LSVP

Author:

Ram Ashwin1,Zhao Shengdong1

Affiliation:

1. NUS-HCI Lab, Department of Computer Science, National University of Singapore, Singapore

Abstract

The ubiquity of mobile phones allows video content to be watched on the go. However, users' current on-the-go video learning experience on phones is encumbered by issues of toggling and managing attention between the video and surroundings, as informed by our initial qualitative study. To alleviate this, we explore how combining the emergent smart glasses (Optical Head-Mounted Display or OHMD) platform with a redesigned video presentation style can better distribute users' attention between learning and walking tasks. We evaluated three presentation techniques: highlighting, sequentiality, and data persistence to find that combining sequentiality and data persistence is highly effective, yielding a 56% higher immediate recall score compared to a static video presentation. We also compared the OHMD against smartphones to delineate the advantages of either platform for on-the-go video learning in the context of everyday mobility tasks. We found that OHMDs improved users' 7-day delayed recall scores by 17% while still allowing 5.6% faster walking speed, especially during complex mobility tasks. Based on the findings, we introduce Layered Serial Visual Presentation (LSVP) style, which incorporates sequentiality, strict data persistence, and transparent background, among other properties, for future OHMD-based on-the-go video learning.

Funder

NUS Advanced Robotics Centre

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

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