Enhancing Education with Online Robots | Summary & Conclusions

1. IEEE ICRA 2002Workshop on Educational Applicatons of Online Robots Summary & Conclusions by Gerard McKee, University of Reading, UK

2. Workshop on Educational Applications of Online Robots Chairs Matt Stein and Ken Goldberg Presentations, Open Discussion and Demonstrations

3. Presentations: am Multimedia Technology for Online Robot Projects, • Gerard McKee, The University of Reading, UK Remote Laboratory Access Through The Internet • Ilhan Konokseven & Aydan Erkmen, Middle East Technical University Collaborative Online Teleoperation and the Tele-Actor for Distance Education, • Ken Goldberg, Berkeley Environment for online experimentation and analysis, • Yves Piquet, Swiss Federal Institute of Technology

4. Presentations: pm A Statistical Approach to Tracking Multiple Moving People with a Mobile Robot and its Application to Improve Tele-Presence • Wolfram Burgard, University of Freiburg Supermedia Enhanced Internet Robots • Imad Elhajj & Ning Xi, Michigan State University Networked Robotics/Mechatronics through the Intelligent Space • Hideki Hashimoto, University of Tokyo EventScope: A Telescience Interface for Internet-Based Education, • Peter Coppin, Michael Wagner, CMU.

5. Demonstrations: • EventScope (science experiments) • SysQuake Remote (automatic control) • plus video sequences.

6. Open Discussion Five Questions: • What is there to be learned from an Online Robot experience? • How can interfaces and systems be designed to foster this learning? • What are the best educational applications/contexts? • How should student experience be evaluated? • Can a site be designed to lead students through an experiment and quiz afterward?

7. What is there to be learned from an Online Robot experience? I.e. How can online robots contribute to an educational experience? • It is a thing of interest in itself. • It is a tool, a medium for exploration. • It allows us to place the student in a remote environment. • A technology-centred equivalent of the field trip. • It has a novelty value. • What happens when the novelty wears off? How to we retain the interest of the student.

8. How can interfaces and systems be designed to foster this learning? • Lively/interactive/animated interfaces • exploit multimedia technology • video streaming; novel, good quality graphics (3D models) • intuitive, easy to use. • The scenarios we create • They must be relevant and interesting. • These must capture and carry the audience. • They must engage the student. • They must retain the student’s interest.

9. What are the best educational applications/contexts? • Depends on the educational context • robotics science (sensors and controls, architectures, algorithms); • science & exploration (physics, chemistry, geography, biology; space programmes (Mars)) • work crews (multi-skill tasks, automation; industrial, space and home applications) • So far, limited sets of contexts • We need to broaden the range of applications? • Educational target • kindergarten, school, college, undergraduate, graduate, and continuing education, the general public

10. How should student experience be evaluated? • Educational merit for students • Updating traditional methods (submission/demonstration of work) • Incorporating new methods (online) • Developing transferable skills (presentation of work) • Exploring opportunities (track student participation) • Maintaining integrity/security (copying; surrogate participation) • Quality of the experience • Explicit: Questionnaires (online, offline, tutor follow-up) • Implicit: Monitor usage of system and the support environment (e.g. group communication; virtual communities; online blackboard systems?)

11. Can a site be designed to lead students through an experiment and quiz afterward? • Can we do this? Yes. • Will it be interesting/effective/relevant? • What are the characteristics of interesting/challenging scenarios? • The learning metaphor • rote learning Vs open, learner-centred, etc. • How do we control the direction/progression of learning? • Is this important? Where is it important?

12. Broad conclusion • There is considerable depth to the field. There is much to be discovered? • There are many issues, raising lots of problems. • There is no one answer, but there are common frameworks that can be established.

13. Online Robots are An important Learning Technology • Robot systems are instruments that help us: • understand our environment (Science and Exploration) • manipulate our environment (Work crews and lab. Assistants) • Robotics Science underpins these possibilities. • The Internet and Multimedia technology has created the possibility for a new kind of learning environment. • Online Robots help us bring to these environments an active, open-ended learning experience. • Online Robot are an important learning technology. Conceptualised as follows:

14. Online Robots are an important learning technology

15. Frameworks • Online Robot systems offer interactive control of remote (real or simulated) robotic artifacts, either • directly via manual controls • or indirectly via modelling interfaces, simulated environments and/or educational scenarios

16. Frameworks

17. Key problems can be identified • The retention problem • getting and maintaining interest • The reset problem. • The scenario problem. • The assessment problem. • The security problem • access and malicious intent • The audience problem

18. The Reset Problem • Resetting the environment to a defined state for the next user. • Laboratory systems • project development and demonstration • Robotic laboratory assistants provide one answer to this problem • Arena/experiment design provides another

19. The Scenario Problem • Developing challenging/interesting educational scenarios. • What are good, interesting, challenging scenarios? • Targets of control? • One or more humans. • Robot (toys), motors – controls • Simulations/models • Integration of simulations/models with real robot systems. • Method of control: • voting, parameter sets, manual driving, scripts, intelligent control (architectures, sensors and controls, algorithms), topical module • Author of control - topic/user-led. Open/closed

20. The Assessment Problem • Immediate - automated assessment-as-you-go. • Off-line delivery – submit reports, code, demos. • Transferable skills - e.g. presentation skills. • Present material via the web. • Acknowledging receipt/assessment of work. • Providing students with the tools to return work. • Annotation scripts, WWW pages, etc.

21. The Security Problem • Avoiding cheating. • Avoiding surrogates. • Controlling access. • Defending against malicious intent. • robots • web sites

22. The Audience Problem • Who is the target audience? • kindergarten, college level students • undergraduate, graduate level • continuing education and professional development • general members of the public • Getting teachers on board. • Educational kits (projects, educational materials, challenges)

23. Additional Issues • Re-use of research facilities. • Turning existing research environments into educational tools. Reuse. After-life funding. • Quality of service • Delivering an appropriate server to the user! Bandwidth problems, networking problems, time-delays. • Education as an application of robotics technology. • Enhancing the ‘presence’ within the remote environment. A target application of robotics techniques.

24. Action Points • Encourage the development of online robot systems: • Educational Challenges • Online scenarios • Create online environments • Provide forums for collecting experience/practice/facilities • WWW sites • Workshops & Conferences • Publications (books, special issues) • Online robot portal; online science programme. • Address the problems

25. Conclusions • There exists educational technologies that can be brought to bear on the educational application of online robots. • There is much that online robots can bring to this educational environment. • There is considerable scope for creating robot-centred learning technologies. • Presentation & application are important.