EBI Equivalence Based Instruction Jaba 43 01 0019

TEACHING BRAIN–BEHAVIOR RELATIONS ECONOMICALLY WITHSTIMULUS EQUIVALENCE TECHNOLOGY

DANIEL M. FIENUP, DANIEL P. COVEY, AND THOMAS S. CRITCHFIELD

ILLINOIS STATE UNIVERSITY

Instructional interventions based on stimulus equivalence provide learners with the opportunityto acquire skills that are not directly taught, thereby improving the efficiency of instructionalefforts. The present report describes a study in which equivalence-based instruction was used toteach college students facts regarding brain anatomy and function. The instruction involvedcreating two classes of stimuli that students understood as being related. Because the two classesshared a common member, they spontaneously merged, thereby increasing the yield of emergentrelations. Overall, students mastered more than twice as many facts as were explicitly taught, thusdemonstrating the potential of equivalence-based instruction to reduce the amount of studentinvestment that is required to master advanced academic topics.

Key words: college students, neuroanatomy, programmed instruction, stimulus equivalence

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Instructional interventions based on stimulusequivalence and related principles of stimulusclass formation (hereafter called equivalence-based instruction or EBI) focus on teachinggeneratively, that is, giving students the con-ceptual building blocks that allow them toreliably ‘‘go beyond the information given’’(Bruner, 1957; p. 41). The defining feature ofEBI is that students learn overlapping condi-tional discriminations that promote the forma-tion of additional, unpracticed abilities (e.g.,Critchfield & Fienup, 2008; Green & Saun-ders, 1998; Sidman, 1994; Stromer, Mackay, &Stoddard, 1992). For example, having learnedto associate the spoken word ‘‘cat’’ with both aphotograph of a cat and the printed word cat, achild may be able without further teaching torelate the cat picture to the printed word cat,even though the child has never experiencedthese together (e.g., see Sidman & Cresson,1973). This suggests that the picture and thespoken and printed words have become func-tionally interchangeable (i.e., the items are

recognized as ‘‘belonging together’’ or ‘‘mean-ing the same thing’’). In the language ofstimulus equivalence, the emergent ability torelate stimuli that were not previously paired,but that share a common associate, is calledtransitivity (Sidman) or transitive inference.Transitive inferences are expected to emergereliably only if certain foundational facts arelearned and only if these reflect overlappingconditional discriminations (Sidman).

Principles of stimulus class formation havebeen applied mainly toward enhancing therepertoires of young children and persons withdevelopmental disabilities. Relevant academicinstruction (for a seminal review, see Stromer etal., 1992) has, therefore, focused on basicacademic repertoires such as translating betweenfractions and decimals (Lynch & Cuvo, 1995),identifying letters (Connell & Witt, 2004; Lane& Critchfield, 1998a) or words (de Rose, deSouza, & Hannah, 1996), and translatingbetween English and Spanish words (Joyce &Joyce, 1993). In recent years, applications alsohave emerged that focus on basic social andcommunicative abilities (e.g., Perez-Gonzalez,Garcıa-Asenjo, Williams, & Carnerero, 2007;Rosales & Rehfeldt, 2007).

The published literature includes few instanc-es in which sophisticated academic material was

We thank Ruth Anne Rehfeldt and Rocio Rosales forhelpful comments on a draft of the manuscript.

Address correspondence to Daniel M. Fienup, who isnow at the Psychology Department, Queens College, 6530Kissena Blvd., Flushing, New York 11367 (e-mail:[email protected]).

doi: 10.1901/jaba.2010.43-19

JOURNAL OF APPLIED BEHAVIOR ANALYSIS 2010, 43, 19–33 NUMBER 1 (SPRING 2010)

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taught to advanced learners using techniquesbased on research on stimulus classes (Fields etal., 2009). We are aware of only two relevantreports, in which college students learned algebraskills through a combination of spoken instruc-tion and stimulus class formation (Ninness et al.,2005, 2006). The dearth of applications withsophisticated learners might not appear to bemuch of an oversight if it is assumed that suchlearners require little academic assistance. Yet, aslearner capability increases, so does the complex-ity of academic subjects. Consider, for example,the challenge of instructing college studentsabout the biological bases of behavior (seeWilson et al., 2000). Even an elementarytextbook on this topic contains many hundredsof unfamiliar terms and concepts related toneuroanatomy and the biochemical functioningof brain regions and individual neurons (e.g.,Carlson, 2005). Each anatomical feature must beunderstood in relation to its various physical andfunctional characteristics. Couple this with thetypical college course schedule, which includesonly a few hours per week of formal instruction,and it is easy to see why even in advancedacademic programs it is important to get themost out of limited instructional time (e.g.,Chew, 2008). The present study illustrates howthis may be achieved through stimulus classformation.

