Achievement/Growth

Supporting Teachers to Develop Equitable Mathematics Instruction Through Rubric-Based Coaching (Collaborative Research: Hill)

This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics.

Lead Organization(s): 
Award Number: 
2100961
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Creating supportive middle school mathematics learning spaces that foster students' self-efficacy and mathematics learning is a critical need in the United States. This need is particularly urgent for mathematics classrooms with students who have been historically marginalized in such spaces. While many instructional improvement efforts have focused on broadening access to mathematical ideas, fewer efforts have paid explicit attention to the ways instructional practices may serve to marginalize students. Supporting teachers in identifying and refining their equitable mathematics instructional practices is a persistent challenge. This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project's work integrates the EAR-MI rubrics into the MQI Coaching model with 24 middle grades mathematics coaches supporting 72 teachers at grades 5-8. The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

The project makes use of a delayed-treatment experimental design to investigate effects on teacher beliefs and practices and student achievement and sense of belonging. A cohort of 14 coaches are randomly selected to participate in the coaching in Years 2 and 3, with the remaining 10 coaches assigned to a business-as-usual model in Year 2 and engaging in the training in Year 3. Coaches engage in a 4-day summer training to become acquainted with the model with coaching cycles and follow-up meetings during the school year. Each coach will engage teachers in 8-10 coaching cycles in treatment years. Data on the nature of the coaching includes logs and surveys from the coaches. Teachers submit surveys related to their beliefs and practices and two lessons each at the start and end of the academic year for analysis. Student assessment data, course grades, and administrative data, combined with survey data from students on classroom belonging and perceptions of ability and confidence in mathematics, are used to describe student outcomes. Teacher outcomes are captured through the analysis of classroom video, surveys about ethnic-racial identity and racial attitudes, beliefs about students and instruction, and beliefs about and efficacy for culturally responsive teaching. The project uses a set of survey measures with established reliability and validity, adapting some instruments to include specific indicators related to the equity and access rubrics. Analysis of the data uses a multi-level model accounting for the clustering of teachers within schools and students within classrooms and schools.

Supporting Teachers to Develop Equitable Mathematics Instruction Through Rubric-based Coaching (Collaborative Research: Litke)

This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics.

Lead Organization(s): 
Award Number: 
2100793
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Creating supportive middle school mathematics learning spaces that foster students' self-efficacy and mathematics learning is a critical need in the United States. This need is particularly urgent for mathematics classrooms with students who have been historically marginalized in such spaces. While many instructional improvement efforts have focused on broadening access to mathematical ideas, fewer efforts have paid explicit attention to the ways instructional practices may serve to marginalize students. Supporting teachers in identifying and refining their equitable mathematics instructional practices is a persistent challenge. This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project's work integrates the EAR-MI rubrics into the MQI Coaching model with 24 middle grades mathematics coaches supporting 72 teachers at grades 5-8. The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

The project makes use of a delayed-treatment experimental design to investigate effects on teacher beliefs and practices and student achievement and sense of belonging. A cohort of 14 coaches are randomly selected to participate in the coaching in Years 2 and 3, with the remaining 10 coaches assigned to a business-as-usual model in Year 2 and engaging in the training in Year 3. Coaches engage in a 4-day summer training to become acquainted with the model with coaching cycles and follow-up meetings during the school year. Each coach will engage teachers in 8-10 coaching cycles in treatment years. Data on the nature of the coaching includes logs and surveys from the coaches. Teachers submit surveys related to their beliefs and practices and two lessons each at the start and end of the academic year for analysis. Student assessment data, course grades, and administrative data, combined with survey data from students on classroom belonging and perceptions of ability and confidence in mathematics, are used to describe student outcomes. Teacher outcomes are captured through the analysis of classroom video, surveys about ethnic-racial identity and racial attitudes, beliefs about students and instruction, and beliefs about and efficacy for culturally responsive teaching. The project uses a set of survey measures with established reliability and validity, adapting some instruments to include specific indicators related to the equity and access rubrics. Analysis of the data uses a multi-level model accounting for the clustering of teachers within schools and students within classrooms and schools.

Supporting Teachers to Develop Equitable Mathematics Instruction Through Rubric-based Coaching (Collaborative Research: Wilson)

This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics.

Award Number: 
2100830
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Creating supportive middle school mathematics learning spaces that foster students' self-efficacy and mathematics learning is a critical need in the United States. This need is particularly urgent for mathematics classrooms with students who have been historically marginalized in such spaces. While many instructional improvement efforts have focused on broadening access to mathematical ideas, fewer efforts have paid explicit attention to the ways instructional practices may serve to marginalize students. Supporting teachers in identifying and refining their equitable mathematics instructional practices is a persistent challenge. This project brings together a successful mathematics rubric-based coaching model (MQI Coaching) and an empirically developed observation tool focused on equity-focused instructional practices, the Equity and Access Rubrics for Mathematics Instruction (EAR-MI). The project's work integrates the EAR-MI rubrics into the MQI Coaching model with 24 middle grades mathematics coaches supporting 72 teachers at grades 5-8. The project measures the effects of the coaching model on teachers' beliefs and instructional practices and on students' mathematical achievement and sense of belonging in mathematics. The project also investigates how teachers' attitudes and beliefs impact their participation and what teachers take away from engagement with the coaching model.

The project makes use of a delayed-treatment experimental design to investigate effects on teacher beliefs and practices and student achievement and sense of belonging. A cohort of 14 coaches are randomly selected to participate in the coaching in Years 2 and 3, with the remaining 10 coaches assigned to a business-as-usual model in Year 2 and engaging in the training in Year 3. Coaches engage in a 4-day summer training to become acquainted with the model with coaching cycles and follow-up meetings during the school year. Each coach will engage teachers in 8-10 coaching cycles in treatment years. Data on the nature of the coaching includes logs and surveys from the coaches. Teachers submit surveys related to their beliefs and practices and two lessons each at the start and end of the academic year for analysis. Student assessment data, course grades, and administrative data, combined with survey data from students on classroom belonging and perceptions of ability and confidence in mathematics, are used to describe student outcomes. Teacher outcomes are captured through the analysis of classroom video, surveys about ethnic-racial identity and racial attitudes, beliefs about students and instruction, and beliefs about and efficacy for culturally responsive teaching. The project uses a set of survey measures with established reliability and validity, adapting some instruments to include specific indicators related to the equity and access rubrics. Analysis of the data uses a multi-level model accounting for the clustering of teachers within schools and students within classrooms and schools.

Supporting Teacher Understanding of Emergent Computational Thinking in Early Elementary Students

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.

Lead Organization(s): 
Award Number: 
2101547
Funding Period: 
Wed, 09/01/2021 to Sat, 08/31/2024
Full Description: 

There is an increasing focus and interest in teaching computer science and computational thinking in early elementary school. 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. The teachers will collaborate using an online platform for sharing resources, and the project will also study how the online platform can help to reach and support more teachers. The teachers’ learning will be supported by instructional coaches who will help the teachers to integrate computer science into their teaching, and to interpret evidence of their students’ understanding of computational thinking.

The project explores how to help teachers identify and support early elementary children’s emergent computational thinking. The professional learning model for teachers includes a community of practice supported by an online platform and a coach with expertise in computational thinking. The work leverages models for professional development in early grades mathematics. The project focuses on creating systems and conditions for scalable professional learning including coherence, coaching, teacher networks, and engagement with school and district leadership. The research questions are: (1) What kind of professional development and guidance do teachers need to identify and support emergent computational thinking development in young students’ language and work process? (2) What kind of professional development and guidance do teachers need to identify emergent computational thinking development in young students’ work products? (3) How can a scalable professional learning system help teachers understand the development of emergent computational thinking in K-2 students? The teachers will develop lessons, use them with students, and reflect about their work with the coach and the other teachers in their community of practice. The data collection and analysis include interviews, surveys, observations, and documentation from the online platform to understand teachers’ professional learning and development.

Measuring the Effectiveness of Middle School STEM Innovation and Engineering Design Curricula

Researchers from Georgia Tech have developed a three-year middle school Engineering and Technology course sequence that introduces students to advanced manufacturing tools such as computer aided design (CAD) and 3D printing, incorporates engineering concepts such as pneumatics, robotics and aeronautics, increases student awareness of career paths, and addresses the concerns of technical employers wanting workers with problem solving, teamwork, and communication skills.

Award Number: 
2101441
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Inclusion of engineering in the Next Generation Science Standards has led to increased opportunities for K-12 students to learn engineering related concepts and skills, and learn about engineering career paths. However, a persistent challenge is the lack of high-quality, research-based engineering curricular resources that align with science and math education standards. Further, the opportunities for K-12 students to also learn about manufacturing and how manufacturing is related to engineering, math, and science are limited. Researchers from Georgia Tech have developed a three-year middle school Engineering and Technology course sequence that introduces students to advanced manufacturing tools such as computer aided design (CAD) and 3D printing, incorporates engineering concepts such as pneumatics, robotics and aeronautics, increases student awareness of career paths, and addresses the concerns of technical employers wanting workers with problem solving, teamwork, and communication skills. This DRK-12 impact study project will investigate the effectiveness of STEM-Innovation and Design (STEM-ID) curricula in approximately 29 middle schools, targeting 29 engineering teachers and approximately 5,000 students across middle grades in Georgia. This impact research study will determine whether STEM-ID courses are equally effective across different demographic groups and school environments under normal implementation conditions and whether the courses have the potential to positively impact a vast number of students around the country, particularly students who have struggled to stay engaged with their STEM education. It is a critical part of a larger effort to move the STEM-ID curricula, developed with NSF support, from the research lab to large-scale practice in schools.

To facilitate large-scale implementation, the project will transfer all curriculum and teacher support materials to an online dissemination site, develop just-in-time teacher support materials to embed within the curriculum, create an online professional development platform, and conduct professional learning in multiple areas of the state. The project team will then assess the transferability of the STEM-ID curricula and identify teacher outcomes that affect the implementation. They will also examine the generalizability of the curriculum by measuring student outcomes in STEM academic achievement and on social-emotional scales. The project’s research questions consider 1) contextual factors that influence scaling; 2) the fidelity of implementation, curriculum adaptations and sustainability; 3) the effects of professional development on teachers’ engineering self-efficacy and instructional practices; 4) the effect of participation on student academic performance in mathematics and science; 5) the effect of participation on student social-emotional outcomes; and 5) the relationship between the way STEM-ID is implemented and the student outcomes.  To examine the effects of STEM-ID on achievement and achievement growth, the investigators will use a multilevel growth model and mediation analysis to explore if the intervention’s effect on achievement was mediated by students’ engagement, academic self-efficacy, and/or interest in STEM. Additionally, drawing upon Century and Cassata’s Fidelity of Implementation framework (FOI), they will examine the array of factors that influence implementation of the STEM-ID curricula across diverse school settings.

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.

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