Improving User Experience with Multi-Dimensional Factors for Effective Interactions in a Dynamic Environment

Abstract

In the field of Human-Computer Interaction (HCI), improving User Experience (UX) of mobile devices has become a necessity due to the emergence of smart technologies and with the popularity of using mobile devices in day to day life rather than traditional desktop systems. The main aim of this research is to develop a model for a mobile device that can suggest adaptive functionalities, based on the current user emotion and the context. To the best of our knowledge, there are not any systems which provide not only adaptive interfaces but also provides adaptive functionalities within a mobile device which will enhance the acceptability and usability of that particular system. As a proof of concept, a keyboard named “Emotional Keyboard” was developed through five prototypes using Evolutionary Prototyping, iteratively. As the methodology, Action Research together with User-Centered Design (UCD) was followed which also included two user surveys. Initial decisions were taken after conducting the first survey and Prototypes 1, 2 and 3 have been developed and those have been evaluated with the participation of 40 users. Prototype 3 has incorporated an Artificial Neural Network (ANN) that was trained using the data collected during the evaluations of the Prototypes 1 and 2, which can decide the most optimal emotion by combining the emotions from facial expressions and text. Consequently, Prototype 4 and 5 were developed which can suggest the most affective function based on the emotion and the context (location, time and user activity), by incorporating the data that was collected by conducting the second survey and built a “Preference Tree” which consists the probabilities of choosing functions and also considering the frequently used functions. The evaluation of Prototype 4 and 5 have been carried out with the participation of 18 users, where an individual and general analysis has been performed and proved that with time the model was able to correctly suggest adaptive functions. This evaluation yields the conclusion of the research, thus paving the way to an “Adaptive System with User Control” to improve the acceptability and the usability of a mobile device which aligns with the research aim