Research Interests
Our fields of research cover issues of personality, personality and
intelligence interaction, achievement motivation, faking, and working
memory. We are interested in theoretical basics as well as practical
implementations. The focus regarding practical implementation is set on
prognostic validity and effects of faking.
Personality
Noncognitive measures are continuously gaining importance. During the
last years, despite many controversies, interest is directed especially
towards the Big-Five. The construct and criterion validity of the
Big-Five was thereby tested in several studies. However, there is an
ongoing debate whether there are higher order factors, above the Big 5.
We study the influence of situational circumstances on these
metatraits.
Personality and Intelligence Interaction
When predicting human performance or learning, intelligence has proven
a powerful variable. Aspects of personality, such as openness to
experience or conscientiousness have also been successfully included in
many studies. However, research on the combined impact of intelligence
and personality is rare. Moreover, usually a linear combination is
assumed. We are conducting several studies exploring possible
interactions between intelligence and personality in the prediction of
human perfomance and learning.
Achievement Motivation
Some studies, especially long-term studies, have shown that, besides
intelligence and personality, differences in achievement motivation
help to explain differences in achievement. However, when it comes to
measuring motives, there exist numerous different approaches:
Objective, subjective, projective, and semi-projective methods. Besides
that there are instruments measuring general motives and others
assessing domain specific aspects. Within a series of our team’s
studies, the similarities of the methods, their predictive validity,
and their sensitivity for falsification are being analyzed.
Faking
As described earlier, the influence of the situation affects construct
and criterion validity of noncognitive measures. In a broader sense,
faking can be understood as situational influence. The effects are
analyzed with a variety of methods, e.g., Latent State Trait Designs,
Individual Causal Effect Designs, and Mixed Rasch Models. The present
results show: Faking aggravates the correlation between personality
measures. If one controls this influence, the correlations fall to
close to zero. Furthermore, we were able to show that the individual
differences related to faking are barely valid for prediction. Other
results show that there are different faking strategies. A model was
developed based on the results.
Intelligence and Working Memory
General Mental Ability has been proven in many studies to be the most
valuable predictor for professional and academic success. Alongside
there exist a couple of other cognitive constructs, including working
memory. Our team analyzes the interaction between intelligence, working
memory, and mental speed. This basic work not only serves the better
understanding of human cognitive performance, but should also improve
the prediction of human behavior.