One key feature of the present study was anattempt to promote generative respondingthrough a phenomenon called class merger, inwhich two stimulus equivalence classes sharing acommon member spontaneously merge to formone larger class (Fienup & Dixon, 2006;Sidman, Kirk, & Willson-Morris, 1985). Classmergers increase the number of potentialrelations among facts that have never beendirectly paired (i.e., more emergent relations;see Lane & Critchfield, 1998b). Nevertheless,this tactic of arranging for class mergers todevelop more relations than those taught rarelyhas been employed to academic advantage. Toillustrate the potential benefits, consider a study

by Lane and Critchfield (1998a) in whichchildren with Down syndrome were taughtrelations between written vowels and thespoken label ‘‘vowel’’ (parallel instruction alsowas used to teach relations involving conso-nants). For example, the children were explic-itly taught to match ‘‘vowel’’ to the letter A andA to the letter O. Without further training,they could also match O and ‘‘vowel’’ (transi-tivity). In the same way the children mastered aclass consisting of ‘‘vowel’’ and the letters E andU. Because two vowel classes shared a commonmember (A), they merged to form one largerclass (A-O-E-U-‘‘vowel’’), thereby allowing thechildren to match additional vowels that hadnever been paired directly during training (e.g.,E and A).

The present study used EBI to establishrelations among brain regions, their anatomicallocations, and psychological functions andpsychological problems associated with them.For efficiency, a few carefully selected relationswere taught with the goal of promoting theemergence of several untaught relations thatwould increase the number of relations learnedabove the number of relations explicitly taught(e.g., Fienup & Dixon, 2006; Sidman et al.,1985). Four classes of five learning stimuli each(defined in Figure 1 and denoted here as A, B,C, D, and E) were employed to which theparticipants were not exposed. Each representeda lobe of the brain, and two small classes wereestablished for each (A-B-C and A-D-E), bothof which incorporated emergent potential. Itwas expected that students would spontaneouslytreat the B and C stimuli as ‘‘belonging with’’the D and E stimuli (i.e., new relations wouldemerge) because the two classes shared amember (A).

METHOD

Participants

Eight college undergraduates volunteeredafter reading a flier posted on a recruitmentbulletin board and participated after providing

20 DANIEL M. FIENUP et al.

informed consent. In exchange for participat-ing, they received vouchers that could beexchanged for bonus credit in psychologycourses. Volunteers were retained in the studyif they scored below 70% on all of the pretests.This criterion was used to avoid ceiling effectsthat could preclude evidence that the experi-mental procedures promoted learning. No dataare reported for 4 individuals whose pretestscores indicated existing mastery of the materialto be taught. The 4 remaining students rangedin age from 18 to 22 years (M 5 20.3, SD 5

1.7). Participants appeared to be roughlytypical of undergraduates at the university atwhich the research was conducted based on self-reported college grade point averages (range,2.4 to 3.7) and ACT college-entrance exami-nation scores (range, 21 to 27). Althoughcollege students often serve as participants ofconvenience in behavioral research (e.g., Ecott& Critchfield, 2004), in the present studycollege students were the population of practi-cal interest.

Setting and Materials

Equipment. The study took place in aclassroom equipped with 30 computer work-stations, with multiple students working simul-taneously. Instructional testing and trainingprocedures were automated using a custom-written computer program created with VisualBasic 2005 (Dixon & MacLin, 2003). Eachstudent worked on an IBM-compatible desktopcomputer (with a 15-in. flat panel monitor,keyboard, and mouse) that ran on the MicrosoftWindows XP operating system.

Learning and feedback stimuli. Figure 2reproduces key features of the computer displaythat students viewed during the lessons. Learn-ing stimuli were presented in black Arial font(24 to 28 point) within white boxes (approx-imately 7.6 cm by 7.6 cm). For all training andtesting, one box was presented at the top of thescreen as a sample stimulus and four boxesbelow as comparison stimuli. In the top rightcorner of the participant’s screen was a visualfeedback box. During training the box dis-

Figure 1. Stimuli used in the study. See text for details of how stimuli were displayed.

