inherent advantages of augmented reality for k 12...
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Inherent Advantages of Augmented Reality for K–12 Education
Marc Ericson C. Santos, Angie Chen, Takafumi Taketomi,
Goshiro Yamamoto, Jun Miyazaki, Hirokazu Kato Interactive Media Design Laboratory
Graduate School of Information Science
Nara Institute of Science and Technology
Nara, Japan
{chavez-s, chen-a, takafumi-t, goshiro, miyazaki, kato}@is.naist.jp
A Review of Augmented Reality Learning Experiences
Presentation has three parts.
1. Report a survey of Augmented Reality Learning Experiences (ARLEs.)
– Objectives
– Method
– Results
2. Propose a participatory design model for ARLEs.
3. Illustrate the use of participatory design.
– Developing AR x-ray interaction
– Paper-prototyping for authoring AR content
Defining AR learning experiences imposes logical uses in education.
Augmented Reality Learning Experience (ARLE)
“any form of personal experience designed to improve knowledge, facilitated by integrating virtual elements onto a real environment.”
Augmented Reality Interactions
Necessary? Beneficial?
Cost-effective?
Educational Interaction Actual Classroom Use*
*Picture from http://newsinfo.inquirer.net/194569/public-schools-to-give-priority-to-early-enrollees
Conduct a review to understand AR interactions in education.
1. To find empirical proof that AR interactions can be beneficial to learning
2. To observe trends in implementation and evaluation that led to good interfaces
Approach for the survey
Search digital libraries
Filter using criteria
Gather data
Analysis and synthesis
IEEE digital library ACM digital library Learning technology publications
Prototype K-12 Education Availability
publication details prototype description use of AR user study
We found 87 ARLE articles.
15
72
Type of Publication
Journal
Conference
61
26
Is it IEEE-Indexed?
Yes
No
0 2 4 6 8 10 12 14 16
IEEE Advanced Learning Technologies
IEEE Int'l Symp. on Mixed and AugmentedReality
IEEE Virtual Reality
IEEE Wireless, Mobile and UbiquitousTechnology in Education
Computers and Education
Number of Articles
There are five types of evaluation methods.
1. Performance metrics
– Performance test
– Self-reported learning
2. Questionnaires
– Motivation
– Presence
– Usability
3. Behavior observation
4. Focused-group discussion
5. Heuristic evaluation
– Teacher evaluation
– Expert evaluation
11
37
39
User Study
Performance
Usability
None
Ref Content Display Participants (Sample) Effect Size
[3] English Handheld Grade school, teachers (67) Large
[5] Solar system HMD High school (40) Large
[6] Kinematics graphs Desktop High school (80) Large
[7] Elastic collision Handheld University students (36) Large
[4] Spatial ability training Desktop University students (49) Moderate to Large
[2] Masterpieces of
Renaissance Desktop High school (69) Moderate to Large
[8] English Desktop Grade school (Six classes) Small to Moderate
[9] Math game Handheld Grade school (123) No effect
[10] Eulerian and Hamilton
Graphs Projector University students (20) No effect
[11] Spatial ability training HMD High school (215) No effect
[12] Library skills Desktop Grade school (116) Small Negative
Reported effect sizes vary widely.
Multimedia material* Teacher’s words + Real AR Annotation
Multimedia Learning Theory [13] (Learning from words and pictures)
AR Annotation (Learning from virtual words
and real objects)
If we substitute: Words virtual symbols (words, numbers, arrows) Pictures real objects;
Then, all of the empirically tested principles of Multimedia Learning Theory applies to AR annotation.
ARLEs (AR annotation) apply multimedia learning theory.
*Picture from http://science.howstuffworks.com/environmental/earth/geophysics/earth3.htm
Virtual apple
Virtual apple + Picture book*
Virtual apple + Real Fridge
More cues
Situated Learning Theory [14] Learning is situated in a specific context and embedded within a particular social and physical environment.
ARLEs apply situated visualization.
