Measuring User Experience Research Articles

Redesain User Interface pada Website Pudam Banyuwangi Menggunakan Metode User Centered Design

PUDAM Banyuwangi is a regional public company that provides clean water services to the community with branches in several areas. The PUDAM Banyuwangi website was built with the aim of making company information and services more accessible. It is known, during the creation of the website the company did a refresh which was carried out almost every five years to improve the functionality of the website. however, user experience testing has never been carried out measurably on the website user interface. initial testing was carried out using the User Experience Questionnaire (UEQ) as a user experience measurement tolls by getting results from 51 respondents showing the value of user experience on the website on 6 components, namely attractiveness (-0.12), clarity (0.15), efficiency (0.11), accuracy (-0.04), stimulation (-0.07), novelty (-0.29) so that it falls into the "Bad" criteria. To improve this, research was conducted using the User Centered Design (UCD) approach to analyze user needs and provide design update recommendations based on test results. The results showed that the design update increased the user experience evaluation value with an attractiveness value of (1.67), clarity (1.73), efficiency (1.71), accuracy (1.65), stimulation (1.55), novelty (1.51) so that it fell into the "Good" criteria. This can prove that this research provides recommendations for appropriate design updates to improve the functionality of the PUDAM Banyuwangi website in its development.

Analysis of Preference Factors by Measuring User Experience Design in Pop-Up Store Space

Analysis of Preference Factors by Measuring User Experience Design in Pop-Up Store Space

Physicians' Views of a Digital Intervention to Support Respiratory Patients: Take-a-Breath Pre-Pilot Usability Study.

Although eHealth interventions are increasingly recognized as a useful tool to support healthcare, relatively few studies focus on the physician-end's usability. This study aims to evaluate the Healthcare Professional's (HCP) platform of the Take-A-Breath project, a Greek initiative for personalized respiratory disease monitoring, training and self-management. The pre-pilot usability study, involving 10 participants, combines qualitative methods, behavioral observations, and standardized measures of user experience and usability. While relatively high scores indicate overall acceptance, concerns are also discussed, particularly related with the volume of information provided and actions available to the users, hindering the usability of the system due to an overload effect. Findings emphasize also the need for more tailored in-app wordings as well as the integration of similar systems with the already set up electronic health record systems. This study contributes to understanding digital intervention success among HCPs in respiratory healthcare.

The effect of preference elicitation methods on the user experience in conversational recommender systems

The prevalence of conversational interfaces is rapidly rising, since improved algorithms allow for remarkable proficiency in understanding and generating natural language. This also holds for Conversational Recommender Systems (CRS), that benefit from information being provided by the user in the course of the dialogue to offer personalized recommendations. However, the challenge remains eliciting the user's characteristics and preferences in a way that leads to the most optimal user experience. Hence, the current research was aimed at investigating the effect of different Preference Elicitation (PE) methods on the user experience of a CRS. We introduce two axes across which PE methods can be classified, namely the degree of system prompt guidance and the level of user input restriction. We built three versions of a CRS to conduct a between-subjects experiment which compared three conditions: high guidance-high restriction, high guidance-low restriction and low guidance-low restriction. We tested their effect on ten constructs of user experience measures on 66 European participants, all working in agriculture or forestry.The study did not find any significant effects of the three preference elicitation methods on all user experience constructs collected through questionnaires. However, we did find significant differences in terms of the objective measures chat duration (Speed), response time (Cognitive Demand) and recommendation performance (Accuracy of Recommended Items). Regarding the recommendation performance, it was found that the preference elicitation methods with high guidance led to a higher match score than the condition with low guidance. The certainty score was highest in the condition with high guidance and high input restriction. Finally, we found through a question at the end of the conversation that users who were satisfied with the recommendation responded more positively to six out of ten user experience constructs. This suggests that satisfaction with the recommendation performance is a crucial factor in the user experience of CRSs.

Robots as Mental Health Coaches: A Study of Emotional Responses to Technology-Assisted Stress Management Tasks Using Physiological Signals.

