Survey-based research is a research method that involves the use of standardized questionnaires to collect information (data) from a sample of individuals in a systematic manner. The surveys can be quantitative (e.g., numerical questions or questions on a Likert scale), qualitative (e.g., open-ended questions), or mixed.
Survey-based research methodology is commonly used in various disciplines, ranging from social sciences to healthcare. However, considering practical constraints, it is difficult to provide real world experience of survey sampling methodologies to students and novice researchers. In this paper, the researchers proposed the development of a virtual learning environment based on agent modeling to help learn about different aspects and challenges of survey-based research.
The agent-based model has been implemented in AnyLogic, and the output (samples) was exported to comma-separated files. A study scenario of the adoption of an improved cookstove was developed as an agent model, where each household (sample point) was an agent. The agent's behavior was defined using statecharts and system dynamics models. The agent-based environment has been used to illustrate various learning points for students and novice researchers.
Canvas capturing the agent, its attributes, and its behavior
In this paper, a virtual learning environment was proposed that was based on agent-based simulation and that could be used as an exploratory and explanatory tool for survey-based research. Preliminary work was done to show how the agent-based environment could be used to model and illustrate various learning points for students and novice researchers.
The agent model was based on the adoption of an improved cookstove (technology solution) among households in a region. The behavior of the households (agents) was determined by system dynamics models, with other attributes initialized randomly.