Student Outcomes

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.

Reducing Racially Biased Beliefs by Fostering a Complex Understanding of Human Genetics Research in High School Biology Students (Collaborative Research: Donovan)

The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs. The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.

Lead Organization(s): 
Award Number: 
2100864
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Genetic essentialism is the belief that people of the same race share genes that make them physically, cognitively, and behaviorally uniform, and thus different from other races. The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs and minimize the threat of backfiring (unintentionally increasing belief in essentialism). The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.  Project research findings, learning materials, and professional development institutes will be made available to educators and researchers across the country who desire to teach genetics to reduce racial prejudice.

To prepare for the research, the project will revise and augment the project’s existing HGL curriculum and professional development institutes.  In year one, the project will develop new versions of the HGL interventions. Using these materials, the project will train teachers to implement new versions of the HGL interventions in their classrooms. Researchers will video and audio record a sample of teachers and students as they learn. These data will be analyzed qualitatively to: (1) examine how the conceptual change of genetic essentialism was promoted or impeded by interactions between teachers, students, and the materials; and (2) identify and corroborate general factors undergirding the backfiring effect.  Knowledge constructed through these studies will be used to revise the HGL interventions and PDIs.  In year three, using the revised versions of the HGL intervention, the project will conduct a cluster randomized trial (CRT). The CRT will compare the HGL interventions to a well-defined “business as usual” genetics curriculum, using a statistically powerful and geographically diverse sample (N = 135 teachers, N = 16,200 students, from 33 states). Using data from the CRT, the project will identify classrooms where the interventions reduced essentialism, had no effect on it, and where it backfired. Then, the project will use stimulated recall methods to interview the teachers and students in those classrooms to make sense of factors that contributed to these outcomes. The project will use this information to develop the final version of the HGL interventions and PDI materials. By the end of year four, the project will have trained an additional 90-100 teachers to use HGL interventions, reaching an additional 10,800-12,000 students, in at least 33 different states.

Reducing Racially Biased Beliefs by Fostering a Complex Understanding of Human Genetics Research in High School Biology Students (Collaborative Research: Duncan)

The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs. The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2100876
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Genetic essentialism is the belief that people of the same race share genes that make them physically, cognitively, and behaviorally uniform, and thus different from other races. The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs and minimize the threat of backfiring (unintentionally increasing belief in essentialism). The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.  Project research findings, learning materials, and professional development institutes will be made available to educators and researchers across the country who desire to teach genetics to reduce racial prejudice.

To prepare for the research, the project will revise and augment the project’s existing HGL curriculum and professional development institutes.  In year one, the project will develop new versions of the HGL interventions. Using these materials, the project will train teachers to implement new versions of the HGL interventions in their classrooms. Researchers will video and audio record a sample of teachers and students as they learn. These data will be analyzed qualitatively to: (1) examine how the conceptual change of genetic essentialism was promoted or impeded by interactions between teachers, students, and the materials; and (2) identify and corroborate general factors undergirding the backfiring effect.  Knowledge constructed through these studies will be used to revise the HGL interventions and PDIs.  In year three, using the revised versions of the HGL intervention, the project will conduct a cluster randomized trial (CRT). The CRT will compare the HGL interventions to a well-defined “business as usual” genetics curriculum, using a statistically powerful and geographically diverse sample (N = 135 teachers, N = 16,200 students, from 33 states). Using data from the CRT, the project will identify classrooms where the interventions reduced essentialism, had no effect on it, and where it backfired. Then, the project will use stimulated recall methods to interview the teachers and students in those classrooms to make sense of factors that contributed to these outcomes. The project will use this information to develop the final version of the HGL interventions and PDI materials. By the end of year four, the project will have trained an additional 90-100 teachers to use HGL interventions, reaching an additional 10,800-12,000 students, in at least 33 different states.

Reducing Racially Biased Beliefs by Fostering a Complex Understanding of Human Genetics Research in High School Biology Students (Collaborative Research: Wedow)

The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs. The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2100959
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Genetic essentialism is the belief that people of the same race share genes that make them physically, cognitively, and behaviorally uniform, and thus different from other races. The project will refine a genetics education curriculum, called Humane Genome Literacy (HGL), in order to reduce belief in genetic essentialism. This research will provide curriculum writers and educators with knowledge about how to design a humane genetics education to maximize reductions in students’ genetic essentialist beliefs and minimize the threat of backfiring (unintentionally increasing belief in essentialism). The research findings will demonstrate how to support teachers who wish to reduce beliefs in genetic essentialism by teaching students about the complexity of human genetics research using the HGL learning materials.  Project research findings, learning materials, and professional development institutes will be made available to educators and researchers across the country who desire to teach genetics to reduce racial prejudice.

