Cognitive load assessment in learning construction sensor data analytics within an end user programming environment

  • Mohammad Khalid
  • , Abiola A. Akanmu
  • , Anthony O. Yusuf
  • , Homero Murzi
  • , Ibukun Awolusi
  • , Nihar Gonsalves

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Computational thinking-supported educational training can equip the construction workforce with the necessary skills and knowledge to implement sensing technologies and perform sensor data analytics aimed at enhancing construction operations. However, construction students struggle to understand the computational concepts and workflows required to translate low-level sensor data into knowledge for supporting decisions. This study compared the cognitive load of construction students performing similar data analytics tasks using an end-user programming environment (EUP) to conventional MS Excel. Comparative analysis using descriptive and inferential statistics demonstrated that participants using EUP perceived lower levels of cognitive loads and more positive experiences than those who used the conventional techniques. The study's findings will advance the understanding of the potential cognitive effects of adopting EUPs for construction sensor data analytics. This study contributes to the cognitive theory of multimedia learning by illustrating how multimodal programming environments can influence learners' cognitive demands.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2023
Subtitle of host publicationData, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023
EditorsYelda Turkan, Joseph Louis, Fernanda Leite, Semiha Ergan
PublisherAmerican Society of Civil Engineers (ASCE)
Pages167-175
Number of pages9
ISBN (Electronic)9780784485224
DOIs
StatePublished - 2024
Externally publishedYes
EventASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, i3CE 2023 - Corvallis, United States
Duration: Jun 25 2023Jun 28 2023

Publication series

NameComputing in Civil Engineering 2023: Data, Sensing, and Analytics - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023

Conference

ConferenceASCE International Conference on Computing in Civil Engineering 2023: Data, Sensing, and Analytics, i3CE 2023
Country/TerritoryUnited States
CityCorvallis
Period6/25/236/28/23

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Civil and Structural Engineering

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