A Reusable and Executable Information Model of Experiments on Human Decision Making in Systems Engineering and Design

Yandi Bao, Zhenjun Ming*, Jitesh H. Panchal, Guoxin Wang, Yan Yan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Understanding decision making in design is becoming increasingly important within systems engineering and design research. While controlled experiments are used for testing hypotheses and are playing a significant role in developing theories, there is a lack of support for capturing and reusing knowledge associated with experimental design. The goal of this paper is to model the information required for designing and executing experiments, thereby enabling the reuse of past experimental designs. Using declarative formulations of four aspects of an experiment, namely, problem, process, participants and incentives, we extract the generic elements and standardize the structure of information as a Decision Experiment Design Support (DEDS) template, based on which an ontology is developed. The information necessary to execute an experiment is archived as DEDS templates and represented by a frame-based ontology that can be reused from one experiment to another. The approach is illustrated using two example experiments for studying the decision strategies of information acquisition, and the impact of domain knowledge on decisions. This paper offers a fundamental step towards reducing the barriers in designing and executing behavioral experiments for design and systems engineering research.

Original languageEnglish
Article number8984367
Pages (from-to)27597-27617
Number of pages21
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020

Keywords

  • Behavioral experiments
  • Decision making
  • Information modeling
  • Ontology

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