To prepare for the research, the project will revise and augment the project’s existing HGL curriculum and professional development institutes.  In year one, the project will develop new versions of the HGL interventions. Using these materials, the project will train teachers to implement new versions of the HGL interventions in their classrooms. Researchers will video and audio record a sample of teachers and students as they learn. These data will be analyzed qualitatively to: (1) examine how the conceptual change of genetic essentialism was promoted or impeded by interactions between teachers, students, and the materials; and (2) identify and corroborate general factors undergirding the backfiring effect.  Knowledge constructed through these studies will be used to revise the HGL interventions and PDIs.  In year three, using the revised versions of the HGL intervention, the project will conduct a cluster randomized trial (CRT). The CRT will compare the HGL interventions to a well-defined “business as usual” genetics curriculum, using a statistically powerful and geographically diverse sample (N = 135 teachers, N = 16,200 students, from 33 states). Using data from the CRT, the project will identify classrooms where the interventions reduced essentialism, had no effect on it, and where it backfired. Then, the project will use stimulated recall methods to interview the teachers and students in those classrooms to make sense of factors that contributed to these outcomes. The project will use this information to develop the final version of the HGL interventions and PDI materials. By the end of year four, the project will have trained an additional 90-100 teachers to use HGL interventions, reaching an additional 10,800-12,000 students, in at least 33 different states.

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.

DataX: Exploring Justice-Oriented Data Science with Secondary School Students

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.

Award Number: 
2101413
Funding Period: 
Thu, 07/01/2021 to Fri, 06/30/2023
Full Description: 

Understanding data is critical for informed citizens. Data science is a growing and emerging field that can incorporate statistics, mathematics, and computer science to develop disciplinary knowledge and address societal challenges. 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 project includes science and social studies teachers in the design of the resources and in testing them in secondary school classrooms. Research and development in data science education is needed to understand how students can learn more about the use of data in meaningful and authentic ways. This interdisciplinary project will also help students meaningfully analyze real-world data sets, interpret social phenomena, and engage in social change.

During a two-year project period, we aim to iteratively advance three design components of the DataX program: (a) a justice-oriented data science curriculum integrated in secondary science and social studies; (b) a web-based learning platform that extends the Common Online Data Analysis Platform (CODAP) to support collaboration and sophisticated data practices; and (c) pedagogical practices that involve learners to work collectively as community. The guiding research question is: What scaffolds and resources are necessary to support the co-development of data, disciplinary, and critical literacies in secondary classrooms? To address this, the project will use participatory design research with science and social studies teachers to develop and test the curriculum, the learning platform, and the pedagogical practices. The data collected will include qualitative sources gathered from participatory design workshops and classrooms, as well as quantitative data from questionnaires and system logs. Using the data, we examine students' data science skills, data dispositions, and social participation in collaborative data investigations.

Building a Flexible and Comprehensive Approach to Supporting Student Development of Whole Number Understanding

The purpose of this project is to develop and conduct initial studies of a multi-grade program targeting critical early math concepts. The project is designed to address equitable access to mathematics and STEM learning for all students, including those with or at-risk for learning disabilities and underrepresented groups.

Lead Organization(s): 
Award Number: 
2101308
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

A critical goal for the nation is ensuring all students have a successful start in learning mathematics. While strides have been made in supporting at-risk students in mathematics, significant challenges still exist. These challenges include enabling access to and learning of advanced mathematics content, ensuring that learning gains don’t fade over time, and providing greater support to students with the most severe learning needs. One way to address these challenges is through the use of mathematics programs designed to span multiple grades. The purpose of this project is to develop and conduct initial studies of a multi-grade program targeting critical early math concepts. The project is designed to address equitable access to mathematics and STEM learning for all students, including those with or at-risk for learning disabilities and underrepresented groups.

