Predicting the extension of equivalence classes from primary generalization gradients: the merger of equivalence classes and perceptual classes.
Pre-training generalization gradients forecast which untrained items will later enter an equivalence class.
01Research in Context
What this study did
The team asked: can a simple pre-test tell us which new items will join an equivalence class?
They showed college students lines of different lengths and nonsense words.
First they mapped how each line length ‘felt’ to the learner. Then they taught four-member classes and checked if the pre-mapped lines slid into the new class.
What they found
The early ‘feel’ ratings matched the final class members.
If a line gave a smooth generalization gradient before training, it later acted as part of the class.
How this fits with other research
Arntzen et al. (2018) later added pictures and a 6-second delay before equivalence training. Their tweak lifted success from 17% to 75%, showing the gradient idea still holds but can be boosted.
McConkey et al. (1999) moved the same logic down to preschoolers. Kids formed, expanded and even flipped their classes, so the gradient rule works across ages.
Fields et al. (2002) swapped equivalence for perceptual classes. They also used gradients to predict membership, proving the trick works beyond word-line setups.
Why it matters
You can now screen stimuli before the first teaching trial. Run a quick generalization probe, pick the items that feel ‘close,’ and use them as nodes or targets. This saves teaching time and cuts failed classes.
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02At a glance
03Original abstract
In Experiment 1, 6 college students were given generalization tests using 25 line lengths as samples with a long line, a short line, and a "neither" option as comparisons. The neither option was to be used if a sample did not go with the other comparisons. Then, four-member equivalence classes were formed. Class 1 included three nonsense words and the short line. Class 2 included three other nonsense words and the long line. After repeating the generalization test for line length, additional tests were conducted using members of the equivalence classes (i.e., nonsense words and lines) as comparisons and intermediate-length lines as samples. All Class 2 comparisons were selected in the presence of the test lines that also evoked the selection of the long line in the generalization test that had been given before equivalence class formation. Class 1 yielded complementary findings. Thus, the preclass primary generalization gradient predicted which test lines acted as members of each equivalence class. Regardless of using comparisons that were nonsense words or lines, the post-class-formation gradients overlapped, showing the substitutability of class members. Experiment 2 assessed the discriminability of the intermediate-length test lines from the Class 1 (shortest) and Class 2 (longest) lines. The test lines that functioned as members of an equivalence class were discriminable from the line that was a member of the same class by training. Thus, these test lines also acted as members of a dimensionally defined class of "long" or "short" lines. Extension of an equivalence class, then, involved its merger with a dimensionally defined class, which converted a close-ended class to an open-ended class. These data suggest a means of predicting class membership in naturally occurring categories.
Journal of the experimental analysis of behavior, 1997 · doi:10.1901/jeab.1997.68-67