Title:	MARKUP LANGUAGE FOR COGNITIVE AND CONTEXT-AWARE ADAPTABLE USER INTERFACES
Author(s):	Sohail Rafiqi, Suku Nair, Ephrem Fernandez
ISBN:	978-989-8533-20-3
Editors:	Hans Weghorn
Year:	2013
Edition:	Single
Keywords:	Cognitive and Context-Aware User Interfaces, Cognitive Load, Affective States, Usability, Reliability, Security
Type:	Full Paper
First Page:	83
Last Page:	91
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	With the widespread deployment of electronic systems, human interaction with computers is continuously increasing. Graphical User Interface (GUI) is the most pervasive method of human-computer interaction. The advent of GUI over 40 years ago and constant improvements have tremendously enhanced productivity. The times have, however, changed where applications are used anywhere/anytime and applications need to understand the changing contexts and human factors that impact usability of the system. GUI is the center of the User Experience (UX) that has direct impact on the usability, reliability and security of the system. Improving user experience by enhancing usability is at the center of this research. While some work is being done on enhancing User Interface, mostly the current interfaces are designed for masses, and have more or less worked as users have adapted themselves to work around the shortcomings and pitfalls of the system. Human behavior is extremely unpredictable, and error prone, the majority of these mistakes are very costly and some are even life threatening. Our work is focused on enhancing the usability and reliability of the application by developing the dynamic adaptable framework that constantly captures and analyzes user’s biometric data (e.g. pupillometric indices of cognitive load), environmental analysis, location and time to make real-time enhancements to the user interface. In this paper, we present the overview of the framework and provide the details of the newly proposed XML-based markup language (CCAML) that enables development of dynamic cognitive and context-aware applications.
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