Data Analytics and Computational Thinking Skills in Construction Engineering and Management Education: A Conceptual System
Data Analytics and Computational Thinking Skills in Construction Engineering and Management Education: A Conceptual System
复制标题
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
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Murzi, Homero
中科院分区：
文献类型：
--
作者：
Akanmu, Abiola A.;Akligo, Vincent S.;Ogunseiju, Omobolanle R.;Lee, Sang Won;Murzi, Homero
数据分析和计算思维对于处理和分析来自传感器的数据以及以适合决策的格式呈现结果至关重要。然而，大多数建筑工程和管理本科生由于缺乏理论基础而难以理解所需的计算概念和工作流程。这导致缺乏具备利用传感器数据开发可持续解决方案所需能力的熟练劳动力。最终用户编程环境为学生提供了一种通过采用可视化编程机制来执行复杂分析的方法。通过最终用户编程，学生可以轻松地提出问题、逻辑组织、分析传感器数据、通过抽象表示数据并使结果适应各种问题。本文提出了一个基于最终用户编程并以学用理论为基础的概念系统，该系统可以使建筑工程和管理专业的学生具备在建筑行业实施传感器数据分析所需的能力。该系统允许学生通过直接与数据和对象交互来指定算法，以分析传感器数据并生成信息以支持建设项目的决策。提出了一个设想的场景，以展示该系统在提高学生数据分析和计算思维技能方面的潜力。该研究有助于补充计算思维和数据分析范式在建筑工程教育中应用的现有知识。
Data analytics and computational thinking are essential for processing and analyzing data from sensors, and presenting the results in formats suitable for decision-making. However, most undergraduate construction engineering and management students struggle with understanding the required computational concepts and workflows because they lack the theoretical foundations. This has resulted in a shortage of skilled workforce equipped with the required competencies for developing sustainable solutions with sensor data. End-user programming environments present students with a means to execute complex analysis by employing visual programming mechanics. With end-user programming, students can easily formulate problems, logically organize, analyze sensor data, represent data through abstractions, and adapt the results to a wide variety of problems. This paper presents a conceptual system based on end-user programming and grounded in the Learning-for-Use theory which can equip construction engineering and management students with the competencies needed to implement sensor data analytics in the construction industry. The system allows students to specify algorithms by directly interacting with data and objects to analyze sensor data and generate information to support decision-making in construction projects. An envisioned scenario is presented to demonstrate the potential of the system in advancing students’ data analytics and computational thinking skills. The study contributes to existing knowledge in the application of computational thinking and data analytics paradigms in construction engineering education.
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