{"title":"评估基于头戴式显示器的装配任务培训转移","authors":"Stefan Werrlich, Phuc-Anh Nguyen, G. Notni","doi":"10.1145/3197768.3201564","DOIUrl":null,"url":null,"abstract":"The automotive industry is growing constantly and more and more assembly workers are needed to negotiate the production volume. The training of new employees is essential to ensure premium quality products and processes. New technologies for training such as head-mounted displays (HMDs) receive a growing amount of attention by the scientific community, especially in the industrial domain. Due to its possibility to work hands-free while providing users with necessary augmented information, HMDs can enhance the quality and efficiency of assembly training tasks. However, comprehensive evaluations in industrial environments regarding the training transfer using augmented reality (AR) technologies are still very limited. In this paper, we aim to close this gap by conducting a user study with two groups and 30 participants, measuring the training transfer. We compare the effects of two slightly different HMD-based training applications. The first group complete a tutorial, beginner, intermediate and expert training level, while the second group received an additional quiz level. Results show that group two needed 17% more time to complete the training but made 79% less sequence mistakes compared to the first group. Additionally, we compare the user satisfaction by using the system usability scale (SUS) and the perceived workload by measuring the NASA-TLX.","PeriodicalId":130190,"journal":{"name":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Evaluating the training transfer of Head-Mounted Display based training for assembly tasks\",\"authors\":\"Stefan Werrlich, Phuc-Anh Nguyen, G. Notni\",\"doi\":\"10.1145/3197768.3201564\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The automotive industry is growing constantly and more and more assembly workers are needed to negotiate the production volume. The training of new employees is essential to ensure premium quality products and processes. New technologies for training such as head-mounted displays (HMDs) receive a growing amount of attention by the scientific community, especially in the industrial domain. Due to its possibility to work hands-free while providing users with necessary augmented information, HMDs can enhance the quality and efficiency of assembly training tasks. However, comprehensive evaluations in industrial environments regarding the training transfer using augmented reality (AR) technologies are still very limited. In this paper, we aim to close this gap by conducting a user study with two groups and 30 participants, measuring the training transfer. We compare the effects of two slightly different HMD-based training applications. The first group complete a tutorial, beginner, intermediate and expert training level, while the second group received an additional quiz level. Results show that group two needed 17% more time to complete the training but made 79% less sequence mistakes compared to the first group. Additionally, we compare the user satisfaction by using the system usability scale (SUS) and the perceived workload by measuring the NASA-TLX.\",\"PeriodicalId\":130190,\"journal\":{\"name\":\"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3197768.3201564\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3197768.3201564","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating the training transfer of Head-Mounted Display based training for assembly tasks
The automotive industry is growing constantly and more and more assembly workers are needed to negotiate the production volume. The training of new employees is essential to ensure premium quality products and processes. New technologies for training such as head-mounted displays (HMDs) receive a growing amount of attention by the scientific community, especially in the industrial domain. Due to its possibility to work hands-free while providing users with necessary augmented information, HMDs can enhance the quality and efficiency of assembly training tasks. However, comprehensive evaluations in industrial environments regarding the training transfer using augmented reality (AR) technologies are still very limited. In this paper, we aim to close this gap by conducting a user study with two groups and 30 participants, measuring the training transfer. We compare the effects of two slightly different HMD-based training applications. The first group complete a tutorial, beginner, intermediate and expert training level, while the second group received an additional quiz level. Results show that group two needed 17% more time to complete the training but made 79% less sequence mistakes compared to the first group. Additionally, we compare the user satisfaction by using the system usability scale (SUS) and the perceived workload by measuring the NASA-TLX.