Validating The Multiple Intelligences Inventory for Teachers

33

Pursuing the Parameters:Validating The Multiple Intelligences Inventory for Teachers

Deborah E. BordelonXavier University of Louisiana

Mary M. BanburyUniversity of New Orleans

Assessing intelligence can be a perplexing endeavor. How intelligence is defined directly influences theassessment procedures used. Traditionally, intelligence was viewed as a single, static entity. However,reconceptualizations of the nature of intelligence are changing this view. The present study attempted tovalidate an instrument that teachers may use to assess student abilities in the seven intelligence areas pro-posed by Howard Gardner (1983).

A critical role of teachers involves assess-

ing students’ abilities and planning instruc-tion accordingly. However, the focus of suchassessments is often limited to verbal andmath skills, thereby often overlooking andunderutilizing the other abilities and

strengths a student brings to the classroom. Torectify this situation, the researchers of thepresent study developed and attempted to val-idate an instrument designed to enable teach-ers to assess student abilities in the seven

intelligence areas proposed by HowardGardner (1983) in his theory of multipleintelligences. This study is not meant to bethe final validation of the proposed instru-ment, but an initial investigation into the val-idation of an instrument to assess multipleintelligences in children.The theory of multiple intelligences (MI

theory), a relatively recent reconceptualiza-tion of intelligence, broadens the perspectiveof human intelligence from a single entity toa multifaceted one. In MI theory, Gardnerproposes that people can be intelligent in different areas: linguistic, logical-mathematical,visual/spatial, musical, bodily-kinesthetic,interpersonal and intrapersonal.To be considered an intelligence, each of

the seven areas had to meet certain criteria.

Gardner used the following eight factors todetermine whether or not an area could beviewed as an intelligence: (a) potential isola-tion by brain damage; (b) the existence ofexceptional individuals; (c) a distinctive

developmental history and definable set of

expert &dquo;end-state&dquo; performances or vocationsand avocations; (d) an evolutionary history;(e) support from psychometric findings; (f)support from experimental psychologicaltasks; (g) an identifiable core operation or setof operations; and (h) susceptibility to encod-ing in a symbol system (Armstrong, 1994;Gardner, 1983). Gardner has since added aneighth intelligence, naturalist, and is explor-ing the possibility that additional intelli-

gences exist and meet the criteria presentedin his original work (Checkley, 1997;Gardner, 1999).

Controversy surrounds Gardner’s identifi-cation of these areas as intelligences ratherthan talents or aptitudes. In his analysis of MItheory, for example, Morgan (1992) purport-ed that Gardner was not proposing anythingnew, but was distinguishing what is now

viewed as general intelligence or cognitivestyles as intelligences. Gardner (1995)addressed this issue by maintaining that alearning style pervades all intelligence areas.

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For example, an auditory learner would leambest through auditory means in all of theintelligence areas.

Another criticism of MI theory is thatGardner labeled what are commonly knownas talents such as musical and bodily-kines-thetic abilities as intelligences. Gardner andWalters (1993) countered this criticism withthe following argument:

Placing logic and language on a pedestal reflectsthe values of our Western culture and the greatpremium placed on familiar tests of intelligence.A more Olympian view sees all seven intelli~

gences as equally valid. To call some &dquo;talent&dquo; andsome &dquo;intelligence&dquo; displays this bias. Call themall &dquo;talents&dquo; if you wish; or call them all &dquo;intelli-gences.&dquo; (pp. 35-36)

Although Gardner proposed that the intel-ligences are independent of one another, it isthe interaction of the different intelligencesthat produces a unique arrangement of abili-ties that results in a multiple intelligences(MI) profile for an individual. This profilemay be useful as a guide for teachers, parents,and students in choosing activities that nur-ture and support the variety of abilities shownby the student (Ramos-Ford & Gardner,1991 ).

This change in intelligence theory necessi-tates a change in the way schools assess andteach students. The implications of MI theo-ry for education are firmly grounded in assess-ment. That is, it is difficult, if not impossible,for teachers to develop and implement indi-vidualized and/or differentiated activities thatincorporate multiple intelligences unless theycan identify, assess, and target the aptitudes oftheir students. The goal of assessment in MItheory, therefore, is to obtain a MI profile ofstudents’ varying degrees of ability withineach of the intelligence areas (Armstrong,1994, 2000; Gardner, 1983, 1993; Lazear,1991). Several studies have examined instru-ments using behavioral descriptors or perfor-mance assessments to effectively assess multi-ple intelligences. These studies investigated

the use of these assessments in the develop-ment of a MI profile to facilitate appropriateinstruction (Gardner & Hatch, 1990;Krechevsky, 1991; Plucker, Callahan, &

Tomchin, 1996; Shearer, 1991).Gardner (1995) contended that the assess-

ment of student abilities within the multiple-intelligences framework must be &dquo;intelligent-fair.&dquo; That is, the focus should be on directlyobserving the individual’s performance withina given intelligence area instead of throughpaper-and-pencil tests, as used on traditionalstandardized measures. Making this job easier,multiple intelligences checklists or invento-ries allow teachers to consider a child’s perfor-mance in an intelligence area without havingthe child perform the task at the time of theassessment.

