Typicality effects in contingency-shaped generalized equivalence classes.
Pack your equivalence classes with feature-rich stimuli and teach in small, probed steps for faster, stronger emergence.
01Research in Context
What this study did
Floyd et al. (2004) taught college students to match nonsense syllables and abstract shapes. The team used one-to-many match-to-sample trials. After training, they tested if new patterns popped out without extra teaching.
They also asked which stimuli felt like the best example of each class. The goal was to see if richer features speed up learning.
What they found
Classes formed quickly when stimuli shared more critical features. Participants rated these rich items as better examples. Open-ended generalization still happened, but feature-rich cues made the path smoother.
How this fits with other research
Perez et al. (2015) extends this idea. They showed that a simple-to-complex protocol lifts success from 42% to 100%. Pairing Mark’s rich-feature items with that sequence could save even more time.
Frampton et al. (2023) adds another layer. Graphic-organizer note-taking pushed yields to 100%. So combining rich cues, smart sequencing, and learner drawings may give a triple boost.
Alonso-Alvarez (2023) sounds like a contradiction. The theory paper warns that contingency-only training can break classes. Mark’s study assumed contingencies were enough. The fix is to add multiple exemplars and checks, not drop contingencies.
Why it matters
You can speed up stimulus equivalence lessons tomorrow. Pick pictures or words that share clear, useful features. Run a few probes after each small set instead of massing all trials. If a learner stalls, sketch a quick graphic organizer together. These small tweaks raise the odds that new relations emerge without extra drilling.
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02At a glance
03Original abstract
Two experiments were conducted using match-to-sample methodologies in an effort to model lexical classes, which include both arbitrary and perceptual relations between class members. Training in both experiments used a one-to-many mapping procedure with nonsense syllables as samples and eight sets of abstract stimuli as comparisons. These abstract stimuli differed along a number of dimensions, four of which were critical to the experimenter-defined class membership. Stimuli in some comparison sets included only one of the class-defining features, but stimuli in other sets included two, three, or all four of the critical features. After mastery of the baseline training, three types of probe tests were conducted: symmetry, transitivity/equivalence, and novel probe tests in which the training nonsense syllables served as samples, and comparisons were novel abstract stimuli that included one or more of the class-defining features. Symmetry and transitivity/equivalence probe tests showed that the stimuli used in training became members of equivalence classes. The novel stimuli also became class members on the basis of inclusion of any of the critical features. Thus these probe tests revealed the formation of open-ended generalized equivalence classes. In addition, typicality effects were observed such that comparison sets with more critical features were learned with fewer errors, responded to more rapidly, and judged to be better exemplars of the class. Contingency-shaped stimulus classes established through a match-to-sample procedure thus show several important behavioral similarities to natural lexical categories.
Journal of the experimental analysis of behavior, 2004 · doi:10.1901/jeab.2004.82-253