Exploring User Micro-Behaviors Towards Five Wearable Device Types in Everyday Learning-Oriented Scenarios

Abstract

ABSTRACT With advances in areas such as sensors and machine learning, wearable technologies will have increased potential to support our daily lives. Even though today’s landscape of smart wearable devices is highly varied, the real-world adoption of wearables has remained lukewarm. We propose that a key reason is that we currently only have a surface-level understanding of people’s interaction behaviors with wearable devices. A deeper understanding of user behaviors toward different wearable devices will help to inform wearable design for more seamless user experiences. We present an empirical study with 50 participants that explore people’s micro-behaviors toward five types of smart wearable devices (wristband, ring, clip, necklace, glasses) in a lab-based information-gathering context. A micro-analysis of participants’ session videos and interviews showed that people have different behaviors and attitudes in terms of affordances and functionality for different forms of wearables giving rise to a variety of design implications.