Students

MothEd - Authentic Science for Elementary and Middle School Students

Widely-adopted science education standards have expanded expectations for students to learn science research processes. To address these needs, the project will research and develop curricular materials and classroom practices that teachers can use to bring authentic science into their classes and engage students as active science researchers. The project, called MothEd, will focus on the study of moths, which are well-suited to the project’s goal of having students conduct authentic scientific investigations.

Lead Organization(s): 
Award Number: 
2100990
Funding Period: 
Sun, 08/15/2021 to Thu, 07/31/2025
Full Description: 

There are few opportunities and curriculum materials that support teachers in engaging elementary and middle-school students in scientific research processes and in conducting their own investigations. Widely-adopted science education standards have expanded expectations for students to learn science research processes. To address these needs, the project will research and develop curricular materials and classroom practices that teachers can use to bring authentic science into their classes and engage students as active science researchers. The project, called MothEd, will focus on the study of moths, which are well-suited to the project’s goal of having students conduct authentic scientific investigations. Moths are ecologically important, easy to capture, and there is a lack of research on moths compared to many other insect species. In the project activities, students will construct moth traps and collect data through research processes that they design and carry out. The project is building on an approach called community science (sometimes called citizen science), where non-scientists in local communities voluntarily contribute to scientific research. Students and teachers will work in partnership with entomologists and science educators to develop and answer questions about local ecological conditions and will become genuine producers of knowledge within science learning communities. Students will work collaboratively within an online platform to design experiments using a complete suite of research tools for collection, expression, and analysis of data, including sensors, photographs, sketches, and graphs. The project will develop curricular materials that will provide teaching and learning materials that are focused on giving students place-based opportunities to conduct age-appropriate scientific investigations.

MothEd’s educational research will investigate several questions: (1) what students understand about scientific research processes and how they see themselves in that process; (2) how students can work as partners with scientists in discovery and what do they learn about research methods and moth ecology; and (3) What supports teachers need in order to support students as active science researchers. Using a mixed methods approach, the project will collect a variety of data for the research: in-class observations of student work; pre- and post- activity surveys about their knowledge of moth ecology and their view and understanding of science research processes; teacher interviews; and analysis of data collected by project software on student work and collaboration. The project will be designed to ensure that the MothEd education materials can be adopted and used independently by teachers across the country. Project research findings and materials will be shared via conferences, journal publications, and the project’s collaborative learning environment.

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.

COVID Connects Us: Nurturing Novice Teachers’ Justice Science Teaching Identities

In COVID Connects Us, the project team investigates the challenges of learning how to support justice-centered ambitious science teaching (JuST). The project team will partner with networks of secondary science teachers as they first implement a common unit aimed at engaging youth in science and engineering practices in ways that are culturally sustaining, focused on explanation-construction and intentionally anti-oppressive.

Lead Organization(s): 
Award Number: 
2101217
Funding Period: 
Thu, 07/01/2021 to Sun, 06/30/2024
Full Description: 

This project relates to two contemporary concerns in the US: the devastation felt by racial and ethnic minoritized communities during the COVID-19 pandemic and the challenges states face as they strategically navigate the adoption of the Next Generation Science Standards. These concerns necessitate a shift in the culture of science classrooms to align with the following findings from current research on learning: (a) students are best motivated when they need to explain real world events and solve problems that are meaningful to them; (b) when students develop explanations of these real-world events or societal problems and are allowed to participate in creative ways, they can develop deep understandings of core science ideas similar to that of scientists and engineers; and (c) students need to develop a critical lens about what science is studied, how it is studied, and who is left out of what is studied to understand how science is impacted by issues of power and to engage in more just forms of participation. Realizing these cultural transformations in science classrooms will require teachers to develop professional identities that are justice-, student- and culture-centered. In COVID Connects Us, the project team investigates the challenges of learning how to support justice-centered ambitious science teaching (JuST). The project team will partner with networks of secondary science teachers as they first implement a common unit aimed at engaging youth in science and engineering practices in ways that are culturally sustaining, focused on explanation-construction and intentionally anti-oppressive. The teachers will then use their shared experiences to revise future instruction in ways that are justice-centered and that engage students in the ways research suggests is important for their learning.

The goals of this three-year project center on developing and understanding core culture-setting teaching routines that can serve as powerful footholds to realize cultural shifts in science classrooms. The project team will collect and analyze teacher narratives to study the impact of two core and focal teacher supports on participating teachers’ professional identity development as practitioners of JuST practices. The supports include 1) a culture setting unit that all teachers will implement on the science of COVID; and 2) teachers’ engagement in a network of learning communities. During each of the first two academic years of the project, about 20 learning communities made up of four teachers in three different sites will engage in design-based implementation research cycles. These learning communities will collectively study videos of their teaching and samples of student-work to understand and address the challenges of JuST practices. Expected contributions of the study include: (a) a set of JuST routines that teachers find to be effective across curricular units; (b) exemplar JuST units including, but not limited to, the initial unit on the science of COVID; (c) research-based findings about how science educators develop critical consciousness related to disciplinary racism and practices that support students’ in developing the same; and d) vignettes and in-depth case studies of teachers’ development of JuST identities.

Bilingualtek: An Integrated Science-Language Approach for Latinx Preschoolers

This project seeks to foster the science achievement of Latinx preschoolers by confronting current barriers that impact their STEM education through an integrated science-language instructional approach for preschool classrooms. The project will use everyday science experiences to engage Latinx preschoolers in learning the practices of scientists, including the practices of obtaining information and using language to communicate scientific findings.

Award Number: 
2101169
Funding Period: 
Tue, 06/01/2021 to Sat, 05/31/2025
Full Description: 

Early childhood education currently faces challenges related to effective science instruction practices that meet the learning needs of culturally and linguistically diverse children, such as Latinx dual language learners (DLL). This project seeks to foster the science achievement of Latinx preschoolers by confronting current barriers that impact their STEM education through an integrated science-language instructional approach for preschool classrooms. The project will use everyday science experiences to engage Latinx preschoolers in learning the practices of scientists, including the practices of obtaining information and using language to communicate scientific findings. These aims will be accomplished by combining engaging science experiences delivered via e-books, and multimedia supports for science and dual-language learning. Consistent with the Next Generation of Science Standards (NGSS), the project offers a transformative model of early childhood science and language education that supports kindergarten readiness at a national level and addresses the vital need for educational resources that build on and enhance the strengths of underserved communities.

The long-term goal of this project is to foster the science achievement of Latinx preschoolers by addressing current challenges impacting their STEM education. These challenges include; limited early science education instruction for teachers, minimal incorporation of NGSS science principles in early science learning for preschoolers, and increasing numbers of Latinx DLLs entering preschools experiencing a shortage of bilingual early childhood teachers. The project addresses these challenges by leveraging recent research with preschool Latinx DLLs across several disciplines into a media-supported integrated science-language instructional approach. These instructional practices provide an NGSS-aligned model for preschool-age science education at the national level, support kindergarten readiness, and directly address the need for educational resources that build on the strengths that diverse children bring to their learning experience. Supporting monolingual teachers’ use of multimedia dual-language science materials will also address preschool teacher professional learning related to science instruction while promoting the participation of underrepresented minorities in STEM education at an early age. The science-language instructional practices will be developed by bringing together preschool teachers and Latinx families in an iterative co-design process to develop instructional content and supports to facilitate science and language learning by Latinx DLLs. The project will be implemented in 28 classrooms to examine its usability, feasibility, and preliminary efficacy, including child outcomes (science talk, science knowledge, and language skills) through a rigorous quasi-experimental field study. The treatment and control groups will each include 42 children and 14 teachers. The project will produce 1) an integrated science and language instructional approach and resource materials relevant to Latinx children’s living experiences, 2) proof of concept of the project’s feasibility; and 3) initial findings on the impact of the project on children’s science and language learning outcomes.

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.

Developing and Evaluating Assessments of Problem-Solving in Computer Adaptive Testing Environments (Collaborative Research: Bostic)

The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2100988
Funding Period: 
Sun, 08/01/2021 to Fri, 07/31/2026
Full Description: 

Problem solving has been a priority within K-12 mathematics education for over four decades and is reflected throughout the Common Core State Standards for Mathematics (CCSSM) initiative, which have been adopted in some form by 41 states. Broadly defined, problem solving involves the mathematical practices in which students engage as they solve intellectually-challenging mathematical tasks. In prior research, problem-solving measures aligned to CCSSM for grades 3-5 were developed and validated to supplement previously established problem-solving measures in grades 6-8. The problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests. Few measures designed to assess students’ mathematical problem-solving ability use this technology. Shorter tests require less in-class time for assessment than current paper-pencil problem-solving measures and increase classroom instruction time. The computer-adaptive problem-solving measures have sufficient reliability and strong validity evidence, and may limit test-taker fatigue. Finally, the project will benchmark current grades 6-8 instruments using an objective standard-setting method, which allows for improved score interpretations with content-related feedback. Immediate results of student- and class-level reports will be produced through the computer adaptive testing system allowing for teachers to modify instruction to improve students’ learning.