The current study investigated the effectiveness of social robots in facilitating stress management interventions for university students by evaluating their physiological responses. We collected electroencephalogram (EEG) brain activity and Galvanic Skin Responses (GSRs) together with self-reported questionnaires from two groups of students who practiced a deep breathing exercise either with a social robot or a laptop. From GSR signals, we obtained the change in participants' arousal level throughout the intervention, and from the EEG signals, we extracted the change in their emotional valence using the neurometric of Frontal Alpha Asymmetry (FAA). While subjective perceptions of stress and user experience did not differ significantly between the two groups, the physiological signals revealed differences in their emotional responses as evaluated by the arousal-valence model. The Laptop group tended to show a decrease in arousal level which, in some cases, was accompanied by negative valence indicative of boredom or lack of interest. On the other hand, the Robot group displayed two patterns; some demonstrated a decrease in arousal with positive valence indicative of calmness and relaxation, and others showed an increase in arousal together with positive valence interpreted as excitement. These findings provide interesting insights into the impact of social robots as mental well-being coaches on students' emotions particularly in the presence of the novelty effect. Additionally, they provide evidence for the efficacy of physiological signals as an objective and reliable measure of user experience in HRI settings.

Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network

The study of user perception and interaction with applications is referred to as user experience, or UX. The intricacy and versatility of software products, from requirements engineering to product functionality are well recognized. UX evaluations are often depends on prototypes, but it's important to consider the semantics embedded in software requirements to ensure project success. In this manuscript, Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network (SRE-UEDM-BDA-CBTCN) is proposed. The input data are collected from Requirements dataset. The collected data are given to the Convolution-Bidirectional Temporal Convolutional Network (CBTCN) to Design Modeling of Big Data Analysis user experience based on the dataset. In general, CBTCN does not express any adaption of optimization techniques for determining the ideal parameters to accurate Design user experience. Hence, African Vultures Optimization Algorithm (AVOA) is proposed in this work to improve the weight parameter of CBTCN. The proposed model is implemented and the efficiency is evaluated utilizing some performance metrics like accuracy, precision, specificity, sensitivity and F1-Score. The proposed SRE-UEDM-BDA-CBTCN method provides 28.46%, 21.34 and 33.81% higher accuracy, 22.88%, 26.52% and 34.63% higher Precision and 28.46%, 21.34 and 33.81% higher specificity compared with the existing techniques like Holistic big data integrated artificial intelligent modeling to improve privacy and safety in data management of smart cities (AIM-BDI-SDM), Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach (MHA-UED-MLA) and Towards Measuring User Experience based on Software Requirements (TM-UEB-SR).

A multifaceted suite of metrics for comparative myoelectric prosthesis controller research.

Upper limb robotic (myoelectric) prostheses are technologically advanced, but challenging to use. In response, substantial research is being done to develop person-specific prosthesis controllers that can predict a user's intended movements. Most studies that test and compare new controllers rely on simple assessment measures such as task scores (e.g., number of objects moved across a barrier) or duration-based measures (e.g., overall task completion time). These assessment measures, however, fail to capture valuable details about: the quality of device arm movements; whether these movements match users' intentions; the timing of specific wrist and hand control functions; and users' opinions regarding overall device reliability and controller training requirements. In this work, we present a comprehensive and novel suite of myoelectric prosthesis control evaluation metrics that better facilitates analysis of device movement details-spanning measures of task performance, control characteristics, and user experience. As a case example of their use and research viability, we applied these metrics in real-time control experimentation. Here, eight participants without upper limb impairment compared device control offered by a deep learning-based controller (recurrent convolutional neural network-based classification with transfer learning, or RCNN-TL) to that of a commonly used controller (linear discriminant analysis, or LDA). The participants wore a simulated prosthesis and performed complex functional tasks across multiple limb positions. Analysis resulting from our suite of metrics identified 16 instances of a user-facing problem known as the "limb position effect". We determined that RCNN-TL performed the same as or significantly better than LDA in four such problem instances. We also confirmed that transfer learning can minimize user training burden. Overall, this study contributes a multifaceted new suite of control evaluation metrics, along with a guide to their application, for use in research and testing of myoelectric controllers today, and potentially for use in broader rehabilitation technologies of the future.

