Upload
university-of-maryland-baltimore-county-department-of-information-systems
View
451
Download
0
Embed Size (px)
DESCRIPTION
From Dr. Anthony: I attended my first Interactive Tabletops and Surfaces (ITS) conference last week and presented an overview of our work to date on the MTAGIC project. I thoroughly enjoyed the conference! There is just so much great and interesting work going on in the areas of touch and gesture interaction for all types of platforms, ranging from smart interactive tabletops, to interactive boards, to Kinect-based mid-air gestures, to mobile touchscreen devices, and more. I presented our MTAGIC findings with respect to how children expect to and do use touchscreen devices differently than adults, focusing on low-level interactions such as touching onscreen targets and making finger gestures.
Citation preview
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 1
Lisa Anthony1 (presenter), Quincy Brown2, Jaye Nias2, Berthel Tate2, Shreya Mohan1 1University of Maryland Baltimore County (UMBC) 2Bowie State University
mtagic.wordpress.com
Touchscreen shipments to reach 833 million by 2013^
5 million iPhone 5 sales Sept 21-Sept 23, 2012*
Children are using mobile devices (own / parents’)m
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 2
^ ISuppli. Touch-Screen Shipments Expected to Reach 833 Million by 2013. 2008.
* http://online.wsj.com/article/BT-CO-20120924-707595.html?mod=WSJ_ComputerHardware_middleHeadlines mChiong, C. and Shuler, C. Learning: Is there an app for that? Investigations of young children's usage and learning with mobile devices and apps. The Joan Ganz Cooney Center at Sesame Workshop, New York, 2010.
mtagic.wordpress.com
Manual dexterity / fine motor control develop with age of child
Shapes children are expected to generate vary by age^
Little hands activate interactors unexpectedly*
Children have difficulty tapping and with drag and dropm
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 3
^ Beery, K., Buktenica, N., and Beery, N.A. The Beery Buktenica Developmental Test of Visual-Motor Integration, 5th Edition. 2004. * McKnight, L. & Cassidy, B. (2010) Children’s Interaction with Mobile Touch-Screen Devices: Experiences and Guidelines for Design. International Journal of Mobile Human Computer Interaction 2 (2), 18 pp. mBrown, Q., Bonsignore, E., Hatley, L., Druin, A., Walsh, G., Foss, E., Brewer, R., Hammer, J., and Golub, E. Clear Panels: a technique to design mobile application interactivity. Proc. DIS 2010, 360–363.
mtagic.wordpress.com
LETTERS (ADULT / CHILD) SHAPES (ADULT / CHILD)
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 4
A E Q
Δ O +
mtagic.wordpress.com
“Mobile Touch and Gesture Interaction for Children”
https://mtagic.wordpress.com/
Funding support: NSF HCC Small NSF CISE #IIS-1218395/IIS-1218664
PIs: Lisa Anthony (UMBC)
Quincy Brown (Bowie State University)
Students: Robin Brewer, Germaine Irwin, Shreya Mohan,
Jaye Nias, Luis Queral, Berthel Tate
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 5
Triangle
Touch cloud
mtagic.wordpress.com
Understand differences between kids and adults in touch / gesture input e.g., can we reliably identify kids?
Design interaction to help kids have more successful interaction e.g., target sizes and active spaces
Develop technology to offer tailored interaction for kids e.g., recognizers and widgets
6 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com
3 studies with kids and adults (S1^, S2*, S3-ongoing) 49 kids (ages 7-17), 36 adults (ages 18+)
Two touchscreen tasks, laboratory setting
7
Study 2 setting
^ Brown, Q. and Anthony, L. 2012. Toward Comparing the Touchscreen Interaction Patterns of Kids and Adults. Proc. ACM SIGCHI Workshop on Educational Software, Interfaces and Technology (EIST’2012), Austin, TX, 05-06 May 2012, 4pp. * Anthony, L., Brown, Q., Nias, J., Tate, B., and Mohan, S. 2012. Interaction and Recognition Challenges in Interpreting Children’s Touch and Gesture Input on Mobile Devices. Proc. ACM Conf. on Interactive Tabletops and Surfaces (ITS’2012), Cambridge, MA, 14 Nov 2012, 225-234.
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com
Task 1: Touch Interaction Touch target with finger (4 sizes)
Measure touch time, touch location (x,y), touch pressure, # of attempts, etc.
