HSI Planning Project: Designing an Online and Integrative Interdisciplinary Data Science Community College Curriculum and Pathway

在NSF 20-599改善本科STEM教育- HSI轨道1规划和试点项目资助的支持下，西新墨西哥大学（WNMU）和西部州长大学（WGU）将合作设计和开发跨学科，在线，两年制科学副学士数据科学课程，学位计划和途径，适用于HSI社区学院和大学学习者，以及即将入学的双录取，高中，社区学院。以及非传统的学习者。社区大学在西班牙裔学生入学中发挥着巨大的作用，但大多数两年制大学不提供数据科学途径，2017年，社区大学提供的大约600个数据科学项目中只有15个，而四年制大学提供的数据科学项目只有15个。拥有HSI称号的社区大学提供的数据科学学位甚至更少。该合作规划项目将满足学生对空间和制度情境化数据科学两年在线课程和一套嵌套的特定学科证书的需求。通过一套针对HSI社区大学学习者的在线数据科学入门学习模块原型，该项目将分析HSI社区大学学习者在自我效能感、归属感和身份认同等关键学习者领域的认知和社会需求。WGU将提供所需的教学设计师和学习者支持结构，以设计和测试一个集成的、引人入胜的在线学习体验，并为不同的学习者提供有效的支持。WNMU将在数据科学和教育方面提供当地的专业知识，并为学生和家庭参与课程和支持结构的开发提供框架。应用基于设计的研究（DBR）框架，该项目将提供一组HSI和社区学院研究人员所需的数据点，以评估典型社区学院STEM数据科学学位课程成功的关键决定因素，该课程专为早期学习者和非工作专业人员设计。提议的参与式设计过程将联合西蒙大洋洲大学和西蒙大洋洲大学的教师专家、学生和项目工作人员，以及行业合作伙伴的审核员，共同创建一个可以在西蒙大洋洲大学实施的数据科学课程。数据科学课程将为大学提供一套可共享的在线和混合教学资源，作为模板，在真实的机构专家领域和背景下定制数据科学课程，无论是在医疗保健、交通运输、商业、教育、社会科学还是其他学科。这些结果将成为其他典型的、处于劣势的两年制和四年制大学以及各地已经提供标准数学和统计学课程的hsi的路线图。HSI计划旨在加强本科STEM教育，扩大STEM参与，并在HSI进行能力建设。考虑到hsi的多样性和背景，实现这些目标需要创新的方法来激励机构和社区转型，并促进基础研究(1)关于参与式学生学习，(2)关于如何有效地使STEM多样化和增加参与，以及(3)提高我们对如何在hsi建立机构能力的理解。HSI计划支持的项目也将借鉴这些方法，为如何实现这些目标提供新的知识。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the NSF 20-599 Improving Undergraduate STEM Education - HSI Track 1 Planning and Pilot Program grant, Western New Mexico University (WNMU) and Western Governors University (WGU) will collaborate on the design and development of an interdisciplinary, online, two-year Associate of Science Data Science curriculum, degree plan, and pathway for HSI community college and university learners and for incoming dual enrollment, high school, community college, and non-traditional learners. Community colleges play an outsized role in Hispanic student enrollments and yet most two-year colleges do not offer data science pathways with only 15 of circa 600 data science programs in 2017 offered by community colleges versus four-year colleges. Even fewer data science degrees are offered at community colleges with the HSI designation. This collaborative planning project will address students’ needs for a spatially and institutionally contextualized data science two-year online curriculum and set of nested, discipline-specific certificates. Through a prototype set of online data science introductory learning modules targeting HSI community college learners, the project will analyze the cognitive and social needs of HSI community college learners in the critical learner domains of self-efficacy, sense of belonging, and identity. WGU will offer the required instructional designers and learner support structures to design and test an integrated and engaging online learning experience, and effective support for diverse learners. WNMU will provide the local subject matter expertise in data science and education, and a framework for student and family participation in the development of the curriculum and support structures. Applying a Design-Based Research (DBR) framework, this project will render a set of data points needed by HSI and community college researchers toward assessing the constellation of critical determinants of success for a typical community college STEM data science degree program designed specifically for early learners and non-working professionals. The participatory design process proposed will join WNMU and WGU faculty experts, students, and program staff together with industry partner reviewers toward creating a data science curriculum that can be implemented at WNMU. The data science curriculum will offer colleges a set of shareable online and hybrid instructional resources that serve as a template to customize a data science curriculum within an authentic institutional expert domain and context, whether in healthcare, transportation, business, education, social sciences, or other disciplines. These outcomes will serve as a roadmap for other typical, disadvantaged two- and four-year colleges and HSIs everywhere that already offer standard math and statistics courses. The HSI Program aims to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs. Achieving these aims, given the diverse nature and context of the HSIs, requires innovative approaches that incentivize institutional and community transformation and promote fundamental research (i) on engaged student learning, (ii) about what it takes to diversify and increase participation in STEM effectively, and (iii) that improves our understanding of how to build institutional capacity at HSIs. Projects supported by the HSI Program will also draw from these approaches to generate new knowledge on how to achieve these aims.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.