Collaborative Research: Encoding Geography - Scaling up an RPP to achieve inclusive geocomputational education

合作研究：编码地理 - 扩大 RPP 以实现包容性地理计算教育

• 批准号: 2031418
• 负责人: Coline Dony
• 金额: $ 40.09万
• 依托单位: Association of American Geographers
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2031418&HistoricalAwards=false
• 关键词: Collaborative; Research; Encoding; Geography; Scaling

The geospatial services industry is a profitable and rapidly growing field; however, employers find it difficult to hire scientists with expertise in both geography and computer science. The limited availability of training opportunities in both computer science and geography has created a shortage of workers with the necessary knowledge and skill sets for those jobs. Through a Researcher-Practitioner Partnership (RPP), The Association of American Geographers (AAG), in collaboration with Texas State University, the University of California-Riverside, San Diego State University, the California Geographic Alliance, Sweetwater Union High School District, and San Diego Mesa College, will create an inclusive high school to college curriculum pathway that bridges concepts in computer science and geography. This RPP will support the development of a curriculum that is conceptually rigorous, inclusive, and culturally relevant. It will also produce a replicable approach for teaching geocomputation that is accessible and motivational for all learners.The Association of American Geographers (AAG), in collaboration with Texas State University, the University of California-Riverside, San Diego State University, the California Geographic Alliance, Sweetwater Union High School District, and San Diego Mesa College, proposes a CSforALL-PreK-14 Pathways Strand project to scale up its Encoding Geography Researcher-Practitioner Partnership (RPP) activities in California. This RPP will pursue research and development activities supporting an inclusive curriculum pathway toward geocomputationally intensive majors and careers. The first year of the project will focus on baseline data collection. In year two, AAG will convene a workshop with RPP members to produce culturally relevant geocomputational lessons and being to implement those lesson in CS and geography courses in high school and college. In the final year, the RPP will revise the lessons for ongoing implementation. The AAG will also implement a dissemination plan to scale up the RPP across California and to other states. An expert committee will provide a formative and summative evaluation of the project. This RPP will produce a replicable methodology for articulating curriculum pathways in geocomputation that are inclusive, accessible, and motivational for all learners. By involving the very stakeholders with whom the curriculum is concerned, systemic change toward a more diverse workforce in geocomputation is more likely to be achieved.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.

地理空间服务行业是一个利润丰厚且增长迅速的领域；然而，雇主发现很难聘请到同时具备地理和计算机科学专业知识的科学家。计算机科学和地理学方面的培训机会有限，导致缺乏具备这些工作所需知识和技能的工人。通过研究人员与实践者合作伙伴关系 (RPP)，美国地理学家协会 (AAG) 与德克萨斯州立大学、加州大学河滨分校、圣地亚哥州立大学、加州地理联盟、斯威特沃特联合高中区和圣地亚哥梅萨学院将创建一个包容性的高中到大学课程路径，连接计算机科学和地理学的概念。该 RPP 将支持概念严谨、包容且文化相关的课程开发。 它还将产生一种可复制的地理计算教学方法，对所有学习者来说都是易于理解和激励的。美国地理学家协会 (AAG) 与德克萨斯州立大学、加州大学河滨分校、圣地亚哥州立大学、加州地理学院合作联盟、斯威特沃特联合高中学区和圣地亚哥梅萨学院提出了一个 CSforALL-PreK-14 Pathways Strand 项目，以扩大其在以下地区的编码地理学研究人员-从业者合作伙伴关系 (RPP) 活动：加利福尼亚州。该 RPP 将开展研究和开发活动，支持通向地理计算密集型专业和职业的包容性课程途径。该项目的第一年将重点关注基线数据收集。 第二年，AAG 将与 RPP 成员召开研讨会，制作与文化相关的地理计算课程，并在高中和大学的计算机科学和地理课程中实施这些课程。在最后一年，RPP 将修订持续实施的经验教训。 AAG 还将实施一项传播计划，以将 RPP 扩大到整个加州和其他州。专家委员会将对项目进行形成性和总结性评估。该 RPP 将产生一种可复制的方法，用于阐明地理计算的课程路径，对所有学习者都具有包容性、可访问性和激励性。通过让与课程相关的利益相关者参与进来，更有可能实现地理计算领域更加多元化的系统性变革。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优势和更广泛的评估进行评估，被认为值得支持。影响审查标准。

项目成果

Big Code

大码

• DOI: 10.1111/gean.12330
• 发表时间: 2022
• 期刊: Geographical Analysis
• 影响因子: 3.6
• 作者: Rey, Sergio J.

Solving Geospatial Problems under Extreme Time Constraints: A Call for Inclusive Geocomputational Education

在极端时间限制下解决地理空间问题：呼吁包容性地理计算教育

• 发表时间: 2023
• 期刊: Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE
• 作者: Dony, Coline C

Geographical Python Teaching Resources: geopyter

• DOI: 10.1007/s10109-021-00346-6
• 发表时间: 2021-04-23
• 期刊: JOURNAL OF GEOGRAPHICAL SYSTEMS
• 影响因子: 2.9
• 作者: Reades, Jonathan;Rey, Sergio J.
• 通讯作者: Rey, Sergio J.

Scalable Spatio-Temporal Top-k Community Interactions Query

可扩展的时空Top-k社区互动查询

• DOI: 10.1145/3474717.3483962
• 发表时间: 2021
• 期刊: 29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2021
• 作者: Abdulaziz Almaslukh, Yongyi Liu