This five-year project aims to advance the use of computer adaptive testing and assessment development for use in mathematics instruction. The project applies an iterative and stakeholder-informed design science-based methodology as well as employs the use of Rasch modeling for the psychometric analysis during item development and validation. The project aims to: (a) benchmark the previously established grades 6-8 problem-solving measures; (b) develop, calibrate, and validate criterion-referenced computer adaptive testing for each measure; (c) construct student- and class-level score reports for integration into the computer adaptive testing system; and (d) investigate teachers’ capacity for implementing, interpreting, and using the assessments and results in STEM learning settings. The project addresses the following set of research questions: (RQ1) What benchmark performance standards define different proficiency levels on problem-solving measures for each grade level? (RQ2) What are the psychometric properties of new problem-solving measures items developed for the computer adaptive testing item bank? (RQ3) Is there significant item drift across student populations on the new problem-solving measure items? (RQ4) To what extent are problem-solving measures item calibrations stable within the computer adaptive testing system? (RQ5) What recommendations for improvements do teachers and students have for the new problem-solving measures items, computer adaptive testing platform and reporting system, if any? (RQ6) To what extent do teachers interact with, perceive, and make sense of the assessment information generated for use in practice? and (RQ7) Does an online learning module build teacher capacity for problem solving measures, computer adaptive testing implementation, interpretation, and use of student assessment outcomes in STEM learning settings? An experimental design will be utilized to investigate teachers’ capacity for implementing, interpreting, and using problem solving measures in a computer adaptive testing system. The project has the potential to impact the field by providing school districts and researchers a means to assess students’ mathematical problem-solving performance at one time or growth over time efficiently and effectively; address future online learning needs; and improve classroom teaching through more precise information about students’ strengths with less class time focused on assessment.

Developing and Evaluating Assessments of Problem-Solving in Computer Adaptive Testing Environments (Collaborative Research: Sondergeld)

The Common Core State Standards for Mathematics (CCSSM) problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests.

Lead Organization(s): 
Partner Organization(s): 
Award Number: 
2101026
Funding Period: 
Sun, 08/01/2021 to Fri, 07/31/2026
Full Description: 

Problem solving has been a priority within K-12 mathematics education for over four decades and is reflected throughout the Common Core State Standards for Mathematics (CCSSM) initiative, which have been adopted in some form by 41 states. Broadly defined, problem solving involves the mathematical practices in which students engage as they solve intellectually-challenging mathematical tasks. In prior research, problem-solving measures aligned to CCSSM for grades 3-5 were developed and validated to supplement previously established problem-solving measures in grades 6-8. The problem-solving measures assess students’ problem-solving performance within the context of CCSSM math content and practices. This project expands the scope of the problem-solving measures use and score interpretation. The project work advances mathematical problem-solving assessments into computer adaptive testing. Computer adaptive testing allows for more precise and efficient targeting of student ability compared to static tests. Few measures designed to assess students’ mathematical problem-solving ability use this technology. Shorter tests require less in-class time for assessment than current paper-pencil problem-solving measures and increase classroom instruction time. The computer-adaptive problem-solving measures have sufficient reliability and strong validity evidence, and may limit test-taker fatigue. Finally, the project will benchmark current grades 6-8 instruments using an objective standard-setting method, which allows for improved score interpretations with content-related feedback. Immediate results of student- and class-level reports will be produced through the computer adaptive testing system allowing for teachers to modify instruction to improve students’ learning.

This five-year project aims to advance the use of computer adaptive testing and assessment development for use in mathematics instruction. The project applies an iterative and stakeholder-informed design science-based methodology as well as employs the use of Rasch modeling for the psychometric analysis during item development and validation. The project aims to: (a) benchmark the previously established grades 6-8 problem-solving measures; (b) develop, calibrate, and validate criterion-referenced computer adaptive testing for each measure; (c) construct student- and class-level score reports for integration into the computer adaptive testing system; and (d) investigate teachers’ capacity for implementing, interpreting, and using the assessments and results in STEM learning settings. The project addresses the following set of research questions: (RQ1) What benchmark performance standards define different proficiency levels on problem-solving measures for each grade level? (RQ2) What are the psychometric properties of new problem-solving measures items developed for the computer adaptive testing item bank? (RQ3) Is there significant item drift across student populations on the new problem-solving measure items? (RQ4) To what extent are problem-solving measures item calibrations stable within the computer adaptive testing system? (RQ5) What recommendations for improvements do teachers and students have for the new problem-solving measures items, computer adaptive testing platform and reporting system, if any? (RQ6) To what extent do teachers interact with, perceive, and make sense of the assessment information generated for use in practice? and (RQ7) Does an online learning module build teacher capacity for problem solving measures, computer adaptive testing implementation, interpretation, and use of student assessment outcomes in STEM learning settings? An experimental design will be utilized to investigate teachers’ capacity for implementing, interpreting, and using problem solving measures in a computer adaptive testing system. The project has the potential to impact the field by providing school districts and researchers a means to assess students’ mathematical problem-solving performance at one time or growth over time efficiently and effectively; address future online learning needs; and improve classroom teaching through more precise information about students’ strengths with less class time focused on assessment.

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