Investigating the Relationship Among the Multiple Intelligences and Reading and Math
Test Scores
C. Branton Shearer
This study examined the relationship between high school students’ academic skills
(reading and math) and their multiple intelligences (MI) profiles. A statistically
significant positive relationship was found between students’ math and reading test
scores and the theoretically predicted MI scales—linguistic and logical-mathematical.
The strongest correlations observed were between the math test and the MI School Math
subscale (r= .58) and Writing/Reading subscale with Reading test (r = .53). There were
319 participants from two suburban high schools. The Ohio state Achievement Tests
were completed by 219 9th grade and 100 10th grade students completed the ACT PLAN
(2005). All students completed the Multiple Intelligences Developmental Assessment
Scales (MIDAS) either at the beginning of their 9th or 10th grade year. The MIDAS is a
standardized self-assessment (Shearer, 1996) that is included in the students’ curriculum
primarily to enhance career planning, but implications for instruction, curriculum and
study strategies are included. It was concluded that the overall pattern of correlations
among tests and scales and criterion group mean scores supported the theoretical model
that MI includes abilities underlying academic skills (reading and math), but also
includes non-academic abilities evident in everyday life. (185 words)
The theory of multiple intelligences described by Howard Gardner (1983, 1993; 1999)
expands the unitary theory that has assumed for over 100 years that a single, general intelligence
(g) adequately describes a person’s full intellectual potential (Binet, 1913; Welscher, 1958;
Hernstein & Murray, 1994). Gardner’s extensive review of empirical, psychological and
neuroscience studies builds on and extends previous “multi-intelligence” theories of mind
(Guilford, 1954; Thurstone, 1938; Sternberg,1985; Goleman, 1995; Horn, 1982). Using a unique,
cross-cultural definition of intelligence, Gardner employs eight criteria to conclude that there is
a sufficient body of evidence to support the existence of at least eight distinct forms of
intelligence (Logical-mathematical, Linguistic, Spatial, Musical, Kinesthetic, Interpersonal,
Intrapersonal and Naturalist (see descriptions in Appendix 1).
1
Some critics of multiple intelligences theory (Gottfiedson, 1998; Sternberg, 1985;
Herrnstein & Murray, 1994; Willingham, 2005) question its essential validity because it does not
include general intelligence (g). This criticism has been refuted by Gardner (1999) in his
clarification that "MI theory questions not the existence but the province and the explanatory
power of g….Interest in g comes chiefly from those who probe scholastic intelligence and those
who study the correlations between test scores. I have long contended that much of the research
in this tradition overlooks too many important ingredients of human intellect. But I do not
consider he study of g to scientifically suspect, and I am willing to accept the utility of g for
certain theoretical purposes” (p. 87). MI theory includes g within its framework as a combination
of the convergent-problem solving aspects of the linguistic and logical-mathematical
intelligences.
Despite Gardner’s clarifications there remains a popular misunderstanding of MI theory
that it denies the importance of g and thus its implementation in schools is assumed to be “antiacademic achievement.” Gardner has likewise adamantly argued otherwise; in fact, he advocates
that the use of MI theory should raise the level of quality work expected of students (1999). This
misunderstanding has placed educators in the middle of two completing initiatives, both with the
goal of improving students' success in school.
Following publication of Frames of Mind in 1983, when MI theory was first introduced,
classroom teachers around the world responded enthusiastically and began to look for ways to
implement it in their classrooms to enhance student achievement and engagement. Not long after
this wave of innovative thinking, a second movement evolved in the United States to require all
students to pass “academic achievement tests” as a means to hold schools accountable for
teaching basic skills and knowledge to students.
2
The relationship among the multiple intelligences and academic achievement is not well
understood and this has resulted in educators being forced into an “either / or” situation: either
you teach to the test in order to quickly raise test scores or you design innovative curricula that
promote “understanding” and also value the creative dimensions of all the intelligences.
While educational theorists and researchers debate the value of MI for enhancing
instruction and curriculum, millions of teachers are stuck between their desire to teach with MI
in mind, but are also forced to focus on strategies to quickly raise students’ academic test scores.
In fact, there are reports of whole schools that have used MI inspired curriculum to improve
students’ test performance (Balanos, 1994; Campbell & Campbell, 1999; Diaz-Leferbvre, 1999;
Hoerr, 2000; Kornhaber, et al, 2004), but these studies have usually focused on schools using MI
for three or more years. Typically, many schools are not accustomed to such long-term planning
and secondly, it is a great challenge for schools to implement comprehensive school reform that
demands system-wide changes in their philosophy, curricular design, staff training, authentic
assessment, etc. Again, school administrators are placed in an "either / or" dilemma where they
must either choose to implement MI completely or not at all.
This research proposes that if the relationship between students’ MI profiles and
academic achievement test scores is better understood, teachers can be guided to design enriched
MI-inspired strategies and curriculum that will be both “personalized” (as advocated by Gardner,
1993) and focused on increasing reading and math skills. A second goal is to clarify the
relationship between students’ self-reported MI disposition and corresponding academic test
scores.
This study conducted an empirical investigation to test the hypothesis that designated
intelligences (Linguistic and Logical-mathematical) are more related to academic achievement
3
than other non-academic intelligences (e.g., Spatial, Kinesthetic, etc.). More specifically, it was
predicted that the convergent-academic aspects of these two intelligences would be more highly
correlated with test scores than are everyday, divergent thinking abilities (e.g., Rhetorical
Speaking, Strategy Games). The researcher hypothesized that reading scores are most associated
with Linguistic intelligence and, in particular, the school-based subscales. Likewise, the Logicalmathematical intelligence will be positively correlated with math test scores, and the
Calculations, School Math subscales will be more highly correlated than the non-academic
subscales (e.g., Strategy Games, Everyday Problem-solving).
The results of two studies are described. Study 1 examined the relationship of MI profiles
of 219 9th grade students to state-mandated reading and math achievement tests. Study 2
examined the relationship of MI profiles, of 100 randomly selected 10th grade students, to their
ACT PLAN (2005) reading and math test scores.
Study 1: Examining the Relationship Between Students’ State Achievement Test
Scores and Their Multiple Intelligences Profiles
Method
Participants
Two hundred and nineteen students comprising the entire 9th grade at a small midwest
U.S. high school participated in this study. There were 123 males (56%) and 91 females (42%)
and about 3% were African American and the remainder Caucasian. Ninth grade students are
typically either 14 or 15 years old and come from working class or lower-middle class families.
