Intellectual Styles: Their Associations and Their Relationships to Ability and Personality

INTELLECTUAL STYLES, ABILITY, AND PERSONALITY 1

Intellectual Styles: Their Associations and Their Relationships to Ability and

Personality

Qiuzhi Xie

Faculty of Education, The University of Hong Kong

Department of Applied Social Sciences, The Hong Kong Polytechnic University

Published in

Journal of Cognitive Education and Psychology, Volume 14, Number 1, Page 63-76, 2015.

http://dx.doi.org/10.1891/1945-8959.14.1.63

This copy is the in press version


Abstract

This study investigated the associations among intellectual styles in the three approaches:

cognition-centered, personality-centered, and activity-centered approaches. Field

dependence-independence, psychological types, and learning approaches were respectively

selected as the representatives of the cognition-centered, personality-centered, and

activity-centered styles. This study also explored the relationships between intellectual styles

and ability as well as between intellectual styles and personality. The participants in this study

were 510 students in a Chinese university. The results showed that the three style constructs did

not significantly share common variance, implying that styles in different approaches likely

represent different rather than similar constructs. Also, field dependence-independence strongly

associated with ability, whereas psychological types and learning approaches strongly

associated with personality. This suggested that different style constructs relate to ability and

personality to different degree: cognition-centered styles may closely relate to ability, whereas

personality-centered and activity-centered styles may highly relate to personality.

Keywords: Intellectual styles; ability; personality; field dependence-independence;

psychological types; learning approaches


“Intellectual style” is an envelope term that refers to all the existing style concepts, such

as thinking style, learning style, and cognitive style. Zhang and Sternberg (2005) defined

intellectual style as “one’s preferred way of processing information and dealing with tasks”

(Zhang & Sternberg, 2005, p.2). To this day, a number of style constructs have been put forward,

such as Witkin’s (1962) cognitive style of field dependence-independence (FDI) and Kolb’s

(1976) learning style. Scholars have proposed different style concepts with their own

perspectives and disregarded others’ work. This resulted in the confused understanding of style

concepts and the declined research on styles in the 1970s. After 1980, scholars have proposed

several models to categorize the existing style constructs.

Grigorenko and Sternberg’s (1995) model classifies style constructs into three

approaches: cognition-centered, personality-centered, and activity-centered approaches.

Cognition-centered styles share similarities with ability, because most of these styles can be

measured through maximal performance. A typical example is Witkin’s (1962) field

dependence-independence. Field independence indicates the tendency to make judgments based

on one’s own perception or thinking, whereas field dependence indicates the tendency to make

judgments by referring to external cues.

Personality-centered styles are ones’ typical preferences rooted in personality. A

typical example is the theory of psychological types (Jung, 1923; Myers & McCaulley, 1985)

that identifies four basic preference indices: extraversion-introversion (EI), sensing-intuition

(SN), thinking-feeling (TF), and judgment-perception (JP). EI refers to one’s tendency to focus

on the outside world (E) versus on the inside self (I). SN refers to one’s mental processes based

on observable facts and happenings (S) versus on meanings and possibilities (N). TF refers to


one’s decision making based on logical consequences (T) versus on values (F). JP refers to

one’s tendency to be organized and purposeful (J) versus to be flexible (P).

Activity-centered styles refer to ones’ preferences in specific activities. Grigorenko and

Sternberg (1995) argued that activity-centered styles arise from both cognition and personality.

A typical example is Biggs’ (1987) learning approaches theory. Students’ learning approaches

can be classified as the deep learning approach and the surface learning approach (Biggs,

Kember, & Leung, 2001). The former indicates the inclination to emphasize thorough

understanding of what has been learned, whereas the latter indicates the inclination to learn by

rote.

Zhang and Sternberg (2005) reviewed a large number of studies on the relationships

among different style constructs, and they found that styles in the same approaches are strongly

associated with one another. Grigorenko and Sternberg (1995) hypothesized that

cognition-centered styles are more closely associated with ability, whereas personality-centered

styles are more closely associated with personality.