TEACHING ABOUT THE BRAIN 21

played the mastery criterion and success towardsmastery. During testing the box displayed thenumber of trials on the test and the trialnumber the participant was currently complet-ing.

During training phases, auditory accuracyfeedback was provided through stereo head-phones. Correct responses were followed by anascending sound, and incorrect responses werefollowed by a descending sound (called a chimeand chord, respectively, in the Windows XPoperating system). No accuracy feedback wasprovided during testing.

General Procedure

General instructions, provided before thestudy began, described the computerized lessonsas in development for eventual classroom use.The students were told that while working onthe lessons they would complete pretests,training sessions, and posttests; that a score ofat least 90% was required on each posttest tocontinue to the next part of the experiment; andthat they would be excused from the study after2 hr or completion of all of the lessons,whichever came first. Instructions did not,however, describe the stimuli used in the lessons

or the relations among them that would betaught.

Overview of lessons. The students completedtwo lessons, each focusing on a unique aspect ofthe subject matter to be taught and eachconsisting of a pretest, training, and a posttest.The pretest and posttest of each lesson wereidentical. The computer program recorded theamount of time that students spent engagedwith the training phase of each lesson (omittingnonlesson activities such as informed consent,instructions provided by the researcher, andtransitions between tasks).

The lessons consisted of a series of trials in amatch-to-sample format (Green & Saunders,1998; Stromer et al., 1992). Each trialpresented a sample stimulus (the question),which appeared near the top of the student’sscreen, and up to four comparison stimuli(possible answers), which appeared in thebottom row of boxes (see Figure 2). Onecomparison stimulus was the correct response,and the remaining stimuli were incorrect. Thesample and comparison stimuli were presentedsimultaneously, and both stimuli remained onthe screen until the student made a response toa comparison stimulus. During training por-

Figure 2. Participant’s display, with example stimuli, as it appeared during training phases.


tions of the study, clicking on any comparisonbox immediately produced auditory and visualaccuracy feedback (described above) followedby the next trial (no intertrial interval). Duringtesting portions of the study, clicking on anycomparison stimulus immediately producedvisual progress feedback.

To complete a lesson, a student had todemonstrate competence both during trainingand on the posttest. During training, masterywas defined as making 12 consecutive correctresponses during a given learning unit (e.g.,ARB). The cumulative probability of selectingthe correct one on 12 consecutive trials was .512

(.0002) or .2512 (.00000006) given two or fourcomparison stimuli, respectively, on each trial.On this basis, the mastery criterion was deemedadequate for distinguishing between genuinemastery and spurious runs of correct responses.Once a student achieved mastery of the trainingportion of a lesson, an on-screen messagedeclared, ‘‘You have passed! Click this buttonto continue.’’ Clicking on this button began thenext scheduled part of the procedure.

For posttests, mastery was defined as scoringat least 90% correct. A lower score initiatedremediation in which the training portion ofthe lesson was repeated, after completion ofwhich the posttest was readministered. After theposttest mastery criterion had been met, thestudent proceeded to the next scheduled portionof the study.

Randomization of trials. During both trainingand testing, the positions of the comparisonstimuli were randomized such that each possiblecomparison stimulus was equally likely to beassigned to each possible screen location. Thetrials that comprised the testing phases of eachlesson (pretest and posttest) occurred in aunique, randomized order for each student;however, each student experienced the samenumber of trials and exposure to differentrelations. During training involving learningunits with two trial types (e.g., A1RB1,A2RB2), the order was randomized every two

trials (e.g., either A1RB1 followed by A2RB2or vice versa). This resulted in no more thantwo consecutive trials involving the same samplestimulus and ensured that the students gainedapproximately the same amount of experiencewith each of the stimulus relations being taught.

Overview of research design. The threestimulus sets were A-B-C (Lesson 1), A-D-E(Lesson 2), and B-C-D-E (relations betweenLessons 1 and 2). Figure 3 displays the order inwhich testing and training were staggered. Thisdesign is similar to that employed by Fienupand Dixon (2006) and was implemented on anindividual basis. The experimental designfollowed the general logic of multiple baselineand multiple probe experiments, in whichabilities are measured at several times todetermine whether changes correspond to theintroduction of an intervention (Johnston &Pennypacker, 1980). The study began bypretesting the Lesson 1 and 2 relations followedby training on Lesson 1 relations. Following themastery of Lesson 1, Lesson 2 and the B-C-D-Erelations were tested. This served as a control tohelp attribute the change in Lesson 1 scores tothe instruction provided. Then, Lesson 2instruction was implemented to replicate theeffects of EBI on generative responding.

