Meshal Albeedan;Hoshang Kolivand;Ramy Hammady;Tanzila Saba
{"title":"用于调查培训的混合现实中的无缝犯罪现场重建:设计与评估研究","authors":"Meshal Albeedan;Hoshang Kolivand;Ramy Hammady;Tanzila Saba","doi":"10.1109/TLT.2023.3337107","DOIUrl":null,"url":null,"abstract":"Investigation training at the real crime scene is a critical component of forensic science education. However, bringing young investigators to real crime scenes is costly and faces significant challenges. Mixed reality (MR) is one of the most evolving technologies that provides unlimited possibilities for practical activities in the education sector. This article aims to propose and evaluate a novel design of an MR system using Microsoft HoloLens 2.0 that is tailored to work in a spatial 3-D-scanned and reconstructed crime scene. The system was designed to be a cost-effective experience that helps young Kuwaiti police officers enhance their investigation skills. The proposed system has been evaluated through system usability, user interaction, and performance metrics quantitatively via 44 young police officers and qualitatively using the think-aloud protocols via a group of experts. Both groups showed positive levels of usability, user interaction, and overall satisfaction, with minimal negative feedback. Based on the positive feedback, the system will be taken into the commercialization stage in the future. Despite the high cost of the MR device, experts stated that the system is needed as an essential tool for crime scene education and investigation practices.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"856-873"},"PeriodicalIF":2.9000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seamless Crime Scene Reconstruction in Mixed Reality for Investigation Training: A Design and Evaluation Study\",\"authors\":\"Meshal Albeedan;Hoshang Kolivand;Ramy Hammady;Tanzila Saba\",\"doi\":\"10.1109/TLT.2023.3337107\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Investigation training at the real crime scene is a critical component of forensic science education. However, bringing young investigators to real crime scenes is costly and faces significant challenges. Mixed reality (MR) is one of the most evolving technologies that provides unlimited possibilities for practical activities in the education sector. This article aims to propose and evaluate a novel design of an MR system using Microsoft HoloLens 2.0 that is tailored to work in a spatial 3-D-scanned and reconstructed crime scene. The system was designed to be a cost-effective experience that helps young Kuwaiti police officers enhance their investigation skills. The proposed system has been evaluated through system usability, user interaction, and performance metrics quantitatively via 44 young police officers and qualitatively using the think-aloud protocols via a group of experts. Both groups showed positive levels of usability, user interaction, and overall satisfaction, with minimal negative feedback. Based on the positive feedback, the system will be taken into the commercialization stage in the future. Despite the high cost of the MR device, experts stated that the system is needed as an essential tool for crime scene education and investigation practices.\",\"PeriodicalId\":49191,\"journal\":{\"name\":\"IEEE Transactions on Learning Technologies\",\"volume\":\"17 \",\"pages\":\"856-873\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2023-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Learning Technologies\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10329468/\",\"RegionNum\":3,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Learning Technologies","FirstCategoryId":"95","ListUrlMain":"https://ieeexplore.ieee.org/document/10329468/","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Seamless Crime Scene Reconstruction in Mixed Reality for Investigation Training: A Design and Evaluation Study
Investigation training at the real crime scene is a critical component of forensic science education. However, bringing young investigators to real crime scenes is costly and faces significant challenges. Mixed reality (MR) is one of the most evolving technologies that provides unlimited possibilities for practical activities in the education sector. This article aims to propose and evaluate a novel design of an MR system using Microsoft HoloLens 2.0 that is tailored to work in a spatial 3-D-scanned and reconstructed crime scene. The system was designed to be a cost-effective experience that helps young Kuwaiti police officers enhance their investigation skills. The proposed system has been evaluated through system usability, user interaction, and performance metrics quantitatively via 44 young police officers and qualitatively using the think-aloud protocols via a group of experts. Both groups showed positive levels of usability, user interaction, and overall satisfaction, with minimal negative feedback. Based on the positive feedback, the system will be taken into the commercialization stage in the future. Despite the high cost of the MR device, experts stated that the system is needed as an essential tool for crime scene education and investigation practices.
期刊介绍:
The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.