide accurate analysis of students' initial ideas and adaptive guidance that gets each student started on reconsidering their ideas and pursuing deeper understanding. Current methods in automated scoring primarily focus on detecting incorrect responses on test questions and estimating the overall knowledge level in a student explanation. This project leverages advances in natural language processing (NLP) to identify the specific ideas in student explanations for open-ended science questions. The investigators will conduct a comprehensive research program that pairs new NLP-based AI methods for analyzing student ideas with adaptive guidance that, in combination, will empower students to use their ideas as starting points for improving science understanding. To evaluate the idea detection process, the researchers will conduct studies that investigate the accuracy and impact of idea detection in classrooms. To evaluate the guidance, the researchers will conduct comparison studies that randomly assign students to conditions to identify the most promising adaptive guidance designs for detected ideas. All materials are customizable using open platform authoring tools.

Using Natural Language Processing to Inform Science Instruction (Collaborative Research: Riordan)

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.

Lead Organization(s): 
Award Number: 
2101670
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Often, middle school science classes do not benefit from participation of underrepresented students because of language and cultural barriers. This project takes advantage of language to help students form their own ideas and pursue deeper understanding in the science classroom. This work continues a partnership among the University of California, Berkeley, Educational Testing Service, and science teachers and paraprofessionals from six middle schools enrolling students from diverse racial, ethnic, and language groups whose cultural experiences may be neglected in science instruction. The partnership 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. The partnership leverages a web-based platform to implement adaptive guidance designed by teachers that feature dialog and peer interaction. Further, the platform features teacher tools that can detect when a student needs additional help and alert the teacher. Teachers using the technology will be able to track and respond to individual student ideas, especially from students who would not often participate because of language and cultural barriers.

This project develops AI-based technology to help science teachers increase their impact on student science learning. The technology is aimed to provide accurate analysis of students' initial ideas and adaptive guidance that gets each student started on reconsidering their ideas and pursuing deeper understanding. Current methods in automated scoring primarily focus on detecting incorrect responses on test questions and estimating the overall knowledge level in a student explanation. This project leverages advances in natural language processing (NLP) to identify the specific ideas in student explanations for open-ended science questions. The investigators will conduct a comprehensive research program that pairs new NLP-based AI methods for analyzing student ideas with adaptive guidance that, in combination, will empower students to use their ideas as starting points for improving science understanding. To evaluate the idea detection process, the researchers will conduct studies that investigate the accuracy and impact of idea detection in classrooms. To evaluate the guidance, the researchers will conduct comparison studies that randomly assign students to conditions to identify the most promising adaptive guidance designs for detected ideas. All materials are customizable using open platform authoring tools.

Anchoring High School Students in Real-Life Issues that Integrate STEM Content and Literacy

Through the integration of STEM content and literacy, this project will study the ways teachers implement project practices integrating literacy activities into STEM learning. Teachers will facilitate instruction using scenarios that present students with everyday, STEM-related issues, presented as scenarios, that they read and write about. After reading and engaging with math and science content, students will write a source-based argument in which they state a claim, support the claim with evidence from the texts, and explain the multiple perspectives on the issue.

Lead Organization(s): 
Award Number: 
2010312
Funding Period: 
Sat, 08/15/2020 to Sun, 07/31/2022
Full Description: 

The STEM Literacy Project sets out to support student learning through developing teacher expertise in collaborative integration of STEM in student writing and literacy skills development. Facilitated by teachers, students will read, discuss, and then write about real-world STEM scenarios, such as water quality or health. The project will build on and research a professional development program first developed through a state-supported literacy program for middle and high school science and math teachers to improve literacy-integrated instruction. The goals of this project include the following: (1) Create a community of practice that recognizes high school teachers as content experts; (2) Implement high quality professional development for teachers on STEM/Literacy integration; (3) Develop assessments based on STEM and literacy standards that inform instruction; and (4) Conduct rigorous research to understand the impact of the professional development. The program is aligned with state and national standards for college and career readiness. Project resources will be widely shared through a regularly updated project website (stemliteracyproject.org), conference presentations, and publications reaching researchers, developers, and educators. These resources will include scenario-based assessment tools and instructional materials.

