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CCLI: Scaling Up Undergraduate Research Experience through Student-led Class-wide Projects in an Introductory Materials Science

CCLI: Scaling Up Undergraduate Research Experience through Student-led Class-wide Projects in an Introductory Materials Science
CCLI:通过学生主导的材料科学导论全班项目扩大本科生研究经验
批准号:
0942298
负责人:
Raymundo Arroyave
金额:
$19.79万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-10-01 至 2015-03-31

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中文摘要
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英文摘要
Engineering - Materials Science (57)This project is modifying a sophomore level introductory materials science course to enable every student in the class to benefit from a one-semester undergraduate research experience. The key premise of the project is that by using modern pedagogies and team-based research projects a scalable and sustainable model can be developed for universal undergraduate research experiences that does not require one-on-one mentoring. By implementing this approach during the sophomore year, the project also seeks to improve engineering student retention. The specific objectives of the course reform are to (1) to improve the learning process in an introductory materials science course by emphasizing active learning pedagogies, (2) to allow the development of scientific reasoning skills and to provide students with direct experience in the scientific process, and (3) to increase the interest of sophomore undergraduate students in science/engineering and materials science. The project includes rigorous formative and summative evaluation plans with both qualitative and quantitative components coordinated by an independent evaluator. The evaluation plan includes an advisory board consisting of representatives from seven institutions that are interested in adopting the revised course materials and pedagogical approach. The project's results are being disseminated through conferences and journal publications and through professional societies.
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DMREF: Optimizing Problem formulation for prinTable refractory alloys via Integrated MAterials and processing co-design (OPTIMA)
DMREF: AI-Guided Accelerated Discovery of Multi-Principal Element Multi-Functional Alloys
CDS&E: Efficient Uncertainty Analysis in Multi-physics Phase Field Models of Microstructure Evolution
Probing Microstructure-Martensitic Transformation Couplings in Metamagnetic Shape Memory Alloys
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