1. Research on Development of Intelligent Tutoring Systems (ITS) to Support Embedded Training (ET) in Future Army Systems presented by : Henry Marshall RDECOM Simulation and Training Technology Center (STTC)

2. 2 Outline Background in ET Proposed ITS Design/ Intelligent Structured Training Concept Applications C2V Robotics Testbed CAT ATD Testbed Experiment Virtual Warrior Testbed Issues and Conclusion

3. 3 Embedded Combined Arms Team Training and Mission Rehearsal ATO ATO Researching Solutions to TRADOCs #1 Training Technology Gap – Mounted/Dismounted Interoperable Embedded Training Vision: Embedded Training & Mission Rehearsal for Combined Arms, Mounted & Dismounted Forces with Embedded AAR Current Sand Tables for Mission Rehearsal Training systems that are difficult or impossible to deploy Future – Interoperable Mounted & Dismounted Embedded Training Mounted Embedded Training Mounted Embedded Training Dismounted Embedded Training Solutions Dismounted Embedded Training Solutions Intelligent Tutoring Intelligent Tutoring Embedded Mission Rehearsal & AAR Embedded Mission Rehearsal & AAR Low-Cost Innovative Dismounted Embedded Training Solutions Low-Cost Innovative Dismounted Embedded Training Solutions Supports FCS & FFW Programs Robotic Embedded Training Robotic Embedded Training

4. 4 ITS and ET, a Good Match? Training (to include Embedded Training) is a Key Performance Parameter for the Future Combat System (FCS) and Ground Soldier Systems (GSS). Also requirement for Abrams, Bradley and Stryker. ET intent is to fully embed training system on the operational platforms The instructional staff at current Army fixed sites will likely not be available for deployed forces Can ITS-based technology be integrated with current simulation common components to replace the role of instructors for ET?

5. 5 FCS/ET – Training Challenge New paradigm requires scenario-based practice for FCS warfighters CCTT has successfully used a Structured Training concept for Basic Techniques, Task and Procedures Structured Training for CCTT STRUCTT Formal tactical doctrine for FCS operational concept is still evolving Desirable to minimize costs of developing and administering training – reduce requirements for human instructors and simplify scenario definition ITS are effective for simulating some of the benefits of a human instructor, especially for a domain with focused, task-based exercises Enter our ITS research to prototype possible solutions

6. 6 Intelligent Structured Training? Goals are to –Maximize Simulation Common Components in developing ITS system –Operate in typical virtual training environment –Develop a system capability of replacing instructors where possible Assumption –Because of the complexity of free play exercises and the number of possible solutions, ITS would be useable for only a limited set of predefined training scenarios Answer –Develop an ITS-based system that supports finite state transitions and provides prompts and feedback, operating in a virtual training scenario. We have named this Intelligent Structured Training (IST)

7. 7 Finite State Machine Evaluations What are they? Transition networks executing in coordination with a simulation to gather data about instructionally significant events and states, and make evaluation conclusions in real time Why use them in an ITS? Several benefits: –Modularity – they can be used separately or in conjunction for a variety of scenarios –Instructional correspondence – individual instructional principles can be associated with independent evaluations –Integration – the FSM structure is easily integrated with free-play simulations and maps well to diagnostics for widely varied outcomes –Authoring ease – they can be represented visually, making them easy for non-programmers to create, maintain, and revise –Application implements as a Behavior Transition Network (BTN)

8. 8 ITS FSM Evaluation Example TACTICAL: Before cresting hills, halt unmanned ground vehicles (UGV) and use mast sensors to scan for enemy

9. 9 Intelligent Structured Training Concept Goal: Provide the benefits of instructor-led training, in an embedded setting Methods –Based on Intelligent Tutoring System (ITS) technology –Intelligent agents perform automated evaluation during execution Subject matter experts define agent behaviors Behaviors defined in hierarchical behavior transition networks (BTN) –Real-time feedback, hinting, or coaching presented in Soldier Machine Interface Must operate on small “footprint” of embedded computer systems

10. 10 C2V Experiment Credit LTC Mike Sanders FA 57, mike.sanders@us.army.mil mike.sanders@us.army.mil Research based on needs of the FCS program to provide embedded training to deployed forces w/o the instructors of a training facility Prototype based on virtual task training for a robotics NCO duty station Explore mechanisms for feedback to the trainee Explore interfaces to OneSAF Testbed for ITS control of OPFOR / BLUFOR to facilitate training

11. 11 Command and Control Vehicle Crewstation Based on CAT ATD C2V Testbed CAT ATD Testbed