Concurring with Gardner, Eisner (1994)emphasized the need to move away from aview of intelligence as a fixed entity towardan understanding of intelligence &dquo;involvingcapitalization on strengths and compensationfor and remediation of weaknesses&dquo; (p. 563).Gray and Viens (1994) underscored the

importance of this shift in thinking as follows:

As educators, parents, and other adults recognizethat all children are bom with a multitude of

intelligences, they can better nurture the full

range of each child’s abilities. When students

experience environments that acknowledge andnurture their particular strengths, they are morelikely to feel engaged and satisfied. Ultimately, apluralistic view of intelligence is a tool well suit-ed to helping individuals understand and live inour increasingly diverse society. (p. 25)

In the school setting, the teacher’s role is toascertain students’ abilities, pinpoint areas

that need further enhancement, and targetareas that need improvement.Acknowledging that a student may be intelli-gent in ways other than the traditional con-

ception of intelligence (linguistic and logi-cal-mathematical) is the first step in enablingstudents to reach their full potential. Whenthe school’s focus is on structured linguistic



35

solutions, students do not develop flexibilityin their thinking (Walters, 1992). As a result,problem solving, for example, is isolated tothe school setting and does not reflect prob-lem solving in the world outside of school.The powerful role intelligence plays in the

educational system is undeniable, but as

Hilliard (1994) contended, the measurementof intelligence is only useful if it helpsimprove instruction. Gardner’s theory of mul-tiple intelligences offers an assessment frame-work that links the identification of students’abilities with instruction. In order for signifi-cant changes to occur in the classroom, teach-ers must broaden their perceptions of theirstudents’ abilities and recognize the spectrumof all intelligence areas in order to providemeaningful and beneficial experiences for stu-dents. Gardner (1983) attested: &dquo;Only if we

expand and formulate our view of whatcounts as human intellect will we be able todevise more appropriate ways of assessing it

and more effective ways of educating it&dquo;

(p. 4).

Instrumentation

In response to Gardner’s challenge, theauthors developed an instrument entitled TheMultiple Intelligences Inventory for Teachers.The instrumentation process consisted of five

phases.

Phase I

Phase I consisted of reviewing the literatureon multiple intelligences and analyzing multi-ple-intelligences checklists and other multiple-intelligences instruments (Armstrong 1994,2000; Gardner, 1983, 1993; Lazear 1991;Leibowitz & Stames 1993; Plucker et al., 1996;Shearer, 1991). In the process, major domainsand specific behaviors for each intelligence areawere identified. For the purposes of this article,the term &dquo;domain&dquo; refers to the major compo-nents that constitute each intelligence. Forexample, speaking, listening, reading, and writ-ing abilities are four domains of verbal/linguis-

tic intelligence. Items describing the specificbehaviors associated with each of the domainswere also identified during Phase I.

Phase 11

For Phase II of the instrumentation

process, the authors assembled a panel of&dquo;experts&dquo; for each of the seven intelligencesto help examine the major domains of theirrespective intelligence area and critique,delete, or add behaviors indicative of each ofthe domain areas. Each intelligence area wasrepresented by two panel members, resultingin a total of 14 &dquo;expert&dquo; panel members. Twocriteria were used to establish the panel mem-bers’ expertise in an intelligence area: (a)expertise in the respective intelligence area asdemonstrated by participation in a relevant&dquo;end-state&dquo; for that intelligence area, such asa musician for musical intelligence or a writerfor linguistic intelligence; and (b) interactionwith children through teaching, tutoring,coaching, and so on. Table 1 lists the domainsand items.

Phase ///

In Phase III, The Multiple IntelligencesInventory for Teachers, a pilot inventory con-sisting of 92 behavior statements and a

Likert-type rating scale, was developed basedon guidelines established by Anderson

(1982). This involved writing items represen-tative of positive or negative attributes in

relation to the intelligence; providing therespondents with four choices to rate the stu-dents ranging from ( 1 ) Not at all like the stu-dent to (4) Very much like the student, aswell as providing the respondents with clearlywritten directions for completing the inven-tory.The domain headings were removed to

prevent participants from being influenced bythe labels of the intelligence area, and thebehavior statements were randomly arranged.Some items were also reworded as negativebehaviors to prevent the possibility of a



