Biology

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.

Supporting the Implementation of Scientific Modeling Instruction in High School Chemistry and Biology in Rural Schools

High school students in many rural school districts have limited access to advanced STEM coursework and advanced technologies, including high-speed Internet. Rural school districts face difficulties in recruiting and retaining STEM teachers. In many cases, rural STEM teachers need additional training and support. The project will identify these, and other barriers rural teachers face and create professional development for teachers.

Award Number: 
2101590
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

High school students in many rural school districts have limited access to advanced STEM coursework and advanced technologies, including high-speed Internet. Rural school districts face difficulties in recruiting and retaining STEM teachers. In many cases, rural STEM teachers need additional training and support. The project will identify these, and other barriers rural teachers face and create professional development for teachers. The training will be designed to increase their discipline specific knowledge and related skills in engaging students in using models to explore, analyze, assess, and improve their thinking about and knowledge of science. Participating teachers will receive 114 hours of formal professional development in the summer and sustained support from follow-up sessions and an innovative virtual mentoring throughout the academic year. The project will revise biology and chemistry curriculum and support 30-90 teachers annually in rural areas in implementing reform-oriented MI instruction benefiting approximately 25,000 rural students. The project will result in a network of leader teachers who can sustain project initiatives. Online STEM professional development courses and digital tools for rural teachers and teachers will be made widely disseminated. In addition, project resources and research findings will be disseminated via conference presentations and peer-reviewed research journals.

Project research is designed to generate knowledge about the development of rural science teachers' pedagogical content knowledge (PCK) and the supports needed as rural teachers implement an approach to teaching called Modeling Instruction (MI). PCK refers to knowledge of and how to teach discipline-specific science concepts. MI is a pedagogical approach where students are actively engaged in using conceptual models that are created and applied to concrete physical, biological, and chemical phenomena to promote their understanding of scientific/mathematical principles. Through longitudinal mixed-methods research, the project will add new knowledge about PCK and MI. The project will investigate the progression of teachers’ PCK associated with the high-level implementation of MI that engages students in science research practices. The research of discipline specific PCK will significantly inform the curriculum and design of preservice and in-service science teacher education programs. The project will also research how various aspects of mentoring (e.g., feedback, interactions, discourse, and the modes and quantity of mentoring activities) support teachers in the effective use of PCK in the classroom. Qualitative research tools will include analysis of videos of teacher implementation of lessons, interviews with teachers focusing on the lessons, focus groups and semi-structured interviews on mentoring experiences, and analysis of teacher mentor-teacher mentee sessions and activity. The Science Instruction Practices Survey will collect quantitative data that will be used to understand each teacher’s implementation of MI, looking at the science practices that teachers in the classroom such as investigation, data collection and analysis, explanation, modeling, and science communication.

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.

Developing the Pedagogical Skills and Science Expertise of Teachers in Underserved Rural Settings

The project will develop and research an innovative model for rural science teacher professional development via technology-mediated lesson study (TMLS). This approach supports translating professional learning into classroom practice by developing a technology-based, social support system among rural teachers.

Lead Organization(s): 
Award Number: 
2101383
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Rural science teachers are often isolated and have few opportunities for meaningful collaboration with fellow teachers, an important source of professional learning. The project will develop and research an innovative model for rural science teacher professional development via technology-mediated lesson study (TMLS). This approach supports translating professional learning into classroom practice by developing a technology-based, social support system among rural teachers. The project will host summer workshops for high school biology and chemistry teachers from four rural Utah regions to learn about 3D science teaching. (3D science teaching incorporates core ideas science disciplines, science research practices, and concepts cutting across disciplines to help students meet performance expectations by engaging with authentic science phenomena.) In the workshops, participants will collaborate with the project team and teachers of the same subject from the same region of the state to co-design 3D science lessons that align with state and national education standards. Building on relationships developed during the workshops, the regional teacher teams will engage in a novel form of professional learning: technology-mediated lesson study. (Lesson study is an instructional inquiry model where teachers work face-to-face in small collaborative groups to craft, deliver, observe, and refine teaching practice.) This project will develop capacity for science teaching for 88 rural science teachers in four regions of the state, who will reach approximately 10,000 rural Utah students each year. Many of the students are members of the sovereign Ute, Paiute, Goshute, Navajo (Diné), and Shoshone Nations. The science lesson plans participants design will be made available to all Utah teachers, and shared with a national audience through a website that shares peer-reviewed science lesson plans. Project research and resources will be further disseminated through conference presentations and publications in peer-reviewed and practitioner journals.

The project will research how TMLS supports teachers in the process of translating professional learning into practice and investigate the impact of changing teachers’ social support network to include teachers of the same subject from other rural schools. The project will study the effects of co-design activities and TMLS cycles on teachers’ changing capacity, practice, and social support system using mixed-methods research. Changes in capacity and practice will be examined qualitatively through interviews, video observations of classroom teaching, and TMLS meetings. The effects of TMLS on teachers’ social support system will be analyzed quantitatively using social network analysis to identify individuals who act as information hubs for 3D science teaching. These teachers will be interviewed to better understand their social interactions. Using design-based implementation research, the project will iteratively improve the professional learning experience collaboratively with the science teacher leaders who participate in the project.