Measuring User Experience Inclusivity in Human-AI Interaction via Five User Problem-Solving Styles

Motivations: Recent research has emerged on generally how to improve AI products’ Human-AI Interaction (HAI) User Experience (UX), but relatively little is known about HAI-UX inclusivity. For example, what kinds of users are supported, and who are left out? What product changes would make it more inclusive? Objectives: To help fill this gap, we present an approach to measuring what kinds of diverse users an AI product leaves out and how to act upon that knowledge. To bring actionability to the results, the approach focuses on users’ problem-solving diversity. Thus, our specific objectives were: (1) to show how the measure can reveal which participants with diverse problem-solving styles were left behind in a set of AI products; and (2) to relate participants’ problem-solving diversity to their demographic diversity, specifically gender and age. Methods: We performed 18 experiments, discarding two that failed manipulation checks. Each experiment was a 2x2 factorial experiment with online participants, comparing two AI products: one deliberately violating one of 18 HAI guideline and the other applying the same guideline. For our first objective, we used our measure to analyze how much each AI product gained/lost HAI-UX inclusivity compared to its counterpart, where inclusivity meant supportiveness to participants with particular problem-solving styles. For our second objective, we analyzed how participants’ problem-solving styles aligned with their gender identities and ages. Results & Implications: Participants’ diverse problem-solving styles revealed six types of inclusivity results: (1) the AI products that followed an HAI guideline were almost always more inclusive across diversity of problem-solving styles than the products that did not follow that guideline—but “who” got most of the inclusivity varied widely by guideline and by problem-solving style; (2) when an AI product had risk implications, four variables’ values varied in tandem: participants’ feelings of control, their (lack of) suspicion, their trust in the product, and their certainty while using the product; (3) the more control an AI product offered users, the more inclusive it was; (4) whether an AI product was learning from “my” data or other people’s affected how inclusive that product was; (5) participants’ problem-solving styles skewed differently by gender and age group; and (6) almost all of the results suggested actions that HAI practitioners could take to improve their products’ inclusivity further. Together, these results suggest that a key to improving the demographic inclusivity of an AI product (e.g., across a wide range of genders, ages, etc.) can often be obtained by improving the product’s support of diverse problem-solving styles.

EVALUASI PENGALAMAN PENGGUNA FLEXIBLE LEARNING UKSW MENGGUNAKAN METODE USER EXPERIENCE QUESTIONNAIRE PADA PROSES PEMBELAJARAN

Advances in the world of technology today are very rapid, especially in the world of education. Universities and schools definitely need a platform or moodle in the academic learning process, especially at Satya Wacana Christian University. Satya Wacana Christian University is one of the well-known universities and is much sought after by students in Central Java Province and outside Java Island. This campus uses Moodle in its learning process, namely Flexible Learning. Flexible Learning is used to simplify the teaching and learning process. However, Moodle learning, namely Flexible Learning, has not been proven to satisfy users. This journal was formed to test the experiences of using Flexible Learning among SWCU students. This research uses user experience with a questionnaire to determine satisfaction with using Flexible Learning among UKSW students. The research will be carried out using the method of determining the scope of research, literature review, problem analysis, research instruments, determining respondents, measuring UEQ, analyzing test results, and conclusions. The test results in this research involved a total of 50 students as respondents. The evaluation obtained from the research, namely the 6 aspects of the UEQ, can convey the results of measuring user experience and conclude the results of the UEQ.

Measuring digital intervention user experience with a novel ecological momentary assessment (EMA) method, CORTO

Digital interventions often suffer from low usage, which may reflect insufficient attention to user experience. Moreover, the existing evaluation methods have limited applicability in the remote study of user experience of complex interventions that have expansive content and that are used over an extensive period of time.To alleviate these challenges, we describe here a novel qualitative Ecological Momentary Assessment (EMA) method: the CORTO method (Contextual, One-item, Repeated, Timely, Open-ended). We used it to gather digital intervention user experience data from Finnish adults (n = 184) who lived with interview-confirmed major depressive disorder (MDD) and took part in a randomized controlled trial (RCT) that studied the efficacy of a novel 12-week game-based digital intervention for depression. A second dataset on user experience was gathered with retrospective interviews (n = 22).We inductively coded the CORTO method and retrospective interview data, which led to four user experience categories: (1) contextual use, (2) interaction-elicited emotional experience, (3) usability, and (4) technical issues. Then, we used the created user experience categories and Template Analysis to analyze both datasets together, and reported the results qualitatively. Finally, we compared the two datasets with each other. We found that the data generated with the CORTO method offered more insights into usability and technical categories than the interview data that particularly illustrated the contextual use. The emotional valence of the interview data was more positive compared with the CORTO data. Both the CORTO and interview data detected 55 % of the micro-level categories; 20 % of micro-level categories were only detected by the CORTO data and 25 % only by the interview data.We found that the during-intervention user experience measurement with the CORTO method can provide intervention-specific insights, and thereby further the iterative user-centered intervention development. Overall, these findings highlight the impact of evaluation methods on the categories and qualities of insights acquired in intervention research.

