Determinar la experiencia de usuario al usar dispositivos y aplicaciones de Inteligencia Ambiental en actividades cotidianas.
Las técnicas asociadas a la inteligencia ambiental permiten tomar un entorno de uso común y convertido en un ambiente proactivo, más amigable o bien que provea de datos para tomar decisiones acertadas. Esto es posible gracias al uso de sensores y actuadores que proveen de los datos necesarios para determinar el estado del entorno. En este proyecto se desea considerar distintos entornos cotidianos para determinar la experiencia de usuario al utilizar distintos dispositivos y aplicaciones en el contexto de un ambiente inteligente.
Impacto del proyecto
Las actividades que se desean desarrollar en este proyecto tienen el potencial de:
-Desarrollar conocimiento en nuevas área de experticia.
-Acercar a estudiantes de pregrado y posgrado para participar en la implementación de nuevas formas de interacción.
-Promover el uso de nuevas tecnologías (sensores y actuadores) para ponerlos al servicio de la comunidad.
-Incentivar el desarrollo de proyectos de graduación a nivel de licenciatura y maestría en un área innovadora.
-Proveer de herramientas para evaluar formas innovadoras de interacciones entre personas y ambientes inteligentes (o bien, y los dispositivos embebidos en el ambiente).
Luis Quesada Quirós
Luis Quesada Quirós
Unidades académicas colaboradoras
Standardized questionnaires are one of the methods used to evaluate User Experience (UX). Standardized questionnaires are composed of an invariable group of questions that users answer themselves after using a product or system. They are considered reliable and economical to apply. The standardized questionnaires most recognized for UX evaluation are AttrakDiff, UEQ, and meCUE. Although the structure, format, and content of each of the questionnaires are known in detail, there is no systematic literature review (SLR) that categorizes the uses of these questionnaires in primary studies. This SLR presents the eligibility protocol and the results obtained by reviewing 946 papers from four digital databases, of which 553 primary studies were analyzed in detail. Different characteristics of use were obtained, such as which questionnaire is used more extensively, in which geographical context, and the size of the sample used in each study, among others.
Tipo de publicación: Journal Article
Publicado en: 13th International Conference on Ubiquitous Computing and Ambient Intelligence UCAmI 2019
This paper proposes the creation of a smart meeting room through the incorporation of a PIR sensor and an AWS IoT button that allows the booking system to reflect a more precise availability of meeting rooms according to the actual occupancy status. The Internet of Things (IoT) devices are controlled using a Wi-Fi module that allows them to connect to the REST web service and to integrate with the open source Meeting Room Booking System (MRBS). In order to evaluate the system a storyboard evaluation was conducted with 47 participants. All participants filled out the User Experience Questionnaires (UEQ), described the product using three words and expressed their opinion through open comments. Finally, 19 participants took part in a real-life simulation of the smart meeting room and evaluated the system using the UEQ questionnaire. Based on the positive acceptance reflected in the evaluations, results show that the proposed system is considered very attractive and useful by the participants.
Tipo de publicación: Conference Paper
Publicado en: 2019 IV Jornadas Costarricenses de Investigación en Computación e Informática (JoCICI)
t present, there are systems in charge of classifying and sending notifications to smart devices at different times. However, there are not many studies that demonstrate the effectiveness of these systems in real world settings. We propose a method that classifies and prioritizes notifications by analyzing only the content of the notification and the sender of the message. We also developed a system implementing this method. User diaries were used to analyze the behavior of the system in real world situations, and the results showed that the implemented system significantly reduces interruptions to users. Additionally, the user experience of the system was evaluated through the standardized questionnaire UEQ (User Experience Questionnaire). The results obtained were positive in most of the scales of this instrument, above the average according to UEQ benchmarks. However, aspects such as stimulation and creativity can be improved in the future to motivate users to use the system.
Tipo de publicación: Book Chapter
Publicado en: Advances in Intelligent Systems and Computing
Standardized questionnaires are well-known, reliable, and inexpensive instruments to evaluate user experience (UX). Although the structure, content, and application procedure of the three most recognized questionnaires (AttrakDiff, UEQ, and meCUE) are known, there is no systematic literature review (SLR) that classifies how these questionnaires have been used in primary studies reported academically. This SLR seeks to answer five research questions (RQs), starting with identifying the uses of each questionnaire over the years and by geographic region (RQ1) and the median number of participants per study (how many participants is considered enough when evaluating UX?) (RQ2). This work also aims to establish whether these questionnaires are combined with other evaluation instruments and with which complementary instruments are they used more frequently (RQ3). In addition, this review intends to determine how the three questionnaires have been applied in the fields of ubiquitous computing and ambient intelligence (RQ4) and also in studies that incorporate nontraditional interfaces, such as haptic, gesture, or speech interfaces, to name a few (RQ5). Methods. A systematic literature review was conducted starting from 946 studies retrieved from four digital databases. The main inclusion criteria being the study describes a primary study reported academically, where the standardized questionnaire is used as a UX evaluation instrument in its original and complete form. In the first phase, 189 studies were discarded by screening the title, abstract, and keyword list. In the second phase, 757 studies were full-text reviewed, and 209 were discarded due to the inclusion/exclusion criteria. The 548 resulting studies were analyzed in detail. Results. AttrakDiff is the questionnaire that counts the most uses since 2006, when the first studies appeared. However, since 2017, UEQ has far surpassed AttrakDiff in uses per year. The contribution of meCUE is still minimal. Europe is the region with the most extended use, followed by Asia. Within Europe, Germany greatly exceeds the rest of countries (RQ1). The median number of participants per study is 20, considering the aggregated data from the three questionnaires. However, this median rises to 30 participants in journal studies while it stays in 20 in conference studies (RQ2). Almost 4 in 10 studies apply the questionnaire as the only evaluation instrument. The remaining studies used between one and five complementary instruments, among which the System Usability Scale (SUS) stands out (RQ3). About 1 in 4 studies analyzed belong to ubiquitous computing and ambient intelligence fields, in which UEQ increases the percentage of uses when compared to its general percentage, particularly in topics such as IoT and wearable interfaces. However, AttrakDiff remains the predominant questionnaire for studies in smart cities and homes and in-vehicle information systems (RQ4). Around 1 in 3 studies include nontraditional interfaces, being virtual reality and gesture interfaces the most numerous. Percentages of UEQ and meCUE uses in these studies are higher than their respective global percentages, particularly in studies using virtual reality and eye tracking interfaces. AttrakDiff maintains its overall percentage in studies with tangible and gesture interfaces and exceeds it in studies with nontraditional visual interfaces, such as displays in windshields or motorcycle helmets (RQ5).
Tipo de publicación: Journal Article
Publicado en: Advances in Human-Computer Interaction