Thinking Styles And Emotions
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The Journal of Psychology, 2008, 142(5), 497–515 Copyright © 2008 Heldref Publications
Thinking Styles and Emotions LI-FANG ZHANG University of Hong Kong
ABSTRACT. This study aimed to explore the relationship between thinking styles and emotions among university students in Hong Kong. Participants were 99 2nd-year students (23 men and 76 women) who responded to the Thinking Styles Inventory–Revised (TSI-R), based on R. J. Sternberg’s (1988) theory of mental self-government, and to the Iowa Managing Emotions Inventory (IMEI), based on A. Chickering’s (1969) theory of psychosocial development. Results indicated not only that thinking styles were associated with emotions but also that thinking styles had predictive power for emotions beyond age. The author discusses implications of these findings for faculty members and studentdevelopment educators. Keywords: Chinese university students, emotions, thinking styles
INTELLECTUAL STYLES IS AN ALL-ENCOMPASSING TERM for constructs such as cognitive styles, learning styles, thinking styles, and teaching styles and refers to people’s preferred ways of processing information and dealing with tasks (Zhang & Sternberg, 2006). It has been established that intellectual styles matter in various domains of a student’s life, including his or her academic achievement (Bagley & Mallick, 1998; Mansfield, 1998), cognitive development (Globerson & Zelniker, 1989; Westreich, Ritzler, & Duncan, 1997), career development (Hilliard, 1995; Morgan, 1997), and personality traits (Deng, Li, & Zhang, 2000; Saleh, 1998). I considered the present study to be related to the final line of the aforementioned investigations (i.e., research on the relation between intellectual styles and personality traits). In literature, some scholars consider constructs such as anxiety, assertiveness, depression, frustration, happiness, and optimism as personality traits (e.g., Costa & McCrae, 1992; Eysenck & Eysenck, 1964). Other scholars, however, refer to such constructs as emotional competence (e.g., Ciarrochi, Deane, The author is grateful to the Committee on Research and Conference Grants, administered by the University of Hong Kong, for funding this project. The author’s special thanks go to all the research participants. Address correspondence to Li-fang Zhang, Faculty of Education, The University of Hong Kong, Pokfulam Road, Hong Kong; [email protected] (e-mail). 497 497
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Wilson, & Rickwood, 2002), emotional intelligence (e.g., Mayer, Salovey, Caruso, & Sitarenios, 2001), mental health (Beck, Steer, & Brown, 1996), subjective wellbeing (Diener, Suh, Lucas, & Smith, 1999), emotions, (Mortenson, 2006; Spangler, Pekrun, Kramer, & Hofmann, 2002) or emotionality (e.g., Hayden, Klein, Durbin, & Olino, 2006). This study adopts the term emotions to achieve consistency with those used in the theoretical framework on which one of the inventories employed in this study stands: the emotions dimension defined in Chickering’s (1969; Chickering & Reisser, 1993) theory of psychosocial development. Furthermore, this construct will be examined against thinking styles, one of the specific style constructs under intellectual styles. Intellectual Styles and Emotions Researchers have investigated the relation between intellectual styles and emotions for more than three decades. However, unlike research on the more general cognitive–affective personality system (e.g., Mischel & Ayduk, 2004; Mischel & Shoda, 1999), research on intellectual styles and emotions has been unfruitful. Campbell and Douglas (1972) conducted the earliest study in which researchers examined children’s responses to and level of optimism toward the threat of frustration in relation to their intellectual styles, on the basis of Witkin’s (1962) field-dependent/independent styles and Kagan’s (1965) reflective and impulsive styles. Compared with children who scored higher on field dependence and impulsivity, children who scored higher on field independence and reflectivity displayed higher levels of optimism toward frustration. I conducted a systematic search on the PsycINFO database (2007), entering two sets of terms in their maximum possible combinations. The first set included emotions, emotional competence, emotional intelligence, emotionality, mental health, and subjective well-being. The second set included cognitive styles, intellectual styles, learning styles, and thinking styles. This search resulted in five additional entries. These studies, however, were all published after the mid 1990s. The first study was conducted in the Netherlands. Jong, Merckelbach, and Nijman (1995) found that among 70 undergraduate students, those with a holistic mode of thinking (i.e., right-brained dominance) demonstrated higher levels of anxiety than did those with the analytic mode of thinking (i.e., left-brained dominance). Riding and Wigley (1997) examined Riding and Cheema’s (1991) two stylistic dimensions (verbal–imagery, analytic–wholistic) against psychoticism. The authors concluded that the wholistic style was highly associated with psychoticism. Gadzella (1999) conducted a third study and administered the Human Information Processing Survey (Torrance, Taggart, & Taggart, 1984) and the 16 Personality Factor Questionnaire (Cattell, Cattell, & Cattell, 1978) to 55 students enrolled in undergraduate psychology classes at a Midwestern university. Results
