# Asymmetries in Collaborative Wearable Interfaces

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5 Overall, subjects felt that the AR condition was more difficult to communicate in than the audio only (AO) and videoconferencing conditions (VC). Figure 5 shows a graph of average subject responses to the question on overall communication; Rate each communication mode according to how much effort you felt it was to converse effectively (0=Very Hard, 14=Very Easy) No-HMD HMD AO VC AR No-HMD HMD Table 2: Average Awareness Scores Finally, figure 6 shows the average response to the statement The mode of communication aided work. As can be seen the AR condition is again rated less helpful than both the audio and video conferencing conditions. A two factor repeated measures ANOVA finds a near significant difference in scores both between conditions (F(2,47)=3.17, P=0.054), but not between subjects (F(1,47)=0.04, P=0.80) AO VC AR 8 6 No-HMD HMD Fig 5: Communication Effort Across Conditions Using a two factor (subject, condition) repeated measures ANOVA, we find a significant difference in scores between conditions (F(2,47)=4.19, P<0.05), but not between subjects (F(1,47)=0.20, P=0.65). A similar result is found in the communication survey given at the end of every condition. Table 1 shows the average response to the statement I was very aware of the presence of my conversational partner (0=Disagree, 14=Agree). The AR condition is given a co-presence rating between that of the audio and video conferencing conditions. Using a two factor repeated measures ANOVA, we find a significant difference in scores between conditions (F(2,47)=4.99, P<0.05), but not between subjects (F(1,47)=0.01, P=0.90). AO VC AR No-HMD HMD Table 1: Average Co-Presence Score Subjects also felt that the visual cues provided by the AR condition were not as useful as the cues provided by the video conferencing condition for determining if their collaborator was busy. Table 2 shows the average scores in response to the question; I could readily tell when my partner was occupied and not looking at me. Using a two factor repeated measures ANOVA, we find a significant difference in scores between conditions (F(2,47)=15.70, P<0.01), but not between subjects (F(1,47)=0.40, P=0.70). Both the video and AR conditions were rated significantly higher than the audio AO VC AR Figure 6: How Much Conditions Aided Work Subject Comments Several subjects commented on the asymmetries introduced by the AR interface. Most of these comments were about the functional asymmetry of the interface. Some desktop users found it disconcerting that the AR user could see them, but they couldn t see the AR user. They also felt uncomfortable seeing their own face in the task space video sent back by the AR user and said that set up an unequal relationship. The virtual image of the remote person was also seen as distracting by some people, especially when it flickered in and out of sight due to the narrow field of view of the head mounted display. Discussion In this experiment subjects were given the same task and access to the same information. However in the AR condition functional, implementation and social asymmetries were present. As these results show these significantly impacted how well the subjects felt they could collaborate together, in some cases causing the subject to feel the AR condition was even less useful than audio alone. These results seem to support our theory that if the roles of the collaborators are the same then combinations of functional, implementation and social asymmetries may impede the collaboration.

7 A single factor ANOVA was used to compare between the average subject scores for each question. Table 4 shows the average answers for each of these questions across the different frame rates, the ANOVA F statistic (F(3,28) and resulting P significance value. 0 ¼ 1 30 F stat. P Value Q1* P<0.01 Q2* P<0.01 Q3* P<0.01 Table 4a: Average Expert Response 0 ¼ 1 30 F stat. P Value Q1* P<0.05 Q2* P<0.05 Q3* P<0.05 Table 4b: Average Wearable User Response As can be seen from these tables all the responses are significantly different. Subjects felt that as the frame rate increased they could understand the situation better (Q1), communicate more effectively (Q3) and give and get guidance more effectively (Q2). In the wearable users case there was little difference between ranking on these questions between 1 and 30 fps, while the expert always ranked the 30 fps case much higher than the 1 fps case. This difference is particularly noticeable in the answers to question 5; What degree of co-presence did you feel with the expert/wearable user (1=None, 10=Very Present)? Figure 8 shows the average scores for the expert and wearable user across the different frame rates. A single factor ANOVA gives a significant difference between the experts co-present ratings (F(3,28) = 9.38, P< 0.05), but not for the wearable user (F(3,28) = 2.95, P = 0.35) FR=0 FR=1/4 FR=1 FR=30 Expert Wearable Fig 8. Subject ratings of Co-Presence (Q5). Interface Components: Subjects were also asked to rank how helpful the individual interface components were on a scale of 1 to 10 (1 = little help, 10 = very helpful). For the expert the interface components were audio (A), video of the task space (TS), shared graphics images (SG), the ability to annotate on the graphics images (AG), and the ability to annotate on the video image (AV). While the wearable user considered the following components; audio (A), the expert view of task space (EV), and the shared graphics image (SG). Table 3a shows the expert users average ratings for each of the components, the ANOVA F statistic (F(3,28)) and the resulting P significance values. Table 5b shows the wearable users component ratings. 0 ¼ 1 30 F stat P values A TS* NA < 0.01 SG AG AV* NA < 0.01 Table 5a: Expert Ratings of Interface 0 ¼ 1 30 F stat P values A EV NA SG Table 5b: Wearable User Interface Ratings As can be seen there are no significant differences between wearable user ratings for interface components across different frame rates. However the remote expert found the video of the task space and the ability to annotate on the video significantly more useful as the frame rate increased. Both the wearable user and expert rated audio as the most helpful interface component. Using a two factor (frame rate, interface component) repeated measures ANOVA we can compare ratings for the different interface components. Doing this for the wearable user we find no significant difference between frame rates (F(2,63)=0.32, P = 0.74), but a highly significant difference in results between interface components (F(2,63)=21.64, P<0.001). Similarly, for the expert user we find a highly significant difference both between frame rates (F(2,90)=15.15, P <0.001), and between interface components (F(4,90)=16.69, P<0.001). Discussion These results agree with our second hypothesis. The wearable users felt they could collaborate equally well with 1 fps video as with 30 fps video, while the experts felt they needed high video frame rates for more effective collaboration. Similarly the experts rated the video view of the task space and the ability to draw on the video significantly more useful as the frame rate increased, while the wearable user thought the usefulness of the experts view didn t change as the frame rate increased. This implies that the expert and wearable user should be able to collaborate together effectively if there is the

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