Analysis of Technical Operations Job Tasks

//Analysis of Technical Operations Job Tasks
Analysis of Technical Operations Job Tasks 2018-07-02T11:44:45+00:00

Project ID and Title: AN002-3 – Analysis of Technical Operations Job Tasks

Project completed May 2018

Collaborators:

  • PI: Dr. Ellen Bass, Professor and Chair, Department of Health Systems and Sciences Research, College of Nursing & Health Professions; Professor, Department of Information Science, College of Computing & Informatics, Drexel University
  • PI: Dr. Steven Landry, Associate Professor and the Associate Head in the School of Industrial Engineering, Purdue University
  • Postdoctoral Researcher: Andrew J. Abbate (Drexel)​
  • Student Researchers: Yul Kwon, Nguyen V.-P. Nguyen (Purdue) ​
  • Industry Partner: Eduworks
  • FAA Sponsor: Luis Ramirez, Technical Training (AJI-2)
  • FAA Technical Monitor: John Stillings

Abstract:

The training curriculum for technical operations and other mission-critical occupations includes thousands of learning objectives distributed across hundreds of courses. As the learning objectives in the curricula evolve, keeping the course materials aligned with the actual curriculum is challenging. To address this problem, this work will evaluate alignment with respect to matching text in the curriculum files and JTA task statements to help the FAA keep materials and objectives aligned.​

Expected Project Outcomes:

  1. Report on task identification and analysis, including current state of training documentation and needs.
  2. Training alignment analysis.
  3. Final report with recommendations.

Value of Research:

The proposed outcomes for this project is to research current job tasks for Technical Operations personnel and to develop a proposed model for integration of this job task analysis into existing courses that have outdated or no task alignment. This project will leverage natural language processing tools and algorithms for getting text from text-based training documents and JTA task statements, preparing text from the task statements and training documents so that they can be compared, comparing the text to identify what training documents are aligned/not aligned, and rendering outputs that the user can analyze.

This project will include:

  • An analysis will be conducted to identify the state of training and training documentation for the tasks.​
  • Development of a formal definition of alignment between job tasks and training, including developing a method for determining alignment for the task and training materials of interest, using natural language processing techniques.​
  • Recommendations for integration of current job task analysis into existing courses that have outdated or no task alignment.​

QUAD CHART AND TECHNICAL POSTERS:

AN002-3 2017 Expo Poster

AN002-03 Quadchart 2017

AN002-3 2018 Technical Poster