Abstract:
ABSTRACT
The mobile technology being one of the fastest growing industrial sectors ever, mobile devices use is a phenomenon that has crossed all age and gender boundaries globally. Mobile applications have blossomed in popularity and ubiquity, with each generation, the multitude and diversity of applications continues to grow. Increasingly large number of the applications installed on smartphones tends to slow the application access efficiency. The results of a study carried out on elderly and mobile devices interactions indicates that users with declining abilities as a result of aging find it difficult to navigate the complex structure of the modern mobile devices interface. Support that can improve daily application interaction experience is poised to be widely beneficial. This research has realized an intelligent application predictor, which predicts the applications that are most likely to be accessed by the user; prediction is based on Naïve Bayesian model leveraging the application accessed properties such as frequency of access, time of access, the health and economic benefit of the application. An evaluation study involving six elderly users was carried out where the predictor was installed in their mobile devices for six weeks,a survey based on three aspects: interface presentation, navigation experience and overall satisfaction. All respondents rated application predictor high in aiding users and saving them on memory trying to recall applications, the users reported increase in efficiency when using the predictor compared to the interaction with the standard user interface (UI).
