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Zhang X, Zhang W, Zhao Y, Zhu Q. Imbalanced volunteer engagement in cultural heritage crowdsourcing: a task-related exploration based on causal inference. Inf Process Manag 2022. [DOI: 10.1016/j.ipm.2022.103027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Yi T, Lee HY, Yum J, Lee JH. The influence of visitor-based social contextual information on visitors’ museum experience. PLoS One 2022; 17:e0266856. [PMID: 35609086 PMCID: PMC9129054 DOI: 10.1371/journal.pone.0266856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 03/28/2022] [Indexed: 11/19/2022] Open
Abstract
Visitor-centered approaches have been widely discussed in the museum experience research field. One notable approach was suggested by Falk and Dierking, who defined museum visitor experience as having a physical, personal, and social context. Many studies have been conducted based on this approach, yet the interactions between personal and social contexts have not been fully researched. Since previous studies related to these interactions have focused on the face-to-face conversation of visitor groups, attempts to provide the social information contributed by visitors have not progressed. To fill this gap, we examined such interactions in collaboration with the Lee-Ungno Art Museum in South Korea. Specifically, we investigated the influence of individual visitors’ social contextual information about their art museum experience. This data, which we call “visitor-based social contextual information” (VSCI), is the social information individuals provide—feedback, reactions, or behavioral data—that can be applied to facilitate interactions in a social context. The study included three stages: In Stage 1, we conducted an online survey for a preliminary investigation of visitors’ requirements for VSCI. In Stage 2, we designed a mobile application prototype. Finally, in Stage 3, we used the prototype in an experiment to investigate the influence of VSCI on museum experience based on visitors’ behaviors and reactions. Our results indicate that VSCI positively impacts visitors’ museum experiences. Using VSCI enables visitors to compare their thoughts with others and gain insights about art appreciation, thus allowing them to experience the exhibition from new perspectives. The results of this novel examination of a VSCI application suggest that it may be used to guide strategies for enhancing the experience of museum visitors.
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Affiliation(s)
- Taeha Yi
- Department of Interior Architecture Design, Hanyang University, Seoul, The Republic of Korea
| | - Hao-yun Lee
- Graduate School of Culture Technology, KAIST, Daejeon, The Republic of Korea
| | - Joosun Yum
- Graduate School of Culture Technology, KAIST, Daejeon, The Republic of Korea
| | - Ji-Hyun Lee
- Graduate School of Culture Technology, KAIST, Daejeon, The Republic of Korea
- * E-mail:
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Leong V, Raheel K, Sim JY, Kacker K, Karlaftis VM, Vassiliu C, Kalaivanan K, Chen SHA, Robbins TW, Sahakian BJ, Kourtzi Z. A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study. J Med Internet Res 2022; 24:e28368. [PMID: 34989691 PMCID: PMC8778570 DOI: 10.2196/28368] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 06/25/2021] [Accepted: 07/27/2021] [Indexed: 01/06/2023] Open
Abstract
Background The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the forefront as a promising solution for the rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. This study examines the opportunities and challenges afforded by the societal shift toward web-based testing and highlights an urgent need to establish a standard data quality assurance framework for online studies. Objective This study aims to develop and validate a new supervised online testing methodology, remote guided testing (RGT). Methods A total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory, and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (n=41) or online using remote guided testing (n=44) and delivered using identical web-based platforms (Cambridge Neuropsychological Test Automated Battery, Inquisit, and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, and response times) and overall task performance measures. Results The results indicated that, across all data quality and performance measures, RGT data was statistically-equivalent to in-person data collected in the lab (P>.40 for all comparisons). Moreover, RGT participants out-performed the lab group on measured verbal intelligence (P<.001), which could reflect test environment differences, including possible effects of mask-wearing on communication. Conclusions These data suggest that the RGT methodology could help ameliorate concerns regarding online data quality—particularly for studies involving high-risk or rare cohorts—and offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance.
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Affiliation(s)
- Victoria Leong
- Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.,Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Kausar Raheel
- Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore
| | - Jia Yi Sim
- Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore
| | - Kriti Kacker
- Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore
| | - Vasilis M Karlaftis
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Chrysoula Vassiliu
- Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge, Cambridge, United Kingdom
| | - Kastoori Kalaivanan
- Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore
| | - S H Annabel Chen
- Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.,Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.,National Institute of Education, Nanyang Technological University, Singapore, Singapore
| | - Trevor W Robbins
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom.,Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Barbara J Sahakian
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.,Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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Rhee CE, Choi J. Effects of personalization and social role in voice shopping: An experimental study on product recommendation by a conversational voice agent. COMPUTERS IN HUMAN BEHAVIOR 2020. [DOI: 10.1016/j.chb.2020.106359] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Barak Ventura R, Rizzo A, Nov O, Porfiri M. A 3D printing approach toward targeted intervention in telerehabilitation. Sci Rep 2020; 10:3694. [PMID: 32111880 PMCID: PMC7048757 DOI: 10.1038/s41598-020-59927-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Accepted: 02/05/2020] [Indexed: 01/11/2023] Open
Abstract
Neuromuscular impairment requires adherence to a rehabilitation regimen for maximum recovery of motor function. Consumer-grade game controllers have emerged as a viable means to relay supervised physical therapy to patients' homes, thereby increasing their accessibility to healthcare. These controllers allow patients to perform exercise frequently and improve their rehabilitation outcomes. However, the non-universal design of game controllers targets healthy people and does not always accommodate people with disability. Consequently, many patients experience considerable difficulty assuming certain hand postures and performing the prescribed exercise correctly. Here, we explore the feasibility of improving rehabilitation outcomes through a 3D printing approach that enhances off-the-shelf game controllers in home therapy. Specifically, a custom attachment was 3D printed for a commercial haptic device that mediates fine motor rehabilitation. In an experimental study, 25 healthy subjects performed a navigation task, with the retrofit attachment and without it, while simulating disability of the upper limb. When using the attachment, subjects extended their wrist range of motion, yet maintained their level of compensation. The subjects also showed higher motivation to repeat the exercise with the enhanced device. The results bring forward evidence for the potential of this approach in transforming game controllers toward targeted interventions in home therapy.