A current influential model that is relevant to this study is Zhang and Sternberg’s (2005)

threefold model. This model classifies styles into Types I-III according to their characteristics.

Styles that denote the preferences for low degree of structure, cognitive complexity,

nonconformity, and autonomy are classified as Type I. Styles that denote the preferences for

high degree of structure, cognitive simplicity, conformity, and authority are categorized as Type

II. Zhang and Sternberg argued that Type I styles are usually more adaptive than Type II styles.

Styles that may take on the characteristics of either Type I or Type II styles are labeled as Type

III, and whether Type III styles are generally positive or negative depend on situational


contingency. Zhang and Sternberg hypothesized that Type I styles are positively related to one

another and so are Type II styles. A few empirical findings supported their hypothesis (e.g.,

DeBell & Crystal, 2005).

A critical controversial issue raised in the threefold model is whether different style

constructs are distinct or similar. A number of studies have investigated the correlations

between different style constructs (e.g., DeBell & Crystal, 2005; Sadler-Smith, 1997). The

current study investigates the relationships among field dependence-independence (FDI; Witkin,

1962), psychological types (Jung, 1923; Myers & McCaulley, 1985), and learning approaches

(Biggs, 1987). So far as I know, no study has explored the relationships between psychological

types and learning approaches as well as between FDI and learning approaches. However,

several scholars have explored the relationships between FDI and psychological types. They

found that field independence was positively associated with intuition and perception, whereas

negatively associated with sensing and judgment (e.g., DeBell & Crystal, 2005; Carey, Fleming,

Roberts, 1989). Schmidt and Cutcheon (1988) investigated the relationships between FDI and

the type combinations. They reported that people with the ENTP and INFP type combinations

were more field independent than people with the ESFP, ISFJ, and ESFJ type combinations.

Furthermore, a long-lasting challenge in the style field is the unclear distinctions of

intellectual styles from ability and personality (e.g., Zhang, Sternberg, & Rayner, 2012).

Because many cognition-centered styles are examined via maximal performance, scholars have

debated as to whether these style constructs are competence or preference variables. Also,

empirical research has consistently reported the significant associations between

cognition-centered styles and abilities, in particular the positive association between field


independence and non-verbal abilities (e.g., McKenna, 1984; Zhang, 2004). Therefore, some

scholars argued that a number of cognition-centered styles refer to abilities or partial abilities

and partial styles (e.g., Davis, 1991; McKenna, 1984). Other scholars argued that

cognition-centered styles are different from ability (e.g., Furnham, 2012; Messick, 1996; Zhang

& Sternberg, 2006). First, abilities are unipolar, whereas styles are bipolar. Two corresponding

styles usually have the opposite characteristics. Second, ability is shown in one domain,

whereas a style can be shown in several domains. For example, FDI pertains to spatial ability as

well as social orientation. Third, abilities are value-directional: having higher ability is always

an advantage. Styles are value-differentiated: whether a style is positive or negative may

depend on situations.

Researchers have also investigated the relationships between ability and the styles in the

personality-centered and activity-centered approaches. Regarding the relationships between

ability and psychological types, a number of researchers found that higher scores on ability tests

were positively related to intuition and negatively related to sensing (e.g., Furnham, Dissou,

Sloan, & Chamorro-Premuzic, 2007; Furnham, Moutafi, & Paltiel, 2005). The findings on the

relationships between abilities and learning approaches are not consistent. Some studies showed

that these two constructs were not related (e.g., Furnham, Monsen, & Ahmetoglu, 2009). Other

studies showed that higher scores on ability tests were positively related to the deep learning

approach, whereas negatively related to the surface learning approach (e.g.,

Chamorro-Premuzic & Furnham, 2008).

