Enhancing UX Research Activities Using GenAI -- Potential Applications and Challenges
November 19, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Stefan Graser, Anastasia Snimshchikova, Martin Schrepp, Stephan BΓΆhm
arXiv ID
2411.12289
Category
cs.HC: Human-Computer Interaction
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
User Experience (UX) Research covers various methods for gathering the users' subjective impressions of a product. For this, practitioners face different activities and tasks related to the research process. This includes processing a large amount of data based on qualitative and quantitative data. However, this can be very laborious in practice. Thus, the application of GenAI can support UX research activities. This paper provides a practical perspective on this topic. Based on previous studies, we present different use cases indicating the potential of GenAI in UX research. Moreover, we provide insights into an exploratory study using GenAI along an entire UX research process. Results show that Large Language Models (LLMs) are useful for various tasks. Thus, the research activities can be carried out more efficiently. However, the researcher should always review results to ensure quality. In summary, we want to express the potential of GenAI enhancing UX research
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