Presenter Email

zihokang@ou.edu

Location

Jim W. Henderson Administration & Welcome Center (Bldg. #602)

Start Date

14-8-2017 1:15 PM

End Date

14-8-2017 2:45 PM

Submission Type

Presentation

Topic Area

Human factors

Keywords

UDL, Universal Design for Learning, ILS, Index of Learning Styles, ATC, Air Traffic Control, ATC Training, Learning Styles, Multi-Modal Training

Abstract

Currently, most learning methods are based on classroom teaching through unidirectional communication using boards or slides. However, the Universal Design for Learning (UDL) asserts that the students can increase their performance if the instructors can provide the students with diversified information representation, expression, and engagement means. Although UDL minimizes the mismatch between the teaching and learning styles, we lack the detailed methods to implement the UDL and its associated multi-modal training methods in the context of air traffic control candidates and/or technical operators. We propose an approach that adapts the Index of Learning Styles (ILS) based on four categories: perception, input, processing, and understanding. Tailored to air traffic control candidates, we show how the adapted ILS framework can be used to (1) map the UDL principles (associated with multi-modal training methods) with the ILS outcomes using specific examples, (2) assess the teaching and learning styles of instructors and students, and (3) provide possible approaches to address any mismatch and/or ways to enhance the teaching materials. The developed approach will be used as a framework to investigate whether and how we would be able to enhance the air traffic control candidates’ performances at the FAA academy.

Presenter Biography

Dr. Kang is an Assistant Professor in Industrial & Systems Engineering and is the Director of the Human Factors and Simulation Laboratory at The University of Oklahoma. Dr. Kang’s background is in human-integrated systems modeling, and his specialty is in eye tracking data analysis methodologies. Dr. Kang’s research objective is to characterize, model, and analyze human decision making processes in order to understand human behavior and to inform the design of complex systems. He previously worked at Samsung and has performed research for National Aeronautics and Space Administration (NASA) and Collaborative Adaptive Sensing of the Atmosphere (CASA). Dr. Kang is currently corroborating with Federal Aviation Administration (FAA) and National Oceanic and Atmosphere Administration (NOAA).

RESEARCH INTERESTS

  • Human-integrated systems engineering
  • Human factors
  • Eye tracking data analysis methodologies
  • Air traffic management system
  • Weather system
  • Healthcare system

EDUCATION

Ph.D., Industrial Engineering, Purdue University

M.S., Industrial Engineering, Purdue University

B.S., Industrial Engineering, Korea University

View Ziho Kang's Bio Page

1073 Kang UDL.pptx (493 kB)
Original PowerPoint, Full-res

 
Aug 14th, 1:15 PM Aug 14th, 2:45 PM

Adaptive Learning Pedagogy in UDL and Multi-Modal Training

Jim W. Henderson Administration & Welcome Center (Bldg. #602)

Currently, most learning methods are based on classroom teaching through unidirectional communication using boards or slides. However, the Universal Design for Learning (UDL) asserts that the students can increase their performance if the instructors can provide the students with diversified information representation, expression, and engagement means. Although UDL minimizes the mismatch between the teaching and learning styles, we lack the detailed methods to implement the UDL and its associated multi-modal training methods in the context of air traffic control candidates and/or technical operators. We propose an approach that adapts the Index of Learning Styles (ILS) based on four categories: perception, input, processing, and understanding. Tailored to air traffic control candidates, we show how the adapted ILS framework can be used to (1) map the UDL principles (associated with multi-modal training methods) with the ILS outcomes using specific examples, (2) assess the teaching and learning styles of instructors and students, and (3) provide possible approaches to address any mismatch and/or ways to enhance the teaching materials. The developed approach will be used as a framework to investigate whether and how we would be able to enhance the air traffic control candidates’ performances at the FAA academy.

 

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