The school has a good academic reputation and meets the state criteria as an “effective school”
based on its overall reading and math test scores and other criteria.
4
Procedures
Students completed the state-mandated reading and math achievement tests in March of
their 8th grade and then completed the Multiple Intelligences Developmental Assessment Scales
(MIDAS) early in their 9th grade. The MIDAS has been completed by all 9th graders in this
school for the past five years and is a component of their career exploration curriculum. The
results of the entire 9th grade class members who completed both assessments were analyzed.
Instruments
Multiple Intelligences.
The Multiple Intelligences Developmental Assessment Scales (MIDAS) is a selfcompleted questionnaire that can be administered and interpreted by teachers, counselors and
psychologists (Shearer, 1996). The MIDAS consists of 119 items each with six response choices
(e.g., “Are you good at finding your way around new buildings or city streets?” Not at all, Fairly
Good, Good, Very Good, Excellent, I don’t know or Does not apply). Response anchors are
uniquely written to match each question’s specific content and calibrated to the responses of a
representative U.S. sample. A Does not apply or I don’t know option is provided for every
question so that the respondent is not forced to guess or answer beyond his or her actual level of
knowledge. Percentage scores for each scale are calculated from the total number of responses.
The MIDAS was initially developed in 1987 as a structured interview format that
provides a quantitative and qualitative profile describing the respondents’ intellectual disposition
in eight main scales and 26 subscales. The MIDAS questions inquire about developed skill,
levels of participation, and enthusiasm for a wide variety of activities that are naturally
encountered as a part of daily life. A MIDAS scale score represents the person’s “intellectual
disposition” which has been defined as "thinking performance in everyday life in terms of skill,
5
behavior and preference." Scores are reported as simple percentages on a scale ranging from 0 –
100%. Criterion validity studies (Shearer, 1996) cite the following general categories to facilitate
interpretation:
100 – 80 = Very High
79 – 60 = High
59 - 40 = Moderate
39 - 20 = Low
0 – 19 = Very Low
Numerous studies in the US and around the world (Canada, Chile, UK, Singapore, Korea,
Hong Kong, Turkey, Taiwan, Malaysia, etc.) have investigated the reliability and validity of the
MIDAS and early studies are summarized in The MIDAS Professional Manual (Shearer, 1996).
More recent studies are available at the publisher’s website www.MIResearch.org. Based on the
results of previously published reliability and validity studies, the MIDAS was favorably
evaluated (Buros, 1999), suggesting support for use of the MIDAS within educational contexts.
Researchers have concluded that a majority of respondents are able to provide a “reasonable
estimate” of their multiple intelligences strengths and limitations.
Achievement Tests
As required by state law, all eighth grade students were administered the Ohio
Achievement Tests for Reading and Math (Ohio Department of Education, 2006). The Reading
test is comprised of four subtests measuring vocabulary, reading processes, information and
literary text analysis. The Math test is comprised of five subtests including number sense,
measurement, data analysis, geometry and algebra.
6
Results
Descriptive statistics for the group reveals MI scale scores ranging from 44% to 58%
with a mean of 51% (see Table 1). These are comparable to other ninth grade students cited in
the Professional Manual (1996). Subscale scores range from 44% (School Math and Expressive
Language) to 61% (Persuasive).
______________________________________________________________________________
Table 1: MIDAS Mean Main Scale and Subscale Scores
______________________________________________________________________________
MIDAS Main Scales
Scale
Interpersonal
Mean
57.69
Std. Deviation
16.82
Kinesthetic
52.89
17.17
Intrapersonal
51.86
13.55
Spatial
51.63
17.44
Musical
51.29
21.68
Linguistic
50.02
17.34
Logical-math
47.97
16.37
Naturalist
44.47
19.86
MIDAS Subscales
Mean
Std. Deviation
School Math
44.82
27.68
Strategy Games
49.00
20.43
Everyday Math
44.14
20.67
Problem Solving
55.99
21.58
Calculations
42.05
22.35
Expressive Sens.
44.15
18.52
Rhetorical
54.34
19.73
Writing/Reading
51.61
22.85
Persuasive
61.34
20.99
Note. n=219. Designated scale categories: 100- 80= V. High; 79 – 60= High;
59 – 40= Mod.; 39 – 20= Low; 19 – 0= V. Low.
________________________________________________________________________
7
The students’ mean Reading test score (432) is in the Advanced range and Math score
(429) is in the Proficient range according to published state guidelines (Ohio Department of
Education, 2005) (Table 2 and Figures 1 and 3). The Reading test scores for the group are
negatively skewed with many more higher scores than lower (Figure 1). There are only 18
students in the two lowest categories while there are 124 students in the two highest categories.
The Math test scores more closely resemble a normal distribution (Figure 3).
_____________________________________________________________________________
Table 2. Math and Reading Mean Test Scores
_____________________________________________________________________________
MATHEMATICS
READING
Mean
429.20
431.58
S.D.
29.99
25.80
Note. n= 219. Math Categories. 459 – 551= Advanced; 432 – 458= Accelerated; 400 – 431=
Proficient; 379 – 399= Basic; 282 – 378= Limited. Reading Categories: 451 – 539= Advanced;
428 – 450= Accelerated; 400 – 427= Proficient; 378 – 399= Basic; 258 – 377= Limited.
____________________________________________________________________________
The correlations among scales and tests are presented in Table 3. The highest correlations
are between the designated main scales (Linguistic and Logical-Math) and the matched Reading
and Math tests (r= .33 and .35, respectively). The remaining scales all have relatively low
correlations with Math and Reading tests (ranging from r= -.03 to .32 with a mean of .13)
Of note, however, the Reading test is also significantly correlated with the Logical-math
and Intrapersonal scales at r= .27 and Interpersonal at .18.
The Math test shows a similar correlational pattern. It is most highly correlated with the
Logical-math scale (.35), which is followed by the .32 correlation with Intrapersonal scale. The
8
lowest significant correlation is with the Linguistic scale (.19). The remaining main MI scale
correlations are not significant and are very low (-.03 to .13).
____________________________________________________________________________
Table 3. Correlations Among MIDAS Main Scales and Reading and Math Tests
____________________________________________________________________________
READING
READING test
MATH
.638(**)
Musical
.131
-.031
Kinesthetic
.059
.133
.356(**)
Logical-math
.269(**)
Spatial
Linguistic
.092
.331(**)
Interpersonal
.182(**)
.133
Intrapersonal
.273(**)
.321(**)
.040
.189(**)
Naturalist
.048
.001
Pearson Listwise n=216
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
_________________________________________________________________________________________
Discussion
Correlations between the MI Linguistic and Logical-Math scales with the Reading and
Math tests are in the low-moderate range. These correlations are statistically significant and are
within the appropriate range of theoretical expectations. The strength and pattern of correlations
with the other MI scales is likewise appropriate.
