Jens Grubert delivered the presentation on August 28th, 2013 during the 15th edition of MobileHCI, International Conference on Human-Computer Interaction with Mobile Devices and Services in Munich, Germany.
ABSTRACT:
We repeated a study on the usage of a magic lens and a static peephole interface for playing a find-and-select game in a public space. While we reproduced the study setup and procedure the task was conducted in a public transportation stop with different characteristics. The results on usage duration and user preference were significantly different from those reported for previous conditions. We investigate possible causes, specifically the differences in the spatial characteristics and the social contexts in which the study took place.
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
ACM MobileHCI 2013 - Playing it Real Again: A Repeated Evaluation of Magic Lens and Static Peephole Interfaces in Public Space
1. Playing it Real Again:
A Repeated Evaluation of Magic Lens and Static
Peephole Interfaces in Public Space
Jens Grubert, Dieter Schmalstieg
Institute for Computer Graphics and Vision, Graz University of Technology
2. (How) do individuals use a Magic Lens interface in
public space if they can use an established interface?
switchable
Interfaces can be switched at any time.
Magic Lens (ML) Static Peephole (SP)
3. Research Questions
Confirmatory
Which interface would be used longer?
Which interface participants would prefer?
Exploratory
(How) does the setting influence the usage?
4. Design of Experiment
Between-subjects design
Factor: location
PUV: public space
(transit area, Vienna), n=10
PUG: public space
(transit area, Graz), n=8
LAB: laboratory, n=8
Dependent variables
Usage duration
Preference
PUV
PUG LAB
5. Findings
Confirmatory
Which interface would be used longer?
ML was used significantly less
compared to both PUG and LAB
(Kruskal-Wallis p < .001, post-hoc pairwise Mann-Whitney U)
PUV PUG LAB
44% 76% 68%
6. Findings
Confirmatory
Which interface participants would prefer?
“I enjoyed using the ML view in the environment”
ML was enjoyed significantly less
compared to PUG
(Kruskal-Wallis p < .001, post-hoc pairwise Mann-Whitney U)
PUV PUG LAB
3.5 5 4
10. A closer look at the spatial and social settings
PUV:
Mainly waiting area
Perceived social distance
Passers-by partly in
peripheral view of partic.
PUG:
Mainly transit area
Central square under CCTV
Passers-by behind partic.
11. PUV
241 passers-by
More and longer intrusions
into social and personal space
PUV: 50%
PUG
691 passers-by
Very few, short interactions
no interaction glimpses stay + watch > 5 sec
22% 8%
PUG: 68% 30% 2%
13. Summary
Repeated study on usage of ML and SP in public spaces
Sign. differences in usage time and preference
Potential causes: spatial and social setting
However, many potential confounding factors:
personality, demand characteristics, intrinsic motivation
14. Future Work
Increase ecological validity of results by
Promoting intrinsic motivation to use the interfaces
(real users with real needs)
Decreasing awareness of study setting
Remote evaluations
Body-worn sensors
Increase external validity of results by
Re-running study
Narrow down potential confounding factors
More measurements: personality tests (BFI), demand
characteristics (PARH)
Editor's Notes
At last years MobileHCI we presented a study about the usage of ML and SP interaction with a poster game in a public space.
The driving question was …
Goals:
Formative: inform design of combined interfaces through observation in potential usage scenario
ML: physical interaction, visually exposes both display and user more to the surrounding
SP: allows for more private interaction, established way of navigating and interacting with content
Which interface would be used longer?
TODO:
Bring in comparative part lab-public
H1: ML will be used less often in the public setting than in the laboratory
Hooray! Participants overwhelmingly used the ML interface and preferred it
Not many significant differences lab – public space
Lab sufficient?
BUT
50% would not use it in public settings similar to the one they were in?
