An application of mathematical programming concepts to behavioural research design

Area of Science:

• Human Factors Engineering
• Behavioral Science Research Methods
• Operations Research

Background:

• Increasing demand for reusable behavioral research and evaluation techniques across various systems.
• Need for robust methods applicable by non-behavioral scientists.
• Challenges in ensuring repeatability and standardization in behavioral research.

Purpose of the Study:

• To present a general model for applying mathematical programming to behavioral research design.
• To demonstrate the utility of mathematical optimization in creating repeatable evaluation techniques.
• To design a simulator certification program for the Strategic Air Command (SAC) using this approach.

Main Methods:

• Utilizing mathematical optimization concepts, such as linear programming, for technique design.
• Developing a generalizable model for integrating optimization into behavioral research.
• Applying the model to a specific case: the Strategic Air Command simulator certification.

Main Results:

• A framework for designing repeatable behavioral research and evaluation techniques.
• Successful application of the model to create a simulator certification program.
• Demonstration of mathematical programming's effectiveness in behavioral research design.

Conclusions:

• Mathematical optimization provides a robust foundation for repeatable behavioral research.
• The proposed model offers a systematic approach for designing evaluation techniques.
• This methodology enhances the applicability and reliability of behavioral research across different domains.