Automatic Feedback for Oral Presentations
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This presentation was given at the Learning Analytics and Knowledge Conference about an automatic feedback for oral presentation system for entry-level higher-education students.
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Automatic Feedback for Oral Presentations
- 1. The RAP System: Automatic Feedback of Oral Presentation Skills using Multimodal Analysis and Low-Cost Sensors Xavier Ochoa, Federico Domínguez, Bruno Guamán, Ricardo Maya, Gabriel Falcones, Jaime Castells Escuela Superior Politécnica del Litoral (ESPOL)
- 3. 4-C’s Skills for the 21st Century Communication Creativity Critical Thinking Collaboration
- 4. 4-C’s Skills for the 21st Century Communication Creativity Critical Thinking Collaboration
- 5. Automated system to provide feedback on basic oral presentation skills for entry-level students But really it is a hybrid system!
- 6. We are not the first
- 8. But we have unique objectives
- 9. Design Goals •Focus on intended use •Immersive experience and unobtrusive •Plug and Play •Relatable feedback •Low cost and scalable
- 10. How we build it
- 11. Very simple sensors • Audio • Omnidirectional microphone • Video • Raspicamera v2.1 of 8MP attached (1080x720)
- 15. Total cost of the system: $ 3.000 Plus on the cloud processing
- 16. What we did it with it
- 17. Modalities and extracted features • Video (Open Pose) • Gaze (P: 0.5 – R: 0.94) • Body posture (P: 0.8 – R: 0.93) • Audio (Praat) • Volume (P: 0.87 – R: 0.81) • Filled pauses (P:0.87 – R: 0.27) • Slides (Apache POI) • Amount of Text • Font size
- 19. (Multimodal) Formative Feedback Report
- 20. (Multimodal) Formative Feedback Report
- 25. How it was perceived
- 27. But there was learning?
- 28. Experiment •Used by 50 students •3 times during the semester •Real classroom presentations •Students used the system on their own
- 29. Effect of the System • Looking at the public: +++ (from 2.36 to 3.36 / 5, ss) • Presentation posture: + (from 4.32 to 4.44 / 5, ss) • Filled pauses: = (no effect, average 3.54 / 5) • Volume: + (from 4.14 to 4.28 / 5, ss) • Slides: = (no effect, average 1.82 / 2)
- 30. Further work •Large scale deployment •Packet basic functionality in Mobile app •Activity detection
- 31. Gracias / Thank you Questions? Xavier Ochoa xavier@cti.espol.edu.ec http://ariadne.cti.espol.edu.ec/xavier Twitter: @xaoch