Masterdefense at Graz University of Technology, June 2013

1. Quan%ta%ve
Digital
Backchannel:
Developing
a
Web-­‐Based
Audience
Response
System
for
Measuring
Audience
Percep%on
in
Large
Lectures
by
Chris)an
Haintz
1

2. Research
Ques)on
ì How
to
create
a
quan)ta)ve
digital
backchannel
with
state
of
the
art
technology
to
support
agile
teaching
in
large
lectures?
2

3. Agile
Teaching
Students
Lecturer
Feedback
adapted
lecturing
3

4. Feedback
Qualita)ve
Quan)ta)ve
4

5. Feedback
-­‐
Backchannel
Frontchannel
Backchannel
5

6. 84
%
Quelle:
APA
25.4.2013,
hPp://oesterreich.orf.at/stories/2581600/
6

7. Backchannel
7

8. Requirements
ì BYOD
support
ì Con)nuous
backchannel
ac)vity
ì Ac)ons
of
students
generate
visible
impact
ì Maximize
informa)on
while
keeping
it
simple
ì …
8

9. Implementa)on
Application ServerApplication ServerDatabase Server
Application ServerApplication Server
Internet
Client Application Server
Auditor Interface
DB
Application
Interface
MVC Application
Lecturer Interface
MVC Application
DB
DBLoadBalancer
9

10. Backchannel
10

11. Dimension
Criterias
ì Understandable
to
the
student
ì Meaningful
to
the
lecturer
ì Clear
extremums
ì Values
should
be
expectable
to
change
over
)me
11

12. Dimensions
ì Happiness
ì Comprehension
ì Presenta)on
Speed
12

13. 13

14. Happiness
Comprehension
Speed
14

15. 15

16. 16

17. Findings
ì 75%
Par)cipa)on
(~100
Students)
ì BYOD
(21
Screen
Res.,
5
OSs,
18
OS
Versions,
8
Browser)
ì Maximize
meaningful
informa)on
ì 35%
in
between
of
extrema
and
neutral
posi)on
ì Con)nuous
Ac)vity
ì Ac)vity
decreases
significantly
over
)me
17

18. Conclusion
ì Dimensions
ì BYOD
ì User
Experience
ì Mo)va)on
to
par)cipate
ì Informa)on
visualiza)on
crucial
for
lecturer
How
to
create
a
quan)ta)ve
digital
backchannel
with
state
of
the
art
technology
to
support
agile
teaching
in
large
lectures?
18

19. Thank
you!
Chris)an
Haintz
chris)an.haintz@cnc.io
19

20. 20

21. 21

22. Agile
Development
Cycle
ì 1.
Planning
2.
Requirements
3.
Analysis
&
Design
4.
Implementa)on
5.
Tes)ng
and
Evalua)on
22

23. 11
Requirements
1. Constant
and
con)nuous
ac)vity
2. Reduce
distrac)on
3. Usability
4. Simplicity
5. Support
BYOD
policy
6. Responsive
Design
7. Auditor
impact
8. Reduce
informa)on
9. Cross-­‐plaiorm
capabili)es
10. Interna)onaliza)on
11. Maximize
meaningful
informa)on
23

24. 24

25. Avatar
-­‐
Image
Sprites
25

26. 1.
Prototypes
for
Collec)ve
Percep)on
26

27. User
Experience
Problem
27

28. Data
Structure
(JSON)
28

29. Facts
-­‐
Test
Lecture
29

30. Raw
Data
-­‐
Test
Lecture
30

31. 31
Ac)vity
Test
Lecture

32. Auditor
Votes
Histogram
–
Test
Lecture
32
12.0%
47.9%
23.9%
10.3%
6.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
0% 1,10% 11,20% 21,30% >30%
%"auditors"
#"votes"
Auditor"Votes"Histogram"

33. Aging
33
!30$
!20$
!10$
0$
10$
20$
30$
40$
50$
0$ 2$ 4$ 6$ 8$ 10$ 12$ 14$ 16$ 18$ 20$ 22$ 24$ 26$ 28$ 30$ 32$ 34$ 36$ 38$ 40$
value&[%]&
*me&[minutes]&
Different&Aging&Approaches&
speed$(no$aging)$ speed$(linear$aging)$ speed$(quadra:c$aging)$
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
10 2 3 4 5 6 7 8 9
value
age [minutes]

34. Laptops'
65%'
Devices'
Mobile'
Devices'
35%'
'
Sta)s)cs
Test
Lecture
34
1.2$ 1.2$
2.4$
3.6$ 3.6$
1.2$
3.6$
2.4$
1.2$ 1.2$ 1.2$
10.8$
1.2$ 1.2$
13.3$
16.9$
7.2$
8.4$
6.0$
7.2$
4.8$
0.0$
2.0$
4.0$
6.0$
8.0$
10.0$
12.0$
14.0$
16.0$
18.0$
20.0$
240x320$320x344$320x480$320x568$360x592$360x640$480x800$601x906$640x360$
720x1230$
720x1280$
768x1024$
1100x2100$
1280x720$
1280x800$
1366x768$
1440x900$
1600x900$
1680x1050$
1920x1080$
1920x1200$
visits%[%]% Screen%Resolu2on%
43.4$
24.1$
19.3$
6.0$
3.6$
1.2$ 1.2$ 1.2$
0.0$
5.0$
10.0$
15.0$
20.0$
25.0$
30.0$
35.0$
40.0$
45.0$
50.0$
Chrome$ Firefox$ Safari$ Android$
Browser$
Opera$ Internet$
Explorer$
Mozilla$
CompaEble$
Agent$
Safari$(inI
app)$
visits%[%]% Browser%
7"
8"
Vista"
XP"
x86_64"
i686"
10.8"
10.7"
10.6"
4.2.2"
4.1.x"
4.0.x"
2.3.x"
2.1.x"
6.1.x"
6.0.x"
5.0.x"
5.1.x"
0.0"
5.0"
10.0"
15.0"
20.0"
25.0"
30.0"
35.0"
Windows" Macintosh" Android" iOS" Linux"
visits%[%]% Opera.ng%System%Versions%