Through the integration of STEM content and literacy, the project will study the ways teachers implement project practices integrating literacy activities into STEM learning. Teachers will facilitate instruction using scenarios that present students with everyday, STEM-related issues, presented as scenarios, that they read and write about. After reading and engaging with math and science content, students will write a source-based argument in which they state a claim, support the claim with evidence from the texts, and explain the multiple perspectives on the issue. These scenarios provide students with agency as they craft an argument for an audience, such as presenting to a city council, a school board, or another group of stakeholders. Project research will use a mixed methods design. Based on the work completed through the initial designs and development of scenario-based assessments, rubrics, and scoring processes, the project will study the impact on instruction and student learning. Using a triangulation design convergence model, findings will be compared and contrasted in order for the data to inform one another and lead to further interpretation of the data. project will analyze the features of STEM content learning after program-related instruction. Data collected will include pre-post student scenario-based writing; pre-post interviews of up to 40 students each year; pre-post teacher interviews; and teacher-created scenario-based assessments and supporting instructional materials. Student learning reflected in the assessments paired with student and teacher interview responses will provide a deeper understanding of this approach of integrating STEM and literacy. The use of discourse analysis methods will allow growth in content learning to be measured through language use. Project research will build knowledge in the field concerning how participation in teacher professional development integrating STEM content in literacy practices impacts teacher practices and student learning.

Incorporating Professional Science Writing into High School STEM Research Projects

The goal of this project is to expand high school student participation in the peer-review process and in publishing in JEI, a science journal dedicated to mentoring pre-college students through peer-reviewed publication. By publishing pre-college research in an open access website, the project will build understanding of how engaging in these activities can change high school students' perceptions and practices of scientific inquiry.

Lead Organization(s): 
Award Number: 
2010333
Funding Period: 
Wed, 07/15/2020 to Fri, 06/30/2023
Project Evaluator: 
Maya Patel
Full Description: 

This exploratory project addresses important challenge of incorporating disciplinary literacy practices in scientific inquiry projects of high school students. The project will incorporate the peer-review process and publication in the Journal of Emerging Investigators (JEI). The Next Generation Science Standards emphasize constructs from disciplinary literacy such as engaging in argument from evidence, and evaluating and communicating information. However, there are few resources available to students and teachers that integrate these constructs in authentic forms that reflect the practices of professional scientists. High school student learners engage in scientific inquiry, but rarely participate in authentic forms of communication, forms that are reflective of how scientists communicate and participate in the primary literature of their fields. The project has three aims: 1) Generate knowledge of the impact of peer-review and publication on perceptions and skills of scientific inquiry and STEM identity, 2) Generate knowledge of how participation in peer-review and publication are impacted by contextual factors (differences in mentors and research contexts), and 3) Develop JEI field-guides across a range of contexts in which students conduct their research.

The goal of the project is to expand high school student participation in the peer-review process and in publishing in JEI, a science journal dedicated to mentoring pre-college students through peer-reviewed publication. By publishing pre-college research in an open access website, the project will build understanding of how engaging in these activities can change high school students' perceptions and practices of scientific inquiry. The project will investigate how participation in peer-reviewed publications will have an impact on student learning by administering a set of pre- and post-surveys to students who submit a paper to JEI. The project will expand student participation in JEI via outreach to teachers in under-resourced and remote areas by delivering virtual and in-person workshops which will serve to demystify peer review and publication, and explore ways to integrate these processes into existing inquiry projects. Other efforts will focus on understanding how student contextual experiences can impact their learning of scientific inquiry. These student experiences include the location of the project (school, home, university lab), the type of mentor they have, and how they became motivated to pursue publication of their research. The project will recruit students from under-resourced schools in New York through a collaboration with MathForAmerica and from rural areas through outreach with STEM coordinators in the Midwest. The resources created will be disseminated directly on the JEI website.

Supporting Students' Language, Knowledge, and Culture through Science

This project will test and refine a teaching model that brings together current research about the role of language in science learning, the role of cultural connections in students' science engagement, and how students' science knowledge builds over time. The outcome of this project will be to provide an integrated framework that can guide current and future science teachers in preparing all students with the conceptual and linguistic practices they will need to succeed in school and in the workplace.

