Predicting attitudes and behavior concerning living materials:

Development of software and analysis methods to apply cognitive affective maps

Cognitive Affective Maps (CAMs) constitute a novel approach for the prediction of acceptance. The aim of this project within livMatS is to advance this method to predict the acceptance of living materials systems. To this end, a software package that supports the usage of CAMs for data collection will be developed and optimized to allow the aggregation of large data samples from many participants.

For the validation of CAMs, assessment of a coherent cohort will be employed. This will be done through the collection of data in three different empirical samples:

  • One group of participants will select basal attributes of living materials systems to construe the maximum positive psychological acceptance.
  • A second group of participants will construe the maximum negative psychological acceptance.
  • A third group of participants will then construe conjoint, individual CAMs by combining positive and negative attributes.

The expectation is that possible positive and negative attributes of the materials will interact.

Prof. Dr. Andrea Kiesel

Principal Investigators
Prof. Dr. Lore Hühn
Prof. Dr. Andrea Kiesel

Responsible Investigators
Prof. Dr. Oliver Müller
Dr. Michael Stumpf

Doctoral Researchers
Sabrina Livanec
Lisa Reuter