S1: 43 total targets, S2&3: 104 targets
8
Study 2 interfaces
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com
Task 2: Gesture Interaction Draw gesture with finger
Measure touch properties grouped by strokes and gestures
S1: 9 gestures (x1 sample per user), S2&3: 20 gestures (x6 samples per user)
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 9
Study 2 interfaces
Study 2 & 3 gestures
mtagic.wordpress.com
Android platform Open source and free to develop
Java-based development environment
S1: Google Nexus One (320 x 480 interface)
S2&3: Google Nexus S (480 x 800 interface)
10 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com
Children miss more targets than adults** S1: 46% kids vs. 32% adults (of all targets)
S2: 23% kids vs. 17% adults (of all targets)
Smallest targets most challenging**
11 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.05 level
Study 2 (must get target correctly)
Study 1 (one attempt per target)
mtagic.wordpress.com
Children miss more targets than adults** S1: 46% kids vs. 32% adults (of all targets)
S2: 23% kids vs. 17% adults (of all targets)
Smallest targets most challenging**
12 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.05 level
Study 2 (must get target correctly)
Study 1 (one attempt per target)
increase area to activate desired target or use probabilities to identify most likely target
follow recommendations for target size in paper
Design: Understand:
mtagic.wordpress.com
Edge-padded targets more challenging** S2: miss rate doubles on edge-padded targets
S2: 99% of misses in “gutter”
13
Study 2
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.05 level
mtagic.wordpress.com
Edge-padded targets more challenging** S2: miss rate doubles on edge-padded targets
S2: 99% of misses in “gutter”
14
Study 2
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.05 level
align targets with edge of screen (Fitts’ Law holds!)
Design: Understand:
mtagic.wordpress.com
Discovered new phenomenon: holdovers touches in location of previous target
96% of holdovers were by children
81% of holdovers were smallest targets
15
Study 2
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com
Discovered new phenomenon: holdovers touches in location of previous target
96% of holdovers were by children
81% of holdovers were smallest targets
16
Study 2
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
Design: Understand:
ignore touches in area of previously active target based on timing
mtagic.wordpress.com
Kids make gestures differently than adults S1: kids make bigger gestures**
S1: kids make gestures with more strokes**
17 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.01 level
Study 1
Adult Child Child Adult
mtagic.wordpress.com
Kids make gestures differently than adults S1: kids make bigger gestures**
S1: kids make gestures with more strokes**
Kids gestures are recognized^ less accurately than adults S1: 34% kids vs. 64% adults**
S2: 81% kids vs. 90% adults**, correlated to age**
18 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.01 level
Study 1
^ Anthony, L. and Wobbrock, J.O. 2010. A Lightweight Multistroke Recognizer for User Interface Prototypes. Proc. Graphics Interface (GI’2010), Ottawa, Canada, 02 Jun 2010, 245-252.
mtagic.wordpress.com
Kids make gestures differently than adults S1: kids make bigger gestures**
S1: kids make gestures with more strokes**
Kids gestures are recognized^ less accurately than adults S1: 34% kids vs. 64% adults**
S2: 81% kids vs. 90% adults**, correlated to age**
19 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
** significant at the p<0.01 level
Design: Understand:
train on kids’ gestures by age group or develop specialized recognizers for kids
Study 1
^ Anthony, L. and Wobbrock, J.O. 2010. A Lightweight Multistroke Recognizer for User Interface Prototypes. Proc. Graphics Interface (GI’2010), Ottawa, Canada, 02 Jun 2010, 245-252.
mtagic.wordpress.com
Understand differences between kids and adults in touch / gesture input e.g., can we reliably identify kids?
Design interaction to help kids have more successful interaction e.g., target sizes and active spaces
Develop technology to offer tailored interaction for kids e.g., recognizers and widgets
20 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com
Short-term: Looking at younger kids
In-context apps
Mid-term: Interaction co-design with kids
Long-term: Tailored recognition for kids
Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012 21
Hokey Pokey Penguin prototype
mtagic.wordpress.com
Lisa Anthony1 (presenter), [email protected]
Quincy Brown2, [email protected]
Jaye Nias2, Berthel Tate2, Shreya Mohan1 1University of Maryland Baltimore County (UMBC) 2Bowie State University
Funding: NSF CISE IIS #IIS-1218395/IIS-1218664
Dept of Ed HBGI Grant Award #P031B090207-11
22 Interaction and Recognition Challenges in Interpreting Children's Touch and Gesture Input on Mobile Devices / ITS 2012
mtagic.wordpress.com