It is theoretically and educationally noteworthy that Reading test scores are most
correlated with the triad of Linguistic, Logical and Intrapersonal abilities and, to a lesser extent,
with Interpersonal understanding. Secondly, it is noted that Math success is most correlated with
Logical and Intrapersonal abilities and, to a lesser extent, Linguistic. These findings are
educationally meaningful because they imply that teaching reading may be enhanced by the
inclusion of Logical and Intrapersonal activities. Likewise, math skills may be developed by the
9
inclusion of Intrapersonal activities, e.g., metacognition, emotional self-management and selftalk or journaling.
It is important to note that the Math and Reading tests are most highly correlated with
each other at .638. This finding indicates a couple of important facts. First, this .63 correlation is
about the same as what is found when IQ scores are correlated with academic grades. Second,
success in math is very dependent upon reading ability.
The next analyses examine more closely the relationship among Reading test scores and
Linguistic subscales (Writing/Reading, Persuasive, Expressive, Rhetorical language).
Reading Results
____________________________________________________________________________
Table 3. Correlations of MI of Subscales with Reading Test
_____________________________________________________________________________
Linguistic
Writing
Persuasive Expressive
Pearson
.418(**)
.294(**)
.232(**)
.331(**)
Correlation
** Correlation is significant at the 0.01 level (2-tailed). Bold are expected highest values.
READING
Rhetorical
.226(**)
_____________________________________________________________________________
The Writing/Reading subscale has the highest correlation of all scales with the Reading
test (r =. 42) and is followed by the scales that describe oral and everyday use of language
Persuasive (.29), Expressive (.23), Rhetorical language (.23). These values are all statistically
significant and in a descending pattern that fits the theoretical model. Reading test scores were
predicted to be most highly correlated with the Writing/Reading subscale and followed by the
Linguistic main scale as is observed in Table 3.
10
The next analyses examine the rate of categorical agreement among test scores and MI
scales. Both MIDAS scales and tests rank their scores in five categorical levels from 1= very low
(Limited) to 5= very high (Advanced).
_____________________________________________________________
Table 4. Categorical Agreement Among Reading Test and Linguistic Main Scale and Writing
Subscales
_____________________________________________________________
Linguistic Category by Reading Category Crosstabulation
Count
Reading Category
MI Scale
Linguistic
Limited
Basic
Proficient
Total
Accelerated
Advanced
1
1
1
4
1
0
7
2
3
4
19
22
6
54
3
3
5
34
33
18
93
4
0
1
11
17
19
48
5
0
0
2
5
3
10
7
11
70
78
46
212
Total
Note. MIDAS Categories: 1= very low, 2= low, 3= moderate, 4= high and 5= very high.
Writing Subscale by Reading Category Crosstabulation
Count
Reading Category
MI Subscale
Writing
Total
Limited
Basic
Total
1
2
2
Proficient
11
Accelerated
3
Advanced
1
2
19
3
8
17
3
1
0
22
20
4
52
30
10
4
1
1
13
63
16
17
5
48
0
0
7
11
7
9
14
30
70
78
46
212
Note. MIDAS Categories: 1= very low, 2= low, 3= moderate, 4= high and 5= very high.
_____________________________________________________________________
The categorical agreement rates for the Linguistic main scale with the Reading test scores
are significant at the .053 level (Phi and Cramer’s V), but the Kappa statistic is not significant at
11
.274. However, the Writing/Reading subscale agreement rates are significant at the .000 level on
all tests of significance.
The Linguistic main scale shows an overall exact categorical agreement rate mean of
26%. There is a 72% agreement +1 category. The mean Writing subscale agreement rates are
37% exact and 75% +1 category. Of particular note is the observation that the Reading test
categories are generally higher by one (or sometimes two) categories than observed for both the
Linguistic main and subscales.
These findings are similar to, but somewhat lower than, the agreement rates and pattern
obtained in previous studies comparing the MIDAS main scales to instructor ratings (i.e., on
average 40% exact and 80% +1 category) (Shearer, 1996). Overall, the Writing/Reading subscale
displays a stronger relationship to test scores than the Linguistic main scale.
The mean Linguistic scale scores are examined for groups of students scoring at each level
of the Reading test (1= Low to 5 = Highest) (Table 5).
_____________________________________________________________
Table 5. Mean Linguistic Scores by Reading Test Categories
_____________________________________________________________
Linguistic Scale
Reading Category
1- Limited
Mean
N
Std. Deviation
37.86
7
12.63
2- Basic
38.30
11
15.35
3- Proficient
46.51
70
15.93
4- Accelerated
51.06
78
17.06
5- Advanced
57.70
46
16.48
Total
49.90
212
17.09
Note. Reading Categories: 451 – 539= Advanced (5); 428 – 450= Accelerated (4); 400 – 427=
Proficient (3); 378 – 399= Basic (2); 258 – 377= Limited (1) as per state guidelines.
_______________________________________________________________________
12
The mean Linguistic scale scores are in an ascending pattern as predicted by MI theory
and guidelines presented in the Manual. There are differences among mean category Linguistic
scale scores that are statistically significant (ANOVA, F 6.0, p. .00) except for the two low
categories that do not differ. Also, according to the Manual the highest category (5) is expected
to have a mean above 60%.
The Writing/Reading subscale means for the five Reading test levels are reported in
Table 6.
____________________________________________________________
Table 6. Mean Writing Subscale Scores by Reading Test Categories
_____________________________________________________________
Writing Subscale
Reading Category
1- Limited
Mean
N
Std. Deviation
34.56
7
17.96
2- Basic
31.27
11
15.84
3- Proficiency
46.00
70
23.19
4- Accelerated
51.06
78
20.77
5- Advanced
67.28
46
18.69
Total
51.34
212
22.89
Note. Reading Categories: 451 – 539= Advanced (5); 428 – 450= Accelerated (4); 400 – 427=
Proficient (3); 378 – 399= Basic (2); 258 – 377= Limited (1) as per state guidelines.
_________________________________________________________________________
This pattern of mean scores is also ascending (35% to 67%), but again the low categories
of 1 and 2 are not different, however, they are appropriately low (<40%). The middle category
(3) is in the moderate range (46%) and then the highest category (5) has the more appropriate
mean score of (67%) meeting theoretical expectations.
Discussion:
13
The students’ mean scores for the MIDAS scales and Math test are in the Moderate
Proficient range and the Reading test is in the Accelerated category.
The pattern of correlations among the MI main scales and Reading and Math tests is
correctly aligned with theoretical expectations. The strength of the relationship between the
Linguistic scale (r= .33) and reading and the Logical-math scale (r=.36) and Math test are
somewhat lower than expected.
The pattern of correlations for Linguistic subscales with Reading test scores is
appropriately aligned with expectations. The Writing/Reading subscale is the highest moderate
level correlation of all scales (r= .42).
Students’ agreement rates among levels of Reading test scores and Linguistic subscale
Writing/Reading are stronger than the Linguistic main scale. This matches the theoretical
expectations that the more specific subscales that assess classroom activities would be better
predictors of test scores than scales measuring the informal use of language.
The mean Linguistic scale scores at each Reading test category are progressively higher
and significantly different (except for the lowest two categories) using ANOVA and T-test posthoc tests. The mean Writing subscale scores are likewise significantly different at each level.
Again, the MIDAS scale means are generally somewhat lower than expected at each level except
for the Writing subscale. The Writing subscale’s highest level mean of 67% and the two lowest
category level means of 34% and 31% match with expectations. The two middle levels – 46%
and 51% - likewise correspond with the theoretical model.
These results indicate that the Linguistic main scale is positively related to the Reading
test scores, but at a lower level than the Writing subscale. A majority of student self-ratings agree
14
with their Reading test scores within one category. Reading test scores are, on whole, higher than
student self-ratings.
The Reading test scores for the whole group are skewed with many more higher scores
than lower (see figure 1). For example, there are only 18 students scoring in the two lowest
categories while there are 124 students in the two highest categories. This is a dramatically
different pattern than observed for the MIDAS Linguistic scale that more resembles a normal
distribution of scores (figure 2).
Math Results
The next set of analyses examines the relationship among students’ Math test scores and
several MIDAS main and subscales. As noted above (Tables 1 and 2), the Math test mean for the
whole group was 429 which is in the Proficient range as was the MIDAS Logical-math scale
(48%) in the Moderate category.
The Logical-math scale mean scores per Math test category level are displayed in Table
7.
__________________________________________________________________________
Table 7. Mean Logical-Math by Math Test Categories
__________________________________________________________________________
Logical-Math Main Scale
Math Category
1- Limited
Mean
N
Std. Deviation
37.72
6
16.52
2- Basic
40.16
28
15.63
3- Proficient
43.42
72
15.31
4- Accelerated
51.14
80
14.86
5- Advanced
59.61
29
16.23
Total
47.89
215
16.46
15
Note. Math Categories. 459 – 551= Advanced (5); 432 – 458= Accelerated (4); 400 – 431=
Proficient (3); 379 – 399= Basic (2); 282 – 378= Limited (1) as per state guidelines.
_________________________________________________________________________
The highest Math test group (5, Accelerated) has a mean Logical-math scale score of
60% (High) while the lowest group (1, Basic) has a mean of 38% (Low range). The Math test
Proficient group (3) has a mean Logical-math scale of 43% (Moderate). The overall ascending
pattern of Logical-math scale means for each Math test group is similar to that observed for the
Linguistic main scale with Reading categories.
The Accelerated (4) Math test group has a mean Logical-math score of 51% which is in
the middle of the Moderate range so again, we see an overall pattern where students are scoring
somewhat lower on the MIDAS main Logical-math scale than on the Math test.
The School Math subscale mean scores per Math test category levels are present in Table
8.
__________________________________________________________________________
Table 8. Mean School Math Subscale Scores by Math Test Categories
___________________________________________________________________________
School Math Subscale
Math Category
1- Limited
Mean
N
Std. Deviation
20.83
6
20.25
2- Basic
23.21
28
17.47
3- Proficient
32.46
72
22.25
4- Accelerated
54.06
80
23.30
5- Advanced
75.86
29
21.86
Total
44.82
215
27.68
Note. Math Categories. 459 – 551= Advanced (5); 432 – 458= Accelerated (4); 400 – 431=
Proficient (3); 379 – 399= Basic (2); 282 – 378= Limited (1) as per state guidelines.
16
_________________________________________________________________________
The pattern of mean scores for the School Math subscale is quite different from that of
the main Logical-math scale (Table 8). The highest Math test group (5, Accelerated) has a mean
School-Math subscale score of 76% (Very High) while the lowest group (1, Basic) has a mean of
21% (Very Low). The Math test Proficient group (3) has a mean School Math scale of 33%
(Low). The ascending pattern of School Math scale means for each Math test group shows a
stronger relationship between the two measures.
The Accelerated (4) Math test group has a mean School Math subscale score of 54%
which is a little higher than that observed for the main Logical-math scale.
Table 9 presents the correlations between the Math test and the MIDAS Logical-math
subscales.
_________________________________________________________________________
Table 9. Correlations Between Math Test Scores and MIDAS Logical Main and Subscales
_________________________________________________________________________
Logical
School
Math
Strategy
Games
Everyday
Math
Problem
Solving
Calculatio
n
MATHEMATICS
Pearson
.356(**)
.584(**)
.496(**)
.224(**)
.376(**)
.022
Correlation
Note. N= 215 ** Correlation is significant at the 0.01 level (2-tailed). Bold indicates expected highest values.
* Correlation is significant at the 0.05 level (2-tailed).
____________________________________________________________________________
The School Math subscale displays the strongest correlation at .58 with the Math test
followed by the Calculations subscale (.50) and Everyday Math correlation of .38 and finally the
main scale of .36. The lowest two correlations are Strategy Games at r=.22 (p = .001) and r=.02
(p=.74) for Problem Solving. Again, we see a pattern where the school-related subscales are
more predictive of Math test scores than are the other scales.
17
The categorical agreement rates between five levels of the Math test compared to the five
levels of the MIDAS main and subscales are examined next (Table 10).
_____________________________________________________________________________
Table 10. Categorical Agreement Rates Between Math Test and Logical-math Main Scale
_____________________________________________________________________________
Logical Category * Math Category Crosstabulation
Count
Math Category
Limited
Logical
Total
Basic
Total
1
1
2
Proficient
5
Accelerated
2
Advanced
0
2
1
13
25
17
3
59
3
3
10
32
41
14
100
4
0
3
9
17
9
38
5
0
0
1
3
3
7
5
28
72
80
29
214
10
_____________________________________________________________________________
Of the five Math test scorers in the lowest category (1, Basic) two are within one
category on the Logical-math main scale, but three are in the 3 (Moderate) category. Of the 72
Math test scorers in the middle (3) category, 44% agree exactly while 92% agree within one
category. 41% of the highest Math test scorers (5) are within one category on the Logical-math
scale. Interestingly, 48% score lower at the Moderate category.