Scholars also have addressed the style-personality relationships for a long time. Messick

(1994) argued that styles bridge personality and cognition. Furnham (2012) argued that styles


have less biological foundation than personality. Moreover, some scholars emphasized

personality’s influence on styles (e.g., Furnham, 1995), and others argued that the

style-personality relationships are bidirectional and interactive (e.g., Kogan & Block, 1991).

The relationships between personality and intellectual styles have been extensively

investigated. McKenna (1983) reviewed studies on the relationships between FDI and Eysenck

and Eysenck’s (1975) personality dimensions and concluded that the relationship between the

two constructs is rather week. Furthermore, some studies suggested that FDI is likely to be

associated with extraversion-neuroticism/psychoticism combination. For example, Glicksohn,

Naftuliev, and Golan-Smooha (2007) found that field independence was positively related to

the combination of extraversion and high psychoticism as well as the combination of

introversion and low psychoticism.

The findings on the relationships between psychological types and the Big Five

personality factors are quite consistent. The extraverted personality strongly related to the

preference index of extraversion-introversion (EI). Openness to experience positively correlated

with intuition and perception, whereas negatively correlated with sensing and judgment.

Conscientiousness correlated positively with judgment and negatively with perception.

Agreeableness correlated positively with feeling and negatively with thinking (e.g., Furnham,

1996; McCrae & Costa, 1989; Tobacyk, Livingston, Robbins, 2008). Based on Eysenck and

Eysenck’s (1975) personality model, researchers found that Eysenck’s extraversion and

neuroticism related to the EI index. Neurotic people were more likely to have the introverted

attitude, rather than the extraverted attitude. In addition, psychoticism positively related to

intuition and perception, whereas negatively related to sensing and judgment (e.g., Francis,


Craig, & Robbins, 2007; Furnham, Jackson, Forde, & Cotter, 2001).

The relationships between learning approaches and personality have been widely

investigated. Researchers consistently found that the deep learning approach was positively

associated with extraversion, openness to experience, and conscientiousness, whereas

negatively associated with neuroticism. The surface learning approach was correlated positively

with neuroticism and negatively with openness to experience (e.g., Chamorro-Premuzic &

Furnham, 2009; Shokri, Kadivar, Farzad, & Sangari, 2007). Several studies also showed that

the surface learning approach was positively correlated with extraversion, whereas negatively

correlated with agreeableness and conscientiousness (e.g., Shokri, et al., 2007; Zhang, 2003). In

addition, researchers found that learning approaches and personality were overlapping to some

degree (e.g., von Stumm & Furnham, 2012; Zhang, 2003).

Because a considerable number of studies demonstrated significant relationships

between styles and personality (e.g., Francis et al., 2007; Shokri et al., 2007), some researchers

argued that the measurement of intellectual styles can be included in personality tests (e.g.,

Jackson & Lawty-Jones, 1996). However, other scholars argued that styles have their

uniqueness (e.g., Zhang & Sternberg, 2005) and assessing styles along with personality is

necessary (e.g., Riding & Wigley, 1997; Zhang & Sternberg, 2006).

Although scholars have extensively studied style relationships as well as style-ability

and style-personality relationships, they have not investigated these relationships based on a

model that classifies styles. Investigating the relationships among styles in different categories

may clarify as to whether these constructs labeled as “styles” are different or similar. Assessing

whether different style constructs are associated with ability and personality to different degree


may help clarify the long-standing issue of style-ability and style-personality relationships.

Furthermore, intellectual styles, ability, and personality are important variables that

address individual differences. Researchers have widely explored the prediction of styles,

ability, and personality for individuals’ behaviors and educational outcomes (e.g., Furnham et

al., 2009; Xie, Gao, & King, 2013). Investigating the associations among different style

constructs as well as among styles, ability, and personality may also help researchers and

educators better understand what personal factors predict behaviors and educational outcomes.

For example, if one style construct is only marginally related to personality, the style may have

unique contribution to outcome variables along with personality. In contrast, if one style

construct is substantially overlapping with personality, the predictive power of this style

construct for outcome variables is likely to be explained by personality to a considerable

degree.

