Supporting Science Learning and Teaching in Middle School Classrooms Through Automated Analysis of Students' Writing (Collaborative Research: Puntambekar)

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Written science explanations are central to learning and practicing science. However, there are two main challenges: first, students struggle to explain their ideas and use supporting data appropriately. Second, it is not realistic for teachers to provide real-time, comprehensive feedback to each student. We will present how PyrEval, a natural language processing (NLP) technology, provided students with timely, personalized, automated feedback. We will discuss opportunities and challenges for using automated feedback in classrooms.

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Supporting Science Learning and Teaching in Middle School Classrooms Through Automated Analysis of Students' Writing (Collaborative Research: Passonneau)

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This project supports students’ writing of science explanations. One main goal is to develop novel, automated natural language processing (NLP) technology to provide middle school students and teachers with real-time feedback on their science essays, to help them reflect on the quality of their explanations, and to foster their ability to write scientific explanations grounded in scientific evidence. A science unit on roller coasters is presented to students in a web-based environment that includes a roller coaster simulation to conduct experiments.

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Supporting School Administrators in Leading Towards Racially Just and Ambitious Mathematics Instruction

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This poster will present one school's partnership work as part of our larger project. As a key lever to lead towards racially just, ambitious mathematics, the leadership team is focused on acknowledging, valuing, and incorporating students and families' funds of knowledge in mathematics into everyday classroom teaching and learning. The poster will describe the multiple pathways they are working to do this, successes, and challenges.

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Supporting Instructional Decision Making: The Potential of an Automatically Scored Three-dimensional Assessment System (Collaborative Research: Zhai)

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This project studied the utility of a machine learning-based assessment system for supporting middle school science teachers in making instructional decisions based on automatically generated student reports (AutoRs).

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

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This project is developing and testing a high school climate change unit and professional learning experience in which teachers localize part of the unit to make it relevant to their students and community context. The study is using a cohort-control quasi-experimental design to examine the impact of the unit and professional learning experience on dimensions of teacher practice and students' sense of agency with environmental science.

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Supporting Elementary Teacher Learning for Effective School-based Citizen Science (TL4CS)

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The goal of TL4CS is to explore how elementary school citizen science (CS) can support students’ engagement with science content and practices. The study addresses three research questions: (1) What kinds of supports foster teacher learning about effective school-based CS? (2) How do supports for teacher learning shape the way teachers enact school-based CS? and (3) What is the potential of school-based CS for positively influencing student learning and student attitudes toward nature and science?

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Strengthening STEM Teaching in Native American Serving Schools Through Long-Term, Culturally Responsive Professional Development

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Indigenous students experience persistent inequitable outcomes in schools, particularly in STEM. Since teacher quality is one of the most important school-based factors impacting K12 students’ learning and engagement in schools, our project provides long-term professional development to teachers in rural, Indigenous-serving schools to support teachers’ development of culturally responsive STEM curriculum units. We provide an overview of our professional development model, and share findings from our work with over 100 teachers during four program years.

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Strengthening Data Literacy Across the Curriculum

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This project has developed and studied multi-week curriculum modules for high school non-AP mathematics classes to promote interest and skills in statistics and data analysis among diverse student populations. Using large-scale data from the U.S. Census Bureau and the online platform CODAP, students gain experience with multivariable thinking as they investigate questions focused on social justice issues in U.S. society. This poster shares strengths and challenges in students’ abilities to reason with multivariable data.

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STEM Sea, Air, and Land Remotely Operated Vehicle Design Challenges for Rural, Middle School Youth

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The STEM SEALs program at North Florida College explores methods for improvement of teaching and learning STEM in rural areas. It consists of three disciplines, “Sea”, “Land”, and “Air”, and three phases, design, review and summer institute for each of the disciplines.
 

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STEM for All Collaboratory: Accelerating Dissemination and Fostering Collaborations for STEM Educational Research and Development

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The poster will look at the impact of the annual STEM for All Video Showcases as well as the STEM for All Multiplex. It will discuss implications for knowledge sharing among grantees and dissemination efforts in the future.

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