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Affiliation(s)
- Roni Barak Ventura
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, New York, 11201, USA
| | - Alessandro Rizzo
- Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Corso Duca degli Abruzzi 24, Torino, 10129, Italy.,Office of Innovation, New York University Tandon School of Engineering, Brooklyn, New York, 11201, USA
| | - Oded Nov
- Department of Technology Management and Innovation, New York University Tandon School of Engineering, 5 MetroTech Center, Brooklyn, New York, 11201, USA
| | - Maurizio Porfiri
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, New York, 11201, USA. .,Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, New York, 11201, USA.
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De Lellis P, Nakayama S, Porfiri M. Using demographics toward efficient data classification in citizen science: a Bayesian approach. PeerJ Comput Sci 2019; 5:e239. [PMID: 33816892 PMCID: PMC7924415 DOI: 10.7717/peerj-cs.239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 10/26/2019] [Indexed: 06/12/2023]
Abstract
Public participation in scientific activities, often called citizen science, offers a possibility to collect and analyze an unprecedentedly large amount of data. However, diversity of volunteers poses a challenge to obtain accurate information when these data are aggregated. To overcome this problem, we propose a classification algorithm using Bayesian inference that harnesses diversity of volunteers to improve data accuracy. In the algorithm, each volunteer is grouped into a distinct class based on a survey regarding either their level of education or motivation to citizen science. We obtained the behavior of each class through a training set, which was then used as a prior information to estimate performance of new volunteers. By applying this approach to an existing citizen science dataset to classify images into categories, we demonstrate improvement in data accuracy, compared to the traditional majority voting. Our algorithm offers a simple, yet powerful, way to improve data accuracy under limited effort of volunteers by predicting the behavior of a class of individuals, rather than attempting at a granular description of each of them.
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Affiliation(s)
- Pietro De Lellis
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Naples, Italy
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
| | - Shinnosuke Nakayama
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
| | - Maurizio Porfiri
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
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Barak Ventura R, Nakayama S, Raghavan P, Nov O, Porfiri M. The Role of Social Interactions in Motor Performance: Feasibility Study Toward Enhanced Motivation in Telerehabilitation. J Med Internet Res 2019; 21:e12708. [PMID: 31094338 PMCID: PMC6540723 DOI: 10.2196/12708] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 02/12/2019] [Accepted: 02/17/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Robot-mediated telerehabilitation has the potential to provide patient-tailored cost-effective rehabilitation. However, compliance with therapy can be a problem that undermines the prospective advantages of telerehabilitation technologies. Lack of motivation has been identified as a major factor that hampers compliance. Exploring various motivational interventions, the integration of citizen science activities in robotics-based rehabilitation has been shown to increase patients' motivation to engage in otherwise tedious exercises by tapping into a vast array of intrinsic motivational drivers. Patient engagement can be further enhanced by the incorporation of social interactions. OBJECTIVE Herein, we explored the possibility of bolstering engagement in physical therapy by leveraging cooperation among users in an environmental citizen science project. Specifically, we studied how the integration of cooperation into citizen science influences user engagement, enjoyment, and motor performance. Furthermore, we investigated how the degree of interdependence among users, such that is imposed through independent or joint termination (JT), affects participation in citizen science-based telerehabilitation. METHODS We developed a Web-based citizen science platform in which users work in pairs to classify images collected by an aquatic robot in a polluted water canal. The classification was carried out by labeling objects that appear in the images and trashing irrelevant labels. The system was interfaced by a haptic device for fine motor rehabilitation. We recruited 120 healthy volunteers to operate the platform. Of these volunteers, 98 were cooperating in pairs, with 1 user tagging images and the other trashing labels. The other 22 volunteers performed both tasks alone. To vary the degree of interdependence within cooperation, we implemented independent and JTs. RESULTS We found that users' engagement and motor performance are modulated by their assigned task and the degree of interdependence. Motor performance increased when users were subjected to independent termination (P=.02), yet enjoyment decreased when users were subjected to JT (P=.005). A significant interaction between the type of termination and the task was found to influence productivity (P<.001) as well as mean speed, peak speed, and path length of the controller (P=.01, P=.006, and P<.001, respectively). CONCLUSIONS Depending on the type of termination, cooperation was not always positively associated with engagement, enjoyment, and motor performance. Therefore, enhancing user engagement, satisfaction, and motor performance through cooperative citizen science tasks relies on both the degree of interdependence among users and the perceived nature of the task. Cooperative citizen science may enhance motivation in robotics-based telerehabilitation, if designed attentively.
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Affiliation(s)
- Roni Barak Ventura
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States
| | - Shinnosuke Nakayama
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States
| | - Preeti Raghavan
- Department of Rehabilitation Medicine, New York University School of Medicine, New York, NY, United States
| | - Oded Nov
- Department of Technology Management and Innovation, New York University Tandon School of Engineering, Brooklyn, NY, United States
| | - Maurizio Porfiri
- Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States.,Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, United States
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