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
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
Agile Teaching
Students Lecturer
Feedback
adapted lecturing
3
Feedback
Qualita)ve Quan)ta)ve
4
Feedback -‐ Backchannel
Frontchannel
Backchannel
5
84 % Quelle: APA 25.4.2013, hPp://oesterreich.orf.at/stories/2581600/
6
Backchannel
7
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
Implementa)on
Application ServerApplication ServerDatabase ServerApplication ServerApplication Server
Internet
Client Application ServerAuditor Interface
DB
Application
Inte
rface
MVC Application
Lecturer Interface
MVC Application
DB
DBLo
ad B
alan
cer
9
Backchannel
10
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
Dimensions
ì Happiness
ì Comprehension
ì Presenta)on Speed
12
13
Happiness
Comprehension
Speed
14
15
16
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
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
20
21
Agile Development Cycle
ì 1. Planning 2. Requirements 3. Analysis & Design 4. Implementa)on 5. Tes)ng and Evalua)on
22
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
Avatar -‐ Image Sprites
25
1. Prototypes for Collec)ve Percep)on
26
User Experience Problem
27
Data Structure (JSON)
28
Facts -‐ Test Lecture
29
Raw Data -‐ Test Lecture
30
31
Ac)vity Test Lecture
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"
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)$
0.10.20.30.40.50.60.70.80.91.0
10 2 3 4 5 6 7 8 9
�ŐŝŶŐ�&ƵŶĐƟŽŶvalue
age [minutes]
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$(inIapp)$
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%