Assessment of health technology acceptability for remote monitoring of patients with COVID-19: A measurement model for user perceptions of pulse oximeters.

This study aims to develop a measurement model for health technology acceptability using a theoretical framework and a range of validated instruments to measure user experience, acceptance, usability, health and digital health literacy. A cross-sectional evaluation study using a mixed-methods approach was conducted. An online survey was administered to patients who used a pulse oximeter in a virtual hospital setting during COVID-19. The model development was conducted in three steps: (1) exploratory factor analysis for conceptual model development, (2) measurement model confirmation through confirmatory factor analysis followed by structural equation modelling and (3) test of model external validity on four outcome measures. Finally, the different constructs of the developed model were used to compare two types of pulse oximeters by measuring the standardised scores. Two hundred and two participants were included in the analysis, 37.6% were female and the average age was 53 years (SD:15.38). A four-construct model comprising Task Load, Affective Attitude, Self-Efficacy and Value of Use (0.636-0.857 factor loadings) with 12 items resulted from the exploratory factor analysis and yielded a good fit (RMSEA = .026). Health and digital health literacy did not affect the overall reliability of the model. Frustration, performance, trust and satisfaction were identified as outcomes of the model. No significant differences were observed in the acceptability constructs when comparing the two pulse oximeter devices. This article proposes a model for the measurement of the acceptability of health technologies used by patients in a remote care setting based on the use of a pulse oximeter in COVID-19 remote monitoring.

자율주행 차량의 스티어링 휠 디자인에 따른 사용자 경험 측정 도구 개발

The purpose of this study is to develop a standardized scale for measuring the user experience of passengers regarding the steering wheel design in Level 5 autonomous vehicles. Preliminary items for user experience were constructed through literature review, and content validity was proved for the expert group. After a pilot test of 20 items, a user experience survey was conducted with 21 participants, evaluating 18 steering wheel designs. Each design was considered an independent case, and reliability and validity were confirmed based on 378 survey data collected from 21 participants. As a result of the validity analysis, four factors were extracted through a total of 19 items. Each factor was named ‘Trust', ’Intention to use', ‘Space utilization', and ’Information accessibility'. The reliability of four factors and the total scale confirmed that Cronbach's α coefficient was higher than 0.7. In this study, a user experience measurement scale that can be applied to various steering wheel designs of autonomous vehicles was developed. It is expected that it can be used as a standardized measurement scale to evaluate user experience for the steering wheel design to be developed in the future.

Analisis Website Pusat Pengembangan Karir Berdasarkan Pengalaman Pengguna: Pendekatan User Experience Questionnaire (UEQ)

Pembangunan National “Veteran” University of East Java has developed the Career Development Center website as a job vacancy information center to prepare graduates who are tough, innovative, and creative in the world of work. The Career Development Center website makes it easier to search for and find job opportunities that suit the field of study, skills, and interests of college graduates. A positive user experience in using the Career Development Center website can increase satisfaction and optimize career searches, so it is important to carry out measurements systematically and objectively. This study aims to measure the level of experience of users of the Career Development Center website using the User Experience Questionnaire (UEQ). UEQ measurements on the Career Development Center website focus on gaining an understanding of the Attractiveness, Pragmatic quality, and Hedonic quality aspects. UEQ provides measurements of technical and non-technical aspects related to the user's emotion or perception of pleasure. The results of measuring user experience on the Career Development Center website can help identify trends and changes in user needs so that they can adapt and develop relevant and innovative features. This study uses quantitative data by distributing 26 items of the UEQ questionnaire online to 350 alumni. The research results stated that the attractiveness aspect had the highest average value of 1.94. These results prove that the Career Development Center website has a high attractiveness value for users, thereby increasing the opportunity for continuous use. Apart from that, based on the high average stimulation value of 1.930, it can be proven that graduates who use the Career Development Center website get large benefits related to alumni career development.

