DEBATING ABILITY TESTING

THE RELATIONSHIPS AMONG STERNBERG’S TRIARCHIC ABILITIES, GARDNER’S MULTIPLE INTELLIGENCES, AND

ACADEMIC ACHIEVEMENT

BIRSEN EKINCI Marmara University

In this study I investigated the relationships among Sternberg’s Triarchic Abilities (STA), Gardner’s multiple intelligences, and the academic achievement of children attending primary schools in Istanbul, Turkey. Participants were 172 children (93 boys and 81 girls) aged between 11 and 12 years. STA Test (STAT) total scores were significantly and positively related to linguistic, logical-mathematical, and intrapersonal test scores. Analytical ability scores were significantly positively related to only logical-mathematical test scores, practical ability scores were only related to intrapersonal test scores, and the STAT subsections were significantly related to each other. After removing the effect of multiple intelligences, the partial correlations between mathematics, social science, and foreign language course grades and creative, practical, analytical, and total STAT scores, were found to be significant for creative scores and total STAT scores, but nonsignificant for practical scores and analytical STAT scores.

Keywords: Sternberg’s Triarchic Abilities Test, multiple intelligences, academic achievement, children, intelligence.

Since 1980 there has been increasing interest in the role of intelligence in learning and its impact on student achievement. Similarly to education theorists, many researchers on intelligence have been conducting studies to apply theories about intelligence, to education in general and, in particular, to the instructional context of the classroom (Castejón, Gilar, & Perez, 2008). The main difference between contemporary and older approaches to the role of intelligence is that,

SOCIAL BEHAVIOR AND PERSONALITY, 2014, 42(4), 625-634 © Society for Personality Research http://dx.doi.org/10.2224/sbp.2014.42.4.625

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Birsen Ekinci, Atatürk Education Faculty, Marmara University. This study was supported by the Marmara University, Scientific Research Projects Center, research number EGT-D-110913-0387. Correspondence concerning this article should be addressed to: Birsen Ekinci, Atatürk Education Faculty, Department of Primary Education, Marmara University, Göztepe Campus, 34722 Kadiköy, Istanbul, Turkey. Email: [email protected]

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in earlier conceptualizations, intelligence was described as involving one factor of general mental ability that encompasses the common variance among all the contributing factors. The existence of this general intelligence factor was originally hypothesized by Spearman in 1927 and labeled as “g” (see Jensen, 1998). It was hypothesized that this g factor exists over and above the various abilities that make up intelligence, including verbal, spatial visualization, numerical reasoning, mechanical reasoning, and memory (Carroll, 1993). However, according to contemporary theories, intelligence must be regarded as existing in various forms and the levels of intelligence can be improved through education. The most widely accepted comparative theories of intelligences in recent literature are Gardner’s (1993) multiple intelligences theory and Sternberg’s (1985) triarchic theory of intelligence. Researchers have reported significant differences between student outcomes for classroom instruction conducted following the principles of multiple intelligences, and student outcomes under traditionally designed courses of instruction in science (Özdermir, Güneysu, & Tekkaya, 2006), reading (Al-Balhan, 2006), and mathematics (Douglas, Burton, & Reese-Durham, 2008).

Gardner (1993) developed a theory of multiple intelligences that comprises seven distinct areas of skills that each person possesses to different degrees. Linguistic intelligence (LI) is the capacity to use words effectively, either orally or in writing. Logical-mathematical intelligence (LMI) is the capacity to use numbers effectively and to reason well. Spatial intelligence (SI) is the ability to perceive the visual-spatial world accurately and to interpret these perceptions. Bodily-kinesthetic intelligence (KI) involves expertise in using one’s body to express ideas and feelings. Musical intelligence (MI) is the capacity to perceive, discriminate, and express musical forms. Interpersonal intelligence (INPI) is the ability to perceive, and make distinctions in, the moods, intentions, motivations, and feelings of other people. Intrapersonal intelligence (INTI) is self-knowledge and the ability to act adaptively on the basis of that knowledge. Naturalist intelligence (NI) is expertise in the recognition and classification of the numerous species – the flora and fauna – of a person’s environment (Armstrong, 2009).

