Conducting Situated Learning in a Collaborative Virtual Environment

1. Conducting Situated Learning in a Collaborative Virtual Environment Yongwu Miao Niels Pinkwart Ulrich Hoppe

2. Overview • Pedagogical motivation – constructivism and situated learning • Approach and principles of 3D collaborative driving simulator • Implementation key decisions (driving place, situation detection, architecture for distribution) • Example scenes • Conclusions and future work Conducting situated learning in a collaborative virtual environment

3. 3D Simulations as constructivist learning environments • Core position of constructivism: learners actively construct knowledge • Knowledge based on interpretation of experiences in the real world (includes other learners!) • 3D Simulations of “real world” sometimes very appropriate (costs, safety)– learners can still be active and make experiences • Example: learning car driving Conducting situated learning in a collaborative virtual environment

4. Existing systems • Lots of 3D car driving simulators exist (games, educational, professional) • Educational systems typically try to confront learners with challenging situations • Often: “full size” systems very costly (advanced visual and audio systems, motion systems, functional cab, software components) • Growing PC and network performance allows “low cost” solutions – usually with pre-defined driving scenarios and tutors Conducting situated learning in a collaborative virtual environment

5. Our approach • Low cost (standard PC and network), support for multiple users • Variety of challenging situations that “might happen” through interaction / collaboration – no predefined scenes! • Consider situated learning principles: Content Community Learner Context Participation Conducting situated learning in a collaborative virtual environment

6. Driving place design • Key requirement: rich data model (realistic content & context), but still small enough for distributed usage • General approach: cell grid • Each cell containing typed objects (static or dynamic) with attributes • Example: “car” object with attributes direction, speed, acceleration, turning angle, brake status, indicator status, sector information Conducting situated learning in a collaborative virtual environment

7. Map editor • Create driving places easily by drag & drop • Maps transformed to VRML • Display via Java 3D Conducting situated learning in a collaborative virtual environment

8. Situation description and recognition • Not needed for most basic functionality (except collision detection) • Essential for advanced functions (user behavior analysis, feedback) • Technical approach: Jess rules acting on object attributes • Situation detection  target specification • Additional control rules to check if targets have been reached Conducting situated learning in a collaborative virtual environment

9. Example: situation recognition (defrule safe_distance_violation (vpcar (position ?pos) (direction ?dir) (speed ?speed)) (car_in_lane (car_position ?carpos) (car_direction ?cardir) (car_speed ?carspeed)) (not (target_state (desc safe_distance_violation))) (test (violated_safe_distance ?pos ?speed ?carpos ?carspeed)) => (bind ?list (create$ "distance")) (?*guidance* addInstruction 6 ?carpos ?list ?pos) (assert (target_state (situid 6) (checkpoint ?carpos) (chkpt_passed FALSE) (targets ?list) (desc safe_distance_violation))) (?*guidance* addMistakes ?list 6)) Attributes of student’s car Attributes of other car in lane Distancetoo small ? Definition of new target Conducting situated learning in a collaborative virtual environment

10. Distributed system architecture • Central tuple space contains attributed objects (driving place and additional information) • Different roles for teacher and student client Conducting situated learning in a collaborative virtual environment

11. Distributed system architecture Reduction of network traffic: • Transmission of only local context (sector arithmetic) • Only status change events (braking,accelerating, indicator) for cars, positions are inferred by clientapplications Conducting situated learning in a collaborative virtual environment

12. Feedback Based on situations recognition and targets, different types of feedback and guidance possible: • Forewarn messages or hints • Feedback after targets missed/reached • Implicit feedback (situation creation) • Guidance on demand Alreadyimplemented Conducting situated learning in a collaborative virtual environment

13. System architecture System prototype (simple graphics, small number of object types, restricted number of modeled situations) exists and has been used in a pilot study Conducting situated learning in a collaborative virtual environment

14. Example – student client Conducting situated learning in a collaborative virtual environment

15. Example – teacher client Conducting situated learning in a collaborative virtual environment

16. Conclusions • “Low-cost” collaborative 3D educational driving simulator, following situated learning approach • Allows training in a lot (though not all) of the skills needed for driving • No hard-coded “challenging situations” created by system, but (more realistic!) provision for collaborative situation creation • Students receive feedback on their performance in real-time Conducting situated learning in a collaborative virtual environment

17. Future Work • Agents simulating students • “Subtle” creation of situations by intelligent agents • Integration of audio communication functions • Evaluations beyond pilot tests Email: nielsp@cs.cmu.edu Conducting situated learning in a collaborative virtual environment