12. 12 Command and Control Vehicle Crewstation UAV Sensor view of the Synthetic Training Environment (STE) UGV Sensor view of the STE (Driver’s Position) UGV Sensor view of the STE (Gunner’s Position)

13. 13 Command and Control Vehicle Crewstation Robotic Assets/Mission Status Tool OCU/Situational Awareness Map Tele-Operation Asset Tool

14. 14 ITS Generated Feedback Prompt Immediate Directive Feedback (Procedural Error Prompt)

15. 15 Approach and Scenario Overview Task Analysis for FCS equipped Unit of Action (UA) Required Functional Capabilities include sensor fusion and engagement techniques User ~ Robotics Operator in the C2V at the Company level Scenario ~ Route Reconnaissance ITS modified to trigger OneSAF behaviors via DIS

16. 16 Robotics Operator Tasks Coordinated use of robotic assets –Example: Maintain proper separation between air asset and ground vehicle Proper reporting procedures –Example: Send SITREP after reaching a control measure Proper engagement procedures –Example: Lase a target before sending call for fire Proper use of asset control tools –Example: Make sure a vehicle is currently being controlled before issuing commands in the control interface.

17. 17 Experimental Design Test group: 20 subjects Comparison conditions –Immediate Directive Feedback (IDF) only ITS generated feedback through prompts –AAR Only (Delayed Feedback) Human facilitated AARs used open-ended, content neutral prompts Experiment phases –Training and test phase Initial human-tutored and computer-aided instruction Two-phased execution Paper and pencil test –Retention and Post-test phase after 1 week delay

18. 18 Experimental Results Retention Scores for Procedural Knowledge Following Feedback MSD IDF Only3.72.92 AAR Only3.801.21 Procedural Errors Following Feedback MSD IDF Only28.2219.50 AAR Only42.0824.59 Retention Scores for Conceptual Knowledge Following Feedback MSD IDF Only3.102.03 AAR Only5.602.12

19. 19 Analysis The timing and type of feedback received during training does affect the acquisition, retention and transfer of knowledge Procedural knowledge –Retention scores elevated in both comparison conditions –Lower number of errors with Immediate Directive Feedback Conceptual knowledge –Retention scores elevated in both comparison conditions –Higher retention scores with AAR Bottom line – proven learning from embedded ITS feedback! This could provide deployable training and save $$$ if authoring cost were economical Improved Pre-Brief or Postbreif capability could help improve the ITS Conceptual Knowledge retention

20. 20 TARDEC CAT ATD Integration Goal Integrate ITS system in actual FCS suggatate Considerable TARDEC interest in ITS Performed interface evaluation via Engineering Evaluation Tests (EET) CAT ATD uses AKit/BKit architecture where A kit relates to vehicle unique, B Kit training simulation unique. Issues with deep integration and getting messages to displays.

21. 21 Virtual Warrior Experiment Credit Major Jason Sims FA 57, jason.sims@us.army.mil@us.army.mil Explore integration of Intelligent Structured Trainer to the Virtual Warrior Dismounted ET Man Wearable Prototype Examine ITS scenario authoring tools to construct training scenarios

22. 22 Authoring Tool Design Provide Visualization tool for 3D Placement of scenario objects Correlate objects to evaluations Format to exchange ITS related data to OTB was a issue Terrain collelation was a issue Used S2 Focus because of relation to VW

23. 23 VW-ITS Design ITS system integrated into VW System to evaluate Ground Soldier System (GSS) ET prototype Evaluation to move as a fireteam w/VW playing one of the team rest OTB Evaluation of Sending Reports as needed Evaluation of room clearing Evaluation of separation and sectors of fire

24. 24 VW-ITS Issues Numerous problems with OTB SAF behaviors filling out the rest of the Squad and OPFOR Evaluations limited by troop availability Most prefer system that would allow most of the squad to be live (e.g. team training) as opposed to interacting with SAF Virtual Locomotion of VW not liked, e.g. ability to move around database. Exposure to fire also a concern. Difficultly sending messages w/ C2 system

25. 25 Issues Integration/Interoperation with OOS and Training Common Components Best Future Direction, Game SDK vs. Training Common Components? Mix with a Operational Coach Mentor? Experiment with Enhanced / Muti-Modal feedback for ITS Integration into vehicles information/ET systems Transition with focus to PM - systems we developed were focused on experimentation Authoring systems for ease of production and usability by topic SMEs. Low Software License Costs. Production costs per tasks will drive economics of ITS acceptance. Explore Team Training Improved CGF for ITS for control of OPFOR/BLUFOR behaviors Exercise automated Pre-Brief/Post Brief Ability to adjust difficultly level either before execution or dynamically

26. 26 Discussion??