Teaching statistical variability with equivalence‐based instruction

Abstract

In the present study, equivalence-based instruction was used to teach 2 4-member classes representing high and low statistical variability to 10 college students. Computerized equivalence-based instruction with multiple-exemplar training was used to teach the classes. A pretest-training-posttest design evaluated performances on both computer-based tests and written multiple-choice tests. Scores improved from pretest to posttest on both the computerized and the multiple-choice tests for all students following equivalence-based instruction. Class-consistent selections also generalized from training to novel stimuli and to a novel context (i.e., written test). Finally, class-consistent performances maintained 1 week after equivalence-based instruction was completed. The study demonstrated that equivalence-based instruction can be used to teach labeling of statistical variability and that a selection-based teaching protocol administered on a computer can promote the emergence of responses to a written selection-based testing protocol.