CatchIt: Capturing Cues of Bookmarked Moment to Feed Digital Parrot

Abstract

CatchIt is a mobile application which aims to capture information about moments in a user’s life in a semi-automatic way. The captured moments are then ready to be fed into an augmented memory system for later retrieval.

In CatchIt, the time and location contexts of the captured moment will be saved automatically from the system and GPS respectively once the user bookmarks the moment with the ability of modifying them later; whereas the desired other context, people, will be saved manually. The user of CatchIt also can capture further details (contents) of the moments by different ways: taking notes (textual information), taking photo, recording video, and recording audio. Additionally, the user can revise an earlier moment if the user wishes to. Later on, the user can transfer the selective bookmarked moments into the augmented memory system called the Digital Parrot. The implementation of CatchIt is the central focus of this study. To do so, the requirements of CatchIt are specified based on results of a previous study and from a scenario. The conceptual architecture and the user interface of CatchIt are designed according to the CatchIt requirements. The user interface is implemented in addition to the database where is the captured information from the user interface will be stored in and retrieved from. Evaluating the usability of CatchIt will come next. In the evaluation, the study will involve three sessions: (1) initial questionnaire to know more about the preferred capturing ways of different scenarios, (2) testing the applications where an existing mobile application, Hansel, will be tested for the same length of testing CatchIt (one week for each) and (3) a guided interview which will extract the usability of CatchIt comparing with Hansel on one hand and adding a new contact to the phone using the application Contacts. An additional goal of the last session of the study will be to extract the feeling and the interests of using CatchIt. The results of this study indicated the user interface of CatchIt needs to be even easier to use. The findings of the study form the foundation for further work to improve the user interface of CatchIt and to understand more of the user needs of such mobile capturing application.