Santiago Criollo-C, Andrea Guerrero-Arias, Javier Guaña-Moya, Soha Rawas, Agariadne Dwinggo Samala, Sergio Luján-Mora
{"title":"Build_PC: Mobile Augmented Reality for Supporting PC Hardware Learning With Low Mental Workload","authors":"Santiago Criollo-C, Andrea Guerrero-Arias, Javier Guaña-Moya, Soha Rawas, Agariadne Dwinggo Samala, Sergio Luján-Mora","doi":"10.1155/hbe2/3687910","DOIUrl":null,"url":null,"abstract":"<p>The use of emerging technologies such as mobile augmented reality (MAR) in education has gained relevance, especially in technical areas such as PC hardware learning. However, a persistent problem is the cognitive load that these applications may impose on students, which could affect learning effectiveness and acceptance. This issue is crucial, as a high mental workload can lead to disengagement and lower knowledge retention. Previous studies have explored technological solutions for education but in many cases failed to optimize cognitive load or generate a satisfactory learning environment. This study proposes a MAR application called Build_PC, designed for hands-on teaching of PC hardware. The NASA-TLX tool was used to evaluate the mental workload in 60 students, analyzing dimensions such as mental, physical, temporal, performance, effort, and frustration level. The results show a low mental workload among students, suggesting that Build_PC achieves a balance between task complexity and interface usability. These findings have significant implications: The use of Build_PC in education enables effective, autonomous learning in a technologically advanced environment without imposing excessive mental workload. This supports MAR’s potential as an effective and sustainable learning tool, particularly in contexts where access to physical laboratories is limited.</p>","PeriodicalId":36408,"journal":{"name":"Human Behavior and Emerging Technologies","volume":"2026 1","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/hbe2/3687910","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Behavior and Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/hbe2/3687910","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The use of emerging technologies such as mobile augmented reality (MAR) in education has gained relevance, especially in technical areas such as PC hardware learning. However, a persistent problem is the cognitive load that these applications may impose on students, which could affect learning effectiveness and acceptance. This issue is crucial, as a high mental workload can lead to disengagement and lower knowledge retention. Previous studies have explored technological solutions for education but in many cases failed to optimize cognitive load or generate a satisfactory learning environment. This study proposes a MAR application called Build_PC, designed for hands-on teaching of PC hardware. The NASA-TLX tool was used to evaluate the mental workload in 60 students, analyzing dimensions such as mental, physical, temporal, performance, effort, and frustration level. The results show a low mental workload among students, suggesting that Build_PC achieves a balance between task complexity and interface usability. These findings have significant implications: The use of Build_PC in education enables effective, autonomous learning in a technologically advanced environment without imposing excessive mental workload. This supports MAR’s potential as an effective and sustainable learning tool, particularly in contexts where access to physical laboratories is limited.
期刊介绍:
Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.