Using Knowledge Construction Theory to Evaluate Learning Processes: A Randomized Controlled Trial on Showing Gradually Built-up Concept Maps Alongside a Scientific Text

Scientific texts convey new and complex information relevant not only to researchers but also to lay audiences. We present a randomized controlled trial that investigated whether showing a concept map, gradually building up as a user reads a scientific text, supports the cognitive processes of knowledge construction. The intervention group (n = 44) exhibited significantly more knowledge construction [t(89) = 1.94, p = .029, d = 0.41] than the control group (n = 47). The intervention supported basic knowledge construction, i.e., simple processing of information, but not medium and complex levels. This study makes two contributions: (1) showing interactive concept maps and building them up gradually alongside reading helps make scientific texts cognitively more accessible to a lay audience, e.g., to inform public debate, and (2) knowledge construction theory can be used as a theoretical foundation for measuring specific aspects of learning processes—complementing other metrics for comparative design examinations, e.g., usability, user experience, or performance-based measures.

Holistic Human-Serving Digitization of Health Care Needs Integrated Automated System-Level Assessment Tools.

Digital health tools, platforms, and artificial intelligence- or machine learning-based clinical decision support systems are increasingly part of health delivery approaches, with an ever-greater degree of system interaction. Critical to the successful deployment of these tools is their functional integration into existing clinical routines and workflows. This depends on system interoperability and on intuitive and safe user interface design. The importance of minimizing emergent workflow stress through human factors research and purposeful design for integration cannot be overstated. Usability of tools in practice is as important as algorithm quality. Regulatory and health technology assessment frameworks recognize the importance of these factors to a certain extent, but their focus remains mainly on the individual product rather than on emergent system and workflow effects. The measurement of performance and user experience has so far been performed in ad hoc, nonstandardized ways by individual actors using their own evaluation approaches. We propose that a standard framework for system-level and holistic evaluation could be built into interacting digital systems to enable systematic and standardized system-wide, multiproduct, postmarket surveillance and technology assessment. Such a system could be made available to developers through regulatory or assessment bodies as an application programming interface and could be a requirement for digital tool certification, just as interoperability is. This would enable health systems and tool developers to collect system-level data directly from real device use cases, enabling the controlled and safe delivery of systematic quality assessment or improvement studies suitable for the complexity and interconnectedness of clinical workflows using developing digital health technologies.

User Experience of Digital Voice Assistant: Conceptualization and Measurement

With the development of digital virtual assistants (DVA), academics and practitioners have increased attention to the DVA user experience. However, the measurement scale of DVA user experience is still under-researched, which may hinder further empirical study on human-DVA interaction. This study rigorously developed dimensions and associated scales of the DVA user experience. We employed a mixed-method approach that integrated qualitative and quantitative methods. This study first developed multilevel dimensions of DVA user experience based on consumers’ online reviews (n = 21,314), then adopted the ten-step method to develop the associate measurement scale with reliability and validity by collecting and examining three data sets (pretest: n = 368, refinement and validation: n = 585, cross-validation: n = 567). This study fills the gap of a lack of research on the classification and measurement of DVA user experience and provides a reference for practitioners in developing DVA and continuously improving the DVA user experience.

Development of UI / UX Design in Web-Based Artificial Intelligence Learning on Student Learning Motivation with a User-centered Design Approach

Artificial Intelligence (AI) is a study of intelligent machines. Starting from elementary school, children should have the opportunity to learn computer science, both from computational thinking and programming. Based on that case, an e-learning platform that discusses AI with block-based programming was created, namely eCraft2Learn. Based on the results of field studies, the measurement of user experience and user interface shows the "bad" category on each scale. Whereas in e-learning, UI/UX is the point of interaction as the key in achieving educational goals. It is necessary to develop UI/UX both in terms of structure and content presentation, collaboration, and interaction so that it can influence student learning and motivation. Thus, the UI/UX development is carried out by applying the four stages of the user-centered design method. After all stages of the method are carried out, it produces a UI/UX design whose value can be measured based on the measurement of user experience and the development of student learning motivation is also measured through four indicators, namely intrinsic motivation, identified regulation, external regulation, and amotivation. From these results, it can be concluded that the UI/UX design that has been developed produces an increased value and has a positive effect on the intrinsic motivation scale and identified regulation. However, the results of this UI/UX design have no influence on the scale of external regulation and motivation

Exploring the context of use for voice user interfaces: Toward context‐dependent user experience quality testing