Note on symmetrical relations. The trainingand testing phases of the study omittedsymmetrical variants of explicitly taught rela-tions (e.g., ARB was taught and tested, but notBRA). We assumed that, for the skilledlearners on whom this study focused, compe-tence on the trained relations implied compe-tence on symmetrical variants (e.g., Fields &Reeve, 1997). This approach also allowed us tolimit the number of trials in the training andtesting phases. When examining potentialtransitive associations among stimuli that hadnot previously been paired, however, we testedthe two symmetrical forms of relevant relations(e.g., B as sample with C as comparison, and Cas sample with B as comparison) and treatedeach form as a separate relation. This approach


was based on the common assumption that forboth of these to emerge, the learner must havemastered the symmetrical version of eachtrained relation (e.g., Sidman, 1994).

Lesson 1 (Lobes and Functions): A-B-C Relations

In this lesson students learned how thefollowing stimuli (textual descriptions) relate:names of brain lobes (A stimuli), a psycholog-ical function associated with the respective brainlobes (B stimuli), and a second functionassociated with the respective brain lobes (Cstimuli). Figure 1 displays the stimuli, Table 1shows the specific trials presented in each phaseof training, and Figure 4 (top left) shows thebasic structure of training and testing, withtrained relations depicted via black arrows andexpected emergent transitive associations de-picted via gray arrows.

ARB training. The students learned fourARB relations. The sample stimuli were brainlobe names (e.g., frontal lobe) and comparisonstimuli were brain functions (e.g., Function 1:Involved in movement). Training occurred inthree blocks of trials, each of which had to bemastered separately. The first training blockinvolved A1RB1 and A2RB2 trials, with B1and B2 serving as comparisons along with twoblank boxes. The second block involvedA3RB3 and A4RB4 relations, with B3 andB4 serving as comparisons along with twoblank boxes. In the third block all four ARBrelations were intermingled in a block of

trials, with all B stimuli presented as compar-isons.

ARC training. The students learned fourARC relations. For this training the samplestimuli were brain lobe names (e.g., frontal lobe)and comparison stimuli were additional brainfunctions (e.g., Function 2: Involved in highercognitive functions). ARC training was similarto ARB training. Training occurred in threeblocks of trials that had to be masteredseparately. The first involved A1RC1 andA2RC2 relations, the second involvedA3RC3 and A4RC4 relations, and the thirdinvolved all four ARC relations.

A-B-C pretest and posttest. The followingtransitive relations were tested: four BRCrelations and four CRB relations. The testincluded four trials of each relation type, for atotal of 32 trials. All four possible comparisonstimuli appeared on each trial (e.g., for BRCrelations the comparison stimuli always wereC1, C2, C3, and C4).

Lesson 2 (Lobes, Locations, and Disorders):A-D-E Relations

In this lesson the students learned how thefollowing stimuli (pictures and textual descrip-tions) relate: brain lobe name (A stimuli), ananatomical location of the respective brain loberepresented by a colored drawing (D stimuli),and an effect (disorder) that can arise due todamage to the respective brain lobe (E stimuli).Figure 1 shows the stimuli that were involved,

Figure 3. Schematic showing the sequence of training and testing phases of the study.


Figure 4. Top: structure of training and testing in the two lessons. Relations that were directly taught are shown asblack arrows; transitive associations that were expected to emerge without direct training are shown as gray arrows.Bottom: structure of the test for class merger. Transitive associations that were expected to emerge without direct trainingare shown as gray arrows. Note that in each phase of the study, the relevant relations were included for four stimulus sets,each representing a different lobe of the brain.

Table 1

Training Sequence

Condition Phase Sample/correct comparison All comparisons

ARB training 1 A1RB1 and A2RB2 B1 and B22 A3RB3 and A4RB4 B3 and B43 A1RB1 and A2RB2 B1, B2, B3, B4

A3RB3 and A4RB4

ARC training 1 A1RC1 and A2RC2 C1 and C22 A3RC3 and A4RC4 C3 and C43 A1RC1 and A2RC2 C1, C2, C3, C4

A3RC3 and A4RC4

ARD training 1 A1RD1 and A2RD2 D1 and D22 A3RD3 and A4RD4 D3 and D43 A1RD1 and A2RD2 D1, D2, D3, D4

A3RD3 and A4RD4

ARE training 1 A1RE1 and A2RE2 E1 and E22 A3RE3 and A4RE4 E3 and E43 A1RE1 and A2RE2 E1, E2, E3, E4

A3RE3 and A4RE4

Note. This table displays the trials that were presented in each phase of the study. For each type of relation (e.g., ARB,ARC) participants began MTS training with stimuli from Sets 1 and 2. Following mastery, participants completedtraining with Sets 3 and 4 followed by a phase with all four sets of stimuli presented (see Figure 1 for description of thestimuli).


and Figure 4 (top right) shows the basicstructure of training and testing, which paral-leled that of Lesson 1.

ARD training. The students learned fourARD relations. The sample stimuli were brainlobe names (e.g., frontal lobe), and comparisonstimuli were pictures of the brain with therespective area highlighted. ARD training wassimilar to ARB training. Training occurred inthree blocks of trials that had to be masteredseparately. The first involved A1RD1 andA2RD2 relations, the second involvedA3RD3 and A4RD4 relations, and the thirdblock involved all four ARD relations.

ARE training. The students learned fourARE relations. For this training the samplestimuli were brain lobe names (e.g., frontal lobe)and comparison stimuli were statements aboutwhat could occur given damage to the respectivebrain region (e.g., Damage causes impulsiveness).ARE training was similar to ARB training.Training occurred in three blocks of trials thathad to be mastered separately. The first involvedA1RE1 and A2RE2 relations, the secondinvolved A3RE3 and A4RE4 relations, andthe third block involved all four ARE relations.

A-D-E pretest and posttest. The followingtransitive relations were tested: four DRE relationsand four ERD relations. The test included fourtrials of each relation type, for a total of 32 trials. Allfour comparison stimuli appeared on each test trial(e.g., for DRE relations the comparison stimulialways were E1, E2, E3, and E4).

Class Merger Test: B-C-D-E

Lesson 1 established A-B-C relations, andLesson 2 established A-D-E relations. If thesetwo stimulus classes merged because of a sharedmember (A), then without explicit training thestudents would also be competent with novel B-C-D-E relations. Figure 4 (bottom) shows thetransitive associations that were expected toemerge without direct training. Note thatprevious tests evaluated relations between theB and C stimuli and between the D and Estimuli. Thus, the novel relations on the class

merger test were BRD (and DRB), BRE (andERB), CRD (and DRC), and CRE (andERC). All four possible comparison stimuliappeared on each trial (e.g., for BRD relationsthe comparison stimuli always were D1, D2,D3, and D4). Each relation was presented fourtimes, resulting in 128 total trials (8 relations 3

4 lobe classes 3 4 trials each).Students completed the class merger test on

two occasions: prior to A-D-E training, before thelessons provided any basis for relating the A-B-Cand A-D-E stimuli, and following A-D-E trainingand the posttests for A-B-C and A-D-E relations.

RESULTS

Results of pretests and posttests are summa-rized in Figure 5. Test outcomes are shown interms of percent correct. Results of the trainingsare summarized in Table 2 in terms of thenumber of trials and amount of time requiredin a given lesson to meet the mastery criteria.Because mastery was required prior to anyposttest, the reader may assume, withoutinspecting the details of Table 2, that eachstudent demonstrated mastery on each learningunit of each training phase.

Prior to any training, all of the students scoredwell below mastery for what would be the focusof Lesson 1 (A-B-C) or Lesson 2 (A-D-E). Dataon the left side of the phase line of Figure 5summarizes pretest results. Mean correct studentresponding on the A-D-E pretest was 50% andslightly higher on the A-B-C pretest. Subse-quently, as Table 2 shows, all students complet-ed Lesson 1 A-B-C training in 121 to 198 trials,including any remediation (see below); thisrequired 10 to 13.5 min of engagement. Onthe ensuing test of emergent relations (data onthe right side of the phase line of Figure 5)involving the B and C stimuli, Students 1 and 3demonstrated mastery. Students 2 and 4 met themastery criterion after failing a first attempt atthe A-B-C posttest and repeating A-B-C train-ing. At this time, no improvements were evidentin A-D-E relations (Figure 5, middle), and no


Figure 5. Performance on tests for taught (top and middle) and emergent relations (bottom).


student showed substantial competence with B-C-D-E relations (Figure 5, bottom).

Next, all of the students completed Lesson 2training (Table 2) in 72 to 93 trials (about 2 to3.5 min of engagement). On the ensuing test ofemergent relations involving the A-D-E stimuli,all students demonstrated mastery; thus, unlikein Lesson 1, no remedial training was needed.At this time all students also demonstrated thatthey had retained the benefits of Lesson 1(Figure 5, rightmost columns, top), and thatthe stimulus classes of Lessons 1 and 2 hadmerged to create additional B-C-D-E emergentrelations (Figure 5, rightmost columns, bot-tom). Accuracy was near 100% in all cases.

DISCUSSION

Results in Practical Context

To summarize the training, each of thecomputerized lessons taught two relations for

each of four stimulus sets (each related to abrain lobe). The study’s critical contributionregards the number of relations that thatemerged without explicit training. Trainingpromoted the emergence of four symmetricalrelations (BRA, CRA, DRA, and ERA) thatwere not explicitly tested but theoretically mustbe in place for transitive relations to emerge (seeSidman, 1994) plus six transitive relations(BRC, BRD, BRE, CRD, CRE, andDRE) and their symmetrical variants (CRB,DRB, ERB, DRC, ERC, and ERD). Ifthese symmetrical variants of transitive relationsare treated as independent relations, as is thenorm in basic research and in Sidman’s (1994)stimulus equivalence theory, then the teachingof 16 relations (four for each of four brain-lobeclasses) supported the emergence of 64 addi-tional untaught relations (those just listed foreach of four brain-lobe classes) or 80 totalrelations. Thus, students learned about five

Table 2

Requirements to Meet Mastery Criteria

StudentA1RB1,A2RB2 A3RB3, A4RB4 All ARB

A1RC1,A2RC2

A3RC3,A4RC4 All ARC Total

Lesson 1 (A-B-C): number of trials

1 12 22 91 12 26 35 1982 13 (12) 21 (22) 12 (12) 16 (12) 12 (12) 24 (12) 1803 12 12 60 12 13 12 1214 19 (26) 27 (12) 13 (12) 13 (12) 12 (17) 12 (12) 187

Lesson 1 (A-B-C): time of engagement (s)

1 34 50 431 37 55 196 8032 50 (38) 69 (88) 43 (47) 48 (34) 31 (38) 95 (39) 6203 92 39 318 60 55 44 6084 53 (64) 66 (37) 64 (73) 65 (48) 39 (51) 60 (80) 700

StudentA1RD1,A2RD2

A3RD3,A4RD4 All ARD

A1RE1,A2RE2

A3RE3,A4RE4 All ARE Total

Lesson 2 (A-D-E): number of trials

1 21 15 14 17 14 12 932 12 12 12 12 12 12 723 13 13 12 13 12 12 754 17 13 12 12 12 21 87

Lesson 2 (A-D-E): time of engagement (s)

1 32 25 31 43 34 33 1982 31 34 22 26 36 30 1793 28 37 21 43 27 34 1904 21 26 27 31 42 66 213

Note. Numbers in parentheses represent remedial training that was required after a student failed a posttest. In suchcases, the Total column includes both iterations of the training phase.


times as many relations as were expressly taught.In a more conservative accounting, in whicheach symmetrical pair of relations is consideredas one relation, the teaching of 16 relationsyielded 24 emergent relations (40 total rela-tions), in which case students learned about twoand a half times as many relations as wereexpressly taught. By either perspective, studentswere able to ‘‘go beyond the information given’’(Bruner, 1957, p. 41) in precisely the ways thatstimulus equivalence theory predicts. EBI thusdelivered the generative responding that consti-tutes its major promise to education (Stromer etal., 1992). Given the technical nature of brainfunction and anatomy as an academic subject(Wilson et al., 2000), this was accomplishedwith surprisingly little student investment (e.g.,about 13 to 17 min of engagement with the twolessons, excluding instructions, tests, and timein transition between activities).

To place the effectiveness of the lessons into apractical context, consider that the masterycriterion defined student success during trainingphases as 100% correct, which would count as aletter grade of A on any academic grading scale.Most likely this success was facilitated by genericfeatures of good behavioral instruction, such asfrequent student responding, frequent feedback,and individualized progress through the lessons(e.g., Keller, 1968; Skinner, 1968). On tests,which included only relations that had not beendirectly taught in the lessons, students had toscore at least 90% correct (which would earn anA on most college grading scales) to move on tothe next task. That they did so reliablyunderscores the novel (generative responding)contribution of EBI to behavioral instruction.

The multiple probes of the present experi-mental design were helpful in highlighting twooutcomes of practical interest to the instruc-tional designer. First, the relations that emergedamong the stimuli of a given lesson weredependent specifically on the training of thatlesson (i.e., Lesson 2 abilities did not improveuntil after Lesson 2 training). Second, the

relations that emerged among the stimuli ofthe two separate lessons depended on thetraining of both lessons. Together, thesefindings support a maxim that Skinner (1968)advanced long ago but bears repeating: Inbuilding complex repertoires, it is importantnot to skip steps.

Although the students showed clear academicgains, including emergent ones, it is importantto note that that this occurred in match-to-sample trials that emphasized selection-basedresponding. By contrast, many academic assign-ments in higher education require topography-based responding (e.g., this is a criticaldifference between multiple-choice and essayassignments), as do many professional tasksbeyond higher education (e.g., writing aresearch report to submit for publication).Because topography-based responding was notassessed in the present study (or in thepreviously mentioned studies by Ninness etal., 2005, 2006), it is not known whether therepertoires established in selection-based proce-dures would contribute to student success ontopography-based tasks. This defines an impor-tant direction for future EBI research.

Conceptual Issues

Class merger. The present study joins only afew others (e.g., Lane & Critchfield, 1998a) insuggesting that spontaneous class merger,promoted by classes that share a commonmember, may be academically beneficial. Whentwo classes unite, emergent relations amongtheir respective members become possible. Ourstudy does not provide unequivocal evidence ofclass merger, however, because strictly speakingthe term merger implies that two classes haveexisted independently prior to their union(Sidman, 1994). In the present study, thestimuli of Lessons 1 and 2 included a commonmember from the outset, so Lesson 2 might bedescribed more conservatively as promoting theexpansion of the classes that were created duringLesson 1. To demonstrate class merger unam-biguously would require the creation of unre-


lated classes during initial lessons, followed byan additional lesson during which the sharedassociate was taught. The underlying distinctionis important conceptually but possibly irrelevantto the instructional designer whose primary goalis to engineer new repertoires as efficiently aspossible.

The role of verbal rules. Although EBI hasbeen used to build new skills economically inpeople with learning difficulties and disorders,few studies have explored the utility of this kindof instruction for building high-level academicskills in typically developing individuals. Previ-ous studies (Ninness et al., 2005, 2006) focusedon mathematics skills; the present study extendsthe generality of EBI to brain–behavior rela-tions. Unlike the studies by Ninness et al.,however, this one was designed to evaluate EBIindependently of instructor-generated verbalrules governing stimulus relations that aretypical employed in a classroom environment.Specifically, Ninness et al. taught algebra skillsvia a treatment package that included explicitinstructor descriptions of how various stimuliwere related as well as relevant match-to-sampletraining (involving overlapping conditionaldiscriminations, performance feedback, andmastery-level training). The lessons were effec-tive, but the studies that evaluated them leftunclear the relative contribution to studentmastery of instructor-generated explanationsand student practice with the componentrelations of stimulus classes. The current studyis valuable in demonstrating that it is not alwaysnecessary to provide college students with rulesabout stimulus relations in order to use EBIsuccessfully in teaching advanced material. Ofcourse, given that the students were verballycapable, they could have generated their ownrules. If so (our experiment was not designed toevaluate this possibility), then this may beviewed as another way in which EBI promotes‘‘going beyond the information given.’’

Is this really stimulus equivalence? We havedescribed the present lessons as exemplifying

instruction based on equivalence relations, andit is worth clarifying what this assertion doesand does not imply. Methodologically speaking,students responded to the academic stimuli in afashion that was consistent with Sidman’s(1994) theoretical account of equivalence. Mostnotably, the students transitively matcheddissimilar stimuli, that is, they treated thestimuli as interchangeable to the extent thatthe instructional procedures allowed. This is notto say, however, that they would treat the samestimuli as interchangeable under all circum-stances. For example, few reading-capableindividuals would, in the abstract, judge thatfrontal lobe and damage causes impulsiveness‘‘mean the same thing,’’ and many situationsmay be imagined in which these phraseswould be called ‘‘different.’’ It is important tonote that stimulus equivalence theory recogniz-es the potential for contextual control in whichstimuli are equivalent in some circumstancesbut not others (Sidman). For example, dober-man may be said to ‘‘go with’’ poodle andbichon in a discussion about the species canusbut not in a discussion about specific dogbreeds. Similarly, no theoretical contradictionexists in asserting that stimuli like frontal lobeand damage causes impulsiveness functioned asequivalent within the confines of the presentlessons but are not unconditionally inter-changeable.

Communicating about academic stimulus rela-tions. The preceding discussion highlights twoimportant points. The first point is that it isdifficult to communicate about stimulus equiv-alence to a nonspecialist audience, whichincludes many readers of this journal. Layeuphemisms (e.g., ‘‘means the same thing’’)often are invoked in an attempt to ease theexposition because, on first blush, these seem tocapture the general idea of stimulus equivalence.Yet such expressions may obscure importantnuances of stimulus relations. Nothing in thepresent lessons indicated to students that frontallobe ‘‘means the same thing’’ as damage causes


impulsiveness; and, as noted above, stimulusequivalence theory does not make exactly thisclaim. Thus, lay vocabulary may carry unwant-ed conceptual baggage. As EBI interventions aredeveloped for use outside of research settings,the need to communicate about them tononspecialists will increase, and it is an openquestion as to whether the expositional benefitsof lay expressions outweigh the potential forconceptual confusion that they introduce.

The second point worth stressing emphasizesa different way in which the learning stimulimay not ‘‘mean the same thing.’’ To illustratefrom the present study, note that damage causesimpulsiveness is not a synonym of frontal lobebut rather a property of it. As relational frametheory (Hayes, Barnes-Holmes, & Roche,2001) teaches, many types of relations (e.g.,opposites, superordinate-subordinate, etc.) canspawn emergent abilities just as equivalencerelations do. Thus, many types of stimulusrelations could serve as the basis for instruc-tional programming (e.g., Ninness et al., 2005,2006). In the present article, our reliance on thelanguage of stimulus equivalence was drivenmainly by practical rather than theoreticalconcerns: This language mapped convenientlyonto the instructional material, and it issomewhat familiar to the journal’s audience.There is no question, however, that the presentstudy could be interpreted within the frame-work of relational frame theory, and giventhe diversity of stimulus relations that aca-demic curricula probably incorporate, a well-elaborated program of instruction could profitfrom drawing from the resources of bothrelational frame theory and stimulus equiva-lence theory.

Limitations and Future Directions

The present lessons were neither a completeprogram of instruction nor likely to promotesophisticated understanding of the targetedconcepts. In the former case, the lessons taughtonly a few facts about brain anatomy andfunction from among the multitude that must

be mastered in even an introductory course thistopic (e.g., see Carlson, 2005), and it could beargued that resulting emergent relations did notreally take students very far ‘‘beyond theinformation given’’ (Bruner, 1957, p. 41).Moreover, the ‘‘information given’’ was, as isoften the case in introductory lessons, not veryprecise. Brain regions are interconnected andmost psychological functions in which theyparticipate are distributed across several regions(Carlson, 2005). Thus, the statements thatserved as this study’s B, C, and E stimuli(Figure 1) are oversimplified. The presentlessons are best appreciated, therefore, as anexample of how to establish selected aspects ofan entry-level higher education repertoireregarding brain structure and function. Sub-ject-matter expertise would require considerableadditional instruction. To concede this pointdoes not contradict our assertion that thesubject matter was more advanced than isnormally seen in EBI investigations (consider,e.g., the challenges that might be encounteredin teaching the same material to very youngchildren or persons with developmental disabil-ities).

It should be noted as well that the learners inthe present investigation were research volun-teers whose learning was not linked to anacademically sanctioned course of instruction.The study was intended to mimic collegeinstruction in important ways (the learners weresimilar to students who typically would en-counter the topic of instruction, and the lessonswere administered to several students simulta-neously in a computer-equipped classroom).Nevertheless, like all other published studies ofEBI to date, the present one qualifies as afeasibility evaluation; that is, it demonstratedlearning-economy benefits under well-con-trolled conditions. Whether similar lessons canhave a significant impact on student progressthrough a course of instruction in a naturalsetting remains to be determined. From anevidence-based practice perspective (Chorpita,


2003), the empirical evaluation of an interven-tion considers two broad features: its efficacy(beneficial effects under controlled conditions)and its transportability (beneficial effects whenextended to specific practice settings). Thepresent study addresses efficacy. With respectto transportability, field studies, in which EBI isevaluated as a part of an ongoing instructionalsystem, are needed to determine whetheracademic benefits that accrue in laboratory-likeenvironments also can be engineered reliablyunder less ideal everyday circumstances.

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Received March 19, 2008Final acceptance September 18, 2008Action Editor, Chris Ninness


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