We are presenting two papers at UbiComp 2025 (Espoo, Finland), both of which focus on mobile and wearable experience sampling. Jixin Li will be leading the presentations (and is on the job market!). Say hello if you are around and ask a lot of questions 🙂

Finally, if you are wondering whether μEMA and EMA collect similar data. We compared the user-level variability captured by μEMA and EMA across 11 affect-based constructs. We found a moderate to strong +ve correlation between μEMA and EMA variability across constructs.

Third, when we measure user burden at the end of 12 months of data collection (only those who completed the study), μEMA was still perceived as less burdensome among those with possible survivor bias in data collection.

Second, we observed that regardless of the users' engagement with the data collection study (e.g., those who completed vs. withdrew vs. unenrolled), μEMA was consistently perceived as less burdensome, despite much higher interruption longitudinally.

First, we found that μEMA response rates were highest among those users who were unenrolled by research staff or voluntarily withdrew from data collection because of EMA burden. This response rate difference was negligible among those who completed 12 months of data collection.

🥳 Pleased to share that our paper "Longitudinal User Engagement with Microinteraction Ecological Momentary Assessment (μEMA)" has been accepted at #IMWUT. In this paper, we conducted the first large-scale longitudinal comparison of μEMA and #EMA over a period of one year.

Compared to a random selection of survey questions, our proposed method reduces imputation errors by 15-50% and survey length by 34-56% across real-world datasets, making surveys personalized to each user with reduced burden.

🥳 Excited to share our new #IMWUT paper, "Ask Less, Learn More: Adapting Ecological Momentary Assessment Survey Length by Modeling Question-Answer Information Gain" led by
Jixin Li.