Creativity and decision making (1)

The first perspective considers the production of creative ideas as a decision process, where numerous ideas come to mind, but some are discarded along the way as they are not ‘useful’ enough, whereas other ideas – reaching some internal threshold – are expressed. The diffusion model, often applied to simple speeded decision tasks, can be adapted to examine this process. In this project an adapted form of the diffusion model will be used to examine the trade-off that takes place when moving to and between the idea generation and evaluation phases of the creative process.

Dr. Claire Stevenson, prof. dr. Han van der Maas & dr. Mathijs Baas

Optimal foraging strategies in semantic search (2)

The second perspective views the creative ideation process as a search process for possible solutions through long term memory – comparable to how people solve verbal fluency tasks (e.g. “List as many countries as possible within one minute.”). In recent papers researchers found that the search trough semantic memory appears to be similar to search in physical space, which involves a dynamic process of mediating between local exploitation and global exploration of clusters of information in much the same way that animals forage among patches of food in their environment. In this research project this optimal foraging strategy will be applied to data of a divergent thinking task (Alternative Uses Task data) to see whether the search process in memory resembles the search process for animals for food.

Dr. Claire Stevenson & Leonie Poelstra

Scoring algorithms of creativity (3)

The third research project focuses on the development of scoring algorithms to assign values of creativity to answers on the Alternative Uses Task. The performance of these algorithms will be compared to traditional scoring methods in terms of reliability and validity. The aim of this project is to develop a time-efficient and low-cost scoring method that can compete with existing methods. See this thesis for the results of the first version of such a scoring algorithm.

Dr. Claire Stevenson & Charlottte Tanis

AUT-networks (4)

The fourth research project focuses on the structure of the semantic memory as an explanation of individual differences in creative potential. We use network models to mimic these semantic memory structures, making it easier to relate the results to existing theories about creativity and memory. In this project responses to the Alternative Uses Task will be used to create a novel task that will be used to construct individual networks. See this thesis for a more thorough theoretic background and the first results.

Dr. Claire Stevenson & Iris Smal

Reliability of divergent thinking tasks (5)

In the fifth research project, we perform a meta-analysis regarding the reliability of divergent thinking tasks. Divergent thinking tasks are often used to measure creative potential and make claims about how creative abilities change over time or after an intervention. However, when you measure a person’s creative potential one day and then repeat this a few days later, the performance can be quite different. This implies that divergent thinking tasks are unreliable for longitudinal or intervention studies. Repeated assessment of creativity is of great interest for educators, developmental psychologists and those interested in the effects of interventions on creativity. For more details about the project, have a look at the Open Science Framework website.

Dr. Claire Stevenson, dr. Baptiste Barbot & Lea Naczenski

Towards a minimal theory of creativity: Theoretical predictions tested with data from a large-scale adaptive learning platform (6)

The minimal theory of creativity (MTC) is a theory that tries to explain creativity in the most logical and parsimonious way possible. It states that only intelligence and domain expertise are substantially related to creativity. In my research project, I seek to assess the plausibility of the MTC. For that purpose, specific predictions have been derived from the MTC and will be tested empirically. The two predictions are a) that intelligence and domain expertise are able to adequately predict creativity levels and b) that a nested model of intelligence + domain expertise model which also includes motivation will not perform any better than the basic intelligence + domain expertise model. To test these hypotheses, structural equation models will be computed and assessed regarding their goodness of fit, as well as compared to each other. The models will be fitted to an extract of a large database that stems from an online adaptive learning system called “Oefenweb”. Testing whether the predictions hold will allow for conclusions about the MTC and hopefully give basic grounds for further endeavors related to the investigation of the MTC.

Dr. Claire Stevenson & Niklas Frerichs

Future student projects (thesis and internship)

  • Use big data to develop and validate an algorithm to automatically score AUT responses.
  • Investigate the originality-utility trade-off in divergent thinking. Are adolescents’ responses more original and adults’ more useful?
  • Create Bayesian cognitive models of the ideation and evaluation phases of divergent thinking.
  • Creativity development: create new creativity tasks for children, investigate their psychometric properties, and gain new insights on creativity development (together with /
  • Combine network science and memory models to understand individual differences in creative ideation.