Data for: How do we measure and increase systems thinking? Comparing self-reported and performative metrics in response to building causal loop models

Systems thinking is a mindset and skill essential to understanding and taking effective action to address complex challenges. However, increasing and measuring systems thinking is difficult. This data set includes multiple approaches to measuring systems thinking. It includes 3 self-reported measures of a systems thinking mindset, and 2 performative measures of systems thinking skills (metrics derived from causal model diagrams of a system that participants created, and accuracy of responses to simple trophic cascade scenarios). The data allow for a comparison between different measurement approaches. They also allow for the evaluation of whether systems thinking is specific to disciplinary domains (ecological vs economic) or generalizes across domains.  Finally, the data provides a preliminary assessment of whether building causal models increased systems thinking.
, Participants (N = 185) were workers from Amazon Mechanical Turk (MTurk) and located in the United States. Participants were paid $5.00 (roughly $10/hour).
Our survey used a mixed-methods counterbalanced design, resulting in both within-and between-subjects measures described in the table below. 
The survey was administered using Qualtrics and was entirely online. After providing informed consent, all participants completed pre-measures (the exact measures varied based on random assignment). All participants then watched a 5-minute instructional video created by the researchers and available at https://vimeo.com/479005460. The video explained and provided an example of how to use Mental Modeler. It did not, however, use the term model or system or discuss or explain anything about systems thinking.
Participants then read a written description of the ecological system. This narrative described how the foxes were dependent on the rabbits as a food source, and that the foxes reduced th..., , # Data for How do we measure and increase systems thinking? Comparing self-reported and performative metrics in response to building causal loop models

[https://doi.org/10.5061/dryad.573n5tbh8](https://doi.org/10.5061/dryad.573n5tbh8)

## Description of the data and file structure

Data can be found in the file DataForHowDoWeMeasureIncreaseSystemsThinking.csv. Each row corresponds to one participant, and missing data is indicated with a blank field.

Variable names and values can be found in the file MetaDataForHowDoWeMeasureIncreaseSystemsThinking.csv.Files and variables

#### File: MetaDataForHowDoWeMeasureIncreaseSystemsThinking.csv

**Description:** Metadata that describes the meaning of each variable and value in the data file

#### File: DataForHowDoWeMeasureIncreaseSystemsThinking.csv

**Description:** Data

## Supplemental materials (Zenodo)

Detailed descriptions of aspects of the study can be found in the supplemental materials files. 

**File**: SI1RippleEffectQuestionDetail..., We received written consent from participants to publish de-identified data. IP addresses, prolific IDs, and all demographic data has been removed from the file.