[CogSci] Call for unpublished data - interleaving in category learning

Yan, Veronica veronicayan at austin.utexas.edu
Fri Nov 8 08:51:21 PST 2019

Hi all,

We are currently conducting a meta-analysis of the effect of interleaving versus blocking study examples on categorization performance. We have recently finished our search of the published literature, and we are currently searching for unpublished (grey) data on the interleaving effect.

The typical paradigm that we are looking for would include the following conditions:

Learning/practice of multiple categories or concepts
Direct comparison of blocking (one category at a time) and interleaving (examples from different categories are intermixed)
A final test in which participants classify new examples from the studied categories

We are interested in the overall effects of sequencing, as well as moderators. We are searching for in-press or unpublished data that researchers are willing to share. This can be in the form of raw data, summary statistics, or other.

Thank you very much for your time and attention. We are very much aware of the effort that researchers must go through to obtain old data, and we appreciate your effort.


Veronica Yan, Assistant Professor, University of Texas at Austin
Luke Eglington, University of Memphis
Brendan Schuetze, University of Texas at Austin

p.s. We did just see that there is an in press interleaving meta-analysis (Brunmair & Richter, Psych Bulletin), but we are still continuing to search for unpublished data as we have a different scope.

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