Researchers have addressed the relationship between multiple intelligences and metrics of different abilities, and of various psychological constructs. Reid, Romanoff, Algozzine, and Udall (2000) showed that SI, LI, and LMI were related to scores in a test to measure the nonverbal abilities of pattern completion, reasoning by analogy, serial reasoning, and spatial visualization, among a group of handicapped and nonhandicapped children aged between 5 and 17 years. Furthermore, the effects of multiple intelligences-based teaching strategies on students’ academic achievement have been studied extensively (Al-Balhan, 2006; Douglas et al., 2008; Greenhawk, 1997; Mettetal, Jordan, & Harper, 1997; Özdermir et al., 2006). In addition, some researchers have investigated the relationship between multiple intelligences and academic achievement (McMahon, Rose, & Parks, 2004; Snyder, 1999). McMahon and colleagues

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found that, compared with other students, fourth-grade students with higher scores on LMI were more likely to demonstrate reading comprehension scores at, or above, grade level. In a similar study, Snyder reported a positive correlation between high school students’ grade point averages and KI. In the same study results showed that there was a positive correlation between the total score for the Metropolitan Achievement Test-Reading developed by the Psychological Corporation of San Antonio, Texas, USA and the categories of LMI and LI.

Sternberg developed the second well-known intelligence theory. According to Sternberg (1999a, 1999b), individuals show their intelligence when they apply the information-processing components of intelligence to cope with relatively novel tasks and situations. Within this approach to intelligence, Sternberg (1985) proposed the triarchic theory of intelligence, according to which there are three different, but interrelated, aspects of intellect: (a) analytic intelligence, (b) creative intelligence, and (c) practical intelligence. Individuals highly skilled in analytical intelligence are adept at analytical thinking, which involves applying the components of thinking to abstract, and often academic, problems. Individuals who have a high degree of creative intelligence are skilled at discovering, creating, and inventing ideas and products. People who have a high level of practical intelligence are good at using, implementing, and applying ideas and products. Sternberg (1997) developed an instrument, the Sternberg Triarchic Abilities Test (STAT), to evaluate triarchically based intelligence. In this instrument each aspect of intelligence is tested through three modes of presentation of problems: verbal, quantitative, and figural. A number of previous researchers have established the construct validity of the STAT (Sternberg, Castejón, Prieto, Hautamäki, & Grigorenko, 2001; Sternberg, Ferrari, Clinkenbeard, & Grigorenko, 1996). Although Sternberg did not intend the STAT to be a measure of general intelligence, as assessed by conventional intelligence tests, in related literature (Brody, 2003) there are contradictory results and opinions on this issue. Sternberg (2000a, 2000b) has claimed that the STAT is independent of measures of general intelligence and a more accurate predictor of academic achievement. However, Gottfredson (2002) pointed out that the data obtained to support this claim are sparse and suggested that the data collected by Sternberg et al. (1996) support the conclusion that the STAT is related to other measures of intelligence and may, in fact, be a measure of general intelligence. The triarchic abilities are related to different intelligence tests scores (e.g., Concept Mastery Test, Watson Glaser Critical Thinking Appraisal, Cattle Culture-Fait Test of g; Sternberg et al., 1996). However, Brody (2003) suggested that although these correlations are substantial, it is likely that they underestimate general intelligence because they were obtained from a sample of high school students who were predominately categorized as gifted, as determined by IQ scores, and these students were, therefore, likely to record a restricted range of scores on the tests.

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In the present study I hypothesized that both multiple intelligences total scores and STAT total scores would be predictors of academic achievement. Specifically, I hypothesized that the LI and LMI, and the analytical STAT, would be predictors of student success in the subject areas of mathematics, science, social science, and foreign- language learning.

Method

Participants Participants were 174 randomly selected fifth- and sixth-grade students (81

girls and 93 boys) attending primary school in Istanbul, Turkey. Students’ ages ranged from 11 to 12 years old.

Instruments The students completed the Turkish version of Gardner’s Multiple Intelligences

Inventory (MII; Saban, 2002) to assess participants’ preferred intelligence within one of the eight categories: LI, LMI, SI, MI, KI, INPI, INTI, and NI. The possible score for the MII ranges from 0 to 80. The individual category in which a student has the highest score is considered to be the type of intelligence in which that student is most skilled. The overall Cronbach’s alpha reliability coefficient in this study was .96, denoting high reliability; .89 for LI; .83 for LMI; .89 for SI; .88 for MI; .78 for KI; .85 for INPI; .85 for INTI; and .84 for NI.

The second instrument that I used in this study was Sternberg’s Triarchic Abilities Test (STAT). The test comprises 81 items divided across three subsections designed to measure analytical, creative, and practical abilities. I translated this test into Turkish using the back-translation technique. In order to ensure that the back-translation retained the meaning of the original form, I conducted validity and reliability checks. The Turkish and the English versions of the test were given to 80 bilingual Turkish- and English-speaking students to complete within two weeks. Analyses of scores for the Turkish and English versions of test completed by these students yielded high correlation values (.85 for analytical, .79 for practical, and .81 for creative subsections). The overall alpha reliability coefficient of this test was .89, and for the subsections it was .80 for analytical, .77 for practical, and .78 for creative. Procedure

The students completed the instruments during class time and in their classrooms. There was no time limit for completion. Each test session lasted approximately 60 minutes. The parents of the participating children gave permission for the researcher to access the students’ grade point average for mathematics, science, social science, and foreign language courses at the end of the year during which the study was conducted. Each participant received a pen and pencil as a thank-you gift for his/her participation in this study.

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Data Analysis The data were analyzed using SPSS version 15 to conduct correlation analysis

and multiple regression analysis.

Results

As shown in Table 1, the children’s STAT total scores (M = 35.34, SD = 9.09) were significantly and positively related to LI (M = 28.98; SD = 7.59), LMI (M = 30.12, SD = 6.87), and INTI (M = 29.10, SD = 7.15) scores (p < .01). Analytical subsection STAT scores (M = 13.76, SD = 3.96) were significantly related to LM intelligence scores (p < .01). STAT practical subsection scores (M = 10.37, SD = 3.06) were significantly correlated only with INTI scores (p < .01).

Table 1. Relationships Among STAT Total Scores, Analytical, Practical, and Creative Ability Scores, and Multiple Intelligences Scores

LI LMI SI MI KI INPI INTI NI

Analytical .303 .413** -.057 .093 .036 .021 .281 -.102 Practical .274 .268 .003 .113 .041 .095 .434** -.109 Creative .291 .540** -.062 .103 .004 -.049 .361* -.098 Total .351* .506** -.051 .123 .031 .019 .425** -.124

Note. ** p < .01, * p < .05. LI = linguistic intelligence, LMI = logical-mathematical intelligence, SI = spatial intelligence, MI = musical intelligence, KI = bodily-kinesthetic intelligence, INPI = interpersonal intelligence, INTI = intrapersonal intelligence, NI = naturalist intelligence.

Mathematics course grades (M = 3.78; SD = 1.20) were significantly related to the STAT total (p < .001) and to the STAT analytical (p < .001), practical (p < .01), and creative (p < .01) subsections. Similarly, social science (M = 3.78, SD = 1.10) and science course grades (M = 3.51, SD = 1.40) were significantly related to the STAT total (p < .01) and to the STAT analytical (p < .01) and creative (p < .01) subsections. However, foreign language course grades (M = 3.57, SD = 1.16) were significantly related to all of the subsection scores of the STAT (p < .001; see Table 2).

Table 2. Relationships Among STAT Total Scores, Analytical, Practical, and Creative Sub- section Scores, and Academic Success

Mathematics Science Social science Foreign language

Analytical .536* .395** .304** .454*

Practical .461** .264 .269 .451*

Creative .491* .378** .307** .442*

Total .588* .415** .347** .527*

Note. * p < .001, ** p < .01.

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Mathematics grades of the participants were significantly related to LI (p < .01), LMI (p < .01), INPI (p < .05), and INTI (p < .01) scores. Similarly, students’ course grades for science were significantly related to LI (p < .05), LMI (p < .01), and INTI (p < .05) scores; students’ social science course grades were significantly related to LI (p < .05), LMI (p < .01), and INTI (p < .05) scores; and students’ course grades for foreign languages were significantly related to LI (p < .01), LMI (p < .01) and INTI (p < .01) scores (see Table 3).

