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Sewing a Digital Thread with Competencies: Applications to Model Based Product Support Fritz Ray: CTO and Software Engineer Extraordinaire (doer) Robby Robson: CEO, Former Mathematician, Current Standards Professional, Competency Wonk (talker)


  1. Sewing a Digital Thread with Competencies: Applications to Model Based Product Support Fritz Ray: CTO and Software Engineer Extraordinaire (doer) Robby Robson: CEO, Former Mathematician, Current Standards Professional, Competency Wonk (talker) Eduworks Corporation, Corvallis, OR USA IT2EC 2020

  2. OPNAV N12 – Manpower and Training Acquisition Requirements for Training Transformation Goal: Apply a model-based product support (MBPS) approach to improve training and operational effectiveness 1 IT2EC 2020

  3. The Big Idea PRODUCT DATA Physical Model TRAINING PERFORMANCE Logical Model Functional Model • Single “threaded” source of truth • Product Data Training Performance • Performance Training Product Requirements 2 IT2EC 2020

  4. Benefits • Engineering changes propagate faster • Vulnerabilities addressed faster • Training based on authoritative source • Training is iteratively improved • Better performance 3 IT2EC 2020

  5. So … How Does it Work? 4 IT2EC 2020

  6. Technical Ingredients STANDARDS • Captures tech data • Creates interactive electronic technical manuals ( IETMs ) • Uses a Common Source Database ( CSDB ) o Single Source o No Duplication 5 IT2EC 2020

  7. Technical Ingredients STANDARDS • Captures Product Logistics Analysis (LSA) data • Specifies o Components and sub-components o Maintenance and Support Tasks o Subtasks o Failure Mode and Effects and Criticality Analysis o Key Performance Indicators • References S1000D (and other S-Series standards) 6 IT2EC 2020

  8. Technical Ingredients STANDARDS • GEIA 0007 • LSA standard (like S3000L) 7 IT2EC 2020

  9. Technical Ingredients STANDARDS • Captures o Training Needs Analysis o Training Design o First two steps in ADDIE • Ties to S1000D / S3000L • Specifies o Task Analysis Process o Task Selection Process (based on importance and frequency) o Media Types o Bloom Levels 8 IT2EC 2020

  10. Technical Ingredients COMPETENCIES Used to Knowledge, Skills, and perform TASK Abilities (KSAs) Needed to Perform the Task Objective is Generates to acquire Assess Learning Objectives Performance Indicators 9 IT2EC 2020

  11. Technical Ingredients Competencies and Skills System (CaSS) • Competencies o KSAs o Learning Objectives o NECs o O*Net Skills o And more • Frameworks o Structured sets of competencies • Linked Data o Identify, retrieve, process via URL Open Source. Part of ADL TLA. o Facilitates updates and integration 10 IT2EC 2020

  12. Technical Ingredients Competencies and Skills System (CaSS) Training Sailor successfully Activity aligned completed activity with competency System xAPI Statement Learning Record Store (LRS) Assertion: Sailor has competency (xAPI statement is evidence) 11 IT2EC 2020

  13. First Threads: The Bridge Project* Adds Produces S1000D SCORM Packaging Module SCORM Course for & Learning Data Module use in LMS Images from S1000D Transformation slides by Wayne Gafford and Tyler Shumaker * Work from 2010 - 2011 12 IT2EC 2020

  14. Next Threads: ARTT 2019 Competency GEIA 0007 and S100D Course & NLP Framework of S300L Content Structure Learning Objectives 13 IT2EC 2020

  15. Current Threads: ARTT 2020 GEIA 0007 and NLP S3000L S1000D ARTT System for Instructional Design (ASID) Tasks to Train Blooms Levels KPIs Associated KSAs Learning Objectives S6000T 14 IT2EC 2020

  16. Future Threads ARTT System Shipboard GEIA 0007 and IETM for Instructional Systems S300L Design (ASID) xAPI CaSS LRS Capture Competency Assertions Analyze Performance Measures of Personnel Readiness Records 15 IT2EC 2020

  17. Case Study: Integrated Low Pressure Electrolyzer (ILPE) Navy Fast Attack Submarine – Virginia Class Integrated Low Pressure Electrolyzer – Oxygen generating system. DEMONSTRATED: 1. ADDIE process based on MBPS 2. Propagation of changes 3. Analysis of results from IETM (not from shipboard systems) 16 IT2EC 2020

  18. Conclusions • Product data to training to performance works o Based on defense industry standards o Using AI (NLP) o With competencies as underlying data • Full two-way digital thread on the horizon 17 IT2EC 2020

  19. Discussion fritz.ray@eduworks.com robby.robson@eduworks.com

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