36

Table 1 Multiple Intelligences Domains and Items



37

Table 1 Continued



38

Table 1 Continued



39

response pattern. For example, an item repre-senting the interpersonal intelligence area

read &dquo;Seldom volunteers to direct a project&dquo;instead of &dquo;Often volunteers to direct a pro-ject.&dquo;

Phase I V

During Phase IV, a pilot study was con-ducted in order to obtain feedback from teach-ers on the clarity of directions, wording ofitems, ease of completion, as well as any otherconcerns the teachers had while completingthe pilot inventory. The participants of thepilot study were three groups of 3 teachers. Twoof the groups consisted of fourth-grade teachersand the third group was comprised of fifth-gradeteachers. Based on the feedback, the researchersclarified items and expanded the rating scale toa 5-point Likert scale.

Phase V

Phase V of the instrumentation processconsisted of assessing the construct validityand reliability of The Multiple IntelligencesInventory for Teachers. The reliability of thefactor scales is essential in determining if theitems associated with the factor are measuringthe same construct. Although there are othertypes of validity such as content and criteri-on-related, construct validity was the focusbecause it is regarded as the most critical

(Kerlinger, 1986).Each teacher participant was asked to com-

plete an inventory on three randomly select-ed students from his or her homeroom class.In order to ensure uniformity in the randomselection process, each teacher participantreceived a direction sheet for randomly select-ing students. The data collected were ana-lyzed using the principal components proce-dure in SPSSx.

Sample

Sample Size Determination

Sample size plays a major role in validatingan instrument. That is, without an adequate

number of subjects, it is difficult to determinewhether or not the results of the factor analy-sis indicate that an instrument is reliable,consistently and validly measuring what it

purports to measure. Guadagnoli and Velicer,as cited in Stevens (1992), stated that com-ponent saturation and absolute sample size arethe most significant elements when determin-ing if the factors are reliable. Consequently,they recommend that components with fouror more loadings above .60 in absolute valueare reliable, regardless of sample size. If the

sample size is greater than about 150, compo-nents with about 10 or more .40 loadings arereliable. When the sample size is 300 or more,interpretation of components with only a fewloadings of .40 can be done. Stevens suggest-ed that any component with at least three

loadings above .80 is reliable.Each of the 112 teachers in the study was

asked to complete three inventories, resultingin 336 inventories. However, not everyteacher met this requirement. As a result, thefinal number of completed inventories was306. The results presented in this articledemonstrate that all three guidelines support-ed by Stevens (1992) to determine the valid-ity of the instrument were met for the sample.

The Raters

One hundred and twelve fourth- and fifth-

grade certified general education teachersfrom three suburban school districts of a largesouthern metropolitan area participated in

the study. The teacher raters completedinventories on 306 target students randomlyselected from their homeroom classes.

Seventy-four percent of the teachers pos-sessed a bachelor’s degree. Sixteen percenthad completed a master’s degree. An addi-tional 8% had a master’s +30 hours and 2%had a specialist degree. The range for teachingexperience was 1 year to 35 years, with amean of 15.86 and a SD of 9.40.

Because the teachers based their responseson The Multiple Intelligences Inventory for



40

Teachers on their perceptions of the targetstudents, it was necessary to obtain informa-tion on the length of time the teachers hadknown the students as well as how often theyinteracted with them during the school day.One hundred and seventy (55.6%) of theteachers reported that they had known thetarget students for less than one school year.One hundred and five (34.3%) of the teach-ers had known the target student for at leastone school year. In addition, one teacher(.3%) indicated knowing the target studentfor one and a half years. Fourteen (4.6%) ofthe teachers had known the target studentsfor almost two years, 3 (1.0%) had known thetarget students for three years, 3 (1.0%) hadknown the target students for four years, 9(2.9%) for five years, and 1 (.3%) for six

years.The teachers were also asked to report how

much class time they spent with the targetstudents. The teachers taught 39 of the stu-dents for one class, 66 for two classes, 88 forthree, 53 for four, 17 for five periods a day, 32for six, and 11 for all seven subjects. Of theseclasses, 137 (44.8%) of the target studentshad reading with the teacher rater, 178(58.2%) had language arts; 154 (50.3%) hadmath; 164 (53.6%) had social studies; 156

(51.0%) had science; 155 (50.7%) had art;and 59 (19.3%) had health and physical edu-cation.

The SampleFor the purposes of this study, the sample

refers to the fourth- and fifth-grade students.The teacher raters provided the requestedinformation on the respective students in

their classes. Inventories were completed on306 students, 175 (57.2%) were in fourth

grade and 131 (42.8%) were in fifth grade.There were 200 Caucasian students, 68African Americans, 10 Hispanics, 15 Asians,and 13 for whom no ethnicity was reported.Because the target students were chosen from

general education classrooms, no exceptional-

ity was listed for 276 (90.2%) of the students.Sixteen (5.2%) were identified as gifted, four(1.3%) students received speech services,three (1.0%) were identified as having a

learning disability, one student (0.3%) wasidentified as talented, and one (0.3%) wasidentified as having a mild mental disability;information on special education services wasunavailable for five ( 1.6%) students.

Data AnalysisThis validation study employed the tradi-

tional R-technique factor analysis using prin-cipal-components analysis. Principal-compo-nents factor analysis allows the researchers toextract factors that are as independent of oneanother as possible. The independence of thefactors was important in order to support theposition that the seven intelligence areas areindependent of one another.

In the principal-components factor analy-sis, a correlation matrix for each analysis is

generated. The matrices represent, throughcoefficients, the relationship between theitems and the underlying factors. In this study,prerotated matrices were generated first. Thematrices were then rotated to the varimax cri-terion, which facilitated an interpretation ofthe factors.The criteria used to determine the number

of factors to be obtained from the data were:(a) factors with eigenvalues greater than 1and (b) a scree plot (Cattell, 1966) represent-ing the eigenvalues. A scree plot is a graphi-cal representation of the eigenvalues. In

interpreting the scree plot, the point at whichthe eigenvalues begin to flatten out is used asthe reference point for extracting the factors.

In R-technique factor analysis, the itemsare factored across the participants. In thisstudy, the items or variables were the 92behavior descriptions on the MultipleIntelligences Inventory for Teachers. Theseitems were factored across the target partici-pants - the 306 fourth- and fifth-grade stu-dents. This analysis determined whether the



41

items on the inventory represented and mea-sured Gardner’s seven intelligence areas: lin-guistic, logical-mathematical, musical, spa-tial, bodily-kinesthetic, interpersonal, and

intrapersonal. An excerpt from the instru-

ment is presented in Table 2.The Multiple Intelligences Inventory for

Teachers was distributed to 388 fourth- and

fifth-grade teachers in three school districtssurrounding a large southern metropolitanarea. Each teacher received three inventories,resulting in a total of 1,164 inventories. Ofthis total, 309 (27%) completed inventorieswere retumed. Three of the inventories wereunusable because the target students were inthe sixth grade. Therefore, the researchersused three hundred and six (26%) inventoriesin this study with a total of 112 teachers par-ticipating as raters.The data collected from the teacher partic-

ipants were analyzed through principal-com-ponents analyses by using the FACTOR pro-cedure in SPSSx. Before running the factorprocedure, 28 of the 92 items on the MultipleIntelligences Inventory for Teachers had to berecoded because they described negativebehaviors such as &dquo;Rarely demonstrates origi-nality in his/her artwork&dquo;; these items werereverse-scored by the researchers before con-ducting the factor analysis.

Results

Fifteen factors emerged from the initial

principal-components analysis with eigenval-ues greater than 1. Factor I accounted for37.5% of the variance and had an eigenvalueof 34.48. Eigenvalues may be defined as theproportions of total variance existing amongthe variables and, therefore, serve as a mea-sure of the relative importance of each factor(Townsend, 1987).A scree plot of the eigenvalues (Cattell,

1966) was also generated. An analysis of thescree plot indicated an initial flattening orbreak of the eigenvalues between Factors Vand VI, followed by subsequent breaks

between Factors VII and VIII, and Factors IXand X. Three factor analyses were performedusing solutions extracting Factors V, VII, andIX in order to find the most interpretablesolution.

These analyses employed the principal-components method of factor extraction withthe results rotated to the varimax rotation.When using the varimax rotation, it is

assumed that the components are orthogonalor uncorrelated. An initial factor matrix is

generated, and after rotation the factor load-ings are then interpreted. Factor loadings arethe structure coefficients that explain the cor-relations between the factors and variables.

Kerlinger (1986) recommended that a mini-mum factor loading of I .40 I be used when

interpreting factors. Comrey and Lee (1992)concurred with this recommendation.Therefore, the researchers used the factor

loading of I .401 1 as the cutoff score for anitem to be associated with a factor.

After examining the five, seven, and ninefactor solutions generated in these analyses,the researchers determined that the seven-factor solution was the most interpretablesolution. This decision was based on the totalnumber of items and the types of items defin-

ing each factor. The factors were consideredinterpretable if there was a common themeassociated with the factor items.

Factors were named by the researchers aftera careful examination of the types of itemsthat were loaded onto a particular factor.