*Picture from http://lifeonthecutoff.wordpress.com/2010/09/18/kerplunk/
Vision but poor haptic Vision and better haptic [4]
Animate Vision Theory [15] Vision data and haptic data are coded in the brain together.
ARLEs apply vision-haptic visualization.
Easier perception, thus more allotment for processing
Processing
Processing
Perception
Perception
Working Memory
AR
N
on
-AR
More cues, better experience, thus more elaborated
knowledge
Some Concept
Some Concept
No
n-A
R
AR
Knowledge as associations
World annotation, situated visualization and vision-haptic visualization improves learning in two ways.
Given the affordances of AR, how can we design ARLEs?
AR and
EdTech
Engineers Teachers
and
Curriculum
Designers
Students
AR
Learning
Object
Implementation Evaluation of
learning
Teaching
Requirements
Delivery to
students
Edit to match
context
Expert
Evaluation
We propose a participatory design model for authoring ARLEs.
Target
Object
Edges
Mask
Alpha
Mask
Virtual
Object
Edge-based
AR X-ray
We tested an implementation of AR x-ray.
AR x-ray on iPad
We conducted two user studies on perception.
1. User Study 1: 23 Filipino students (9 male, 14 female, aged 5-15) attending 13 different schools
2. User Study 2: 47 students (21 male, 26 female, aged 11-16) from Spring Christian School
3. Questionnaire:
– Q1. The object is inside the box.
– Q2. The object is easy to see.
– Q3. The object seems real.
– Q4. The object seems flat.
– Q5. I can see the different parts of the object clearly.
– Q6. My classmates will say the object is real.
User study set up
Control: without occlusion
Experiment: with occlusion
Demonstration
Set up for User Study 1 (involving younger kids)
There are no significant differences in perception.
Question (Construct) Without Occlusion With Occlusion (x-ray)
Mean (95% Conf.)
STDV Mean
(95% Conf.) STDV
Q1 (Depth) 3.7 (3.1 – 4.2) 1.2 3.6 (3.1 – 4.1) 1.3 Q2 (Visibility) 4.0 (3.5 – 4.4) 1.0 3.3 (2.8 – 3.7) 1.2 Q3 (Realism) 3.4 (2.8 – 3.9) 1.4 2.7 (2.2 – 3.3) 1.3 Q4 (Depth) 4.1 (3.7 – 4.6) 0.9 4.0 (3.5 – 4.4) 1.2 Q5 (Visibility) 4.0 (3.6 – 4.5) 0.9 3.6 (3.1 – 4.1) 1.3 Q6 (Realism) 3.3 (2.8 – 3.8) 1.2 3.1 (2.6 – 3.7) 1.3
Question (Construct) Without Occlusion With Occlusion (x-ray)
Mean (95% Conf.)
STDV Mean
(95% Conf.) STDV
Q1 (Depth) 3.4 (2.9 – 3.9) 1.2 3.4 (3.0 – 3.9) 1.2 Q2 (Visibility) 3.8 (3.3 – 4.3) 1.1 4.0 (3.5 – 4.4) 1.1 Q3 (Realism) 3.1 (2.6 – 3.7) 1.2 3.0 (2.5 – 3.5) 1.3 Q4 (Depth) 3.3 (2.9 – 3.7) 1.0 3.3 (2.9 – 3.7) 1.0 Q5 (Visibility) 4.0 (3.5 – 4.5) 0.6 3.7 (3.2 – 4.1) 1.0 Q6 (Realism) 3.4 (3.0 – 3.9) 1.0 3.7 (3.4 – 4.2) 1.0
User Study 1
User Study 2
(p-value = 0.041) Significant based on t-test.
Schools find ARLEs beneficial and would like to use it for specific content.
Focused group discussions with Teachers, Parents,
School Administrators
Perceived advantages in practice 1. “Learning by experience” 2. Improved attention 3. Increased motivation
Perceived issues in practice 1. Cost and availability of technology 2. Accuracy of virtual information 3. Time constraint
On-going paper-prototyping for ARLEs.
