Using HCI in Cross-Disciplinary Teams: A Case Study of Academic Collaboration in HCI-Health Teams in the US Using a Team Science Perspective
September 01, 2022 Β· Declared Dead Β· π Proc. ACM Hum. Comput. Interact.
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Elena Agapie, Shefali Haldar, Sharmaine Galvez Poblete
arXiv ID
2209.00216
Category
cs.HC: Human-Computer Interaction
Citations
16
Venue
Proc. ACM Hum. Comput. Interact.
Last Checked
4 months ago
Abstract
Human-centered computing research has been increasingly applied to address important challenges in the health domain. Conducting research in cross-disciplinary teams can come with a lot of challenges in integrating knowledge across fields. Yet, we do not know what challenges HCI researchers encounter in building collaborations with health researchers, and how these researchers negotiate challenges while balancing their professional goals. We interviewed 17 early- and mid-career HCI faculty working in the United States who conducted research in collaboration with health researchers. Drawing from a Team Science framework, we share participants' lived experiences and identify major challenges that HCI researchers encounter when finding, collaborating with, and negotiating with health collaborators when building technologies. We propose ways to better support research collaboration aimed at designing technologies using human-centered computing approaches. This includes strategies to support HCI researchers at individual, institutional, research community, and funding agencies levels through tools to translate disciplinary approaches. We suggest institutional policies to support HCI researchers through training, networking, and promotion.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted