ABA Fundamentals

Teaching statistical variability with equivalence-based instruction.

Albright et al. (2015) · Journal of applied behavior analysis 2015
★ The Verdict

A short computer lesson taught college kids to spot statistical variability and the skill lasted one week on paper.

✓ Read this if BCBAs who train staff or clients to read data charts.
✗ Skip if Clinicians only doing direct early-intervention drills with toddlers.

01Research in Context

01

What this study did

Albright et al. (2015) sat 10 college students at a computer.

The screen taught them to label graphs as high or low statistical variability.

Lessons used equivalence-based instruction with many examples.

No control group—just pre-test, training, post-test, and a one-week check.

02

What they found

After the lesson every student sorted new graphs correctly.

They still could do it a week later on paper tests.

Skills moved from computer to pencil-and-paper without extra teaching.

03

How this fits with other research

Oliveira et al. (2021) later showed you can cut training time.

They used the same 1-to-many (OTM) structure and kept the high scores.

Benitez et al. (2023) moved the method out of the lab.

Parents and teachers used equivalence lessons to teach reading to kids with autism.

All three studies show the same core tool works across ages, places, and topics.

04

Why it matters

You can pack tough concepts into short computer lessons.

Equivalence-based instruction builds links that survive time and setting changes.

Try it when you need staff or clients to master data patterns fast—no hand-holding required.

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→ Action — try this Monday

Build a five-trial equivalence set on your next graphing skill—train one exemplar, test two new ones, and check again Friday.

02At a glance

Intervention
stimulus equivalence training
Design
pre post no control
Sample size
10
Population
neurotypical
Finding
positive
Magnitude
large

03Original 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.

Journal of applied behavior analysis, 2015 · doi:10.1002/jaba.249