Home // CENTRIC 2023, The Sixteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services // View article
Authors:
Stefan Graser
Stephan Böhm
Martin Schrepp
Keywords: User Experience (UX); UX Measurement; UX Factors; Measurement Items; Generative AI (GenAI); Large Language Model (LLM); ChatGPT; Semantic Textual Similarity (STS).
Abstract:
Measuring User Experience (UX) with standardized questionnaires is a widely used method. A questionnaire is based on different scales that represent UX factors and items. However, the questionnaires have no common ground concerning naming different factors and the items used to measure them. This study aims to identify general UX factors based on the formulation of the measurement items. Items from a set of 40 established UX questionnaires were analyzed by Generative AI (GenAI) to identify semantically similar items and to cluster similar topics. We used the LLM ChatGPT-4 for this analysis. Results show that ChatGPT-4 can classify items into meaningful topics and thus help to create a deeper understanding of the structure of the UX research field. In addition, we show that ChatGPT-4 can filter items related to a predefined UX concept out of a pool of UX items.
Pages: 19 to 28
Copyright: Copyright (c) IARIA, 2023
Publication date: November 13, 2023
Published in: conference
ISSN: 2308-3492
ISBN: 978-1-68558-100-8
Location: Valencia, Spain
Dates: from November 13, 2023 to November 17, 2023