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.

Supporting High School Students and Teachers with a Digital, Localizable, Climate Education Experience

This partnership of BSCS Science Learning, Oregon Public Broadcasting, and the National Oceanic and Atmospheric Administration advances curriculum materials development for high quality units that are intentionally designed for adaptation by teachers for their local context. The project will create a base unit on carbon cycling as a foundation for understanding how and why the Earth's climate is changing, and it will study the process of localizing the unit for teachers to implement across varied contexts to incorporate local phenomena, problems, and solutions.

Lead Organization(s): 
Award Number: 
2100808
Funding Period: 
Thu, 07/01/2021 to Mon, 06/30/2025
Full Description: 

Teachers regularly adapt curriculum materials to localize for their school or community context, yet curriculum materials are not always created to support this localization. Developing materials that are intentionally designed for localization has potential to support rich science learning across different contexts, especially for a topic like climate change where global change can have varied local effects. This partnership of BSCS Science Learning, Oregon Public Broadcasting, and the National Oceanic and Atmospheric Administration advances curriculum materials development for high quality units that are intentionally designed for adaptation by teachers for their local context. It will develop and test a design process bringing together national designers and teachers across the country. Teachers will be supported through professional learning to adapt from the base unit to create a local learning experience for their students. The project will create a base unit on carbon cycling as a foundation for understanding how and why the Earth's climate is changing, and it will study the process of localizing the unit for teachers to implement across varied contexts to incorporate local phenomena, problems, and solutions. The unit will be fully digital with rich visual experiences, simulations, and computer models that incorporate real-time data and the addition of localized data sets. These data-based learning experiences will support students in reasoning with data to ask and answer questions about phenomena. Research will study the unit development and localization process, the supports appropriate for teachers and students, and the impact on classroom practice.

The project will adopt an iterative design process to create a Storyline base unit, aligned to Next Generation Science Standards, for localization, piloting, and an implementation study with 40 teachers. To support teacher learning, the project adopts the STeLLA teacher professional learning model. To support student learning, the project addresses climate change content knowledge with a focus on socioscientific issues and students’ sense of agency with environmental science. The project will research how the educative features in the unit and the professional development impact teachers’ practice, including their content knowledge, comfort for teaching a socioscientific issue, and their ability to productively localize materials from a base unit. The study uses a cohort-control quasi-experimental design to examine the impact of the unit and professional learning experience on dimensions of students' sense of agency with environmental science. The study will also include exploratory analyses to examine whether all students benefit from the unit. It uses a pre-post design to examine impacts on teacher knowledge and practice.

Fostering Computational Thinking through Neural Engineering Activities in High School Biology Classes

This project will develop and study a curriculum and app that support computational thinking (CT) in a high school biology unit. The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply CT principles.

Lead Organization(s): 
Award Number: 
2101615
Funding Period: 
Wed, 09/01/2021 to Sun, 08/31/2025
Full Description: 

Computational thinking (CT) is a set of processes to identify and solve problems using algorithms or steps, and can be applied not only in computer science but in other disciplines. This project will develop and study a curriculum and app that support CT in a high school biology unit. Through a month-long neural engineering unit, approximately 500 students in 18 classes will measure their own muscle and brain activity with a low-cost, portable, wearable technology. Students will then analyze the data and design a brain-computer interface to turn neural signals into real-world output (e.g., a mechanical claw controlled by brain activity). The curriculum will be supported by: (1) a web-based instructional application that will guide students through the neural engineering design process; (2) neuroscience and engineering PhD students and postdocs acting as STEM mentors; and (3) a professional development program for teachers and mentors. The goal is to increase the students’ knowledge and interest regarding neurobiology, engineering, and computational thinking. This can contribute to their long-term capacity to pursue STEM careers. By integrating CT education into high school science, this expands the accessibility of the engineering and computing experiences beyond other efforts that focus primarily on programming and computer science courses.

The project will engage students in rich data practices by gathering, manipulating, analyzing, simulating, and visualizing data of bioelectrical signals from neural sensors, and in so doing give the students opportunities to apply computational thinking principles. The project will produce curriculum materials for the neural sensors and associated data practices. It will develop an app to help students design and construct a brain-computer interface, including computational elements like coding blocks, sensor and data simulation, and connecting to external devices. The five proposed research questions of the study are: How does students’ CT change throughout their participation in the neural engineering design process? What is the cross-cultural validity of two CT scales in a sample of high school students in the US? How does the process of collecting and analyzing real-world data relate to students’ experience of he engineering design process? How do students’ attitudes toward STEM change over the course of their participation in a neural engineering design process? How does teachers’ self-efficacy for fostering CT in their students via engineering design change through their participation in professional development and in implementation of the proposed curriculum?

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