The current study investigates whether styles in different approaches are similar or

different. It also looks into whether different style constructs relate to ability and personality to

different degree. Witkin’s (1962) FDI, Jung’s (1923) psychological types, and Biggs’ (1987)

learning approaches respectively represent cognition-centered, personality-centered, and

activity-centered styles in this study. These three style constructs have been extensively studied

(e.g., Chamorro-Premuzic & Furnham, 2009; Leary, Reilly, & Brown, 2009; Smith & Cage,

2000) and are strongly associated with other style constructs in their approaches (e.g.,

Sadler-Smith, 1997; Zhang & Sternberg, 2005).

It is hypothesized that field independence, the intuitive and perceptive processes, and

the deep learning approach are positively related, because these styles are labeled as Type I.


Field dependence, the sensing and judging processes, and the surface learning approach are

positively related. These styles are labeled as Type II. This hypothesis is based on Zhang and

Sternberg’s (2005) argument that Type I styles positively associate with one another and so do

Type II styles. Moreover, FDI most closely relates to ability, whereas psychological types and

learning approaches strongly relate to personality. Field independence relates to higher score on

the ability test. Neuroticism relates positively to the surface learning approach and negatively to

the deep learning approach. Extraversion positively relates to the deep learning approach and

the extraverted attitude, whereas negatively relates to the surface learning approach and the

introverted attitude. Openness to experience positively relates to the deep learning approach as

well as the intuitive and perceptive processes. Openness to experience also negatively relates to

the surface learning approach as well as the sensing and judging processes. Agreeableness

relates positively to the feeling process and negatively to the thinking process.

Conscientiousness positively relates to the deep learning approach and the judging process,

whereas negatively relates to the surface learning approach and the perceptive process. The

hypotheses are based on the conceptual similarities between these constructs as well as the

empirical findings (e.g., Chamorro-Premuzic & Furnham, 2009; McCrae & Costa, 1989;

McKenna, 1984).

Method

Participants

The participants in this study were 510 students between ages 16 to 23 years (M=19.20,

SD=1.10) in a Chinese university. Among these students, 123 were males, 361 were females,

and 26 did not indicate their gender; 278 students were Science majors, 212 students were


Humanity majors, and 20 students did not indicate their majors. There were 263 Year 1 students,

241 Year 3 students, and the remaining 6 students did not indicate their year of study.

Instruments

The Group Embedded Figures Test (GEFT; Witkin, Oltman, Raskin, & Karp,

1971)

The GEFT (Witkin et al., 1971) examines FDI. In the testing session, eight simple

figures and twenty-five complex figures are presented. Participants are required within time

limitation to discover as many embedded simple figures in the complex ones as possible. Each

correct answer merits one point. This test requires participants to overcome the influence of the

complex background to get the correct answers. Field-dependent people are more likely than

field-independent people to be influenced by external irrelevant information. Therefore, a high

score in the GEFT indicates the style of field independence, whereas a low score indicates the

style of field dependence.

A modified Chinese version of the GEFT (S. Y. Chen, Yang, & Gao, 1989) was used.

This version is slightly different from the original one. Several figures were modified to

increase difficulty. Each correct answer on the easy level merits one point, a correct answer on

the medium level merits six points, and a correct answer on the difficult level merits seven

points. This version comprises two sections. The first section contains seven items and is timed

two minutes, whereas the second section contains eighteen items and is timed nine minutes. A

number of studies showed that this Chinese version of the GEFT has good psychometric

properties (e.g., S. Y. Chen et al., 1989; Zhang, 2004).