Lead Organization(s): 
Award Number: 
2010633
Funding Period: 
Tue, 09/01/2020 to Sat, 08/31/2024
Full Description: 

The Language, Culture, and Knowledge-building through Science project seeks to explore and positively influence the work of science teachers at the intersection of three significant and ongoing challenges affecting U.S. STEM education. First, U.S. student demographics are rapidly changing, with an increasing number of students learning STEM subjects in their second language. This change means that all teachers need new skills for meeting students where they currently are, linguistically, culturally, and in terms of prior science knowledge. Second, the needs and opportunities of the national STEM workforce are changing rapidly within a shifting employment landscape. This shift means that teachers need to better understand future job opportunities and the knowledge and skills that will be necessary in those careers. Third, academic expectations in schools have changed, driven by changes in education standards. These new expectations mean that teachers need new skills to support all students to master a range of practices that are both conceptual and linguistic. To address these challenges, teachers require new models that bring together current research about the role of language in science learning, the role of cultural connections in students' science engagement, and how students' science knowledge builds over time. This project begins with such an initial model, developed collaboratively with science teachers in a prior project. The model will be rigorously tested and refined in a new geographic and demographic context. The outcome will be to provide an integrated framework that can guide current and future science teachers in preparing all students with the conceptual and linguistic practices they will need to succeed in school and in the workplace.

This project model starts with three theoretical constructs that have been integrated into an innovative framework of nine practices. These practices guide teachers in how to simultaneously support students' language development, cultural sustenance, and knowledge building through science with a focus on supporting and challenging multilingual learners. The project uses a functional view of language development, which highlights the need to support students in understanding both how and why to make shifts in language use. For example, students' attention will be drawn to differences in language use when they shift from language that is suited to peer negotiation in a lab group to written explanations suitable for a lab report. Moving beyond a funds of knowledge approach to culture, the team view of integrating students' cultural knowledge includes strengthening the role of home knowledge in school, but also guiding students to apply school knowledge to their out-of-school interests and passions. Finally, the project team's view of cumulative knowledge building, informed by work in the sociology of knowledge, highlights the need for teachers and students to understand the norms for meaning making within a given discipline. In the case of science, the three-dimensional learning model in the Next Generation Science Standards makes these disciplinary norms visible and serves as a launching point for the project's work. Teachers will be supported to structure learning opportunities that highlight what is unique about meaning making through science. Using a range of data collection and analysis methods, the project team will study changes in teachers' practices and beliefs related to language, culture and knowledge building, as teachers work with all students, and particularly with multilingual learners. The project work will take place in both classrooms and out of class science learning settings. By working closely over several years with a group of fifty science teachers spread across the state of Oregon, the project team will develop a typology of teachers (design personas) to increase the field's understanding of how to support different teachers, given their own backgrounds, in preparing all students for the broad range of academic and occupational pathways they will encounter.

How Deep Structural Modeling Supports Learning with Big Ideas in Biology (Collaborative Research: Capps)

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2010223
Funding Period: 
Sat, 08/01/2020 to Wed, 07/31/2024
Full Description: 

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. This need is forcefully advanced by policy leaders including the National Research Council and the College Board. They point out that learning is more effective when students organize and link information within a consistent knowledge framework, which is what big ideas should provide. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology. In DSM, students learn a big idea as the underlying, or "deep" structure of a set of examples that contain the structure, but with varying outward details. As learners begin to apprehend the deep structure (i.e., the big idea) within the examples, they use the tools and procedures of scientific modeling to express and develop it. According to theories of learning that undergird DSM, the result of this process should be a big idea that is flexible, meaningful, and easy to express, thus providing an ideal framework for making sense of new information learners encounter (i.e., learning with the big idea). To the extent that this explanation is born out in rigorous research tests and within authentic curriculum materials, it contributes important knowledge about how teaching and learning can be organized around big ideas, and not only for deep structural modeling but for other instructional approaches as well.

This project has twin research and prototype development components. Both are taking place in the context of high school biology, in nine classrooms across three districts, supporting up to 610 students. The work focuses on three design features of DSM: (1) embedding model source materials with intuitive, mechanistic ideas; (2) supporting learners to abstract those ideas as a deep structure shared by a set of sources; and (3) representing this deep structure efficiently within the model. In combination, these features support students to understand an abstract, intuitively rich, and efficient knowledge structure that they subsequently use as a framework to interpret, organize, and link disciplinary content. A series of five research studies build on one another to develop knowledge about whether and how the design features bring about these anticipated effects. Earlier studies in the sequence are small-scale classroom experiments randomly assigning students to either deep structural modeling or to parallel, non modeling controls. Measures discriminate for the anticipated effects during learning and on posttests. Later studies use qualitative methods to carefully trace the anticipated effects over time and across topics. As a group, these studies are contributing generalized knowledge of how learners can effectively abstract and represent big ideas and how these ideas can be leveraged as frameworks for learning content with understanding. Two research-tested biology curriculum prototypes are being developed as the studies evolve: a quarter-year DSM biology curriculum centered on energy; and an eighth-year DSM unit centered on natural selection.

