Trend Detection in Simulation-Based Training Performance Scores Obtained Under Varying Experimental Conditions / Mikel D. Petty.

Format:

Book

Author/Creator:

Petty, Mikel D., author.

Language:

English

Subjects (All):

Quantitative research.

Physical Description:

1 online resource

Place of Publication:

London : SAGE Publications Ltd, 2025.

Summary:

Virtual simulation is often used for training complex psychomotor skills, such as driving a vehicle or piloting an aircraft. In such simulation-based training, the assistance of an instructor is generally assumed to enhance the training's effectiveness. However, trainees may have opportunities to engage in simulation-based training when instructors are not available. In this study, the research question was to determine whether an experimental subject's task performance improved over a lengthy series of trials in a simulation without instructor assistance. However, over the course of the trials the experimental conditions sometimes changed in a way that affected the subject's performance, introducing a confounding factor into the data. A normalization method was used to make the subject's performance measure values comparable across trials. Then three nonparametric statistical methods for trend detection in a time series were used to determine if the subject's performance improved over time. This case study illustrates data analysis methods suitable in similar circumstances.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-03-621513-X

9781036215132

OCLC:

1523168747