Nozawa presentation

Efficacy of Technical Illustrations in a Technical Communication

Environment Masato Nozawa (s1170033)

Technical Communication Lab

University of Aizu

February 2013 1 Graduation Thesis Presentation

Overview �  Introduction �  Problem � Method ◦  Research tool ◦  Participants ◦  Data Collection ◦  Data Analysis

�  Results � Discussion � Conclusion and Future Work


Introduction � What is mental imagery? Our general understanding of how different objects

functions in space without direct visualization.

�  Pursue a mental rotation. This is the ability to rotate two-dimensional and three-

dimensional objects in space but as an internal representation of the mind.


Problem � How do we design body/object positions

in user manuals most effectively for second language speakers such that a minimalist text approach is viable?

� How do we enhance a motor skill

efficiently by using user manual?


Research tools 1 � Poser Figure Artist software This is used to design body positions and

angles.


Research tools 2 �  SPSS software

This is a software package used for statistical analysis. In this study, it was used to measure users’ accuracy with different body angles (5 positions), height of the bat and action positions (holding versus hitting).


Participants ･41 subjects(student of Aizu university).

These subjects had no pervious experience with design analysis or perspective studies.


Data collection ･ 41subjects took part in the experiment and each subject rated 40

image types, divided into two blocks of 20 each.

This study considered only one set of analysis (20 image combinations): Bat positions (holding and hitting; chest and waist height and 5 angular rotations).


Data Analysis – Mean Accuracy Scores


Result 1

.64

.66

.68

.70

.72

.74

.76

.78

.80

.82

.84

.86

.88

.90

.92

.94

Holding chest front

Holding chest 1/3 side

Holding chest side

Holding chest 1/3 back

Holding chest back

mean

mean

Maximum value: .93

Minimum value: .83

Holding - Chest


Result 2

.64

.66

.68

.70

.72

.74

.76

.78

.80

.82

.84

.86

.88

.90

.92

.94

Hitting chest front

Hitting chest 1/3 side

Hitting chest side

Hitting chest 1/3 back

Hitting chest back

mean

mean

Maximum value: .85

Minimum value: .66

Hitting - Chest


Result 3

.64

.66

.68

.70

.72

.74

.76

.78

.80

.82

.84

.86

.88

.90

.92

.94

Holding waist front

Holding waist 1/3 side

Holding waist side

Holding waist 1/3 back

Holding waist back

mean

mean

Maximum value: .93

Minimum value: .85

Holding - Waist


Result 4

.64

.66

.68

.70

.72

.74

.76

.78

.80

.82

.84

.86

.88

.90

.92

.94

Hitting waist front

Hitting waist 1/3 side

Hitting waist side

Hitting waist 1/3 back

Hitting waist back

mean

mean

Maximum value: .93

Minimum value: .68

Hitting - Waist


Discussion The data as obtained from this study remains

inconclusive as to whether there could be a strict preference for canonical viewpoints showing three-quarter views and depth perceptions.

However, preliminary indications suggest that canonical viewpoints have higher levels of accuracy, along with some other combinations.

Further analysis of body heights and angular combinations are required for future studies.


Conclusion and future work My main purpose of this study is aimed at carrying

forward the studies performed by Krull et al (2004) and Krull and Roy (2005).

�  Future work ü  Various actions 1. Carrying 2. Lifting 3. Pulling 4. Pushing ü  Differentiate between postures 1. Chair 2. Ball 3. Box 4. Handle 5. Sphere/Triangle


February 2013 Graduation Thesis Presentation 16

Thank you

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