The School Math subscale categorical agreements with Math test are presented in Table
11.
______________________________________________________________________________
Table 11. Categorical Agreement Rates Between Math Test and School Math Subscales
______________________________________________________________________________
18
School Math Category by Math Category Crosstabulation
Count
Math Category
MI Subscale
School
1
Math Cat
2
Limited
Basic
Proficient
Total
Accelerated
Advanced
4
14
24
6
1
49
0
10
23
17
2
52
3
2
3
18
28
3
54
4
0
1
3
15
9
28
5
0
0
4
14
14
32
6
28
72
80
29
215
Total
__________________________________________________________________________
Seventy-five percent of the Math test lowest scorers (Limited) also score at the lowest
level for the School Math subscale. Sixty-one percent of the Proficient Math test scorers score
within one School Math subscale category. Likewise 72% of the highest Math test group
Advanced score within one category on the School Math subscale (see Table 11). These subscale
statistics again show a stronger relationship between the School Math and Math test results than
do the MIDAS main scale rates of agreement.
Discussion:
The distribution of Math test scores for the whole group is more similar to the Logicalmath scale than that of the Linguistic scale compared with the Reading test scores. This may
account for some of the higher correlations and agreement rates between students’ self-reported
abilities. See Figure 3.
Overall, we see a somewhat better theoretical fit between the MIDAS School Math
subscale than for the main scale. This supports the hypothesis that the subscale will be a better
predictor of math achievement than the main scale that also assesses logical reasoning outside of
the school environment.
These results provide statistically significant data to support the hypothesis that the
MIDAS subscales matched with academic tests provide the best predictors of reading and math
19
test scores. These correlations are in the moderate ranges (.42 to .58), which is not unexpected. It
is similar to many other research studies (Duckworth & Seligman, 2005; Matarazzo, 1972;
Wilhelm and Engle, 2005; Block and Dworkin, 1976) that have found that IQ scores are likewise
moderately correlated with grades (in the .32 - .60 range).
What needs to be kept in mind when reviewing these data is that the Ohio state academic
tests (along with many other US states’ tests) have been regularly criticized as being too lenient
and “dumbed down” in order to maximize the rate of student passing and the appearance of
achievement. These criticisms have gained so much influence to the point where the tests are
being abandoned in favor of the more stringent tests aligned with Common Core standards. If
these criticisms are true, then the MIDAS scales may present are more realistic picture of
students’ reading and math achievement than the tests. Likewise, if the achievement categories
were scaled down then we’d observe a very meaningful improved rate of agreement and
correlation between the tests and the MIDAS scales.
Study 2: Examining the Relationship Between Students’ ACT PLAN Reading and
Math Scores and Their Multiple Intelligences Profiles
Method
Participants
One hundred students consisting of a random sample of the entire 10th grade at a large
midwest, suburban U.S. high school were included in this study. There were 43 males and 57
females with over 90% Caucasian. Tenth grade students are typically either 15 or 16 years old
and a majority come from middle class families. The school has an excellent academic reputation
and has received designation as a Blue Ribbon School.
20
Procedures
Students completed the ACT PLAN (2005) achievement and interest tests in October of
their 10th grade and then completed the Multiple Intelligences Developmental Assessment Scales
(MIDAS) two weeks later. The MIDAS has been given to all 10th graders in this school for the
past six years and is a component of their career exploration curriculum. A random sample of
100 student scores were analyzed for this study.
Instruments
Academic Skills.
Four subtest scores from the ACT PLAN (2005) are included in these analyses: English,
Reading, Math and Composite. According to the publisher, the English test is a measure of
standard written usage/mechanics and rhetorical skills. The Reading test measures reading
comprehension skills such as drawing conclusions, making comparisons and generalizations. The
Math test assesses practical quantitative problems involving algebra and plane geometry. The
PLAN is the tenth grade version of the ACT test used for college admission decisions. The
Composite score is an average of the academic tests (Reading, Math and Science) and is an
estimate of what a student can expect to achieve on the ACT test.
Multiple Intelligences.
The same version of the Multiple Intelligences Developmental Assessment Scales
(MIDAS) was used with the 10th graders in Study 2 as with 9th graders in Study 1.
Results
Descriptive statistics for the group reveals MI scale scores ranging from 45% to 58%
with a mean of 51% (see Table 1). These are comparable to other 10th grade students cited in the
21
Professional Manual (1996). Subtest scores range from 48% (Everyday Math) to 62%
(Persuasive).
_________________________________________
Table 12. Mean MIDAS Scale Scores
_________________________________________
Mean
SD
Interpersonal
57.58
14.05
Musical
53.40
20.99
Intrapersonal
53.16
11.87
Kinestethic
51.29
16.89
Logical-math
50.75
15.20
Lingustic
50.17
15.89
Spatial
49.96
16.00
Naturalist
45.21
19.66
Note. n= 100.
____________________________________________________________________________________
_______________________________________________________________________
Table 13. Mean MIDAS Logical-Math and Linguistic Subscale Scores
_______________________________________________________________________
Mean
61.24
Std. Deviation
22.17
Strategy Games
51.15
18.49
Everyday Math
48.09
17.28
Problem Solving
58.50
19.58
Calculations
52.50
17.92
Expressive
46.41
17.39
Rhetorical
56.52
16.69
Writing/Reading
56.85
20.51
Persuasive
62.28
19.17
School Math
Note. n= 100
22
_____________________________________________________________________________
The students’ mean academic ACT test scores are reported in percentile ranks and for this
sample range from 64%ile to 70%ile. (See Table 14)
______________________________________________________________________________
Table 14. Mean ACT English, Reading, Math and Composite Scores
______________________________________________________________________________
Percentile
English
Mean
Std. Deviation
68.22
24.24
Math
70.34
24.96
Reading
64.43
29.95
Composite
69.94
26.48
Note. n= 100.
______________________________________________________________________________
Data analysis begins by comparing the academic tests to all of the MIDAS scales (Table
15).