The Myers-Briggs Type Indicator (MBTI; Myers & McCaulley, 1985)


The MBTI measures psychological types and contains four scales on the four preference

indices: Extraversion-Introversion (EI), Sensing-Intuition (SN), Thinking-Feeling (TF), and

Judgment-Perception (JP). Each scale is composed of two subscales on the two opposite types

(i.e., E and I, S and N, T and F, and J and P). Form G (the standard version) of this survey was

used, which contains 95 items on the four scales. Myers and McCaulley (1985) estimated that

the split-half reliability coefficients for the scales of Form G range from .77 to .90 and the

test-retest reliability coefficients range from .48 to .87. A number of studies reported that the

Chinese version of this questionnaire is of good psychometric properties (e.g., J. Chen, Tian,

Miao, & Chia, 2009; Miao, Huangfu, Chia, & Ren, 2000).

Dichotomic preference scores and continuous scale scores can be calculated1 (Myers &

McCaulley, 1985). Low continuous scale scores indicate the preferences for E, S, T, and J,

whereas high scores indicate the preferences for I, N, F, and P.

The Revised Two Factor Version of Study Process Questionnaire (R-SPQ-2F; Biggs

et al., 2001)

The R-SPQ-2F includes 20 items on two scales: the deep learning approach (DA) and

the surface learning approach (SA) scales. Each scale comprises the learning motivation and the

learning strategy subscales. Therefore, the four subscales are about the surface learning

motivation (SM), the surface learning strategy (SS), the deep learning motivation (DM), and the

deep learning strategy (DS). A 5-point Likert scale (1= never or only rarely true of me; 5 =

1 For E, S, T, and J, the preference score is 2 × (higher score – lower score) – 1; for I, N, F, and P, the preference

score is 2 × (higher score – lower score) + 1. For example, if the E score is 9 and the I score is 18, the preference

score on EI is 2 × (18 – 9) + 1 equals I 19. If the preference score is on any side of E, S, T, and J, the continuous

scale score is 100 – preference score. If the preference score is on any side of I, N, F, and P, the continuous score is

100 + preference score. For example, if the preference score is I 19, the continuous score on EI is 119.


always or almost always true of me) is used for scoring. The score on each learning approach

scale is the sum of the scores on its learning motivation and learning strategy subscales. Biggs

et al. (2001) reported that the Cronbach alpha coefficients were .73 for DA scale and .64 for SA

scale and they ranged from .57 to .72 for the four subscales. This questionnaire was translated

in Chinese by the current author and back translated by another researcher.

The Raven’s Advanced Progressive Matrices (APM; Raven, Court, & Raven, 1985)

The APM assesses non-verbal reasoning ability, which is referred to as fluid intelligence.

This test presents multiple choice questions and requires participants to identify the missing

element that completes a pattern. The test is composed of two sets of items. Set I includes 12

items and is used to make participants be familiar with the test. Set II includes 36 items, and the

difficulty level of these items increases gradually.

A short form of the APM (Arthur & Day, 1994) was used to reduce the testing time. The

short form contains 12 items selected from the Set II. The selection of these items was based on

item-total correlation, item difficulty, and the Cronbach alpha coefficient after the deletion of

each item. Arthur and Day (1994) reported that the correlation coefficient between the original

longer version and the revised short one was .66 and the structure of the short form well

represented that of the original longer one.

The NEO Five-Factor Inventory-3 (NEO-FFI-3; McCrae & Costa, 2007)

The NEO-FFI-3 assesses personality based on the Big Five model. It has 60 items on the

five personality scales: Neuroticism, Extraversion, Openness to experience, Agreeableness, and

Conscientiousness. A 5-point Likert scale (from strongly disagree to strongly agree) is used for

scoring. Costa and McCrae (2008) contented that this questionnaire has good reliability and


construct validity. Researchers also reported good psychometric properties of the NEO-FFI

(Costa & McCrae, 1992) in the Chinese version (e.g., Zhang, 2003). The several revised items

in the NEO-FFI-3 were translated by the current author and back translated by another

researcher.

Data analysis

First, mean scores and standard deviation were calculated for each variable. Cronbach

alpha coefficients were calculated for these instruments, except for the ability test. Split-half

coefficient (split items by odd number and even number) was calculated for the short form of

the APM, because the overall difficulty of the odd number items and the even number items is

similar. Second, partial correlations were conducted to explore the relationships among the

three style constructs and among styles, ability, and the personality, controlling for gender, age,

year of study, and academic disciplines. Last, exploratory factor analysis (EFA) was conducted

to explore the shared variance among the three style constructs, as well as among intellectual

styles, ability, and personality. The extraction method for EFA was Unweighted Least Squares,

and the rotation method was Promax with Kaiser Normalization (Kappa = 4).

Results

The relationships among FDI, learning approaches, and psychological types

The results (see Table 1) show the correlations between learning approaches and the JP

preference index: the judging process positively correlated with the deep learning approach and

negatively correlated with the surface learning approach; the perceptive process correlated with

learning approaches in an inverse way. Moreover, the deep learning strategy correlated


positively with the thinking process and negatively with the feeling process.

The exploratory factor analysis shows that the three style constructs loaded on three

different factors (see Table 2). The SN and JP indices loaded on the first factor. Learning

approaches loaded on the second factor. FDI loaded on the last factor.

The relationships between intellectual styles, ability, and personality

The results show that ability significantly correlated with FDI. Those who scored higher

on the ability test tended to be more field independent. Psychological types and learning

approaches were not correlated with ability.

Personality correlated with learning approaches and psychological types. Extraversion,

openness to experience, and conscientiousness correlated positively with the deep approach to

learning and negatively with the surface approach to learning. Agreeableness also correlated

negatively with the surface learning approach. Neuroticism correlated positively with the

surface learning approach and negatively with the deep learning approach. The extraverted

personality strongly correlated with the EI preference index. Neuroticism correlated positively

with the introverted attitude and negatively with the extraverted attitude. Openness to

experience correlated positively with the intuitive process and negatively with the sensing

process. Agreeableness correlated positively with the feeling process and negatively with the

thinking process. Conscientiousness positively correlated with the preferences for extroversion,

thinking, and judgment, whereas negatively correlated with the preferences for introversion,

feeling, and perception. Personality was not correlated with FDI. These results are presented in

Table 1.


The exploratory factor analysis (see Table 3) suggests that personality had shared

variance with psychological types and learning approaches, whereas ability and FDI had shared

variance. These variables loaded on six factors. The first factor indicated extraversion: the

extraverted personality loaded positively, whereas the EI index loaded negatively. Learning

approaches, openness to experience, and conscientiousness loaded on the second factor: the

deep learning approach and the two personality factors loaded positively, whereas the surface

learning approach loaded negatively. The SN and JP indices loaded heavily and positively on

the third factor, whereas conscientiousness loaded negatively on this factor. The TF index and

agreeableness loaded positively on the fourth factor. FDI and ability loaded heavily and

positively on the last factor.

Discussion

This study demonstrates the relationships among FDI, psychological types, and learning

approaches. The deep learning approach positively related to the thinking process and

negatively related to the feeling process. This seems to be reasonable: students with the thinking

process are more interested to find basic truth and principle; therefore, they are more likely to

be deep learners. The relationships between learning approaches and the JP index were contrary

to the hypothesis. Students with the judging process were more likely to use the deep learning

approach, whereas students with the perceptive process were more likely to use the surface

learning approach. This is likely because both the deep learning approach and the judging

process positively associated with conscientiousness. Students with the judging process are

more dutiful and, thereby, more likely to be deep learners. The findings do not support Zhang

and Sternberg’s (2005) hypothesis that Type I styles are positively related to one another and so


are Type II styles.

The results also suggest that FDI, learning approaches, and psychological types did not

significantly share common variance, indicating that these style constructs are largely

independent rather than overlapping. The three style constructs are highly associated with the

other styles in the same approaches (e.g., Sadler-Smith, 1997; Zhang & Sternberg, 2005).

Therefore, they can be regarded as the representatives in their approaches. The findings imply

that although styles in different approaches may be correlated to some degree, they likely

represent different rather than similar constructs.

