MeetinVR

Evaluated usability testing on MeetinVR's interface, using qualitative and quantitative protocols to assess user experience. Identified insights for desktop and VR applications. MeetinVR: Business Meeting & Collaboration in VR, version V28, offers customizable avatars, note-taking, and document upload features. Available on various platforms, targeted at companies for virtual meetings and workshops.

Overview of the Research

Users

There were 10 users total, five four each application version. The users fell between 20-23 years old. All participants were in the Muncie area, as well. The users were primarily students or young professionals, which varies from the interface’s target demographic, companies.  

Qualitative Protocols

We investigated how interface design affects user experiences and usability. Using qualitative methods like contextual inquiry and heuristics evaluation, along with quantitative assessments of efficiency and effectiveness, we gained insights into MeetinVR. Our findings informed discussions on usability and engagement in virtual meeting technology.

Quantitative Protocols

To rigorously evaluate the product, we utilized quantitative protocols to measure both efficiency and effectiveness. Efficiency metrics assessed resource optimization and process streamlining, including factors like response times and task completion rates. Effectiveness metrics gauged the product's ability to meet user expectations, analyzing accuracy, reliability, and user satisfaction scores.

Qualitative Controls

Contextual Inquiry

  1. Create a Mind Map of users' morning routines.

  2. Change the meeting room. 

  3. Grab a pen from behind the ear.

Ethnographies

  1. Two virtual ethnographies that looked at online reviews and online community

  2. Looked at reviews on Lifewire, G2, MeetinVr, and Oculus for online reviews.

  3. Looked at Twitter, Facebook,Instagram, and Youtube for online community.

Heuristics Evaluation

  1. Used Nielsen’s Golden 10 in addition to domain-specific heuristics for VR Interface and desktop interface.

Highlights of our Analysis

Analysis Method: Utilized Grounded Theory.

Data Collection: Gathered from virtual ethnographies, four heuristics evaluations, and three contextual inquiries.

Excerpts Collected: 202 excerpts.

Initial Coding: Developed 20 codes and 17 categories, mainly focused on usability issues, clarity, and user satisfaction with the onboarding tutorial.

Hypotheses Development: Formulated three hypotheses regarding lack of background knowledge, issues with iconography, and affordance impacting usability.

Intermediate Coding: Expanded to 64 intermediate codes, emphasizing user-centered design issues, such as lack of labeling, unclear affordance, and inadequate information.

Advanced Codes: 18 categories identified, with top frequencies in Lack of User Consideration, Lack of Clarity, and Function Error, suggesting users struggled with interface clarity and function performance.

Core Category Idea: Identified as usability issues related to bad user-centered design, supported by storyline analysis.

Results & Findings

    • Observed social media platforms: Facebook, Twitter, Instagram, and YouTube.

    • Focused on community interactions in VR and desktop applications.

    • Concluded after 2.25 hours: MeetinVR community is close-knit, mainly tech enthusiasts, with curiosity but minimal user experience sharing.

    • Users noted interface's revolutionary concept, addressing social distancing needs.

    • Positives include ease of use via tablet, but negatives include limited avatar customization and lack of mobile support.

    • Concluded: Users find initial navigation challenging.

    • Contextual inquiry tasks (mind map creation, room change, pen grab) showed users found interface navigation difficult.

    • Heuristics evaluation highlighted high-severity errors in guidance, interface alternatives, error messaging, customization, lag, and cues.

    • Supports findings of ethnographies, inquiries, and heuristic averages.

    • Users faced a learning curve due to lack of intuitive interface and clarity.

    • Many users self-taught through trial and error.

    • Interface design impacts user understanding and usability, lacking direction in onboarding.

    • Lack of signifiers and affordances hinder user interaction and navigation.

    • Majority found interface interesting but ended frustrated, pointing to issues with customization, accessibility, and user-centered design.

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