______________________________________________________________________________
Table 15. Correlations Among ACT Math, Reading, Composite Tests and MI Scales
______________________________________________________________________________
music
Math
Reading
Composite
Pearson
Correlation
Pearson
Correlation
Pearson
Correlation
kinest
logic
spatial
ling
interper
intraper
Nature
.060
.049
.326(**)
.100
.260(**)
.005
.288(**)
-.051
.189
.080
.212(*)
.191
.498(**)
.180
.337(**)
.094
.099
.084
.319(**)
.207(*)
.430(**)
.116
.384(**)
.047
Note. n= 100. Bold values indicate expected highest correlations.
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
______________________________________________________________________________
23
The highest correlations among the designed main scales (Linguistic and Logical-math)
and the matched Reading and Math tests are r = .50, and .33, respectively. The remaining scales
all have low correlations with Math and Reading tests (ranging from r= .000 to .034). The
Reading test, however, is also significantly correlated with Intrapersonal scale (.34) and Logicalmath (.21).
The Math test shows a similar pattern of significant correlations with other scales. Its
highest correlation is with the Logical-math scale (r= .33) followed by a .29 correlation with
Intrapersonal and .26 with Linguistic. The remaining non-significant correlations are quite low
range from -.05 to .10
Discussion:
These MI main-scale correlations with academic tests are quite similar to the strength and
pattern observed in Study 1 except for the higher moderate relationship between the Linguistic
main scale and (r=.50) and the Reading test. This pattern of correlations matches theoretical
expectations.
Reading and Math Results
____________________________________________________________________________
Table 16. Correlations Among ACT English and Reading Tests and Linguistic Scales
_____________________________________________________________________________
Linguistic Expressive
English
Reading
Pearson
Correlation
Pearson
Correlation
Rhetoric
Writing
Persuasive
.350(**)
.339(**)
.190
.405(**)
.165
.499(**)
.479(**)
.300(**)
.531(**)
.310(**)
Note. n= 100. ** Correlation is significant at the 0.01 level (2-tailed). Bold indicates highest
expected values.
____________________________________________________________________________
24
The Writing/Reading subscale has the highest correlation of all scales with the Reading
test at .53 and is followed the main Linguistic scale (.50) and Expressive language (.48). Lower
values are observed for the non-academic Linguistic subscales (Rhetorical, Persuasive). These
values are all statistically significant and in a descending pattern that fits the theoretical model.
Three of the subscales are also significantly correlated with the English test (.35 to .41), but at a
lower level than observed with the Reading test.
__________________________________________________________________________
Table 17. Correlations Among ACT Math Test, Composite and Logical-mathematical Scales
_____________________________________________________________________________
Logicalmath
Math
Composite
Pearson
Pearson
.326(**)
.320(**)
School
Math
.550(**)
.467(**)
Strategy
Games
Everyday
Math
Problem
Solving
.246(*) .370(**)
.230(*) .363(**)
Calculate
.027 .501(**)
.077 .443(**)
Note. n= 100 ** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed). Bold indicates highest expected values.
______________________________________________________________________________
The School Math subscale displays the highest correlation with both the Math test (.55)
and Composite score (.47). This is followed by the Calculations subscale with the Math test at
.50 and Composite at .44. The Everyday Math subscale has the third highest correlation with the
Math test at .37. These values are all stronger than the main Logical-math scale (.33). This
pattern and strength of correlations closely resembles that observed in Study 1.
Summary
These two studies compared the MI scale scores for 316 high school students to their
Reading and Math test scores (see Tables 18 and 19).
________________________________________________________________________
25
Table 18. Correlations of Reading Tests with All MI Scales for Studies 1 and 2
________________________________________________________________________
Study 1
Music
.131
Kinesth
.059
Logic
.269(**)
Spatial
. 092
Ling
.331(**)
Interper
.182
Intraper
.273(**)
Nature
.048
Study 2
.189
.080
.212(*)
.191
.498(**)
.180
.337(**)
.094
Note. Study 1, n= 215; Study 2, n= 101. Bold values indicate expected highest correlations.
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
_______________________________________________________________________
The correlations among all MI scales and Reading test scores for both groups are very
similar in both pattern and strength. The lowest (Naturalist) and highest (Linguistic) correlations
are the same for both groups. The values are likewise similar except for the Linguistic scale
where Study 2 group has a stronger correlation at r = .49 vs. r=.33 for Study 1.
_______________________________________________________________________
Table 19. Correlations of Math Tests with All MI Scales for Studies 1 and 2.
_______________________________________________________________________
Study 1
Music
Kinest
-031
.133
Logic
.356**
Study 2
.060
.049
.326**
Spatial
Ling
Interper
Intraper
Nature
.040
.189**
.133
.321**
.001
.100
.260**
.005
.288**
-.051
Note. Study 1, n= 215; Study 2, n= 101. Bold values indicate expected highest correlations.
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
________________________________________________________________________
Again, the correlations among all MI scales and math test scores for both groups are very
similar in both pattern and strength. The lowest two correlations (Naturalist and Musical) and
highest (Logical) correlations are the same for both groups. Significant correlations are also
observed for the Intrapersonal and Linguistic scales. The values are likewise generally similar
26
except Study 1 has a slightly higher correlation between Logical-math main scale and the Math
test (r=.35 vs. r= .32).
________________________________________________________________________
Table 20. Correlations of MI Linguistic Main and Subscales with Reading Tests for Studies 1
and 2.
________________________________________________________________________
Linguistic Expressive
Study 1
.331(**)
.499(**)
Study 2
Rhetoric
.232(**)
.479(**)
.226(**)
.300(**)
Writing
Persuasive
.294(**)
.418(**)
.310(**)
.531(**)
Note.Study 1, n= 215; Study 2, n= 100. Bold values indicate expected highest correlations.
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
________________________________________________________________________
The correlations between Reading test scores and the various Linguistic scales are
generally higher for Study 2 with the strongest values for the Writing/Reading subscale (r = .53)
and the Linguistic main scale (r =.50). These values are well within the range predicted by
theoretical expectations.
________________________________________________________________________
Table 21. Correlations of Logical-math Main and Subscales with Math Tests for Studies 1 and 2.
______________________________________________________________________
Study 1
Study 2
Logicalmath
.356(**)
.326(**)
School
Math
.584(**)
.550(**)
Strategy
Games
.224(**)
.246(*)
Everyday
Math
.376(**)
.370(**)
Problem
Solving
.022
.027
Calculate
.496(**)
.501(**)
Note. Study 1, n= 215; Study 2, n=100 ** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed). Bold indicates highest expected values.
