color-rule

Data & Materials from

Zettersten, M., & Lupyan, G. (2020). Finding categories through words: More nameable features improve category learning. Cognition, 104135. doi: 10.1016/j.cognition.2019.104135

Abstract

What are the cognitive consequences of having a name for something? Having a word for a feature makes it easier to communicate about a set of exemplars belonging to the same category (e.g., “the red things”) - might it make it easier to learn the category itself? Here, we provide evidence that the ease of learning category distinctions based on simple visual features is predicted from the ease of naming those features. Across seven experiments, participants learned categories composed of colors or shapes that were either easy or more difficult to name in English. Holding the category structure constant, when the underlying features of the category were easy to name, participants were faster and more accurate in learning the novel category. These results suggest that compact verbal labels may facilitate hypothesis formation during learning: it is easier to pose the hypothesis “it is about redness” than “it is about that pinkish-purplish color”. Our results have consequences for understanding how developmental and cross-linguistic differences in a language’s vocabulary affect category learning and conceptual development.

Link to OSF project:

https://osf.io/fmhku/

Link to AsPredicted pre-registration forms:

Experiment 2B: https://osf.io/4euck

Experiment S4: https://osf.io/zfqy8

Link to preprint:

https://psyarxiv.com/uz2m9/

Analysis

The folder analysis contains the following documents:

• CRN_analysis.R: An R script documenting all analyses included in the manuscript

• summarizeData.R: An R script including help functions to summarize data

• vif.mer: An R script containing help functions to assess multicollinearity in mixed-effects models

Data

The folder data contains the following documents:

Main files

• CRN_data.txt: The complete experimental data set

• CRN_codebook.txt: A codebook for the experimental dataset (CRN_data.txt)

Additional files

• color_discriminability_rt_data.csv: Data from behavioral reaction-time task norming color discriminability

• color_properties.csv: File containing summary information on individual color feature properties

• color_properties_discriminability.csv: File containing summary information about the pairwise discriminability of color features

• CRN_verbal_strategies.csv: Coded self-reported verbal strategy data

• CRN_verbal_strategies_codebook.txt: Codebook for self-reported verbal strategy data (CRN_verbal_strategies.csv)

• property_data_codebook.txt: A codebook for files containing summary information about feature properties:

  • color_discriminability_rt_data.csv
  • color_properties.csv
  • color_properties_discriminability.csv
  • shape_discriminability_rt_data.csv
  • shape_properties.csv
  • shape_properties_discriminability.csv
  • tangram_properties.csv

• shape_discriminability_rt_data.csv: Data from behavioral reaction-time task norming shape discriminability

• shape_properties.csv: File containing summary information on individual shape feature properties (Exp 3A & 3B)

• shape_properties_discriminability.csv: File containing summary information about the pairwise discriminability of shape features (Exp 3A & 3B)

• tangram_properties.csv: File containing summary information about the properties of the shape features used in Experiment 4

Stimuli

The folder stimuli contains all stimuli used across the experiments reported in the paper and in the supplementary materials.

Figures

The folder figures contains figures from the manuscript (in some cases, some additional editing was conducted in Keynote, e.g. adding stimulus images to plots).

Questions

Feel free to contact me at [email protected] if you have any comments or questions about the data or the analyses.