Collaborative Research: Improving Students’ Computational Thinking Skills in Construction Engineering and Management

协作研究:提高学生在建筑工程和管理方面的计算思维能力

基本信息

项目摘要

This project aims to serve the national interest by creating a tool to help students learn computational thinking skills in construction engineering and management courses. The project focuses on active learning experiences in which students learn how to extract meaningful information from large datasets and use the results to make informed engineering decisions. These experiences can help better prepare students to address construction industry needs, such as increasing productivity, reducing waste, and improving worker safety. The use of sensors on construction sites is a growing trend because they provide real-time data showing what is happening on a site. Students need to develop skills in data analytics and computational thinking so that they can process sensor data, perform data analyses, and develop an understanding of construction site operations. To accomplish these aims, the project team will develop a web application that provides students with a graphical interface to select, analyze, and display sensor data. Students will be able to explore a construction site in real-time to understand behaviors and relationships between objects on a site and how they relate to construction project safety and productivity. The web application software will be made available to the engineering education community through public software repositories. By addressing the computational skills gap in the construction industry, this project will benefit construction workers and the economic competitiveness of construction companies.The goal of this project is to improve students’ computational thinking skills by engaging students in real world problems on construction sites. It will do so by developing a web application that provides interactive programmable objects for students to perform computational functions in the context of construction engineering. The application will help students analyze sensor data and improve their understanding of important computational concepts for engineering problem solving. Students will learn about sensor data collected from construction sites, computational approaches for data analyses, and making sense of low-level sensor data to support decision making. The application will be developed for web browsers and will include a Python package that contains custom objects (e.g., vehicles, workers) and a library of computational functions. A mixed-method research study will be conducted to answer research questions that address (1) competencies in data analytics that are needed in the construction industry, (2) the elements of the web application that are needed to help students develop the competencies, and (3) the impact of the web application on students’ computational thinking. A nationwide survey of construction engineering and management professionals will be conducted to identify skills that are needed for working with construction site sensing systems and to determine the value of and demand for these skills in the construction industry. The project will introduce high school students to computational thinking in the construction industry through an existing outreach activity that involves a construction project. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the 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.
该项目旨在通过创建一个工具来帮助学生在建筑工程和管理课程中学习计算思维技能,从而为国家利益服务。该项目侧重于主动学习体验,让学生学习如何从大型数据集中提取有意义的信息,并利用结果做出明智的工程决策。这些经验可以帮助学生更好地应对建筑行业的需求,如提高生产力、减少浪费和改善工人安全。在建筑工地使用传感器是一种日益增长的趋势,因为它们可以提供实时数据,显示工地上正在发生的事情。学生需要培养数据分析和计算思维的技能,这样他们就可以处理传感器数据,进行数据分析,并了解建筑工地的操作。为了实现这些目标,项目团队将开发一个web应用程序,为学生提供一个图形界面来选择、分析和显示传感器数据。学生将能够实时探索建筑工地,了解工地上物体之间的行为和关系,以及它们与建筑项目安全和生产力的关系。网络应用软件将通过公共软件库提供给工程教育界。通过解决建筑行业的计算技能差距,该项目将有利于建筑工人和建筑公司的经济竞争力。这个项目的目标是通过让学生参与到建筑工地的实际问题中来提高学生的计算思维能力。它将通过开发一个web应用程序来实现这一目标,该应用程序为学生提供交互式可编程对象,以便在建筑工程环境中执行计算功能。该应用程序将帮助学生分析传感器数据,并提高他们对解决工程问题的重要计算概念的理解。学生将学习从建筑工地收集的传感器数据,数据分析的计算方法,以及理解低层传感器数据以支持决策。该应用程序将为web浏览器开发,并将包括一个包含自定义对象(例如,车辆,工人)和计算函数库的Python包。将进行一项混合方法研究,以回答以下研究问题:(1)建筑行业所需的数据分析能力,(2)帮助学生培养能力所需的web应用程序元素,以及(3)web应用程序对学生计算思维的影响。将在全国范围内对建筑工程和管理专业人员进行调查,以确定使用建筑工地传感系统所需的技能,并确定建筑行业对这些技能的价值和需求。该项目将通过现有的一个涉及建筑项目的外展活动,向高中生介绍建筑行业的计算思维。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。通过参与学生学习轨道,该计划支持有前途的实践和工具的创建,探索和实施。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。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Data Analytics and Computational Thinking Skills in Construction Engineering and Management Education: A Conceptual System
建筑工程与管理教育中的数据分析和计算思维技能:概念系统
  • DOI:
    10.1061/9780784483985.021
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Akanmu, Abiola A.;Akligo, Vincent S.;Ogunseiju, Omobolanle R.;Lee, Sang Won;Murzi, Homero
  • 通讯作者:
    Murzi, Homero
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Abiola Akanmu其他文献

