Examining the Effects of Course Climate, Active Learning, and Intersectional Identities on Undergraduate Student Success in Computing
检查课程气氛、主动学习和交叉身份对本科生计算机成功的影响
基本信息
- 批准号:2111376
- 负责人:
- 金额:$ 35.7万
- 依托单位:
- 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:2021-07-01 至 2024-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project aims to serve the national interest by improving undergraduate student success in computer science courses. To do so, it will study relationships between student success and the course climate and teaching practices of their computer science courses. It will further analyze these relationships for students with intersecting identities, such as women who are first generation college students. Many STEM classrooms feature passive learning approaches and intentionally or unintentionally establish create competitive course climates that inhibit collaboration. Alternative teaching approaches that encourage collaboration and active learning are gaining traction in many undergraduate computing programs. Studies have generally indicated a positive relationship between collaborative active learning and increased student learning outcomes. However, implementation of active learning varies and the results on student learning have been inconsistent. It is possible that the inconsistencies may reflect differential impacts of competitive, passive learning on groups of students with specific intersecting identities. This project aims to explore the relationship between active learning and cooperative course climate on students with intersecting identities, including race, gender, and social class. The knowledge generated by this research has the potential to improve student success in computer science and thus broaden participation of individuals from groups that are not yet equitably represented in computing.This project identifies course structure and sociality as two major components of course climate. Course structure includes features such as the course timeline, expectations for attendance or participation, and how grades are determined. Sociality involves forming and working in supportive communities. The project uses the constructs of course structure and sociality to capture pedagogical components that faculty select and combine in their adoption active learning approaches. Correlations will then be identified between these active learning components and student outcomes, and will be used to explore differential outcomes across intersectional student identities. This knowledge may help instructors select active learning strategies that would lead to more effective student learning, or combine elements of structure and sociality to develop new promising pedagogies in undergraduate computing education. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. This project is in the Engaged Student Learning track, through which the IUSE 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.
该项目旨在通过提高本科生在计算机科学课程中的成功来服务于国家利益。要做到这一点,它将研究学生的成功和他们的计算机科学课程的课程气氛和教学实践之间的关系。 它将进一步分析这些关系的学生与交叉身份,如妇女谁是第一代大学生。 许多STEM教室采用被动学习方法,并有意或无意地建立竞争性课程氛围,抑制合作。 鼓励协作和主动学习的替代教学方法在许多本科计算课程中越来越受欢迎。研究普遍表明,积极合作的学习和提高学生的学习成果之间的积极关系。 然而,主动学习的实施情况各不相同,对学生学习的结果也不一致。这种不一致性可能反映了竞争性的被动学习对具有特定交叉身份的学生群体的不同影响。 本研究旨在探讨具有种族、性别、社会阶层等多重身份认同的学生,其主动学习与合作课程气氛之间的关系。这项研究所产生的知识有可能提高学生在计算机科学的成功,从而扩大个人的参与,从团体尚未公平代表在computing.This项目确定课程结构和社会性作为课程气候的两个主要组成部分。课程结构包括课程时间轴、出勤或参与的期望以及如何确定成绩等功能。 社会性包括在支持性社区中形成和工作。该项目使用的课程结构和社会性的结构,以捕捉教师选择和联合收割机在他们采用主动学习方法的教学成分。然后,这些积极的学习组件和学生的成绩之间的相关性将被确定,并将被用来探索跨交叉学生身份的差异结果。这些知识可以帮助教师选择积极的学习策略,这将导致更有效的学生学习,或联合收割机的结构和社会性的元素,以开发新的有前途的教学在本科计算教育。NSF IUSE:EHR计划支持研究和开发项目,以提高所有学生STEM教育的有效性。该项目是在学生学习的轨道,通过该IUSE计划支持创建,探索和实施有前途的做法和工具。 该奖项反映了NSF的法定使命,并被认为是值得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的支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Mary Lou Maher其他文献
