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.
Highlights
As a useful and influential method to gain scientific understanding, experimentation is attracting increasing attention from systems and engineering (SE&D) community
This paper has studied 1) the information and/or information flow involved in creating design decision making experiments, 2) the formalization of the manner in which the information is structured and the associated information flows, and 3) the representation of the information in an achievable and executable way
We propose a research question, as shown in Figure 4: what is a reusable and executable model of experiments? Considering the research gap of SE&D community, answering this question means three encountered problems need to be resolved: 1) determining what information and/or information flow are involved in creating design decision making experiments; 2) formalizing the manner in which the information is structured and the associated information flows; 3) representing the experimental design knowledge to support designers in an achievable and executable way
Summary
As a useful and influential method to gain scientific understanding, experimentation is attracting increasing attention from systems and engineering (SE&D) community. The remainder of this paper is organized as follows It begins with the foundations, which frames the scope of experiments modeling, generally depicts the information levels of experimental design, identifies and illustrates the gap of this research. In terms of the underlying principles within decision centric activities of design, certain similarities emerge experiments are diverse irrespective of their forms or purposes Based on these similarities and some components in social science (e.g., the way to incentivize an individual), a generic information model of experiments can be developed. This paper attempts to provide an information model that supports researchers of SE&D community designing experiments on decision-making behavior.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