The results support our hypothesis that FDI mostly associate with ability, whereas

psychological types and learning approaches highly associate with personality. FDI and ability

were overlapping. Personality was overlapping with psychological types and learning

approaches. The EI index was overlapping with the extraverted personality, suggesting that

outgoing people are more interested in the outside world, rather than the inner self. The SN and

JP indices shared variance with conscientiousness, suggesting that conscientious people tend to

be down to earth, organized and purposeful, rather than imaginative and flexible. The TF index

and agreeableness had common variance, suggesting that agreeable people tend to make

decisions by weighting what people care about, rather than by logical analysis. Learning

approaches shared variance with openness to experience and conscientiousness, indicating that

those who are intellectually curious, open-minded, and dutiful are more likely to use the deep

learning approach, rather than the surface learning approach. These results are justifiable and

indicate the conceptual similarities between the constructs investigated in this study. These

findings imply that styles are highly likely rooted in stable and enduring traits.


Cognition-centered styles may strongly associate with ability and may be partially explained by

ability. Personality-centered and activity-centered styles may highly relate to personality and

may be partially explained by personality. However, our findings do not indicate that FDI is

identical to ability or psychological types are identical to personality. Styles likely have the

unique variance that cannot be explained by either ability or personality. In addition, these

findings indicate that Grigorenko and Sternberg’s (1995) model that classifies styles is valid.

The current study has practical significance. A number of researchers and educators are

interested in predicting people’s behaviors and educational outcomes from intellectual styles,

ability, and personality. This study suggests that we may not infer as to whether a style

construct predicts an outcome variable from knowing the predictive power of another style

construct in a different approach. Furthermore, the current study also suggests that the

prediction of some styles for outcome variables may be partially explained by ability or

personality. For example, if we find that learning approaches predict academic achievement, we

know that personality also likely predicts academic achievement, because personality partially

explains students’ learning approaches. However, this study also implies that styles have their

unique variance; therefore, their predictive power has the potential to be beyond that of

personality. This implication is consistent with some earlier findings. For instance, several

studies suggested that the predictive power of learning approaches for academic achievement

exceeds the predictive power of personality (Furnham, 2011).

This study has at least two limitations. First, the study merely selects one style construct

in each approach. Therefore, the theoretical implications on style associations and styles’

relationships to ability and personality may not be convincible enough. Future studies that


involve other style constructs in each approach are necessary to investigate style associations as

well as style-ability and style-personality relationships. Second, only Raven’s Matrices is used

as the ability test in the current study. Despite that the non-verbal reasoning ability is widely

investigated as fluid intelligence, using other intelligence tests can provide a more holistic

picture of abilities. Therefore, future studies should involve more than one ability test to look

into the style-ability relationship.


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Table 1 Descriptive statistics and partial correlations among FDI, learning approaches, psychological types, ability, and personality (Controlling for gender, age, year

of study, and academic majors)