The three aims of the project are to: (1) develop a set of 10 Bridging Lessons designed to link existing kindergarten and first grade intervention programs (2) develop a second grade intervention program that in combination with the kindergarten and first grade programs will promote a coherent sequence of whole number concepts, skills, and operations across kindergarten to second grade; and (3) conduct a pilot study of the second grade program examining initial promise to improve student mathematics achievement. To accomplish these goals multiple methods will be used including iterative design and development process and the use of a randomized control trial to study potential impact on student math learning. Study participants include approximately 220 kindergarten through second grade students from 8 schools across three districts. Study measures include teacher surveys, direct observations, and student math outcome measures. The project addresses the need for research developed intervention programs focused on advanced whole number content. The work is intended to support schools in designing and deploying math interventions to provide support to students both within and across the early elementary grades as they encounter and engage with critical mathematics content.

Learning about Viral Epidemics through Engagement with Different Types of Models

The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models.

Award Number: 
2101083
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

The project will develop new curriculum and use it to research how high school students learn about viral epidemics while developing competencies for scientific modeling. The COVID-19 pandemic has highlighted the need for supporting student learning about viral outbreaks and other complex societal issues. Given the complexity of issues like viral outbreaks, engaging learners with different types of models (e.g., mechanistic, computational and system models) is critical. However, there is little research available regarding how learners coordinate sense making across different models. This project will address the gap by studying student learning with different types of models and will use these findings to develop and study new curriculum materials that incorporate multiple models for teaching about viral epidemics in high school biology classes. COVID-19 caused devasting impacts, and marginalized groups including the Latinx community suffered disproportionately negative outcomes. The project will directly recruit Latinx students to ensure that design products are culturally responsive and account for Latinx learner needs. The project will create new pathways for engaging Latinx students in innovative, model-based curriculum about critically important issues. Project research and resources will be widely shared via publications, conference presentations, and professional development opportunities for teachers.

The project will research three aspects of student learning: a) conceptual understandings about viral epidemics, b) epistemic understandings associated with modeling, and c) model-informed reasoning about viral epidemics and potential solutions. The research will be conducted in three phases. Phase 1 will explore how students make sense of viral epidemics through different types of models. This research will be conducted with small groups of students as they work through learning activities and discourse opportunities associated with viral epidemic models. Phase 2 will research how opportunities to engage in modeling across different types of models should be supported and sequenced for learning about viral epidemics. These findings will make it possible to revise the learning performance which will be used to develop a curricular module for high school biology classes. Phase 3 will study the extent to which students learn about viral epidemics through engagement in modeling practices across different models. For this final phase, teachers will participate in professional development about viral epidemics and modeling and then implement the viral epidemic module in their biology classes. A pre- and post-test research design will be used to explore student conceptual understandings, model-informed reasoning, and epistemic understandings.

Education and Experience: Do Teacher Qualifications in Career-Focused STEM Courses Make a Difference?

Using high school statewide longitudinal data from Maryland from 2012-2022, this study will first document who has taught STEM-CTE courses over this period. After exploring the teaching landscape, the study will then explore whether qualifications (i.e., education, credentials, teaching experience) of teachers in STEM-CTE high school courses were associated with their students’ success.

Lead Organization(s): 
Award Number: 
2101163
Funding Period: 
Sun, 08/01/2021 to Mon, 07/31/2023
Full Description: 

When high school students take “STEM-CTE” (i.e., career and technical education courses in science, technology, engineering, and mathematics fields), they have much stronger outcomes across the school-to-college/career pipeline, including lower dropout rates and better attendance in high school, stronger math achievement in 12th grade, and higher odds of pursuing advanced STEM courses in high school and college. Growing teacher research shows that teachers matter for students’ success, particularly in STEM. In particular, research has established that teacher education and credentials in STEM fields, as well as years of classroom teaching experiences are key teacher factors in supporting student outcomes. However, there has been limited prior research regarding (a) who teaches STEM-CTE courses and (b) whether the benefits of these courses and pathways are driven or influenced by specific characteristics of STEM-CTE teachers. This project will aim to explore these questions.

Using high school statewide longitudinal data from Maryland from 2012-2022, this study will first document who has taught STEM-CTE courses over this period. The dataset includes approximately 5,000 unique teacher observations and approximately 500,000 unique student observations. After exploring the teaching landscape, the study will then explore whether qualifications (i.e., education, credentials, teaching experience) of teachers in STEM-CTE high school courses were associated with their students’ success. Indicators of success in the dataset include end-of-course grades, STEM-CTE concentration/industry-recognized credentialing, advanced STEM coursetaking (e.g., honors, AP, IB, dual-enrollment), STEM standardized test scores, math SAT/ACT scores, attendance/suspension rates, on-time graduation, and reduced dropout. Data analysis includes multivariate regression analyses, supplemented with tests for nonrandom sorting of teachers to students.

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