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ChatGPT, powered by a large language model (LLM), has revolutionized everyday human-computer interaction (HCI) experiences since its 2022 release. While now used by millions around the world, a coherent framework for evaluating the user experience (UX) ChatGPT offers remains missing. In this rapid review of the literature, I will investigate how ChatGPT UX has been approached quantitatively so far. I will focus on the independent variables (IVs) manipulated, the dependent variables (DVs) measured, the methods used for measurement, and the relationships between IVs and DVs. Findings are expected to reveal current trends, gaps, and emerging consensus in UX assessments of ChatGPT as a representative LLM-based chatbot. I aim to advance standardization in approaches to ChatGPT UX evaluation, elevate the field of ChatGPT UX, and empower researchers and practitioners in optimizing user interactions with ChatGPT and similar LLM-based systems. Note that this is based on an earlier rapid review for voice UX: https://osf.io/423pq

The aim of the current study is to develop an adapted version of User Experience Questionnaire (UEQ) and evaluate a learning management system. Although there is a growing interest on User Experience, there are still limited resources (i.e. measurement tools or questionnaires) available to measure user experience of any products, especially learning management systems. Two hundreds and thirteen computer science students participated and completed the adapted version of UEQ. In the study, the researchers used a learning management system named Student Centered e-Learning Environment (SCELE). Several types of learning materials are posted in SCELE such as audio files, simulations, PowerPoint slides, multimedia contents, and webpage links. Most of the lecturers use discussion forums in their courses to encourage students to participate in active learning setting. Staff and lecturers sometimes post academic-related announcements on the SCELE homepage. Two hundred thirteen students enrolled in Computer Science program were invited to evaluate the SCELE. This study will benefit UX practitioners, HCI educators, program and center of learning resources administrators, and learning management system developers. Findings of the present study may also be valuable for universities and high schools which are using computer-based learning environments.