How Deep Structural Modeling Supports Learning with Big Ideas in Biology (Collaborative Research: Shemwell)

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2010334
Funding Period: 
Sat, 08/01/2020 to Wed, 07/31/2024
Full Description: 

This project addresses the pressing need to more effectively organize STEM (science, technology, engineering, and mathematics) teaching and learning around "big ideas" that run through science disciplines. This need is forcefully advanced by policy leaders including the National Research Council and the College Board. They point out that learning is more effective when students organize and link information within a consistent knowledge framework, which is what big ideas should provide. Unfortunately, finding ways to teach big ideas effectively so they become useful as knowledge frameworks is a significant challenge. Deep structure modeling (DSM), the innovation advanced in this project, is designed to meet this challenge in the context of high school biology. In DSM, students learn a big idea as the underlying, or "deep" structure of a set of examples that contain the structure, but with varying outward details. As learners begin to apprehend the deep structure (i.e., the big idea) within the examples, they use the tools and procedures of scientific modeling to express and develop it. According to theories of learning that undergird DSM, the result of this process should be a big idea that is flexible, meaningful, and easy to express, thus providing an ideal framework for making sense of new information learners encounter (i.e., learning with the big idea). To the extent that this explanation is born out in rigorous research tests and within authentic curriculum materials, it contributes important knowledge about how teaching and learning can be organized around big ideas, and not only for deep structural modeling but for other instructional approaches as well.

This project has twin research and prototype development components. Both are taking place in the context of high school biology, in nine classrooms across three districts, supporting up to 610 students. The work focuses on three design features of DSM: (1) embedding model source materials with intuitive, mechanistic ideas; (2) supporting learners to abstract those ideas as a deep structure shared by a set of sources; and (3) representing this deep structure efficiently within the model. In combination, these features support students to understand an abstract, intuitively rich, and efficient knowledge structure that they subsequently use as a framework to interpret, organize, and link disciplinary content. A series of five research studies build on one another to develop knowledge about whether and how the design features bring about these anticipated effects. Earlier studies in the sequence are small-scale classroom experiments randomly assigning students to either deep structural modeling or to parallel, non modeling controls. Measures discriminate for the anticipated effects during learning and on posttests. Later studies use qualitative methods to carefully trace the anticipated effects over time and across topics. As a group, these studies are contributing generalized knowledge of how learners can effectively abstract and represent big ideas and how these ideas can be leveraged as frameworks for learning content with understanding. Two research-tested biology curriculum prototypes are being developed as the studies evolve: a quarter-year DSM biology curriculum centered on energy; and an eighth-year DSM unit centered on natural selection.

Responsive Instruction for Emergent Bilingual Learners in Biology Classrooms

This project seeks to support emergent bilingual students in high school biology classrooms. The project team will study how teachers make sense of and use an instructional model that builds on students' cultural and linguistic strengths to teach biology in ways that are responsive. The team will also study how such a model impacts emergent bilingual students' learning of biology and scientific language practices, as well as how it supports students' identities as knowers/doers of science.

Lead Organization(s): 
Award Number: 
2010153
Funding Period: 
Wed, 07/01/2020 to Fri, 06/30/2023
Full Description: 

The population of students who are emergent bilinguals in the US is not only growing in number but also, historically, has been underrepresented in STEM fields. Emergent bilingual students have not had access to the same high-quality science education as their peers, despite bringing rich academic, linguistic and cultural strengths to their learning. Building on smaller pilot studies and ideas that have shown to be successful in supporting emergent bilingual students' learning of elementary science, this project seeks to support emergent bilingual students in high school biology classrooms. The project team will study how teachers make sense of and use an instructional model that builds on students' cultural and linguistic strengths to teach biology in ways that are responsive. The team will also study how such a model impacts emergent bilingual students' learning of biology and scientific language practices, as well as how it supports students' identities as knowers/doers of science. The collaboration will include two partner districts that will allow the project work to impact about 11,000 high school students and 30 biology teachers in Florida. Over time, the project team plans to enact and study three cohorts of teachers and students; use the information learned to improve the instructional model; and develop lessons, a website, and other materials that can be applied to other contexts to support emergent bilingual students' learning of biology. This project will increase emergent bilingual students' participation in biology classes, improve their achievement and engagement in science and engineering practices, extend current research-based practices, and document how to build on emergent bilingual students' strengths and prior experiences.

In two previous pilot studies through the collaboration of an interdisciplinary team, the project team developed an instructional model that they found supported emergent bilingual students to have high-quality opportunities for science learning. The model builds on research related to culturally responsive instruction; funds of knowledge (including work on identity affirmation and collaboration); and linguistically responsive instruction (including using students' home languages and multiple modalities, and explicit attention to academic language). Using design-based research, the project team will gather data from two primary settings: their professional development program and biology teachers' classrooms. They will use these data both to improve the instructional model and professional development for biology teachers. Additionally, the project team will study how teachers use the model to support emergent bilingual students' biology engagement and achievement, as well as study how biology teachers enact the instructional model in two school districts. The project will work toward three main outcomes: a) to develop new knowledge related to how diverse learners develop language and content knowledge in biology through engaging in science and engineering practices; b) to generate new knowledge about how biology teachers can adapt responsive instruction to local contexts and student populations; and c) to articulate an instructional model for biology teachers of emergent bilingual students that is rigorous, yet practical. The dissemination and sustainability include publishing and presenting findings at a range of conferences and journals; making available the refined instructional framework and professional development materials on a website; communication with district leaders and policymakers; and white papers that can be more widely distributed.


 Project Videos

2021 STEM for All Video Showcase

Title: RIEL Biology for Emergent Bilingual Learners

Presenter(s): Julie Brown, Mark B. Pacheco, E. Christine Davis, & Karl G Jung


Responding to an Emerging Epidemic through Science Education

This research project will produce curricular materials designed to help students learn about viral epidemics as both a scientific and social issue. It will engage students in scientific modeling of the epidemic and in critical analyses of media and public health information about the virus. This approach helps students connect their classroom learning experiences with their lives beyond school, a key characteristic of science literacy.

Partner Organization(s): 
Award Number: 
2023088
Funding Period: 
Sun, 03/01/2020 to Sun, 02/28/2021
Full Description: 

At this moment, there is global concern about the coronavirus disease 2019 (COVID-19) and its potential to become an epidemic in the U.S. and other countries. Reports of past studies on student understanding of epidemics and how they are taught in school indicate that teachers are reticent to teach the material because the science is unclear given the emerging nature of evidence, or because they don?t understand it well themselves. Curricular resources are limited. Consequently, many students are left on their own to grapple with a potential public health emergency that could affect them and their families. The problem is further complicated by misinformation that may be spread through social media. There is less public understanding about the science of the virus and how it spreads; the risk of being infected; treatment, or, the severity of the illness. This research project will produce curricular materials designed to help students learn about viral epidemics as both a scientific and social issue. It will engage students in scientific modeling of the epidemic and in critical analyses of media and public health information about the virus. This approach helps students connect their classroom learning experiences with their lives beyond school, a key characteristic of science literacy. This project is an example of how science education can be both engaging and relevant.

Researchers at the University of North Carolina and the University of Missouri have been studying how to teach about issues at the crossroads of science and social concerns such as community health; they have developed a framework to build curriculum materials focused on student learning of such complex issues through modeling and inquiry. For this study on the coronavirus disease 2019 (COVID-19); first, the researchers will study student responses to the epidemic in real time, collecting data on student initial understandings and concerns. Then, using this information, they will work with 7 high school science teachers familiar with their framework to build a prototype curriculum unit, and test it in classrooms in 4 high schools selected for their socio-economic and ethnic/racial diversity. The study will gather data on student interest in the epidemic, as well as how students access information about it through various forms of media, and how they vet news reports and social media. The researchers will also use pre- and post-test data to assess student learning. After this initial enactment of the curriculum materials developed to teach about the epidemic, researchers and teachers will revise the curriculum materials to make them more effective. The final products will be a curriculum unit that will be readily available and modifiable for teaching and learning about future epidemics, as well as greater understanding about how students deal with vast amounts of information about societal issues that affect their immediate lives and the science behind them.


 Project Videos

2021 STEM for All Video Showcase

Title: Responding to an Emerging Epidemic through Science Education

Presenter(s): Troy Sadler, Pat Friedrichsen, Li Ke, & Laura Zangori


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