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indicated that students with an analytic mode of thinking displayed higher levels of self-control than did students with a holistic mode of thinking, and that students comfortable with either the analytic or the holistic mode of thinking scored higher on the anxiety scale than did students with an integrative mode of thinking (i.e., whole-brained thinking). Deng et al. (2000) investigated the relations among field-dependence/ independence to assertiveness. Their results showed that the field independent participants scored significantly higher on assertiveness than did the field dependent ones. Hayden et al. (2006) examined the links of positive and negative emotions at age 3 to depressive attributional styles at age 7 years. Although little evidence was obtained for a relationship between negative emotions and depressive attributional styles, lower positive emotions at age 3 predicted greater helplessness in the interpersonal domain. There are at least two reasons to continue this investigation. First, the majority of the existing studies were based on style models that describe two bipolar styles (e.g., field-dependent versus field-independent; impulsive versus reflective). The present research adopted a style model much broader in scope in that it describes multiple stylistic dimensions: Sternberg’s (1988, 1997) theory of mental self-government. Second, the emotions examined against intellectual styles have been isolated and not those deemed important to a specific target group. The present study examines five types of emotions addressed in Chickering’s (1969; Chickering & Reisser, 1993) theory of psychosocial development targeted to university students: happiness, attraction, anger, depression, and frustration. These emotions were given special attention in Chickering’s work. According to him, these emotions are important to young university students because recognizing and effectively managing them would positively contribute to their formation of identity—a critical component of psychosocial development. Theory of Mental Self-Government and Its Research Sternberg (1988, 1997) has contended that just as there are different ways of governing a society, there are different ways in which people use their abilities, which are known as thinking styles. According to Sternberg, 13 thinking styles fall under five dimensions: function, form, level, scope, and leaning. Based on both empirical data and theoretical arguments (Kogan, 1980; Messick, 1996), Zhang (2003) reconceptualized the 13 thinking styles into three types. Type I thinking styles include the legislative, judicial, hierarchical, global, and liberal styles, and tend to be more creativity-generating and denote higher levels of cognitive complexity. Type II thinking styles include the executive, local, monarchic, and conservative styles, and suggest a norm-favoring tendency and denote lower levels of cognitive complexity. Type III thinking styles include
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the anarchic, oligarchic, internal, and external styles and may manifest the characteristics of either Type I or Type II thinking styles, depending on the stylistic demands of a task. In Appendix A, the main characteristics of each of the 13 thinking styles are described. The notion of three types of intellectual styles (Zhang & Sternberg, 2005) has been developed to accommodate additional style labels such as fieldindependent/dependent styles and reflective/impulsive styles. For example, along with Type I thinking styles, the field-independent and reflective styles were classified as Type I intellectual styles. Along with Type II thinking styles, the field-dependent and impulsive styles were classified as Type II intellectual styles. Moreover, along with Type III thinking styles, the feeling and integrative styles were classified as Type III intellectual styles. Individual styles from 10 theoretical models were organized into the three types of intellectual styles. In Appendix B, the specific styles in each of the three types of intellectual styles are listed (see Zhang & Sternberg, 2006, for definitions of individual styles). Much empirical evidence has supported the validity of Sternberg’s (1988) original theory and its reconceptualized notion of three types of thinking styles (Kaufman, 2001; Zhang, 2005). The most frequently used testing tool is the Thinking Styles Inventory (TSI; Sternberg & Wagner, 1992) and its revision, the Thinking Styles Inventory–Revised (TSI-R; Sternberg, Wagner, & Zhang, 2003). Research using these inventories suggests that thinking styles vary as a function of both personal characteristics (e.g., age, gender) and environmental characteristics (e.g., nature of academic discipline). This research also indicates that, in general, thinking styles make a difference in students’ academic achievement, cognitive development, and psychosocial development (Zhang & Sternberg, 2006). Chickering (1969)—and later, Chickering and Reisser (1993)—delineated psychosocial development, which we examined in the aforementioned research. Chickering’s Theory of Psychosocial Development and Its Research Theories of psychosocial development originated from Erikson’s (1959) work. Such theories address developmental issues or tasks that occur throughout one’s life, as well as one’s pattern of responses. Chickering (1969; Chickering & Reisser, 1993) proposed seven vectors (i.e., dimensions) of developmental tasks for university students in the United States: (a) developing competence, (b) managing emotions, (c) developing autonomy, (d) establishing identity, (e) freeing interpersonal relationships, (f) developing purpose, and (g) developing integrity. Since its publication, Chickering’s (1969) theory has been guiding much of the research on university students’ psychosocial development and has been operationalized through the Student Developmental Task and Lifestyle Inventory (SDTLI; Winston, Miller, & Prince, 1987) and the Iowa Student Development Inventory (ISDI; Hood, 1986, 1997).
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The ISDI is composed of seven inventories, each measuring one developmental task. In the managing emotions dimension, university students are portrayed as becoming more aware of their emotions and more able to integrate them as they advance through their education. Five types of both positive and negative emotions are especially pertinent to university students: happiness, attraction, anger, depression, and frustration. The Iowa Managing Emotions Inventory (IMEI; Hood & Jackson, 1997) assesses these emotions. Apart from being tested among students from two universities in Iowa during the process of its development (White, 1986; White & Hood, 1989), the IMEI has not been examined in any other study. Both existing studies, however, have obtained satisfactory internal scale reliability data, with Cronbach’s alphas ranging from the mid .70s to the mid .80s. Furthermore, the correlations among the various scales ranged from the low .60s to the mid .70s. These high interscale correlations indicated that the levels of differentiation among the five scales could be improved. These studies have also yielded a moderate amount of evidence for the external construct validity of the IMEI. For example, students who demonstrated higher levels of ability to manage their emotions (as this inventory measured) tended to rate themselves higher on dimensions such as personal development and social development; they also tended to rate themselves higher on critical thinking and on their ability to understand diverse philosophies and cultures. Students who evaluated themselves as being more capable of managing their emotions also tended to earn higher grade point averages. I adopted the IMEI because it has good reliability and validity data and was designed to assess a wide range of emotions among university students. I also adopted this inventory because I expect significant relations between these emotions and the thinking styles defined in the theory of mental self-government, on the basis of past finding that intellectual styles and emotions were closely associated with each other. The Present Study There were two objectives of this study: to validate the IMEI among university students in Hong Kong and, more important, to explore the predictive power of thinking styles for students’ emotions. Given that past research indicated that Type I intellectual styles (e.g., fieldindependent style and reflective style) were associated with positive emotions and that Type I thinking styles were related to attributes that are perceived as being more positive (e.g., higher levels of self-esteem and cognitive development; Zhang & Sternberg, 2006), it was predicted that in general, Type I thinking styles would be statistically predictive of a higher capacity for managing one’s emotions. Regarding Type II and Type III styles, I did not make specific hypotheses because there was no foundation for making them. Furthermore, because
