Evidence-Based Materials for Teaching Quantum Information Science and Technology
Evidence-Based Materials for Teaching Quantum Information Science and Technology
批准号:
2235464
负责人:
Beth Thacker
金额:
$29.94万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-10-01 至 2026-09-30
中文摘要
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英文摘要
This project aims to serve the national interest by developing evidence-based curricular materials for use in courses in Quantum Information Science and Technology (QIST), which is a growing, interdisciplinary field. Recent growth in QIST in the government and commercial sectors is creating jobs for quantum computer scientists, and this workforce demand is challenging universities to build interdisciplinary pathways to undergraduate degrees in QIST. Responding to this challenge, the investigators will explore students' strengths and difficulties with key QIST concepts and will develop a set of evidence-based (research-based) materials to be used in introductory undergraduate QIST courses.This project involves an interdisciplinary team of researchers and educators in QIST across physics, engineering, computer science, and science education at an "R1" (Very High Research Activity) university that is also a Hispanic Serving Institution. The project's main objectives are (1) to understand students' strengths and difficulties in learning QIST topics, (2) to develop a set of pre- and post-tests to assess students' conceptual understanding and reasoning skills in QIST, and (3) to develop a set of materials (mini-tutorials) to be used in introductory courses in QIST at the junior/senior level. The investigators will make the pre- and post-tests and mini-tutorials available to faculty across the nation through websites and workshops. Faculty will be able to use these materials in QIST courses and programs that are being developed to help expand the QIST workforce. The NSF IUSE: EDU program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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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