Enabling Investigation of Impacts of Inclusive Collaborative Active Learning Practices on Intersectional Groups of Students in Computing Education
调查包容性协作主动学习实践对计算机教育中交叉学生群体的影响
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Sri Yash Tadimalla;Celine Latulipe;Mary Lou Maher;Marlon Mejias;Jamie Payton;A. Rorrer;John Fiore;G. Kwatny;Andrew Rosen - 通讯作者:
Andrew Rosen
Risks and benefits of mass screening for colorectal neoplasia with the stool guaiac test
通过粪便愈创木脂试验大规模筛查结直肠肿瘤的风险和益处
- DOI:
- 发表时间:
1983 - 期刊:
- 影响因子:0
- 作者:
D. Winchester;Joanne Sylvester;Mary Lou Maher - 通讯作者:
Mary Lou Maher
An Exploratory Study on the Impact of AI tools on the Student Experience in Programming Courses: an Intersectional Analysis Approach
人工智能工具对学生编程课程体验影响的探索性研究:交叉分析方法
- DOI:
10.1109/fie58773.2023.10343037 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Mary Lou Maher;Sri Yash Tadimalla;Dhruv Dhamani - 通讯作者:
Dhruv Dhamani
Implications of Identity in AI: Creators, Creations, and Consequences
人工智能中身份的含义:创造者、创造和后果
- DOI:
10.1609/aaaiss.v3i1.31268 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Sri Yash Tadimalla;Mary Lou Maher - 通讯作者:
Mary Lou Maher
A Grassroots Mammography Demonstration Project Targeted to Medically Underserved Rural and Urban Illinois Women of Diverse Races and Ethnicity
针对医疗服务不足的伊利诺伊州农村和城市不同种族和族裔妇女的草根乳房X光检查示范项目
- DOI:
10.1111/j.1524-4741.1997.tb00137.x - 发表时间:
1997 - 期刊:
- 影响因子:0
- 作者:
Lola Flamm;Arthur G. Michel;H. J. Lasky;Mary Lou Maher;Joanne Sylvester;Stephen F. Sener - 通讯作者:
Stephen F. Sener
Mary Lou Maher的其他文献
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{{ truncateString('Mary Lou Maher', 18)}}的其他基金
Conference: NSF Workshop: Expanding Capacity and Diversity in AI Education
会议:NSF 研讨会:扩大人工智能教育的能力和多样性
- 批准号:
2330257 - 财政年份:2023
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
I-Corps: Digital Platform for Informal Learning Experiences to Encourage Curiosity in STEM Career Paths
I-Corps:提供非正式学习体验的数字平台,鼓励对 STEM 职业道路的好奇心
- 批准号:
2031900 - 财政年份:2020
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
EAGER: An Interactive Learning Analytics Framework based on a Student Sequence Model for understanding students, retention, and time to graduation
EAGER:基于学生序列模型的交互式学习分析框架,用于了解学生、保留率和毕业时间
- 批准号:
1820862 - 财政年份:2018
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
Collaborative Research: Developing a Systemic, Scalable Model to Broaden Participation in Middle School Computer Science
合作研究:开发系统的、可扩展的模型以扩大中学计算机科学的参与
- 批准号:
1837240 - 财政年份:2018
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
RI: Small: CompCog: Pique: A Cognitive Model of Curiosity for Personalizing Sequences of Learning Resources
RI:小:CompCog:Pique:用于个性化学习资源序列的好奇心认知模型
- 批准号:
1618810 - 财政年份:2016
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
IUSE/PFE:RED: The Connected Learner: Design Patterns for Transforming Computing and Informatics Education
IUSE/PFE:RED:互联学习者:变革计算和信息学教育的设计模式
- 批准号:
1519160 - 财政年份:2015
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
AISL: Innovations in Development: Community-Driven Projects That Adapt Technology for Environmental Learning in Nature Preserves
AISL:发展创新:社区驱动的项目,采用自然保护区环境学习技术
- 批准号:
1423212 - 财政年份:2015
- 资助金额:
$ 35.7万 - 项目类别:
Continuing Grant
EAGER: Collaborative Research: A Computational Model for Evaluating the Quality of Citizen Science Contributions
EAGER:协作研究:评估公民科学贡献质量的计算模型
- 批准号:
1451079 - 财政年份:2014
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
VOSS: Crowdsourcing interaction design for citizen science virtual organizations
VOSS:公民科学虚拟组织的众包交互设计
- 批准号:
1221513 - 财政年份:2012
- 资助金额:
$ 35.7万 - 项目类别:
Standard Grant
HCC: Small: Designing Tangible Computing for Creativity
HCC:小型:为创造力设计有形计算
- 批准号:
1218160 - 财政年份:2012
- 资助金额:
$ 35.7万 - 项目类别:
Continuing Grant
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