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Smartphone Text Input Method Performance, Usability, and Preference With Younger and Older Adults.
Amanda L Smith1, Barbara S Chaparro2
1Wichita State University, Wichita, Kansas amanda.smith@wichita.edu.
Human Factors
|April 8, 2015
Summary
Voice and physical Qwerty smartphone text input methods are most effective for both younger and older adults. Handwriting input performed the worst, highlighting design implications for diverse user groups.
Area of Science:
- Human-Computer Interaction
- Usability Engineering
- Gerontology
Background:
- Smartphones are integral for communication beyond calls, including texting and web browsing.
- Existing research on smartphone text input methods shows significant variability in findings.
- This study directly compares five common input methods for novice younger and older adult users.
Purpose of the Study:
- To compare user performance, perceived usability, and preference for five smartphone text input methods.
- To evaluate these methods across two distinct age groups: younger (18-35) and older (60-84) novice adults.
- To identify effective and ineffective text input strategies for different demographics.
Main Methods:
- Fifty novice adult participants (25 younger, 25 older) performed text entry tasks.
- Five input methods were tested: physical Qwerty, onscreen Qwerty, tracing, handwriting, and voice.
- Data collected included entry speed, error rates, perceived usability, and user preference.
Main Results:
- Voice input was equally fast for both age groups; older adults were slower with other methods.
- Physical Qwerty and voice input yielded low error rates for both groups.
- Older adults made more errors with onscreen Qwerty, tracing, and handwriting.
- Voice and physical Qwerty were preferred by both age groups; handwriting was least preferred and performed worst.
Conclusions:
- Voice and physical Qwerty are the most effective smartphone text input methods for both younger and older adults.
- Handwriting input is the least effective method overall for novice users.
- Findings inform the design of future smartphone text input interfaces, especially for older adults.

