7 resultados para User Centred Design
em CORA - Cork Open Research Archive - University College Cork - Ireland
Resumo:
Since children already use and explore applications on smartphones, we use this as the starting point for design. Our monitoring and analysis framework, BaranC, enables us to discover and analyse which applications children uses and precisely how they interact with them. The monitoring happens unobtrusively in the background so children interact normally in their own natural environment without artificial constraints. Thus, we can discover to what extent a child of a particular age engages with, and how they physically interact with, existing applications. This information in turn provides the basis for design of new child-centred applications which can then be subject to the same comprehensive child use analysis using our framework. The work focuses on the first aspect, namely, the monitoring and analysis of current child use of smartphones. Experiments show the value of this approach and interesting results have been obtained from this precise monitoring of child smartphone usage.
Resumo:
An overview is given of a user interaction monitoring and analysis framework called BaranC. Monitoring and analysing human-digital interaction is an essential part of developing a user model as the basis for investigating user experience. The primary human-digital interaction, such as on a laptop or smartphone, is best understood and modelled in the wider context of the user and their environment. The BaranC framework provides monitoring and analysis capabilities that not only records all user interaction with a digital device (e.g. smartphone), but also collects all available context data (such as from sensors in the digital device itself, a fitness band or a smart appliances). The data collected by BaranC is recorded as a User Digital Imprint (UDI) which is, in effect, the user model and provides the basis for data analysis. BaranC provides functionality that is useful for user experience studies, user interface design evaluation, and providing user assistance services. An important concern for personal data is privacy, and the framework gives the user full control over the monitoring, storing and sharing of their data.
Resumo:
A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.
Resumo:
Major factors influencing food development and food marketing strategies in global market places at present can be attributable to the changing age structure of the population. The significant shifts in global age structure will inevitably lead to the number of people aged 60 reaching an all-time high of one billion by the year 2020. The rapidly growing population of ageing people globally represents a large, neglected and very much under-developed category within the Food Industry. The primary focus of this study was the integration of knowledge creation techniques at early NPD stages, for the development of market-oriented new health promoting foods for the ageing population. The methodology of this study was centered on an exploratory sequential mixed methods strategy. Stage one of the study involved in-depth semi-structured interviews with 16 Stakeholders to facilitate the need identification stage of the NPD process. The main outputs identified were the need for: the fortification of foods for a preventative nutrition approach, the development of foods that targeted age-related conditions such as cognitive, heart, gut and bone health, the integration of ageing compensatory packaging adaptations and the creation of marketing messages with an active lifestyle message. Stage two consisted of a market-oriented computer assisted NPD technique, a user centered design interaction (UCD) to integrate consumers as co-creators throughout the idea generation stage of the NPD process. The most important product attributes identified in this stage included: products targeted at brain and cognitive health, liquid based beverages, easy to use packaging with environmentally friendly elements, simplistic marketing with a clear focus on health not age and realistic health claims constructed with consumer friendly terminology. Finally, Stage three used an abbreviated means-end chain (MEC) analysis to complete the concept development stage of the NPD process. This stage identified commercial information that could be used by food firms for the development of positioning and communication strategies. Equally, the information generated could be of high strategic importance to governments, policy makers, health professionals and medical professionals. The values and goals listed in this stage included: better overall health, active lifestyle, optimum nutrition and wellbeing feelings. Overall, this research illustrated that knowledge creation techniques can assist firms in the development of market-oriented health promoting foods for the ageing population.
Resumo:
User Quality of Experience (QoE) is a subjective entity and difficult to measure. One important aspect of it, User Experience (UX), corresponds to the sensory and emotional state of a user. For a user interacting through a User Interface (UI), precise information on how they are using the UI can contribute to understanding their UX, and thereby understanding their QoE. As well as a user’s use of the UI such as clicking, scrolling, touching, or selecting, other real-time digital information about the user such as from smart phone sensors (e.g. accelerometer, light level) and physiological sensors (e.g. heart rate, ECG, EEG) could contribute to understanding UX. Baran is a framework that is designed to capture, record, manage and analyse the User Digital Imprint (UDI) which, is the data structure containing all user context information. Baran simplifies the process of collecting experimental information in Human and Computer Interaction (HCI) studies, by recording comprehensive real-time data for any UI experiment, and making the data available as a standard UDI data structure. This paper presents an overview of the Baran framework, and provides an example of its use to record user interaction and perform some basic analysis of the interaction.
Resumo:
Mobile Cloud Computing promises to overcome the physical limitations of mobile devices by executing demanding mobile applications on cloud infrastructure. In practice, implementing this paradigm is difficult; network disconnection often occurs, bandwidth may be limited, and a large power draw is required from the battery, resulting in a poor user experience. This thesis presents a mobile cloud middleware solution, Context Aware Mobile Cloud Services (CAMCS), which provides cloudbased services to mobile devices, in a disconnected fashion. An integrated user experience is delivered by designing for anticipated network disconnection, and low data transfer requirements. CAMCS achieves this by means of the Cloud Personal Assistant (CPA); each user of CAMCS is assigned their own CPA, which can complete user-assigned tasks, received as descriptions from the mobile device, by using existing cloud services. Service execution is personalised to the user's situation with contextual data, and task execution results are stored with the CPA until the user can connect with his/her mobile device to obtain the results. Requirements for an integrated user experience are outlined, along with the design and implementation of CAMCS. The operation of CAMCS and CPAs with cloud-based services is presented, specifically in terms of service description, discovery, and task execution. The use of contextual awareness to personalise service discovery and service consumption to the user's situation is also presented. Resource management by CAMCS is also studied, and compared with existing solutions. Additional application models that can be provided by CAMCS are also presented. Evaluation is performed with CAMCS deployed on the Amazon EC2 cloud. The resource usage of the CAMCS Client, running on Android-based mobile devices, is also evaluated. A user study with volunteers using CAMCS on their own mobile devices is also presented. Results show that CAMCS meets the requirements outlined for an integrated user experience.