________________________________________________________________________
27
Once again, the strength and pattern of correlations between the various Logical-math
scales and the Math tests are very similar for both groups ranging from r=.02 (Problem Solving)
and r = .58 (School Math). These results are fully aligned with theoretical predictions and it is
noteworthy that the subscale expected to correspond most strongly with Math test is the observed
School Math subscale. The only subscale not significantly correlated is Problem Solving, and the
content of this scale does not pertain to academic skills.
Study 1 found notable significant differences in the mean Logical-math main scale and
School Math subscale for each of the Math test categories. The patterns for both scales are
different, but are ascending in value and generally in appropriate ranges, indicating
differentiation among tested levels of skill (see Table 22).
________________________________________________________________________
Table 22. Mean Logical-Math and School Math Scales by Math Test Categories
________________________________________________________________________
Logical-Math
Math Category
1- Limited
Mean
SD
School Math
Std.
Mean
Deviation
37.72
16.52
20.83
20.25
2- Basic
40.16
15.63
23.21
17.47
3- Proficient
43.42
15.31
32.46
22.25
4- Accelerated
51.14
14.86
54.06
23.30
5- Advanced
59.61
16.23
75.86
21.86
Total
47.89
16.46
44.82
27.68
Note. n= 215. Math Categories. 459 – 551= Advanced (5); 432 – 458= Accelerated (4); 400 –
431= Proficient (3); 379 – 399= Basic (2); 282 – 378= Limited (1) as per state guidelines.
_____________________________________________________________________________
28
Study 1 compared the MI main Linguistic and Writing/Reading scales to the Reading test
and found a strong relationship between tested reading skill levels and the pattern of scale mean
values (see Table 23).
______________________________________________________________________________
Table 23. Mean Linguistic Main and Writing/Reading Scale Scores by Reading Test Categories
______________________________________________________________________________
Linguistic Main
Reading Category
1- Limited
Mean
Writing/Reading
SD
Mean
SD
37.86
12.63
34.56
17.96
2- Basic
38.30
15.35
31.27
15.84
3- Proficiency
46.51
15.93
46.00
23.19
4- Accelerated
51.06
17.06
51.06
20.77
5- Advanced
57.70
16.48
67.28
18.69
Total
49.90
17.09
51.34
22.89
Note. n=212 Reading Categories: 451 – 539= Advanced (5); 428 – 450= Accelerated (4); 400 –
427= Proficient (3); 378 – 399= Basic (2); 258 – 377= Limited (1) as per state guidelines.
___________________________________________________________________________
The ACT Composite score is a combination of the Reading, Math and Science test scores
and is a good representation of student’s estimated IQ score. Table 24 presents the correlations in
descending order between the ACT Composite score and the MI scales theoretically predicted to
correspond with IQ-related skills.
____________________________________________________________________________
Table 24. Correlations of MI Matched Main and Subscales with ACT Composite Test for
Studies 1 and 2.
_____________________________________________________________________________
IQsub
Comp
%
.593**
Schlmat
.467**
Write
Calc
IQest
Expre
Eymth
Persu
Rhet
.455**
.443**
.429**
.414**
.363**
.265**
.264**
29
Stratg
.230*
PrbSl
.077
** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).
Comp% = Composite percentile;
IQsub= IQ subscale mean; Schlmat = School Math; Write = Writing/Reading; Calc= Calculations;
IQest = IQ main scales mean; Expre = Expressive; Eymth = Everyday Math; Pers = Persuasive;
Rhet = Rhetorical; Stratg = Strategy Games; PrbSl= Problem Solving.
______________________________________________________________________________
To test the relationship between MI and estimated IQ, two sets of analyses were
performed. First, the Linguistic and Logical main scales were combined and the mean of the two
was computed (IQest). Then, two subscales theoretically expected to correspond with IQ skills
(School Math and Writing/Reading) were likewise combined to compute an IQsub score (Table
24).
The resulting correlations conform with theoretical expectations, with the IQsub having
the highest (r = .593) followed by the Calculations (r=.443) and then the IQest (r=.429).
Conclusions
The idea of multiple intelligences is an innovative and unique theoretical construct whose
measurement is made difficult due to the creative and contextual basis for each of the identified
intelligences (Gardner, 1983). However, just because standardized tests alone are inadequate to
fully assess a person’s Linguistic intelligence, for example, does not mean that the linguistic
construct is unrelated to nor denies the value of those particular linguistic skills underlying
successful reading test performance, e.g., comprehension, vocabulary, textual decoding, etc. The
same holds true for the Logical-mathematical intelligence and skillful performance on tests of
mathematics, calculations and analytical reasoning.
These two studies of 316 high school students provides consistent evidence supporting
the conclusion that standard reading and math tests measure the convergent, academic
dimensions of the Linguistic and Logical-mathematical intelligences. Likewise, it is evident from
30
these data that g (general intelligence) is accounted for in MI theory as a combined subset of
skills from the academic (School Math and Writing/Reading) aspects of these two intelligences.
A second conclusion supported by this research is that students are able to provide a
“reasonable estimate” of their abilities related to academic performance as measured by reading
and math tests. While not perfectly correlated with test results, students’ descriptions of their
“intellectual disposition” can be a good basis for understanding each student’s unique intellectual
profile.
Since MI theory was introduced in 1983, educators worldwide have searched for an
assessment that would be both valid and useful. Unfortunately, a quick, easy and efficient MI test
that captures the complex and real-world dimensions of the intelligences is not a realistic
possibility. A verbal test may indicate something about students’ reading comprehension skill,
but may be unrelated to his/her oral persuasion, story telling or rhetorical-speaking proclivities.
The MIDAS was created as a thoughtful self-assessment that would provide a process for
describing and measuring a person’s intellectual disposition. Numerous studies have tested the
psychometric characteristics of the MIDAS and its educational utility, but the essential meaning
and validity of the concept of “intellectual disposition” has remained unclear.
The MIDAS proposes that a unique construct like multiple intelligences theory requires
an equally innovative, process-oriented approach to assessment of a person’s academic abilities
and everyday, creative thinking. Thus, the idea of “intellectual disposition” was conceived to
measure a combination of one’s demonstrated skill, active involvement and expressed
enthusiasm. Previous research found that the strength of one’s intellectual disposition
discriminates among appropriately matched careers, educational attainment, teacher ratings,
group participation and avocational interests (Shearer, www.MIResearch.org). Additionally,
31
small-scale studies found that the Logical-mathematical and Linguistic scale scores can be
predictive of individually administered IQ and other academic ability tests (Shearer, 1996).
Criterion-group membership studies found that high achieving students and Mensa group
members differed significantly from others on these two scales (Shearer, 1999).
