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Making Sense of Models: Investigating Mechanistic Reasoning as a Bridge for Connecting 6th Grade Mathematics and Science Learning

Making Sense of Models: Investigating Mechanistic Reasoning as a Bridge for Connecting 6th Grade Mathematics and Science Learning
理解模型:研究机械推理作为连接六年级数学和科学学习的桥梁
批准号:
1934126
负责人:
Irene Lee
金额:
$172.16万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-01-01 至 2024-12-31

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中文摘要
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英文摘要
This project addresses the following problem of practice: Middle school science teachers find that they have to reteach mathematics concepts to prepare their students to use and analyze computer models of scientific phenomena in their science classes, which takes some significant time away from instruction. Some of them find that students do not know why mathematics is useful and how it can be applied in science contexts. Modeling has also become an increasingly emphasized component of both the Common Core State Standards in Mathematics and the Next Generation Science Standards. This project will address these concerns by focusing on mechanistic reasoning in an agent-based modeling environment appropriate for 6th grade mathematics and science classes. Mechanistic reasoning involves creating entities and understanding interactions that produce an end state or change of state and explain how and why something works or generates a phenomenon. The research component of the project will fill a gap in computational thinking (CT) integration literature by investigating how programing solutions to mathematical problems can simultaneously reinforce mathematical concepts and prepare students for scientific modeling. Furthermore, the project will: support the participation of underrepresented groups in mathematics, computer science, and scientific modeling; contribute to breaking down of siloed disciplines within middle school; enhance infrastructure for research and education through the co-design of multidisciplinary curriculum spanning math and science classrooms; and develop a curriculum that prepares students for future endeavors in STEM and CT.The project will develop and implement a multidisciplinary CT program that uses computer modeling activities to form a bridge that connects regular school day mathematics and science learning. Sixth grade students and their teachers in three districts will learn to use CT and mechanistic reasoning in mathematics classes and then apply those skills in decoding and modifying scientific models in science classes. The research objectives of the project are as follows: (1) Conduct design-based research cycles to develop a math and science CT curriculum for 6th grade students; (2) Develop, test and refine a year-long teacher professional development program that supports teacher learning and implementation of the integrated curriculum; and (3) Conduct a mixed-methods study on the impact of the integrated curriculum on student learning, teacher and student perception of math and CT, and the role of mechanistic reasoning in CT. The project will employ a design collaborative between teachers and the project team, which will provide support for the workshops, teacher professional development, and the development of a teacher facilitation model. A quasi-experimental study and case studies will be used to test the hypothesis that mechanistic reasoning is a necessary skill that enables students to link abstraction and automation when they create computational artifacts and engage in analysis when they decode computational models.The project is funded by the STEM + Computing Program, which seeks to study the applied integration of computational thinking and computing within disciplinary STEM teaching and learning in early childhood education through high school.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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Mechanism for the selection of undamaged physiological substrates by the ATP-dependent protease Lon
  • 批准号:
    2210869
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2022
  • 负责人:
    Irene Lee
  • 依托单位:
Everyday AI for Youth: Investigating Middle School Teacher Education, Classroom Implementation, and the Associated Student Learning Outcomes of an Innovative AI Curriculum
EAGER: Developing AI Literacy Interventions to Teach Fundamental Concepts in AI
Activity Probes to Monitor ATP-Dependent Proteolysis
  • 批准号:
    1507792
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $48.0万
  • 财政年份:
    2015
  • 负责人:
    Irene Lee
  • 依托单位:
国内基金
海外基金
基于P-T-t-D-shear sense轨迹和数值模拟探讨羌塘中部冈玛错-拉雄错地区高压变质岩的折返机制
  • 批准号:
    42172259
  • 项目类别:
    面上项目
  • 资助金额:
    60万元
  • 批准年份:
    2021
  • 负责人:
    李典
  • 依托单位: