Peer-vasive computing: Leveraging peers to enhance the accuracy of self-reports in mobile human studies
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
We discuss two methods designed to increase the accuracy of human-labeled data. First, Peer-ceived Momentary Assessment (Peer-MA), a novel data collection method inspired by the concept of Observer Reported Outcomes in clinical care. Second, mQoL-Peer, a platform aiming to equip researchers with tools to assess and maintain the accuracy of the data collected by participants and peers during mobile human studies. We describe the state of the research and specific contributions.
| Original language | English |
|---|---|
| Title of host publication | UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers |
| Number of pages | 6 |
| Publisher | Association for Computing Machinery |
| Publication date | 2018 |
| Pages | 600-605 |
| ISBN (Electronic) | 9781450359665 |
| DOIs | |
| Publication status | Published - 2018 |
| Event | 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore Duration: 8 Oct 2018 → 12 Oct 2018 |
Conference
| Conference | 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 |
|---|---|
| Land | Singapore |
| By | Singapore |
| Periode | 08/10/2018 → 12/10/2018 |
| Sponsor | ACM SIGCHI, ACM SIGMOBILE |
- Ecological Momentary Assessment, Observer's Assessment, Peer-ceived Momentary Assessment, Self-Assessment
Research areas
ID: 217339989