Table 3. Relationships Between Multiple Intelligences Scores and Academic Success

LI LMI SI MI KI INPI INTI NI

Mathematics .458** .695** .080 .174 .285 .356* .522** .140 Science .340* .575** .007 .070 .239 .312 .379* .085 Social science .359* .598** .125 .118 .217 .319 .356* .139 Foreign language .484** .718** .211 .201 .260 .316 .495** .227

Note. ** p < .01, * p < .05. LI = linguistic intelligence, LMI = logical-mathematical intelligence, SI = spatial intelligence, MI = musical intelligence, KI = bodily-kinesthetic intelligence, INPI = interpersonal intelligence, INTI = intrapersonal intelligence, NI = naturalist intelligence.

Multiple regression analyses were conducted in which the variance caused by the MII was removed, and partial correlations were computed between course grades and children’s STAT total and subsection scores. Separate analyses were conducted for each subject area using first the STAT subsections and then using just the STAT total scores. Analyses regarding mathematics course grades yielded significant partial correlations for the creative subsection score (Pr = .44, p < .01) and for the total STAT score (Pr = .62, p < .01), but the partial correlations were not significant for the analytical (Pr = .14) and practical (Pr = 05) STAT scores. Similarly, the regression analyses predicting students’ science course grades yielded significant partial correlations for STAT total scores (Pr = .53, p < .01) and for the creative subsection score (Pr = .42, p < .01), but not for the analytical (Pr = .14) or practical (Pr = .06) STAT scores. Additionally, when I performed the same analyses of social science course grades these yielded significant partial correlations with STAT total scores (Pr = .54, p < .01) and creative subsection scores (Pr = .34, p < .05) but not with analytical (Pr = 19) or creative (Pr = .04) STAT scores. Finally, analyses yielded the same pattern for foreign language course grades and STAT total and subsection scores. Regression analyses yielded significant partial correlations for practical subsection scores (Pr = .41, p < .02) and for total STAT scores (Pr = .61. p < 01). Thus, the total STAT scores and creative subsection scores significantly predicted academic achievement in mathematics, science, social science, and foreign language courses, independent of multiple intelligences scores; however, the analytical and practical subsection scores did not. Correspondingly, the partial correlations

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between course grade (for mathematics, social science, science, and foreign language) and the MII subsection scores, with the variation caused by the STAT removed, were significant only for LMI (Pr = .70, p < .01) scores. This finding indicates that, independent of the STAT, only LMI scores predicted achievement in any subject area.

Discussion

The results in this study showed that STAT total scores were significantly related to LI, LMI, and INTI scores. Analytical subsection STAT scores were significantly related to LMI scores. Practical STAT subsection scores were significantly correlated only with INTI scores. These results are based on the partial correlations between multiple intelligences and STAT scores. However, I limited the scope of this study to the students’ own preferences in regard to their multiple intelligences. In future studies students’ intelligence types should be assessed together with the performances of students on related intelligences for different age groups and different subject areas. In the present study mathematics course grades were significantly related to STAT total scores and to scores for the STAT analytical, practical, and creative abilities subsections. Similarly, science, social science, and foreign language course grades were significantly related to the LI, LM, and INTI scores of the participants.

Results of multiple regression analyses indicated that total STAT scores and creative ability scores significantly predicted academic achievement in mathematics, social science, science, and foreign language learning, independent of multiple intelligences scores; however, the analytical and practical ability scores did not. These results are consistent with those reported by Sternberg et al. (2001), who found that total STAT and creative ability scores significantly predicted academic achievement. However, contrary to the findings reported by Sternberg et al., in my study the analytical and practical ability scores did not relate significantly to academic achievement. On the other hand, Koke and Vernon (2003) reported that total STAT scores and only practical ability scores predicted psychology course midterm grades of university students. All these results might indicate that there may be cultural differences within the dominant cognitive abilities represented in the national education systems of various countries.

My results in this study also revealed that the partial correlation between course grades for all of the subject areas and each of the MII subsection scores, with the variation caused by the STAT removed, was significant for only the LMI score. This indicates that, independent of the STAT, only LMI scores predicted achievement in any subject area. It should also be noted that in this study the students’ multiple intelligences scores were based on their own preferences for

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the items representing various kinds of intelligences. In other words, the multiple intelligences scores did not indicate the actual performance of the children in each type of intelligence. I believe that it would be of value for future researchers to test how well the STAT would predict academic achievement for scores on a test in which students’ multiple intelligences scores were each taken into account separately. The relationship between other tests and STAT scores could also be examined with more heterogeneous sample groups.

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