benitez2020: Benitez et al. (2020) temporal-structure-of-naming experiment...

In XSLmodels: Run and Optimize Cross-Situational Word Learning Models

Benitez et al. (2020) temporal-structure-of-naming experiment data

Description

A named list of 7 xslData objects from Benitez, V. L., et al. (2020), "The temporal structure of naming events differentially affects children's and adults' cross-situational word learning" (data/materials: https://osf.io/2hmxr/): one per condition (Interleaved, Massed, Unstructured) x age-group (kids, adults) combination, except Unstructured's first training order, which only has child data. Unstructured has two training orders; its second and third were confirmed identical by the original extraction and are pooled as "order 2/3".

Usage

benitez2020

Format

An object of class list of length 7.

Details

8 symmetric word-object pairs (word i pairs with object i), 2 pairs per training trial, 12 trials, followed by an 8-item 2AFC test. accuracy and response_matrix are real per-word 2AFC accuracy and raw response counts for that condition/age-group combination (not an estimate) – structurally this could join xsl_datasets, but is kept standalone deliberately as held-out generalization-test data; see xsl_holdout_datasets. data-raw/Benitez2020-rep/Benitez2020_XSLdata_extraction.R extracts the raw OSF data into training orders, 2AFC test trials, and response matrices; data-raw/add_benitez2020.R builds the xslData objects from those.

Examples

benitez2020[["Interleaved, kids"]]$accuracy
m <- xsl_run(baseline(), benitez2020[["Massed, adults"]])$fits[[1]]$matrix
mafc_test(m, benitez2020[["Massed, adults"]]$test)

XSLmodels documentation built on Oct. 18, 2026, 5:08 p.m.