Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/40290
Title: Comparison of adaptive user interfaces in a student study aid application
Authors: Mallia, George
Keywords: User interfaces (Computer systems)
Application software -- Development
Educational technology
Issue Date: 2018
Citation: Mallia, G. (2018). Comparison of adaptive user interfaces in a student study aid application (Bachelor's dissertation).
Abstract: Since adaptive user interfaces (AUIs) have gained popularity over the years, they are a concept that are currently being applied and used for common applications and systems. “There is no such thing as an average user” . Efficiency and user satisfaction in the interface is determined by knowing who the target users are, thus, knowing how the potential users will use the system. In this FYP, we experiment with the development of two different adaptive user interfaces in a student study application aimed to determine whether there is a difference in the overall user satisfaction, efficiency and overall usability between the two implemented interfaces. An initial survey was conducted with potential users to shed light on the possible segments within the target demographic. Representations of these segments were created in the form of personas. Once the system was designed and implemented, based on the personas created, the mechanisms responsible for the adaptive features were implemented and integrated with the base application, to aid the user whilst performing particular everyday tasks. One interface provides adaptive recommendations to the users based on a predefined list of relationships between the features while the other interface provides adaptive recommendations using association rule mining. To check whether there is a difference between the two interfaces in how they provide the adaptive recommendations; the system was given to the users for a period of time and a usability test was performed to gather enough data to try and demonstrate the hypotheses. This hypothesis states that the adaptive user interface with usage mining will allow the user to perform better than the normal adaptive interface since it provides a more personalized interface. Once the data was collected in the usability testing, a statistical analysis on the data was performed to check whether there is a significant difference between the efficiency, usability and satisfaction whilst using the two interfaces implemented.
Description: B.SC.SOFTWARE DEVELOPMENT
URI: https://www.um.edu.mt/library/oar//handle/123456789/40290
Appears in Collections:Dissertations - FacICT - 2018
Dissertations - FacICTCIS - 2018

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