The research results presented here provide further evidence to clarify our understanding
that “intellectual disposition” also refers to one’s demonstrated success on group-administered
tests of academic achievement. To summarize, intellectual disposition corresponds with tested
abilities, expert ratings, career choice, involvements and enthusiasms. A limitation, however, is
that intellectual disposition is not a “pure” concept. All tests involve error due to instrument
design. A bias of self-reports is that the item responses are filtered through the respondent’s
perspective, so sources of error may include self-concept, emotional status and other
psychological factors inherent in the assessment process (e.g., excessive modesty, selfcriticalness, social desirability, non-compliance, etc.). The MIDAS process-approach provides a
structured procedure for managing and filtering out these influences during Profile interpretation
(Shearer, 1996).
The ACT and state achievement tests involved in these two studies are often used for
“high stakes” decisions affecting the lives of students and school systems alike. It is important to
note that the school-related MIDAS subscales are most highly related to the reading and math
tests while other linguistic and logical abilities are not. When making judgments or decisions it is
important to heed Gardner’s warning about not rushing to judgment to over-generalize about a
person’s abilities based on a single “test” (e.g., “His low score on the math fractions test
indicates that his Logical-mathematical intelligence is poorly developed.”) A student may score
only “average” on a test of calculations, but still display excellent practical, everyday reasoning
32
abilities. The inclusion of the MIDAS assessment with an academic skills test battery provides
valuable information about the students’ abilities in a variety of settings and contexts so that
more “ecologically valid” and nuanced judgments are possible. With this information, students,
teachers and parents can consider how to design learning activities that will make use of MIinspired strategies to maximize full intellectual development as well as reading and math skills,
as appropriate.
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APPENDIX
Appendix 1. Descriptions of the Multiple Intelligences and MIDAS Scales and Subscales
36
Musical: To think in sounds, rhythms, melodies and rhymes. To be sensitive to pitch, rhythm,
timbre and tone. To recognize, create and reproduce music by using an instrument or voice.
Active listening and a strong connection between music and emotions.
Vocal Ability: a good voice for singing in tune and in harmony
Instrumental Skill: skill and experience in playing a musical instrument
Composer: makes up songs or poetry and has tunes on her mind
Appreciation: actively enjoys listening to music of some kind
Kinesthetic: To think in movements and to use the body in skilled and complicated ways for
expressive and goal directed activities. A sense of timing, coordination for whole body
movement and the use of hands for manipulating objects.
Athletics: ability to move the whole body for physical activities such as balancing, coordination
and sports
Dexterity: to use the hands with dexterity and skill for detailed activities and expressive moment
Logical-Mathematical: To think of cause and effect connections and to understand relationships
among actions, objects or ideas. To calculate, quantify or consider propositions and perform
complex mathematical or logical operations. It involves inductive and deductive reasoning skills
as well as critical and creative problem-solving.
Everyday Math: used math effectively in everyday life
School Math: performs well in math at school
Everyday Problem Solving: able to use logical reasoning to solve everyday problems, curiosity
Strategy Games: good at games of skill and strategy
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Spatial: To think in pictures and to perceive the visual world accurately. To think in threedimensions and to transform one's perceptions and re-create aspects of one's visual experience
via imagination. To work with objects effectively.
Space Awareness: to solve problems of spatial orientation and moving objects through space
such as driving a car
Artistic Design: to create artistic designs, drawings, paintings or other crafts
Working with Objects: to make, build, fix, or assemble things
Linguistic: To think in words and to use language to express and understand complex meanings.
Sensitivity to the meaning of words and the order among words, sounds, rhythms, inflections.
To reflect on the use of language in everyday life.
Expressive Sensitivity: skill in the use of words for expressive and practical purposes
Rhetorical Skill: to use language effectively for interpersonal negotiation and persuasion
Written-academic: to use words well in writing reports, letters, stories, verbal memory, reading /
writing
Interpersonal: To think about and understand another person. To have empathy and recognize
distinctions among people and to appreciate their perspectives with sensitivity to their motives,
moods and intentions. It involves interacting effectively with one or more people in familiar,
casual or working circumstances.
Social Sensitivity: sensitivity to and understanding of other people's moods, feelings and point of
view
Social Persuasion: ability for influencing other people
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Interpersonal Work: interest and skill for jobs involving working with people
Intrapersonal: To think about and understand one's self. To be aware of one's strengths and
weaknesses and to plan effectively to achieve personal goals. Reflecting on and monitoring one's
thoughts and feelings and regulating them effectively. The ability to monitor one's self in
interpersonal relationships and to act with personal efficacy.
Personal Knowledge / Efficacy: awareness of one's own ideas, abilities; able to achieve personal
goals
Calculations: meta-cognition "thinking about thinking' involving numerical operations
Spatial Problem Solving: self awareness to problem solve while moving self or objects through
space
Effectiveness: ability to relate oneself well to others and manage personal relationships
Naturalist: To understand the natural world including plants, animals and scientific studies. To
recognize, name and classify individuals, species and ecological relationships. To interact
effectively with living creatures and discern patterns of life and natural forces.
Animal Care: skill for understanding animal behavior, needs, characteristics
Plant Care: ability to work with plants, i.e., gardening, farming and horticulture
Science: knowledge of natural living energy forces including cooking, weather and physics
____________________________________________________________________________
Figure 1. Distribution of Reading Test Scores
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80
Count
60
40
20
0
1
2
3
4
5
Reading Category
__________________________________________________________________________
Figure 2. Distribution of Linguistic Scale Scores
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40
100
80
Count
60
40
20
0
1
2
3
4
5
Linguistic Cat
______________________________________________________________________
_____________________________________________________________________
Figure 3. Distribution of Math Test Scores and Logical-Math Scale Scores
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80
Count
60
40
20
0
1
2
3
Math Category
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4
5
100
80
Count
60
40
20
0
1
2
3
4
5
Logical Category

Gardner (1999) defines intelligence as, “a biopsychological potential to process information
that can be activated in a cultural setting to solve problems or create products that are of value in
a culture” (p. 34).”

Appendix 1. The eight criteria used to identify the intelligences are:
1- identifiable cerebral systems
2- evolutionary history and plausibility
3- identifiable core operation or set of operations
4- meaning that can be encoded in a symbol system
5- a distinct developmental history & mastery or “expert” levels
6- existence of savants, prodigies and exceptional people
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7- evidence from experimental psychological tasks
8- psychometric findings
Another important factor not explicitly included asa criteria is "cross-cultural evidence".
44