Quantitative Digital Backchannel: Developing a Web-Based Audience Response System for Measuring Audience Perception in Large Lectures
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The document describes research into developing a quantitative digital backchannel system to measure audience perception in large lectures. It outlines requirements for the system including supporting many devices, maximizing meaningful information while keeping it simple, and continuous backchannel activity. The system was implemented and tested in a lecture with 100 students, with findings like 75% participation rate and that activity decreased over time. The conclusion is that dimensions, BYOD support, user experience, and motivating participation are important for an effective quantitative backchannel system.
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Quantitative Digital Backchannel: Developing a Web-Based Audience Response System for Measuring Audience Perception in Large Lectures
- 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
- 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
- 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%