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age and gender have been found to be significantly related to thinking styles (e.g., Zhang & Sachs, 1997) in examining the relation between thinking styles and emotions, this study took age and gender into account. Method Participants Participants were 99 university students (23 men and 76 women) in their 2nd year at the Chinese University of Hong Kong. The participants ranged from 18–50 years old, with a mean age of 22 years (SD = 1.83 years) and a median age of 21 years. Studying toward their bachelor’s degree in either education or the arts, students from three sessions of an introductory educational psychology course participated in the research in exchange for extra credit. Instruments The participants responded to two self-report tests: the TSI-R (Sternberg, Wagner, & Zhang, 2003) and the IMEI (Hood & Jackson, 1997). Consisting of 65 statements, the TSI-R assesses the 13 thinking styles described in Sternberg’s theory, with all five statements measuring 1 of the 13 thinking styles. For each statement, the participants rated themselves on a 7-point response scale, with 1 indicating that the statement does not at all represent the way in which they normally carry out their tasks, and 7 indicating that the statement characterizes extremely well the way in which they normally carry out their tasks. Two sample questions are (a) “When faced with a problem, I use my own ideas and strategies to solve it” (i.e., legislative style); and (b) “I like to figure out how to solve a problem following certain rules” (i.e., executive style). The TSI-R has been used in more than a half dozen studies, including Zhang’s (2004a) study of university students in Beijing, Zhang’s (2004b) study of university students in Hong Kong, Fan’s (2006) study of university students in Shanghai, Zhang’s (2005) study of Chinese business personnel in mainland China, and Zhang and Higgins’s (2008) study of business personnel in Great Britain. These studies obtained good psychometric data for the inventory. In the present study, Cronbach’s alphas are .73, .66, .72, .60, .61, .83, .81, .70, .64, .76, .64, .72, and .78, respectively, for the legislative, executive, judicial, global, local, liberal, conservative, hierarchical, monarchic, oligarchic, anarchic, internal, and external styles. These alpha coefficients are comparable in magnitude to those reported in the aforementioned studies. An exploratory factor analysis yielded a two-factor solution. The first factor was dominated by loadings of Type I thinking styles. The second factor was dominated by loadings of Type II thinking styles. Last, loadings of Type III thinking styles were split between the first two factors. These results reveal good validity of the TSI-R because the
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first two factors are consistent with the characteristics of three types of thinking styles. Furthermore, they support the validity data from previous studies of samples from not only the West (e.g., the United Kingdom, the United States) but also Asia (e.g., Hong Kong, mainland China). The IMEI (Hood & Jackson, 1997) measures Chickering’s managing emotions dimension. Composed of 60 statements, this inventory pertains to five types of emotions: happiness, attraction, anger, depression, and frustration. For each statement, the respondents rated themselves on a 5-point response scale, with 1 indicating that the statement does not describe themselves at all regarding how they feel or act in various situations, and 5 indicating that the statement represents extremely well how they feel or act in various situations. Some of the statements are positively scored; others are reversely scored. For example, the statement “I try to understand my own anger” is a positively scored anger item (i.e., higher scores on this item indicate higher capacity for dealing with anger). The statement “I rarely look beyond my feelings of anger for causes,” however, is a reversely scored anger item (i.e., higher scores on this item indicate lower capacity for dealing with anger). The present study employed a Chinese version of the inventory. Linguistic equivalency was obtained via the back-translation technique. As we discussed previously, the two existing studies obtained reasonably good internal scale reliability data and proved that the inventory possesses good external validity, although its interscale correlations had much room for improvement. Cronbach’s alpha coefficients for the present data are .68, .78, .70, .75, and .52, respectively, for anger, depression, frustration, happiness, and attraction. Although the first four alpha coefficients were similar in magnitude to those in the two existing studies, the alpha coefficient for the attraction scale was substantially lower than that reported in previous studies. The Pearson product–moment correlations ranged from .31 to .72, and the majority fell below .40. These interscale correlation coefficients suggest better differentiation among the five scales than those obtained in the United States. Data Analysis I conducted preliminary statistical analyses to examine possible significant group differences in the two main variables based on gender and age. I found no gender difference in the thinking style and emotion scales. However, I identified age differences in several scales across the two inventories. For example, older students tended to score higher on the legislative, judicial, and internal thinking styles and indicated better capability for dealing with frustration. Two statistical analyses followed. First, I used a zero-order correlation procedure to explore the basic relations between thinking styles and emotions. Second, I used hierarchical multiple regressions in which thinking styles were the independent variables, emotions were the dependent variables, and age was
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the control variable because of its significant correlations with several of the thinking styles. These regressions aimed to test the predictive power of thinking styles for emotions when I took students’ ages into consideration. Results Zero-Order Correlation Coefficients Between Thinking Styles and Emotions Zero-order correlation coefficients suggest significant relation between thinking styles and emotions. Of the 65 correlation coefficients (13 styles by 5 types of emotions), 22 (34%) were statistically significant. From the perspective of thinking styles, the hierarchical style was most frequently involved in the statistically significant relations. The hierarchical style was significantly correlated with all of the emotion scales except the attraction scale. From the perspective of emotions, anger and frustration resulted in the largest number of statistically significant correlations. Anger related to 6 of the 13 styles, with 4 Type I styles (all but the global style) and 2 Type III styles (anarchic, external). Frustration was related to 7 thinking styles, with 4 Type I styles (again, all but the global style), and 3 Type II styles (conservative, executive, monarchic). I identified three general patterns of correlations when I took all 22 statistically significant correlations into account. First, Type I styles were positively associated with the ability to deal with emotions. Second, the anarchic and external styles (two Type III styles) also had a positive relation with the ability to deal with emotions. Last, significant correlations involving Type II styles were inconsistent; the executive and monarchic styles were positively associated with frustration, but the conservative style was negatively associated with the ability to handle both frustration and depression. It is important to mention that although statistically significant, the majority of the correlations are weak and that the links of emotions to some styles are at best tenuous. Detailed statistics are presented in Table 1. Predicting Emotions From Thinking Styles, Controlling for Age Results from hierarchical multiple-regressions indicated that statistically significant predictive relations were obtained for all five types of emotions. Across the five emotion scales, 6 of the 13 thinking styles were involved in the statistically significant predictions. The anger scale was positively predicted by the hierarchical style, with 9% of the variance in the former being explained by the latter beyond age. The depression scale was positively predicted by the hierarchical style but negatively predicted by the oligarchic style. The 2 styles accounted for 17% of the variance in the depression scale beyond age. The frustration scale was positively predicted by the hierarchical and liberal styles but negatively predicted by the anarchic style. The 3 styles contributed to 20% of the
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TABLE 1. Zero-Order Correlation Coefficients for Thinking Styles and Emotions (N = 99) Scale
Anger
Depression
Frustration
Happiness
Legislative Executive Judicial Global Local Liberal Conservative Hierarchical Monarchic Oligarchic Anarchic Internal External
.31** .06 .22* –.02 .20 .27* –.16 .28* .07 .12 .27* .09 .26*
.16 .08 .18 –.06 .03 .17 –.22* .33** –.04 –.13 .04 .02 .15
.26* .23* .27* –.09 .11 .31** –.22* .32** .25* .08 .07 .03 .22*
.11 .14 .22* .02 –.03 .18 –.10 .25* –.05 .02 .01 –.10 .27*
Attraction .05 .17 .26* –.09 .10 .09 .05 .14 .08 .01 .06 –.12 .08
*
p < .05. **p < .01.
