Date of Award

5-2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Industrial Engineering

Committee Chair

Vincent G. Duffy

Committee Member 1

Mark Lehto

Committee Member 2

Mihaela Vorvoreanu

Committee Member 3

Nathan W. Hartman

Abstract

The objective of this research is to use four individual studies to validate the Object-Oriented User Interface Customization (OOUIC) framework for solving three challenges of implementing User Interface (UI) customization in Complex Information System (CIS) and improving usability and user performance of complex UI. The first challenge is that adaptive UI, which tailors a UI to be relevant to a user role, has difficulties in identifying numerous users’ complex requirements and simplifying UIs for them. The second challenge is that adaptive UI cannot satisfy every individual’s unique needs. The third challenge is that adaptable UI, which allows a user to adjust UI objects to meet his or her needs, has a low acceptance rate, especially when the UI is complex. To solve these challenges, the OOUIC framework applies User-Centered Design (UCD) to develop adaptive UI, implements interactive adaptable UI to motivate users to customize UI, combines adaptive UI and adaptable UI to satisfy each individual’s needs, and relies on Artificial Intelligence (AI) to support users to use adaptable UI. This framework is an iterative process to ensure usability and user performance of CIS. The first study used Use Case Analysis (UCA) to develop adaptive UIs for CIS and justified that adaptive UIs had less complexity than original UIs of CIS. Thus, the first study proved that the first challenge could be solved by UCD methods. The second study compared drag-and-drop method with click method on editing UI objects in complex UI and proved that drag-and-drop could trigger users’ intention to accept adaptable UI. This study indicated that the third challenge could be concurred by using interactive adaptable UI. The third study investigated adaptive UI, adaptable UI, and combination UI of these two customization techniques and demonstrated that combination UI improved usability and user performance of complex UI and adaptive UI. The fourth experiment used interruption as a factor to validate that adaptive UI, adaptable UI, and combination UI could still improve user performance when an interruption occurred, and they could minimize adverse effects of interruption. Thus, combining adaptive UI and adaptable UI could solve the second challenge and improve usability and user performance of complex UI. These studies validated the efficacy of OOUIC framework for solving three challenges of implementing UI customization in CIS and improving usability and user performance of complex UI. The findings of this research may serve as references for designers to apply UI customization in CIS to simplify complex UI and trigger users' intention to tailor the UI, which will subsequently satisfy user needs and increase usability and user performance of CIS.

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