Developing inclusive, interdisciplinary undergraduate data science curricula in computing and social science

在计算和社会科学领域开发包容性、跨学科的本科数据科学课程

基本信息

  • 批准号:
    2245879
  • 负责人:
  • 金额:
    $ 64.67万
  • 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
  • 起止时间:
    2023-06-01 至 2026-05-31
  • 项目状态:
    未结题

项目摘要

Data science is a rapidly growing field that is having a significant impact on how we live, work, and interact. The goal of this project is to create a cross-cutting data science curriculum at the intersection of computer science and behavioral and social science. This curriculum will provide training in both core computing and programming concepts as well as core quantitative behavioral and social science methods. The curriculum will be designed to be multidisciplinary, culturally relevant, and rigorous. The core proposed course development activity aims to transform computer science education through a collaborative approach to curricular creation that involves faculty from diverse disciplines, diverse institutions, and diverse backgrounds. Tribal colleges, HBCUs, and California Community Colleges, will be invited to curriculum symposia events and supported in adopting these materials.Classroom materials will be designed as a scaffolded collection of instructional lecture videos, computing labs, guided discussions, projects, and concept assessments that can be adopted partly or wholly at institutions across the nation. The open-source curriculum will consist of standalone course modules grounded in modern socio-technical systems and data. Investigators will design and test a hybrid instructional delivery mechanism to ensure broad accessibility to instructors nationwide. Continuous assessment and research will inform investigators on how the project activities will promote further study in interdisciplinary computing education amongst students from traditionally underrepresented communities. The project will identify aspects of the curriculum that build learner confidence in computational thinking and data science and will contribute best practices for inclusive computer science and data science education.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.
数据科学是一个快速发展的领域,对我们的生活、工作和互动方式产生了重大影响。该项目的目标是在计算机科学、行为科学和社会科学的交叉点上创建一个跨领域的数据科学课程。本课程将提供核心计算和编程概念以及核心定量行为和社会科学方法的培训。该课程将被设计为多学科,文化相关,严格。拟议的核心课程开发活动旨在通过协作的课程创建方法来改变计算机科学教育,该方法涉及来自不同学科、不同机构和不同背景的教师。部落学院、HBCUs和加州社区学院将被邀请参加课程研讨会活动,并支持采用这些材料。课堂材料将被设计为教学视频、计算实验室、指导讨论、项目和概念评估的脚手架集合,可以部分或全部在全国各地的机构中采用。开放源码课程将包括以现代社会技术系统和数据为基础的独立课程模块。调查人员将设计和测试一种混合教学交付机制,以确保全国范围内的教师广泛使用。持续的评估和研究将告知调查人员,项目活动将如何促进传统上代表性不足的社区的学生在跨学科计算教育方面的进一步研究。该项目将确定课程的各个方面,建立学习者对计算思维和数据科学的信心,并将为包容性计算机科学和数据科学教育提供最佳实践。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)

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Yasmeen Rawajfih其他文献

Auburn University Robo Camp K12 Inclusive Outreach Program: A three-step model of Effective Introducing Middle School Students to Computer Programming and Robotics
奥本大学机器人营 K12 包容性推广计划:有效向中学生介绍计算机编程和机器人技术的三步模型
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    D. Marghitu;Taha Ben Brahim;John Weaver;Yasmeen Rawajfih
  • 通讯作者:
    Yasmeen Rawajfih

Yasmeen Rawajfih的其他文献

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{{ truncateString('Yasmeen Rawajfih', 18)}}的其他基金

Catalyst Project: Indoor Moving Objects Trajectory Generation and Query Evaluation
Catalyst 项目:室内移动物体轨迹生成和查询评估
  • 批准号:
    2000348
  • 财政年份:
    2020
  • 资助金额:
    $ 64.67万
  • 项目类别:
    Standard Grant

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