Sticky Notes - a tool for supporting collaborative activities in a 3D virtual world
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The document describes a sticky notes tool developed for a 3D virtual world called vAcademia to support collaborative learning activities. The tool allows users to create, move, edit and delete digital sticky notes on virtual whiteboards. Texture generation for the notes is performed using graphics processing units for improved performance. Evaluation showed the tool supported collaborative tasks well with stable functionality and no delays even when numerous whiteboards and notes were used simultaneously. Future work involves designing new learning scenarios and further user testing of the virtual environment.
Sticky Notes - a tool for supporting collaborative activities in a 3D virtual world
- 1. 1 Sticky Notes – a Tool for Supporting Collaborative Activities in a 3D Virtual World 14th International Conference on Advanced Learning Technologies (ICALT) July 7–9, 2014 Athens, Greece Mikhail Morozov and Andrey Smorkalov Volga State University of Technology, Russia Mikhail Fominykh Norwegian University of Science and Technology, Norway VSUT
- 2. 2 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 3. 3 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 4. 4 Motivation and challenges: Applying 3D VWs for learning 3D Virtual Worlds (VWs) – Have great features… … but not widely used o Challenges – Steep learning curve – Demand for computational and network resources – Lack of features that educators use in everyday teaching o Solution Proposal – Enabling learning scenarios which require large amounts of 2D graphical content displayed VSUT
- 5. 5 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 6. 6 Related work: Large Amount of Graphics in 3D VWs VSUT Multiple workspaces or virtual screens with limited performance: o Small number of active screens (Second Life has a limit of five) o Static images (Sametime 3D has a sticky notes tool, but notes are static, placed on slots, constant size, and no other tools on the same screen o Individual use of screens
- 9. 9 VSUT
- 10. 10 Related work: Current technological limitations Usually, an image is calculated on a CPU on client side (e.g., in Second Life™ and Blue Mars™) or server side (e.g., in Open Wonderland™) and then loaded into the stream-processor memory as a texture. Therefore, the use of dynamic 2D images in existing 3D VWs is very limited. VSUT
- 11. 11 Outline o Motivation and Challenges o Related Work o Texture Generation Model (motivation) o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 12. 12 Texture Generation Model: Motivation for a new approach Sticky Notes tool ‒ Supporting synchronous collaborative activities ‒ Constantly creating, moving, editing, and deleting notes Virtual screen needs to be updated frequently The need for high-speed texture generation VSUT
- 13. 13 Texture Generation Model: Motivation o CPU ‒ CPU is loaded maintaining 3D environment ‒ source data for the synthesis of images and the data area for the resultant images are in the local memory of other devices o Stream processors ‒ 3D visualization is hardware-based and conducted on SPs ‒ SPs’ computing power usually exceeds the capabilities of CPUs tenfold o Challenge ‒ SPs have hardware limitations which do not allow to use them for implementing most of the classical image processing algorithms VSUT
- 14. 14 VSUT Interactive virtual whiteboard (VWB) of vAcademia
- 15. 15 VSUT
- 17. 17 Original methods for processing large amounts of graphics in 3D VWs o Sharing Changing Blocks ‒ Sharing application window – Sharing video ‒ Sharing web-camera image – Sharing screen area o Sharing Attributed Vector Figures ‒ Drawing figures and typing text – Inserting text o Processing Static Images ‒ Slideshow – Area print screen ‒ Image insert – Backchannel ‒ Sticky notes VSUT
- 18. 18 Original methods for processing large amounts of graphics in 3D VWs o Sharing Changing Blocks ‒ Sharing application window – Sharing video ‒ Sharing web-camera image – Sharing screen area o Sharing Attributed Vector Figures ‒ Drawing figures and typing text – Inserting text o Processing Static Images ‒ Slideshow – Area print screen ‒ Image insert – Backchannel ‒ Sticky notes VSUT
- 19. 19 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 20. 20 Sticky notes
- 21. 21 Sticky Notes. Visualization Graphical and textual notes = Source + Background + o Coordinates x and y o Width and height o Depth o Background color o Font color o Username of the owner VSUT