Industry perception of competencies for human—robot collaboration in the construction industry: A Delphi study
  • DOI:
    10.1007/s42524-025-4224-x
  • 发表时间:
    2025-06-05
  • 期刊:
  • 影响因子:
    7.700
  • 作者:
    Ebenezer Olukanni;Abiola Akanmu;Houtan Jebelli
  • 通讯作者:
    Houtan Jebelli
Psychophysiological impacts of working with powered exoskeletons on construction sites
在建筑工地使用动力外骨骼的心理生理影响
  • DOI:
    10.1016/j.autcon.2025.106312
  • 发表时间:
    2025-09-01
  • 期刊:
  • 影响因子:
    11.500
  • 作者:
    Amit Ojha;Shayan Shayesteh;Yizhi Liu;Houtan Jebelli;Abiola Akanmu
  • 通讯作者:
    Abiola Akanmu
Assessment of active back-support exoskeleton on carpentry framing tasks: Muscle activity, range of motion, discomfort, and exertion
木工框架作业中主动式背部支撑外骨骼的评估:肌肉活动、活动范围、不适和用力程度
  • DOI:
    10.1016/j.ergon.2025.103716
  • 发表时间:
    2025-05-01
  • 期刊:
  • 影响因子:
    3.000
  • 作者:
    Akinwale Okunola;Abiola Akanmu;Houtan Jebelli;Adedeji Afolabi
  • 通讯作者:
    Adedeji Afolabi
Understanding the drivers of and barriers to adopting passive back- and arm-support exoskeletons in construction: Results from interviews and short-term field testing
了解建筑行业采用被动式背部及手臂支撑外骨骼的驱动因素和障碍:访谈及短期现场测试的结果
  • DOI:
    10.1016/j.ergon.2025.103732
  • 发表时间:
    2025-05-01
  • 期刊:
  • 影响因子:
    3.000
  • 作者:
    Mohamad Behjati Ashtiani;Wallace Morris;Aanuoluwapo Ojelade;Sunwook Kim;Feyisayo Akinwande;Alan Barr;Carisa Harris-Adamson;Abiola Akanmu;Maury A. Nussbaum
  • 通讯作者:
    Maury A. Nussbaum

Abiola Akanmu的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Abiola Akanmu', 18)}}的其他基金

Collaborative Research: Embodied Interactive Environment for Advancing Data Sensing and Computational Thinking Skills in the Built Environment
协作研究:在建筑环境中提升数据感知和计算思维技能的具体交互环境
  • 批准号:
    2241786
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Investigating the Impact of an Immersive VR-based Learning Environment for Learning Human-Robot Collaboration in Construction Robotics Education
研究基于 VR 的沉浸式学习环境对建筑机器人教育中人机协作学习的影响
  • 批准号:
    2235375
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: NRI: Understanding Underlying Risks and Sociotechnical Challenges of Powered Wearable Exoskeleton to Construction Workers
合作研究:NRI:了解建筑工人动力可穿戴外骨骼的潜在风险和社会技术挑战
  • 批准号:
    2221166
  • 财政年份:
    2022
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: Connecting Professional and Educational Communities to Prepare Construction Engineering Students for the Workplace
合作研究:连接专业和教育社区,为建筑工程专业的学生做好进入工作场所的准备
  • 批准号:
    2201641
  • 财政年份:
    2022
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Continuing Grant
Impact of Interactive Holographic Scenes in Developing Engineering Students' Competencies in Sensing Technologies
交互式全息场景对培养工程学生传感技术能力的影响
  • 批准号:
    1916521
  • 财政年份:
    2019
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Improving Upper Division Physics Education and Strengthening Student Research Opportunities at 14 HSIs in California
合作研究:改善加州 14 所 HSI 的高年级物理教育并加强学生研究机会
  • 批准号:
    2345092
  • 财政年份:
    2024
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: Improving Upper Division Physics Education and Strengthening Student Research Opportunities at 14 HSIs in California
合作研究:改善加州 14 所 HSI 的高年级物理教育并加强学生研究机会
  • 批准号:
    2345093
  • 财政年份:
    2024
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
SBP: Collaborative Research: Improving Engagement with Professional Development Programs by Attending to Teachers' Psychosocial Experiences
SBP:协作研究:通过关注教师的社会心理体验来提高对专业发展计划的参与度
  • 批准号:
    2314254
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: Improving Worker Safety by Understanding Risk Compensation as a Latent Precursor of At-risk Decisions
合作研究:通过了解风险补偿作为风险决策的潜在前兆来提高工人安全
  • 批准号:
    2326937
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Continuing Grant
Collaborative Research: Improving Model Representations of Antarctic Ice-shelf Instability and Break-up due to Surface Meltwater Processes
合作研究:改进地表融水过程导致的南极冰架不稳定和破裂的模型表示
  • 批准号:
    2213704
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: SaTC: CORE: Small: Measuring, Validating and Improving upon App-Based Privacy Nutrition Labels
合作研究:SaTC:核心:小型:测量、验证和改进基于应用程序的隐私营养标签
  • 批准号:
    2247952
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: Reducing Model Uncertainty by Improving Understanding of Pacific Meridional Climate Structure during Past Warm Intervals
合作研究:通过提高对过去温暖时期太平洋经向气候结构的理解来降低模型不确定性
  • 批准号:
    2303568
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Continuing Grant
Collaborative Research: SitS: Improving Rice Cultivation by Observing Dynamic Soil Chemical Processes from Grain to Landscape Scales
合作研究:SitS:通过观察从谷物到景观尺度的动态土壤化学过程来改善水稻种植
  • 批准号:
    2226647
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: SitS: Improving Rice Cultivation by Observing Dynamic Soil Chemical Processes from Grain to Landscape Scales
合作研究:SitS:通过观察从谷物到景观尺度的动态土壤化学过程来改善水稻种植
  • 批准号:
    2226648
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
Collaborative Research: SCH: Improving Older Adults' Mobility and Gait Ability in Real-World Ambulation with a Smart Robotic Ankle-Foot Orthosis
合作研究:SCH:使用智能机器人踝足矫形器提高老年人在现实世界中的活动能力和步态能力
  • 批准号:
    2306660
  • 财政年份:
    2023
  • 资助金额:
    $ 47.73万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了