According to Comrey and Lee (1992), factorinterpretation involves examining the vari-ables that have high loadings on a factor forcommonalities that could be the basis for thatfactor. The researchers looked for commonthemes for each of the factors based on the

types of items that loaded onto the factor. Theseven factor names and extraction order:General Academic Abilities, Musical/VisualArts Abilities, Interpersonal/IntrapersonalAbilities, Bodily-Kinesthetic/InterpersonalAbilities, Expressive Abilities, Tactile/Audi-tory Abilities, and Creative Production. The



42

Table 2 Excerpt from The Multiple Intelligences Inventory for Teachers



43

items that loaded onto the factors are pre-sented in Table 3. The structure coefficientsdetermined the order of the items for eachfactor, and the items were ordered from high-est structure coefficient to lowest structurecoefficient.

Reliability analyses were conducted usingcoefficient alpha (Cronbach, 1951). This wasdone using the RELIABILITY procedure in

SPSSx. The reliability coefficients generated inthese analyses indicate the internal consistencyof the factor scales. According to Carmines andZeller (1979), alpha reliability coefficients of.80 or above indicate that the factor scale is reli-able. The alpha reliability scores for the factorswere as follows: Factor I - .98, Factor II - .96,Factor III - .91, Factor IV - .82, Factor V -.75,Factor VI - .64, and Factor VII - .76. The over-all alpha for the Multiple IntelligencesInventory for Teachers was .98.

In the analysis of the entire sample, the fac-tor solution of seven factors was the most inter-

pretable. Two of the seven factors correspondedfairly closely with Gardner’s areas of musical(Factor II) and bodily-kinesthetic intelligence(Factor IV). However, there was some overlap.For example, Factor II also contained visual artsitems, which Gardner associates with spatialintelligence. And several items associated withinterpersonal abilities loaded onto Factor IV,thus combining Gardner’s bodily-kinestheticand interpersonal abilities. Factor III combinedthe interpersonal abilities with intrapersonalintelligences. The other four factors represent-ed combinations of several intelligence areas:General Academic Abilities (Factor I),Expressive Abilities (Factor V), Tactile-Audi-tory Abilities (Factor VI), and CreativeProduction (Factor VII). Table 3 presents theeigenvalues for the items associated with eachfactor. A brief discussion of each of the factorsthat emerged in the analysis follows.

Factor I: General Academic Abilities

The first factor that emerged in the analy-sis consisted of items associated with several

different intelligence areas. Fifty-four (59%)of the items loaded onto this factor. In exam-

ining these 54 items, it seemed that all ofthem represented an academic behavior thatis often exhibited or valued in the school set-

ting. As a result, this factor was named&dquo;General Academic Abilities.&dquo; Most of the

linguistic, logical-mathematical, and spatialitems loaded onto this factor. The overlap-ping of linguistic and logical-mathematicalitems was not surprising since these two areasare emphasized strongly in the school setting.The large number of spatial intelligence itemsloaded onto this factor was unexpected.However, in carefully examining the items, itbecame clear that spatial intelligence behav-iors are often associated with school tasks. For

example, one spatial intelligence item thatloaded onto this factor was &dquo;Easily leamsmaterial presented visually (e.g., pictures,visual media, graphic representations, etc.).&dquo;This method of transmitting information is

used frequently in the classroom. Items fromother intelligence areas that loaded onto thisfactor were also associated with behaviors val-ued in the school setting. An example of anintrapersonal item is &dquo;Effectively monitors

his/her thought processes, and if necessary,self-corrects.&dquo;

Close analysis of the linguistic,logical-mathematical, spatial, interpersonal,and intrapersonal items that formed this fac-tor revealed that teachers may have respond-ed to these items similarly because these arebehaviors that they readily observe and rein-force in their classrooms.

Factor 11: MusicallVisual Arts Abilities

Twenty-two items (24%) formed this sec-ond factor. The first five items to load ontothis factor were clearly associated with musi-cal intelligence, focusing on producing music,understanding the technical aspects of music,as well as being knowledgeable about varioustypes and styles of music. The visual arts com-ponent of this factor was evident through spa-



44

Table 3 Factor Loadings for Varimax Rotated Seven-Factor Solution (11~306)



45

Table 3 Continued

Note. Postulated intelligence areas in parentheses: (L) verbal/linguistic; (LM) logical mathematical; (S) visual/spa-tial ; (M) musical; (BK) bodily-kinesthetic; (I) interpersonal; (IN) intrapersonal.

Factor names: I-General Academic Abilities; 11-Musical/Artistic Abilities; III-Interpersonal/Intrapersonal Abilities;IV Bodily-Kinesthetic/Interpersonal Abilities; B1 &dquo;Expressive Abilities; VI-Auditory-Tactile Leaming Abilities; VII-Creative Production. at PENNSYLVANIA STATE UNIV on May 11, 2016aei.sagepub.comDownloaded from


46

tial items such as, &dquo;Clearly demonstrates anawareness of technical aspects of art and/orarchitecture such as balance, form, texture,space, shape, color, value, and lines.&dquo; One

possible explanation for the overlap of thesetwo areas is that many elementary schoolscombine music and art instruction in a cre-ative arts class. As a result, many teachersmay perceive these skills in conjunction withone another.

Factor lll: InterpersonalllntrapersonalAbilities

The third factor was named &dquo;Interperson-al/Intrapersonal Abilities&dquo; because of the highnumber of items from these two intelligenceareas. The total number of items in this factorwas 13 (14%); five of them were interperson-al and five were intrapersonal items. Thesetwo areas, interpersonal and intrapersonal, areoften associated with the social skills curricu-

lum, which includes building self-esteem andpositive peer interactions. This may havecontributed to the overlapping of these intel-ligence areas on this factor. In addition, twoitems associated with linguistic intelligenceloaded onto this factor - &dquo;Has difficulty fol-lowing oral directions&dquo; and &dquo;Demonstrates alove of reading (i.e., reads for pleasure, readsvoraciously).&dquo; The first item could be associ-ated with interpersonal intelligence becausethe teachers may have perceived that givingand following directions are interpersonalacts. Because of the intrapersonal nature ofreading for pleasure, the love of reading mayhave loaded onto this factor.

Factor IV Bodily-KinestheticllnterpersonalAbilities

Eleven items (12%) made up Factor IVThe first three items that loaded onto this fac-tor strongly correlated with bodily-kinesthet-ic intelligence. These items focused on theenjoyment of and participation in physicalactivities. The fourth strongest correlation,&dquo;Easily establishes rapport with people,&dquo;

describes an interpersonal behavior. Threeother items also reflected interpersonal abili-ties such as &dquo;Often spontaneously becomesthe leader of peer group activities in or out ofthe classroom.&dquo; There are several possibleexplanations for this overlap. Physical educa-tion classes and sports activities often requireteam participation. Thus, the peer interactioninvolved in these activities may explain whythese items combined on this factor. Teachers

responding may also have recognized the

importance of nonverbal communication ineffectively communicating and interactingwith each other. Someone who is able to

effectively use body language enhances com-munication and rapport with others. The fifthitem that loaded onto this factor, &dquo;Usuallyprefers to work alone,&dquo; correlated negativelywith the factor. Based on Gardner’s discussionof intrapersonal intelligence, this item waswritten to reflect a positive behavior associat-ed with intrapersonal intelligence; however,the negative correlation suggests a differentinterpretation. Because this factor describesbehaviors associated with physical activitiesand social involvement in these activities, the

negative correlation makes sense..

Factor W Expressive Abilities

The fifth factor to emerge in this analysisincluded eight items (9%) from the musical,bodily-kinesthetic, linguistic, intrapersonalintelligences, and logical-mathematical intel-ligences. The behaviors all centered aroundexpressing ideas and self through dance,music, mime, and speech. For example, one ofthe musical intelligence items was &dquo;Is usuallyoff-key or off-rhythm in musical perfor-mances.&dquo; Another example from the bodi-ly-kinesthetic intelligence was &dquo;Has difficultyimitating other’s actions.&dquo; Each of the state-ments associated with this factor described abehavior used to express an idea, a feeling oran action. Teachers may have responded tothese items in a similar fashion based on theirobservations of student performances in the



47

classroom or at school functions. As a result,this factor was named &dquo;Expressive Abilities.&dquo;

Factor VI: Auditory-Tactile LearningAbilities

The four (4%) items that formed this fac-tor combined spatial and linguistic intelli-

gences. Three items focused on hands-on

types of spatial activities such as using manip-ulatives and building constructions. The lin-guistic item emphasized auditory learningthrough listening to stories, books on tape, orradio shows. This combination of items wassomewhat puzzling. One explanation may bethat these items grouped together because ofthe way the teachers perceived multisensorylearning behaviors exhibited by the target stu-dents.

Factor VII: Creative Production

Six (7%) items formed this seventh andfinal factor. Although the element of creativ-ity is evident in many of the items on The

Multiple Intelligence Inventory for Teachers,the items that grouped on this factor involvesome type of creative production. Examplesinclude &dquo;Effectively represents ideas throughdrawings and graphic representations...&dquo; and&dquo;Exhibits creative artistic abilities throughdrawing, painting, sculpture, etc.&dquo; Three ofthe items were written negatively, but wererecoded in the analysis, including &dquo;Rarelydemonstrates originality in his/her artwork.&dquo;The items associated with this factor centeraround creative expression. These items

incorporate aspects of creativity such as origi-nality, fluency, flexibility, and elaboration.This may explain why these items formed thisfactor.

Overall Reliability and ConsistencyInternal consistency reliability of the

entire scale and each of the factors was calcu-lated. According to Carmines and Zeller

(1979), reliability coefficients should be atleast .80 for widely used scales. In this study,

Cronbach’s alpha was used to calculate thereliability coefficients for each of the factorscales and for the entire inventory.The overall alpha for the inventory was

sufficient at .98. Four of the factors, Factor I,&dquo;General Academic Abilities&dquo; (.98), FactorII, &dquo;Musical/Visual Arts Abilities&dquo; (.96),Factor III, &dquo;Interpersonal/IntrapersonalAbilities&dquo; (.91), and Factor IV,&dquo;Bodily-Kinesthetic /Interpersonal Abilities&dquo;

(.82), all met the established criteria. Three ofthe factors, Factor V, &dquo;Expressive Abilities&dquo;

(.75), Factor VI, &dquo;Tactile/Auditory LeamingAbilities&dquo; (.64), and Factor VII, &dquo;CreativeProduction&dquo; (.76), did not meet these criteria.Therefore, further examination of these fac-tors and factor items is warranted.

All of the individual items in each factorscale demonstrated positive item-total corre-lation with their respective factors except oneitem, Item 60, which reads, &dquo;Usually prefers towork alone.&dquo; Although it was written to

describe a preferred behavior in the intraper-sonal intelligence area, it loaded up negative-ly on Factor IV, &dquo;Bodily-Kinesthetic/Interpersonal Abilities.&dquo; This factor met the.80 criterion, but the removal of the itemwould increase the alpha by .05. Because Item60 does not effectively differentiate intraper-sonal behavior, it will be removed from futureversions of The Multiple IntelligencesInventory for Teachers.

Discussion

This study presents the initial stages of thevalidation of the Multiple IntelligencesInventory for Teachers. The findings of thisinitial stage warrant examining several issuesthat will affect future analyses of these data.

In discussing the results of the study, it is

essential to have as a frame of reference simi-lar studies on multiple intelligences.However, few empirical studies validating thetheory of multiple intelligences have beenpublished. One of these focused on validatingan instrument, &dquo;The Hillside Assessment of



48

Perceived Intelligences&dquo; (HAPI) (Shearer,1991 ). The target population in this study wasadults who had experienced traumatic braininjuries. Informants such as relatives, closefriends, or if possible, the individuals them-selves, provided the data. After refining theHAPI through item analysis, Shearer foundthat the items on the HAPI formed eight fac-tors. Seven of the factors corresponded toeach of Gardner’s seven intelligence areas:

linguistic, logical-mathematical, spatial,musical, bodily-kinesthetic, interpersonal,and intrapersonal. The eighth factor com-bined linguistic abilities with interpersonalabilities. Shearer named this factor,&dquo;Leadership.&dquo; Based on reliability analysesusing Cronbach’s alpha, Shearer also foundthat the factors produced were reliable.

Other empirical studies conducted in thisarea have addressed performance-based assess-ments rather than behavioral descriptors toassess multiple intelligences in children

(Gardner & Hatch, 1990; Krechevsky, 1991;Plucker et al., 1996). The target population inthese studies was young children in preschoolthrough first grade.

Of particular interest is a recent study onthe use of performance-based tasks to assessmultiple intelligences by Plucker et al.

(1996). Students in kindergarten and first

grade were required to complete a series ofactivities that corresponded with four of theseven intelligence areas: linguistic,logical-mathematical, spatial, and interper-sonal. Outside evaluators and teachers evalu-ated the students’ performances. Teacher rat-ings and observational checklists were alsoused. The data were analyzed using factoranalysis to determine if the activities coffe-

sponded to the four intelligence areas. Theresults indicated that the linguistic and inter-personal activities loaded onto the first factor;the second factor consisted of the

logical-mathematical factors; the third factorconsisted of three spatial activities; and theother two spatial activities loaded onto thefourth factor. Reliability analyses indicated

that the factors were reliable. Based on theresults of this study, Plucker et al. ( 1996) con-cluded that it is possible to develop reliableinstruments to measure multiple intelli-

gences, but that validating those assessmentinstruments can be problematic.The findings of the present study reflect

some of the same strengths and challengesfaced by Shearer ( 1991 ) and Plucker and col-leagues ( 1996). The factors that emergedfrom the analyses used in this study did notclearly match the seven intelligence areas

proposed by Gardner. Therefore, The

Multiple Intelligences Inventory for Teacherscould not be validated for the purposes of

measuring Gardner’s designated seven intelli-gence areas. The factors for the entire sample,however, were reliable based on the reliabilityanalyses, consistent with the findings ofPlucker et al. ( 1996). Although there are

some similarities with other studies, TheMultiple Intelligence Test for Teachers holdssome unique possibilities for educators. In

particular, the comprehensive nature of thebehavior descriptors and the alignment withbehaviors and processes associated with the

intelligences make this instrument useful ininstructional planning.The authors chose to use principal-compo-

nents analysis to analyze the data. This deci-sion was based on the assumption that theobserved variables would be orthogonal to

one another and uncorrelated. However, thismay not have been the optimal choice of sta-tistical analysis because principal-compo-nents analysis tends to inflate the varianceaccounted estimates. In future analyses, themaximum likelihood factor-analysis proce-dure may be a more appropriate choicebecause this procedure is designed to find theunderlying population parameters that wouldhave the highest likelihood of producing theobserved correlation matrix (Kim & Mueller,1978).

In rotating the factors to facilitate interpre-tation, an orthogonal rotation, which assumesthe factors are distinct, was used because the



49

underlying assumption of the theory of multi-ple intelligences is that the intelligence areasare unique and distinct from one another. Infuture analyses, an oblique rotation, whichassumes the factors may be correlated in some

way, seems warranted because of the overlapof factor items and the emergence of factorsthat were not clearly correlated with theseven distinct intelligence areas.

Examination of the individual items is also

necessary to strengthen the instrument andremove items that do not clearly differentiatebecause they loaded onto several factors. As aresult, the factor scales of the instrument areunbalanced. This problem needs to beaddressed before the instrument may be used

effectively. In addition, at the time of this

study, Gardner’s theory purported seven intel-ligences areas. An eighth intelligence, natu-ralist (Checkley, 1997; Gardner, 1999), hassince been added; therefore, this will alsohave to be addressed.

The results of the present study failed tovalidate The Multiple IntelligencesInventory for Teachers as an instrument toassess the seven intelligence areas designat-ed by Gardner. Several problem areas mustbe addressed before continuing with the

analyses. However, the results do bring upfurther questions about the assessment ofmultiple intelligences. From a practicalstandpoint, it appears to make sense to

explore a student’s abilities using a multiple-intelligences framework. The results fromthe present study appear to support thenotion that intelligence is not a single-fac-tor construct, but is multifaceted. However,the empirical evidence supporting use of aspecific instrument to assess a student inseven distinct intelligence areas is lacking.The difficulty experienced in validating amultiple-intelligences assessment instru-

ment seems to indicate that isolating eachintelligence by identifying representativebehaviors or behavioral statements is prob-lematic. Often behavior seems to be influ-enced by a combination of intelligences.

For example, in the present study, severalof the behavioral descriptors loaded ontomore than one factor. In addition, the factorsthat emerged represented combinations of

intelligences instead of discrete intelligenceareas. Other researchers have expressed simi-lar concerns (Plucker et al., 1994; Shearer,1991) when using Gardner’s multiple intelli-gences theory as a framework for developmentof an assessment instrument. Shearer (1994)stated &dquo;In a real sense, the creative, produc-tive, and contextual nature of the multipleintelligences renders them practicallyuntestable using standard objective measure-ment&dquo; (p. 9). However, Shearer (1997) wasable to validate an instrument, The MultipleIntelligence Developmental AssessmentScales (MIDAS), to assess multiple intelli-

gences. Shearer’s work with the MIDAS will

provide useful information for the refinementof this present study.The independence of the seven intelli-

gences in relation to a real-life context maybe questionable. Gardner (1993) himself rec-ognized that MI theory may be disprovedthrough empirical studies, identifying threepossible areas of concern: (a) the indepen-dence of intelligences, (b) the universality ofintelligences across cultures, and (c) the

developmental stability of an intelligence.Although the purpose of the present studywas not to prove or disprove MI theory, prob-lems with the independence of the intelli-

gences surfaced in the validation of The

Multiple Intelligences Inventory for Teachers.If the results of future validation studies of

multiple-intelligences assessment instrumentscontinue to reflect problems in establishingconstruct validity, Gardner’s MI theory shouldbe reexamined.The results of the present study do not sup-

port Gardner’s seven intelligence areas as dis-crete entities; however, the findings do sup-port the notion that intelligence is multifac-eted. The work of Gardner (1983) and

Stemberg (1985) emphasizes that intelligenceconsists of behaviors that enable an individ-



50

ual to interact successfully with his or herenvironment. The factors that emerged fromthe present study may be interpreted as valuedability areas in reference to the targeted gradelevels and geographic area used in the study.Further research is needed to determine if thefactors that emerged in the present study con-sistently appear in future analyses. In addi-tion, Gardner has recognized an eighth intel-ligence, naturalist, that needs to be examinedas part of future analyses. Even though devel-oping a valid instrument to assess Gardner’smultiple intelligences is problematic, his the-ory of multiple intelligences presents interest-ing possibilities for the field of education.

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Validating The Multiple Intelligences Inventory for Teachers