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Mobile Interaction | HCI | Paper Summary

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This is a summary of all mandatory papers, which are required to learn for the final exam.

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  • September 16, 2024
  • 4
  • 2024/2025
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Paper 1: Innova-ve Text Entry Systems
Goal
To evaluate the effec-veness of a novel -lt-based text entry technique called Shape Wri-ng
in Mo-on (SWiM) for single-handed text entry on large mobile devices.

Approach
The study compared three text entry techniques: one-thumb typing, one-thumb shape
wri-ng, and SWiM. Par-cipants completed transcrip-on and composi-on tasks using these
techniques. A longitudinal study was also conducted with one par-cipant to observe
performance improvement over -me.

Results
• Transcrip3on Task: SWiM had a lower entry rate (15.48 wpm) compared to one-
thumb typing (25.22 wpm) and shape wri-ng (29.03 wpm).
• Composi3on Task: SWiM's entry rate was about half of the other techniques.
• Longitudinal Study: Significant improvement in SWiM's entry rate over -me,
reaching 32.18 wpm aRer several sessions.
• Error Rate: SWiM had a higher error rate compared to other techniques but showed
improvement with prac-ce.

Conclusion
SWiM, while ini-ally slower and more error-prone, showed significant improvement with
prac-ce, indica-ng poten-al for effec-ve single-handed text entry on large devices. It is
par-cularly useful when the user's other hand is encumbered.


Paper 2: ForceRay: Extending Thumb Reach via Force Input
Goal
To develop and evaluate ForceRay (FR), a technique that extends thumb reach via force input
to enable selec-on of out-of-reach targets on large mobile touchscreens while maintaining a
stable device grip.

Approach
Two user studies were conducted:
1. Study 1: Compared FR to direct touch (DT), One-Handed Mode (OM), MagS-ck (MS),
and BezelCursor (BC) in terms of speed, accuracy, and device mo-on.
2. Study 2: Evaluated trained user performance of FR and BC over mul-ple sessions.

Results
• Study 1: FR caused the least device mo-on but was slower and had a slightly higher
error rate than BC.
• Study 2: Training improved performance for both FR and BC, with FR becoming
almost as fast as BC for border targets.

Conclusion

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