Papers Accepted to CHI LBW and IJHCI!

Congratulations to Neha Rani, Dr. Sharon Lynn Chu, Yvette Williamson, and Sindy Wu for their late-breaking works paper, Curiosity-Inspired learning: Insitu versus Post-Event Approaches to Recall and Reflection, being accepted to the 2021 ACM CHI Virtual Conference on Human Factors in Computing Systems (CHI 2021)! See the abstract below:

We often get questions about the processes and things that we observe in our surroundings, but there exists no practical support for exploring these questions. Exploring curiosity can lead to learning new science concepts. We propose a post-event recall and reflection approach to support curiosity-inspired learning in everyday life. Our approach involves capturing contextual cues during the curiosity moment and later using them for recall and focused reflection. Wearables can allow capturing contextual cues in daily life. First, we conducted a preliminary study to explore different cues and their effectiveness in recalling these curiosity moments. Further, we conducted a virtual study to evaluate the amount of exploration through the proposed approach of post-event recall and reflection and compared it with insitu recall and reflection. Results show a significant increase in questions and reflections made with the proposed approach, providing evidence for better learning outcomes from everyday curiosity.

But that’s not all! Neha, Dr. Sharon Lynn Chu, and Qing Li also had their paper, Exploring User Micro-behaviors with Five Wearable Device Types in Everyday Information-seeking Scenarios, accepted to the International Journal of Human-Computer Interaction! See the abstract below:

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 towards 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 towards 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.

Congratulations to Neha and her co-authors!