Joseph Rozell, J. Stonewall, Samual Vacura, Haylee Lawrence, Jarrett Loseke, Matthew Greiner, Nicholas Wilson, Riley Hogan, Madissen Lawrence, Emily Oldham, Stephen B Gilbert, Benjamin Purdy, Hannah Wellik, Kennedy Cook, A. Jasper, Nick Fetty, Leilani Hammel, Carley Haus, Y. Vardhan, Kaitlyn Ouverson, Rachel E. Dianiska, Colin Johnston, L. Robbins, Elizabeth Belling, Charles J. Peasley, James Oliver, Peggy Wu
{"title":"Circuit World: A Multiplayer VE for Researching Engineering Learning","authors":"Joseph Rozell, J. Stonewall, Samual Vacura, Haylee Lawrence, Jarrett Loseke, Matthew Greiner, Nicholas Wilson, Riley Hogan, Madissen Lawrence, Emily Oldham, Stephen B Gilbert, Benjamin Purdy, Hannah Wellik, Kennedy Cook, A. Jasper, Nick Fetty, Leilani Hammel, Carley Haus, Y. Vardhan, Kaitlyn Ouverson, Rachel E. Dianiska, Colin Johnston, L. Robbins, Elizabeth Belling, Charles J. Peasley, James Oliver, Peggy Wu","doi":"10.1109/VRW52623.2021.00272","DOIUrl":null,"url":null,"abstract":"Business travel leads to the consumption of large amounts of energy. Circuit World (CW), a Unity virtual environment, uses avatars and realistic simulations of electrical circuits to test the effectiveness of teaching complex engineering tasks without travel. To evaluate CW, a study compares how well participants learn to repair a circuit when trained face-to-face, via Zoom, and within CW wearing an HMD. After training and completion of a knowledge quiz, learners are given a circuit to repair by themselves using a non-immersive desktop version of CW. Participants repair it again two weeks later to test retention. Each study session involves three people: learner, trainer, and researcher. The learner and trainer control avatars and the researcher, invisible, observes over the learner’s shoulder. Collected data includes task performance logs from CW, knowledge quiz scores, and, based on video recordings, eye gaze tracking, behavioral coding, and measures of facial synchrony between trainer and learner.","PeriodicalId":256204,"journal":{"name":"2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VRW52623.2021.00272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Business travel leads to the consumption of large amounts of energy. Circuit World (CW), a Unity virtual environment, uses avatars and realistic simulations of electrical circuits to test the effectiveness of teaching complex engineering tasks without travel. To evaluate CW, a study compares how well participants learn to repair a circuit when trained face-to-face, via Zoom, and within CW wearing an HMD. After training and completion of a knowledge quiz, learners are given a circuit to repair by themselves using a non-immersive desktop version of CW. Participants repair it again two weeks later to test retention. Each study session involves three people: learner, trainer, and researcher. The learner and trainer control avatars and the researcher, invisible, observes over the learner’s shoulder. Collected data includes task performance logs from CW, knowledge quiz scores, and, based on video recordings, eye gaze tracking, behavioral coding, and measures of facial synchrony between trainer and learner.