Target Object
Authoring on target object
Drop-down Menu
Annotated frog
• Can test knowledge in navigation
• Limited interactions and experience
Summary of contributions
We showed that:
• ARLEs have variable effect to learning.
• ARLEs have inherent advantages that improve perception and knowledge construction.
We recommend that:
• We can design better ARLEs using participatory design.
Using participatory design, we…
• Tested perception in AR x-ray interactions
• Gathered preliminary user requirements for ARLEs
Future Work
Simple Authoring Tool for Teachers
Implement Augmented Reality Learning Objects
(ARLOs)
Standard ARLE file that packages AR content (real object, virtual
objects, interactions)
Main Goal
Continue using Participatory Design
Continue implementing
state-of-the-art AR interactions
Example: AR x-ray, AR Annotation
Model that considers teachers and students in
the authoring process
1. “Advanced Learning Technologies Journal List,” CELSTEC, http://celstec.org/content/advanced-learning-technologies-journal-list. Aug. 2012.
2. A. Di Serio, M. B. Ibáñez and C. D. Kloos, "Impact of an Augmented Reality System on Students’ Motivation for a Visual Art Course," Computers & Education, 2012.
3. T. Y. Liu, "A context‐aware ubiquitous learning environment for language listening and speaking," Journal of Computer Assisted Learning, vol. 25, no. 6, pp. 515-527, 2009.
4. J. Martín-Gutiérrez, J. L. Saorin, M. Contero, M. Alcañiz, D. C. Pérez-López and M. Ortega. "Design and validation of an augmented book for spatial abilities development in engineering students," Computers & Graphics, vol. 34, no. 1, pp. 77-91, 2010.
5. A. K. Sin and H. B. Zaman. "Live Solar System (LSS): Evaluation of an Augmented Reality book-based educational tool," Proc. IEEE Symp. Information Technology (ITSim ‘10), vol. 1, pp. 1-6. 2010.
6. T. F. L. Jerry and C. C. E. Aaron. "The impact of augmented reality software with inquiry-based learning on students' learning of kinematics graph," Proc. IEEE Conf. Education Technology and Computer (ICETC ‘10), vol. 2, pp. V2-1. 2010.
7. N. Li, L. Chang, Y. X. Gu and H. B. L. Duh. "Influences of AR-Supported Simulation on Learning Effectiveness in Face-to-face Collaborative Learning for Physics," Proc. IEEE Conf. Advanced Learning Technologies (ICALT ‘11), pp. 320-322. 2011.
8. H. K. Jee, S. Lim, J. Youn and J. Lee, "An augmented reality-based authoring tool for E-learning applications," Multimedia Tools and Applications, pp. 1-11, 2011.
9. P. O'Shea, C. Dede and R. Mitchell, "A Study of the efficacy of an Augmented Reality curriculum," Proc. AACE Conf. Information Technology & Teacher Education (SITE ’09), pp. 1510-1514, 2009.
10.H. Mitsuhara, Y. Yano and T. Moriyama, "Paper-top interface for supporting note-taking and its preliminary experiment," Proc. IEEE Conf. Systems, Man and Cybernetics (SMC ‘10), pp. 3456-3462, 2010.
11.A. Dunser, K. Steinbugl, H. Kaufmann and J. Gluck, "Virtual and augmented reality as spatial ability training tools," Proc. ACM SIGCHI New Zealand Conf. Computer-human interaction: design centered HCI (CHINZ '06), vol. 158, pp. 125-132. 2006.
12.C. M. Chen and Y. N. Tsai, "Interactive augmented reality system for enhancing library instruction in elementary schools," Computers & Education, 2012.
13.Mayer, Richard. Multimedia Learning 2nd ed. Cambridge, 2009. 14.Lave, Jean, and Etienne Wenger. Situated learning: Legitimate peripheral participation. Cambridge university press,
1991. 15.Ballard, Dana H. "Animate vision." Artificial intelligence 48.1 (1991): 57-86.
References