- 22. 22 Sticky Notes. Synchronization Synchronized invisible object (SIO) is created for each sticky note o SIO is attached to the VWB where the note was posted o SIO contains all synchronized properties of the sticky note o All SIOs are registered to belong to VWBs they were posted on or moved to VSUT
- 23. 23 Sticky Notes. Manipulation o Activate the Sticky Notes mode on VWB o Preview and Add new notes o Move on and between VWBs o Edit and delete own notes o See actions of other users in real time o Draw and type on top of the notes o Save a VWB with all sticky notes o Teacher/ coordinator mode VSUT
- 24. 24 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 25. 25 Performance Evaluation I. Comparison of the algorithm performance on SPs and CPU II. General efficiency of the system We present average results acquired by running the system on ‒ 20 different hardware configurations with Intel CPU and NVidia / ATI graphics adapters from the same price range ‒ On each hardware configuration 10 runs were conducted for each image size. VSUT
- 26. 26 0 10 20 30 40 50 128х128 256х256 512х512 1024х1024 2048х2048 Improvement factor, TCPU/TSP Imagesize(px) Performance Evaluation: I. Algorithms on SPs and CPU The rationale behind using SPs (instead of CPU) for image processing in vAcademia is confirmed. VSUT 0 20 40 60 80 128x128 256x256 512x512 1024x1024 2048x2048 Improvement factor, TCPU/TSP Imagesize(px) Forward DWT Inverse DWT Rasterization of attributed vector figures
- 27. 27 Performance Evaluation: II. General Efficiency of the System Tested: Performance degradation as f of the # of: o VWBs (in one location) o actively used VWBs o simultaneous changes of images on VWBs Texture generation time as f of the # of: o sticky notes VSUT
- 28. 28 Testing performance with 50 VWBs VSUT
- 29. 29 Performance degradation as a function of the number of VWBs VSUT 92% 93% 94% 95% 96% 97% 98% 99% 100% 0 10 20 30 40 50 Performance Number of whiteboards Average Peaking
- 30. 30 Performance degradation as a function of the number of actively used VWBs VSUT 75% 80% 85% 90% 95% 100% 0 5 10 15 20 25 Performance Number of actively used whiteboards Average Peaking
- 31. 31 Performance degradation as a function of the number of simultaneous changes of images on VWBs VSUT 80% 84% 88% 92% 96% 100% 1 2 3 4 5 Performance Number of simultaneous changes of images Average Peaking
- 32. 32 VSUT Testing performance with 100 sticky notes
- 33. 33 Texture generation time as a function of the number of sticky notes VSUT 0 20 40 60 80 100 1 5 10 20 40 70 100 Texture gen. time, T (ms) Number of sticky notes CPU SPs
- 34. 34 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 35. 35 User Evaluation o Diagram designing task using provided templates o 23 second-year CS students o No tutorials on vAcademia were given o All participants had experience playing 3D video games o Data: system logs, questionnaires, and an interview VSUT
- 37. 37 User Evaluation VSUT Question Str. agree Agree N D SD VWB functions are easy to access. 16 7 It was comfortable "to look" at VWBs in 3D. 15 8 VWBs displayed the contents crisply (no blur). 14 9 VWBs displayed the contents quickly (no delays). 14 8 No delays when increasing the # of VWBs. 13 10 VWB is a convenient for similar tasks. 13 8 2 vAcademia tools are more comfortable than traditional tools, for similar tasks. 15 8 It was clear how to work in vAcademia. 19 4
- 38. 38 VSUT
- 39. 39 VSUT
- 40. 40 VSUT
- 41. 41 Outline o Motivation and Challenges o Related Work o Texture Generation Model o Original Methods o Sticky Notes tool o Performance Evaluation o User Evaluation o Conclusions VSUT
- 42. 42 Conclusions o Original method for collaborative work with large amount of graphical content o Design & implementation of Sticky Notes tool in vAcademia o The algorithms we applied – are superior to the commonly used ones o The tools we designed – have stable work and – have educational value VSUT
- 43. 43 Future Work o Designing scenarios for new learning activities possible using our method o Conducting a full-scale user evaluation testing all designed tools o Developing new tools based on our method VSUT
- 44. 44 Thank you! Andrey Smorkalov smorkalovay@volgatech.net Mikhail Morozov morozovmn@volgatech.net Mikhail Fominykh mikhail.fominykh@ntnu.no http://vacademia.com/ http://www.facebook.com/vAcademia/ @vacademia_info http://slideshare.net/vacademia/ http://slideshare.net/mfominykh/ VSUT