Wilcoxon signed rank test with continuity correction
for rank data (ordinal)
# I felt comfortable using the Augmented Reality view in the environment check original question.
# I did not pay attention to the environment when using the Augmented Reality view
# I enjoyed using the Augmented Reality view in the environment but then for vienna
# 6 3 I would rather do the task with the Augmented Reality view only
cor(likert_q_jakomini$p9.6, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # 0.5773503
cor(likert_q_lab$p9.6, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # 0.8510645
cor(likert_q_wiensr$p3, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # 0.519512
# 7 4 I would rather do the task with the map view only
cor(likert_q_jakomini$p9.7, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # -0.4076871
cor(likert_q_lab$p9.7, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # -0.6849175
cor(likert_q_wiensr$p4, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # -0.5036856
# 4 1 I enjoyed using the Augmented Reality view in the environment
cor(likert_q_jakomini$p9.4, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # -0.2886751
cor(likert_q_lab$p9.4, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # 0.3504383
cor(likert_q_wiensr$p1, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # -0.6467555
# 5 2 I enjoyed using the map view in the environment
cor(likert_q_jakomini$p9.5, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # -0.8647909
cor(likert_q_lab$p9.5, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # -0.7433301
cor(likert_q_wiensr$p2, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # -0.6343888856
Wilcoxon signed rank test with continuity correction
for rank data (ordinal)
# I felt comfortable using the Augmented Reality view in the environment check original question.
# I did not pay attention to the environment when using the Augmented Reality view
# I enjoyed using the Augmented Reality view in the environment but then for vienna
# 6 3 I would rather do the task with the Augmented Reality view only
cor(likert_q_jakomini$p9.6, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # 0.5773503
cor(likert_q_lab$p9.6, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # 0.8510645
cor(likert_q_wiensr$p3, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # 0.519512
# 7 4 I would rather do the task with the map view only
cor(likert_q_jakomini$p9.7, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # -0.4076871
cor(likert_q_lab$p9.7, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # -0.6849175
cor(likert_q_wiensr$p4, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # -0.5036856
# 4 1 I enjoyed using the Augmented Reality view in the environment
cor(likert_q_jakomini$p9.4, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # -0.2886751
cor(likert_q_lab$p9.4, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # 0.3504383
cor(likert_q_wiensr$p1, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # -0.6467555
# 5 2 I enjoyed using the map view in the environment
cor(likert_q_jakomini$p9.5, levelTimes_perPartic_rel_jakomini$relTimesAR, method = "spearman") # -0.8647909
cor(likert_q_lab$p9.5, levelTimes_perPartic_rel_lab$relTimesAR, method = "spearman") # -0.7433301
cor(likert_q_wiensr$p2, levelTimes_perPartic_rel_wiensr$relTimesAR, method = "spearman") # -0.6343888856
the potentially large number of confounding factors which can influence the evaluation outcomes.
fatigue, the perceived severity of tracking errors, the role of personality (e.g., intro- and extraversion), intrinsic motivation to use the interfaces, the novelty of the ML metaphor and demand characteristics.
PUV:
mainly waiting area
Disadvantaged area
Passers-by partly in peripheral view of partic.
PUG:
mainly transit area
Central square under CCTV
Passers-by behind partic.
PUV:
mainly waiting area
Disadvantaged area
Passers-by partly in peripheral view of partic.
PUG:
mainly transit area
Central square under CCTV
Passers-by behind partic.
The PUG condition was carried out a location primarily used as transit area for changing tram lines with the major waiting areas being more than 20m away (see Figure 5). It was located in a wide open space in the city center. People from all social contexts are using this place for changing trams. The general area is under video surveillance and the building at which the study took place was actively operated by the local tram company. It was a place with a high frequency of passers-by coming from several directions but only a few people were standing in the social space of the participants (rather walking behind the participants, see Figure 5).
In contrast the location in the PUV condition was primarily used as waiting area for people coming from the exit of a near-by metro line (see Figure 6). It was located in a disadvantaged area (Vienna Leopoldstadt). Comments of participants about the “shabby” area and experimenter’s observations indicate that there might have been a larger social distance between participants (mostly middleclass, students) and people with lower socioeconomic status present at the tram stop compared to PUG.
Those differences between the locations could indicate that the social context in PUV could have inhibited the use of expressive, socially not common spatial gestures used in the ML interface, which is supported by the observations in Akpan et al. [1].
50%
50%
Compare with
EXAMINING MOBILE PHONE USE IN THE
WILD WITH QUASI-EXPERIMENTATION
https://www.hiit.fi/files/admin/publications/Technical_Reports/hiit2004-1.pdf
Compare with
EXAMINING MOBILE PHONE USE IN THE
WILD WITH QUASI-EXPERIMENTATION
https://www.hiit.fi/files/admin/publications/Technical_Reports/hiit2004-1.pdf