EPÆG

Research Methods

EPÆG follows a multimethodical and multimodal research strategy. Multimethodical in terms of behavioural, neurophysiological and neuropsychological research procedures. Multimodal, as EPÆG wants to go beyond single modalities by investigating cross-modal and multimodal aspects of, for instance, aesthetics in car interiors (visual properties, haptics) or adaptation effects (visual and acoustical). EPÆG research with focus on vision modality in the field of „dynamics of aesthetic appreciation“, and with focus on haptics and cross-modalities in industry-based projects.EPÆG follows a multimethodical and multimodal research strategy. Multimethodical in terms of behavioural, neurophysiological and neuropsychological research procedures. Multimodal, as EPÆG wants to go beyond single modalities by investigating cross-modal and multimodal aspects of, for instance, aesthetics in car interiors (visual properties, haptics) or adaptation effects (visual and acoustical). EPÆG research with focus on vision modality in the field of „dynamics of aesthetic appreciation“, and with focus on haptics and cross-modalities in industry-based projects.

EPÆG brings together a team of scientists interested in Ergonomics, Psychological Æsthetics and Gestaltung. Our research goes from psychophysics to high level cognitive mechanisms, while developing and empirically testing psychological theories of Æsthetic perception and cognition. We develop guidelines and principles for applied solutions in design and ergonomics.


Statistical methods

  • Descriptive statistics (numeral and graphical inspection and analysis)
  • Inferential statistics (e.g., experimental designs, correlational analysis, group comparisons, analysis of variance, multivariate methods)
  • Practical statistics (e.g., regression analysis, bi-dimensional regression, causal path analysis)
  • Statistical classification (e.g., cluster analysis, muliti-dimensional scaling, discrimination analysis)
  • Further complex statistical methods (e.g., structural equation models, multi-group analysis)
  • Empirical test construction (e.g., factor analysis)
  • To explore multifaceted phenomena (like the emergence and dissemination of conspiracy theories), we also collect data in the field. The gathering of qualitative data — e.g., with a chinese whisper design of repeated playing and re-production — is an integral part of our research. These studies are usually accompanied by quantitative pen-and-paper approaches; and are, in most cases but a first step towards a controlled examination of single aspects in the lab.

Cognitive modeling

In addition to statistical approaches, we apply the full range of machine learning algorithms to find regularities in the data of multi-factorial, exploratory studies. By using classification algorithms (like decision trees and ID3), artificial neural networks (ANN) and other means, we get a grip on phenomena with lots of independent variables – where, with regression analysis or an ANOVA, hundreds of test subjects would be needed. This helps us identify the most important determinants, that then will enter a classical design.

Specific experimental designs

  • Adaptation paradigm
  • Repeated Evaluation Technique (RET)
  • SDT implementation
  • Measure of emotional reaction via startle reflex
  • IAT/mdIAT (multi-dimensional Implicit Association Test)

Physiological measurements

  • Eyetracking (scan paths, pupillometry, and attentional landscapes)
  • EDA/SCR/GSR (electrodermal activity/skin conductance response/galvanic skin response)
  • EEG/MEG (electroencephalogram, magnetoencephalogram)
  • EMG (electromyogram)
  • fMRI (functional magnet resonance imaging)