remote experimentation
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2021 ◽  
Author(s):  
David Saffo ◽  
Sara Di Bartolomeo ◽  
Liudas Panavas ◽  
Caglar Yildirim ◽  
Cody Dunne

Over the last decade, remote experiments have become a widely used and integral method for many human-computer interaction domains. Nonetheless, extended reality (XR) researchers have been slow to adopt remote research methods. This can largely be attributed to standard remote experimentation techniques being ill-suited for the unique XR domain constraints. Existing research, albeit limited, has aimed to overcome these constraints and demonstrate the viability of traditional remote research methods for XR studies, yet most XR experiments have remained in-lab. This gap in XR methodology has never been more evident or detrimental than during the ongoing global COVID-19 pandemic. During the pandemic, safe and ethical co-present in-lab experimentation has become increasingly difficult, if not impossible. Many researchers struggled to transition to remote research methods resulting in delayed, canceled, or unsatisfactory experiments. Beyond this current crisis, remote research methods present several advantages, such as obtaining a larger sample and accessing specific user populations that have not been leveraged in XR research — leading to missed opportunities and potentially less rigorous results.Our previous research demonstrated the efficacy of using existing social virtual reality (VR) platforms to implement and conduct remote VR experiments. Social VR platforms provide an experienced and VR-equipped user base to recruit from and customizable distributed synchronous virtual environments to implement experiments, which makes them a natural fit for VR experiments. They allow researchers to be co-present in the same virtual environment as participants to proctor experiments, similar to how they would during a co-present in-lab study. However, existing social VR platforms were not built with this use-case in mind, resulting in several limitations, such as the inability to easily save data externally. These limitations prevent existing social VR platforms from being a viable long-term XR research method. Our previous work identified two potential paths towards establishing long-term social VR remote research methods. The first potential path is to partner with existing social VR platforms to create official channels for remote studies. The second potential path is to build a bespoke social VR platform specifically for conducting XR remote experiments. We believe both of these paths have their respective strengths and weakness and are viable long-term solutions for remote XR studies. In this position paper, we aim to contribute a detailed discussion of both of these paths, their benefits, limitations, and potential architecture. In so doing, we hope to provide the XR community our insights into how social VR research methods can be expanded and inspiration for the potential future of remote XR research.


2021 ◽  
Author(s):  
Klaudia Krawiecka ◽  
Jack Sturgess ◽  
Alina Petrova ◽  
Ivan Martinovic

2021 ◽  
Author(s):  
Nina Slamnik-Kriještorac ◽  
João Francisco Nunes Pinheiro ◽  
Thomas Huybrechts ◽  
Daniel van den Akker ◽  
Johann M. Marquez-Barja

Author(s):  
Krishnashree Achuthan ◽  
Dhananjay Raghavan ◽  
Balakrishnan Shankar ◽  
Saneesh P. Francis ◽  
Vysakh Kani Kolil

AbstractAccess and personalized instruction required for laboratory education can be highly compromised due to regulatory constraints in times such as COVID-19 pandemic or resource shortages at other times. This directly impacts the student engagement and immersion that are necessary for conceptual and procedural understanding for scientific experimentation. While online and remote laboratories have potential to address the aforementioned challenges, theoretical perspectives of laboratory learning outcomes are critical to enhance their impact and are sparsely examined in the literature. Using Transactional Distance Theory (TDT), this paper addresses the gap through a case study on Universal Testing Machine (UTM). By comparing physical (PL-UTM) and remotely triggerable (RT-UTM) laboratory platforms, the structure and interactions as per TDT are analysed. Characterization of interactivity between remote learners and instructors disclose indicative parameters that affect transactional distances and aid in conceptual understanding in remote laboratory learning environment. An extensive pedagogical study through development of two instruments towards assessing conceptual understanding and perception of platform effectiveness that was conducted both on physical laboratory and RT-UTM showed: (1) remote users conducted experiments 3 times more frequently (2) completed assignments in 30% less time and (3) had over 200% improvement in scores when RT-UTM platform was integrated into mainstream learning.


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