M SD Reliability

Coefficient

FDI DA SA DM DS SM SS E I S N T F J P

FDI 79.38 23.85 .81 1.00

DA 2.66 .70 .84 -.01 1.00

SA 2.49 .65 .77 .15 -.22** 1.00

DM 2.62 .76 .70 -.02 .94** -.24** 1.00

DS 2.70 .73 .70 -.01 .94** -.17** .76** 1.00

SM 2.53 .69 .58 .15 -.18** .90** -.20** -.13** 1.00

SS 2.44 .75 .65 .11 -.22** .91** -.22** -.17** .63** 1.00

E 13.44 6.08 .79 .13 .10 -.06 .11 .09 .00 -.10 1.00

I 12.30 6.74 .81 -.12 -.10 .09 -.11 -.10 .02 .14 -.96** 1.00

S 16.78 5.16 .60 -.08 -.04 -.01 -.08 .00 -.05 .04 -.08 .08 1.00

N 11.28 4.15 .50 .01 .10 .01 .13 .06 .04 -.03 .04 -.04 -.83** 1.00

T 13.20 5.38 .64 .00 .18** -.05 .14 .21** -.06 -.03 -.11 .10 .23** -.13 1.00

F 11.12 4.32 .60 -.05 -.18** .07 -.13 -.20** .08 .05 .16** -.13 -.24** .18** -.83** 1.00

J 17.87 5.56 .76 -.04 .27** -.27** .24** .26** -.28** -.20** -.01 .00 .43** -.40** .20** -.22** 1.00

P 11.63 5.46 .74 .06 -.25** .30** -.22** -.23** .30** .23** -.01 .02 -.41** .35** -.17** .21** -.95** 1.00

Ability 8.02 2.42 .65 .27** -.04 .10 -.02 -.04 .07 .11 .02 -.03 -.01 -.01 -.01 -.07 -.04 .02

Neuro 1.89 .55 .79 -.09 -.20** .21** -.23** -.15** .14** .23** -.30** .29** .13 -.08 -.02 .01 -.05 .09

Extra 2.25 .49 .70 .06 .22** -.17** .23** .19** -.11 -.18** .65** -.64** -.07 .03 -.01 .04 .11 -.13

Open 2.39 .56 .63 .12 .41** -.15** .41** .36** -.13 -.14** .14 -.14 -.33** .30** .02 -.03 -.01 -.01

Agr 2.57 .43 .63 .01 .05 -.19** .08 .01 -.15** -.18** .14 -.13 -.06 .01 -.21** .25** .09 -.11

Con 2.34 .54 .82 .01 .50** -.24** .45** .47** -.18** -.25** .22** -.19** .13 -.10 .16** -.16** .47** -.47**

Notes. Split-half coefficient was calculated for the ability scale; Cronbach alpha coefficients were calculated for the other (sub) scales. FDI = Field

dependence-independence, DA = Deep learning approach, SA = Surface learning approach, DM = Deep learning motivation, DS = Deep learning strategy, SM

= Surface learning motivation, SS = Surface learning strategy, E = Extraverted attitude, I = Introverted attitude, S = Sensing process, N = Intuitive process, T =

Thinking process, F = Feeling process, J = Judging process, P = Perceptive process, Neuro = Neuroticism, Extra= Extraversion, Open = Openness, Agr =

Agreeableness, Con = Conscientiousness.

** p < .01.


Table 2 Exploratory factor analysis of FDI, learning approaches, and psychological types

Factors

1 2 3

FDI .43

DA -.64

SA .56

EI

SN 1.00

TF

JP .43

Variance explained (%) 24.448 19.207 15.590

Cumulative (%) 24.448 43.654 59.244

Eigenvalues 1.711 1.344 1.091

Notes. FDI = Field dependence-independence, DA = Deep learning approach, SA = Surface

learning approach.

Extraction Method: Unweighted Least Squares.

Rotation Method: Promax with Kaiser Normalization.

Rotation converged in 4 iterations.

KMO = .50, p < .000. Variables with factor loadings of less than |.40| are omitted.


Table 3 Exploratory factor analysis of intellectual styles, ability, and personality

Factors

1 2 3 4 5

FDI .65

DA .73

SA -.44

EI -.77

SN .70

TF .42

JP .69

Ability .52

Neuro

Extra .90

Open .64

Agree .84

Con .42 -.46

Variance explained (%) 20.101 14.747 11.960 10.064 8.666

Cumulative (%) 20.101 34.848 46.808 56.872 65.538

Eigenvalues 2.613 1.917 1.555 1.308 1.127

Notes. FDI = Field dependence-independence, DA = Deep learning approach, SA = Surface

learning approach, Neuro = Neuroticism, Extra= Extraversion, Open = Openness, Agr =

Agreeableness, Con = Conscientiousness. Extraction Method: Unweighted Least Squares.

Rotation Method: Promax with Kaiser Normalization.

Rotation converged in 6 iterations.

KMO = .62, p < .000. Variables with factor loadings of less than |.40| are omitted.

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Intellectual Styles: Their Associations and Their Relationships to Ability and Personality

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