Relationships

This page includes screenshots of the automatically processed dilemma and survey data. The values and images are periodically updated, most recently in June 2025.

Install the application for free to review the detailed dilemma scenarios and survey questions. Also, see the list of most promising Research Findings with dilemma descriptions and graphs.

Dilemmas and surveys

The creation of lessons and the selection of surveys depend on our team’s research interests and the input of our institutional partners.

Connections

To uncover factors that play a part in moral decision-making, data from user interaction is processed to identify possible connections between entries. Correlation and probability values are calculated to evaluate these relationships. Even though the data is quantitative, this is still explorative research, and all findings are preliminary and indicative. Due to the crowd-sourced data collection and high representation of Finnish university students, the data has a high risk of bias. As exploratory research, the aim is to generate hypotheses.

Between dilemmas

Correlations between answers to the dilemma scenarios and the respective sample sizes. A high positive correlation means that A-A and B-B connections are more likely; in turn, a high negative correlation implies that A-B and B-A connections are more likely. A value close to zero implies no connection between the two dilemmas. Many dilemma pairs have too few overlapping entries to have reliable correlation values.

With surveys

The correlation, probability, and sample size tables assist in analyzing whether these factors are determinants of the dilemma answers. High (positive or negative) effect size (or correlation), low p-value, and a large sample indicate a connection between the dilemma and the measured tendency. Some findings may seem over-promising because dilemma answers were overly uneven (A: 95%, B: 5%), which can distort the result. Importantly, these can only be used to rule out false positives; the only thing helping with false negatives is additional data.

Effect size = High positive value means that users with a high survey score are likely to answer A. Same reversed.
Probability = Low value means that it is likely that the survey is connected to the dilemma answer.
Sample size = The bigger the sample, the more reliable the result.

Due to the desire to automate the initial data screening process, Microsoft Excel is used to calculate correlations and probabilities. For publications, we instead use JMP with more advanced statistical methods.

Relationships between surveys and dilemmas hint that these factors may affect our judgments on bioethical questions. Which influence would be morally justified, or just an unwarranted bias?

Dilemma elaborations

After voting on a dilemma, users have an opportunity to elaborate on their decision. They can report their level of moral certainty and perceived moral significance of the question under consideration (slider scale 0-10). Additionally, after completing each lesson set, users can rate it. Correlations and probabilities are calculated based on user-specific averages to find out if some measured tendency influences these factors. Note that samples are still rather small.

The relationship between reported certainty and significance is presently being studied…

Sign up for updates on the Research page or contact the development team via Support to request access to data.