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Articles

ContextZoom: A Single-Handed Partial Zooming Technique for Touch-Screen Mobile Devices

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ABSTRACT

Despite its ubiquitous use, the pinch zooming technique is not effective for single-handed interaction with touch-screen mobile devices. A novel technique for single-handed zooming on touch-screen mobile devices, ContextZoom, is proposed in this paper. It allows users to specify any location on a device screen as the zooming center and ensures that this intended zooming center remains at the original location after zooming. ContextZoom works as an add-on feature for existing zooming techniques by supporting zooming in/out a portion of a viewport and provides a quick switch between partial and whole viewports, which can be operated with a single hand only. An empirical evaluation of ContextZoom through a controlled laboratory experiment was conducted to compare participants’ performance and perceptions while using the Google Maps’ single-handed (GMS) zooming technique and a button-based (BB) zooming technique with and without ContextZoom. Results show that equipped with ContextZoom, users’ performances with the GMS zooming technique and the BB zooming technique in partial viewport zooming were improved significantly in terms of task completion time and number of discrete actions. Participants also reported higher levels of perceived effectiveness and overall satisfaction with ContextZoom than without ContextZoom while using the GMS zooming technique and reported a similar level of perceived ease of use. On the other hand, ContextZoom increased the completion time but reduced the number of discrete actions in whole viewport zooming, and users did not perceive ContextZoom as a whole viewport zooming tool as well as its counterparts.

Funding

This material is based upon work supported by the National Science Foundation (Award #: IIS-1250395). Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the 815 National Science Foundation.

Additional information

Funding

This material is based upon work supported by the National Science Foundation (Award #: IIS-1250395). Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the 815 National Science Foundation.

Notes on contributors

Jianwei Lai

Jianwei Lai is an assistant professor in the School of Information Technology at Illinois State University. Her research interests include human–computer interaction and ubiquitous computing, primarily focusing on mobile interaction techniques.

Dongsong Zhang

Dongsong Zhang received his Ph.D. in Management Information Systems from the University of Arizona. He is a full professor in the Department of Information Systems at the University of Maryland, Baltimore County, USA. His research interests include mobile HCI, social computing, and health IT.

Sen Wang

Sen Wang is a master student in Information Systems at University of Maryland, Baltimore County. He is interested in human–computer interaction and data mining research.

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