AbstractVoice user interface (VUI) systems, such as Alexa, Siri, and Google Assistant, are popular and widely available. Still, challenges such as privacy and the ability to have a dialog remain. In the latter example, the user expects a human‐like conversation, that is, that the VUI understands the dialog and its context. However, this VUI feature of context‐aware interaction is rather error prone. For this reason, we intend to explore the VUI context of use and its impact on interaction, that is, relevant user experience (UX). We see a demand for context‐dependent UX measurement because analyzing the context of use and UX assessment are both critical human‐centered design (HCD) methods. Therefore, we examine the VUI context of use by asking users about how, where, and for what they use VUIs, as well as their UX and improvement proposals. We interviewed people with disabilities who rely on VUIs and people without disabilities who use VUIs for convenience or fun. We identified VUI context‐of‐use categories and factors and explored their impacts on relevant UX qualities. Our result is a matrix containing these elements; thus, it provides an overview of the contextual UX of our target group's VUI interaction. We intend to develop a VUI context‐of‐use conceptual structure in the future based on this matrix, which is needed to create an automated context‐dependent UX measurement recommendation tool for VUIs. This conceptual structure could also be useful for automated UX testing in the context of VUI.

A9Immersive Technology Experience Measure (ITEM): pilot study on participant experience using novel questionnaire and VR scenario

A scoping review identified a significant growth in research with immersive technology in healthcare education. However, there are few validated measures that capture the user experience of participants [1]. This study aims to investigate the use of an immersive virtual reality (VR) simulation on sepsis management and measure user experience using a validated tool, the Immersive Technology Evaluation Measure (ITEM) [2]. ITEM was formulated on a learning theory called Model for Immersive Technology in Healthcare Education (MITHE), which borrows cognitive and behavioural theories to help explain our level of immersion and enjoyment that can be facilitated by technology (see Model of immersive technology in healthcare education (MITHE) This single-study quasi-experimental investigation was conducted at a single site. Nine participants were recruited, consisting of medical students and healthcare professionals. Participants were trained on varied immersive devices: sepsis management using an immersive VR simulation developed by Gogglemind, and augmented reality (AR) holographic patient with respiratory distress, which included realistic patient scenarios and interactive decision-making. User experience was measured using the ITEM, which assesses user; immersion, cognitive load, intrinsic motivation, debrief and technology usability. Nine participants had high levels of immersion (mean 39.6, total 50), high levels of intrinsic motivation (mean 39.6, total 50), high technology score (mean 79.4, total 100), optimum cognitive load (average 59.5, optimum 39–61) and moderate score on debrief (mean 18.1, total 25). ITEM subscores indicated an enjoyable and immersive experience with good technology interface on usability scores. Self-directed debrief in VR had lower scores with emotional considerations and identifying domains of performance and learning. The use of the ITEM provided valuable insights into the user experience of the VR simulation, which can be used to improve the design and implementation of future simulations. This contributes to an ongoing ITEM validation process. This study highlights the importance of training in healthcare and the potential benefits of using immersive technologies such as VR and AR simulations. Authors confirm that all relevant ethical standards for research conduct and dissemination have been met. The submitting author confirms that relevant ethical approval was granted, if applicable.

The Method User Experience Questionnaire Analysis of Identitas Kependudukan Digital Application

User Experience (UX) becomes important to explore and fulfill the needs for developing user-focused applications or products. The problems that exist to measure the level of user experience in the Digital Resident Identity (IKD) application and complaints submitted by users tend to lead to system and service quality problems in the IKD application. Then research purposes are assessed to evaluate the extent to which users can utilize and interact with the application. The method used by researchers is the User Experience Questionnaire (UEQ). UEQ is a widely used scoring methodology used to quantitatively measure user experience by administering a questionnaire to individuals that measures their subjective experiences and perceptions. Variables in UEQ, namely: efficiency, perspicuity, dependability, novelty, stimulation, and interestingness. The evaluation results of user experience in IKD applications using UEQ showed that there were 5 variables that received positive evaluation results, including attractiveness variables (mean 2.14), clarity variables (perspicuity) (mean 1.725), efficiency variables (efficiency) ( mean 1.725), accuracy variable (mean 1.525), and stimulation variable (mean 1.475). Whereas the novelty variable (mean 0.602) gets neutral evaluation results. From these results it can be used by IKD application developers to improve the user experience (user experience) of IKD applications on novelty variables by improving the appearance of applications that are more creative, inventive, and also cutting edge. The developer can pay attention to the recommendations that have been presented in this study. Parties who wish to conduct further research can use other evaluation methods such as Heuristic Evaluation.