variance in the frustration scale beyond age. The happiness scale was positively predicted by the external and hierarchical styles but negatively predicted by the anarchic style. The unique contribution of the 3 styles to the variance in happiness over age was 18%. Last, the attraction scale was positively predicted by the judicial styles and its unique contribution was 6%. See Table 2 for other details from these regression procedures. Discussion This study aimed to achieve two objectives: to validate the Chinese version of the IMEI (Hood & Jackson, 1997) for a sample of university students in Hong Kong and, more important, to understand the relations between university students’ thinking styles and their capacity for being aware of and managing their emotions, in particular, how their thinking styles contributed to their capacity when researchers take age and gender into consideration. Both objectives were achieved. The IMEI scales yielded reliabilities that are comparable to those obtained in the two existing studies of university students in the United States. It should be noted that the internal scale reliability for the attraction scale (α = .52) was substantially lower than that yielded by the U.S. data sets. This low internal scale consistency could have resulted from several possibilities; most notably, the notion of attraction might operate differently in the American culture and the
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TABLE 2. Contributions of Thinking Styles to Emotions Beyond Age (N = 99) Variable summary Variable Anger Age Hierarchical Depression Age Hierarchical Oligarchic Frustration Age Hierarchical Liberal Anarchic Happiness Age External Anarchic Hierarchical Attraction Age Judicial
Model summary
β weight
R
F
df
.11 .30**
.02a .11b
2.109a 4.76b*
1, 77 2, 76
.11 .41*** –.26*
.04a .15b .21c
3.02a 6.50b** 6.49c**
1, 75 2, 74 1, 77
.15 .41** .34** –.30*
.05a .14b .20c .25d
3.79a 5.93b** 5.82c** 5.90d***
1, 73 2, 72 3, 71 4, 70
.14 .33* –.36* .27*
.01a .08b .14c .19d
1.10a 3.66b* 3.97c* 4.13d**
1, 76 2, 75 3, 74 4, 73
.09 .24*
.02a .08b
1.31a 4.01b*
1, 76 2, 75
2
Note. List-wise cases exclusion was used. aPredictors were constant and age. bPredictors were constant, age, and the first style predictor. cPredictors were constant, age, the first style predictor, and the second style predictor. dPredictors were constant, age, the first style predictor, the second style predictor, and the third style predictor. * p < .05. **p < .01. ***p < .001.
Chinese culture. Thus, future studies using the Chinese version of this inventory are recommended to further modify and test the items in the attraction scale. Out of the many possible revisions of the items in the attraction scale, understanding the meaning of attraction among American students and among Chinese students is fundamental. I can discuss the validity of the inventory from three perspectives. The first pertains to the way in which the IMEI scales were correlated with one another. On the one hand, the moderate strength of the correlation coefficients among the scales suggests that the five scales assess an overarching construct: emotions. On the other hand, this moderate magnitude indicates that the correlations among the scales are low enough to be distinguished from one another. Second, the validity of the inventory is evident through the fact that the older students scored in the more favorable direction than did the younger ones on three of
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the five scales: anger, depression, and frustration. Chickering’s theoretical underpinnings expected this significant difference in emotions related to age. As they mature, students become more aware of and better at integrating their emotions. In the third perspective to determine the validity of the inventory, researchers observe how the emotion scales were related to the thinking styles. The way in which the two constructs were related to each other in the present data is largely supportive of the research hypothesis of this study. As expected, Type I thinking styles demonstrated the strongest predictive power for students’ ability to recognize and manage their emotions. From this perspective, researchers determine external validity of the IMEI. Apart from exploring the general relations between emotions and thinking styles by calculating zero-order correlation coefficients among the scales in the two inventories, I tested the predictive power of thinking styles for emotions, taking into consideration the effects of age on the two main variables. Putting together the two sets of the resultant statistics, I found that although most thinking styles (except the global, local, internal styles) are associated with emotions, only fewer than half (6 of 13) were significant predictors for emotions. Although the positive contributors to students’ abilities to cope with emotions are three of the five Type I styles (hierarchical, liberal, judicial) and a Type III style (the external style), the negative contributors are two Type III styles (anarchic, oligarchic). Researchers could argue that given that only 6 of the 13 thinking styles significantly contributed to the variance in emotions beyond age, these significant results might have been obtained by statistical chance. I would maintain that such an argument would be ill grounded. For at least three reasons, researchers should argue that the statistically significant regression results were more likely to reflect true variations in emotions as a function of thinking styles than to have been obtained by statistical chance. First, because there is no semantic resemblance between the statements in the TSI-R and in the IMEI, the statistically significant relations found between the two constructs cannot be considered coincidental. Second, the way in which thinking styles contributed to the variance in emotions (i.e., Type I styles positively contributed to positive emotions or to better control of negative emotions) is supportive of the predictions made earlier. It is more important that these results make substantive sense. For example, both the liberal and hierarchical styles predicted students’ scores on the frustration scale in a favorable direction. An individual with a liberal thinking style prefers to engage in tasks that involve novelty and ambiguity. An individual with a hierarchical thinking style tends to distribute attention to several tasks that are prioritized according to his or her valuing of the tasks. In both of these thinking styles, the propensity for taking risks, working creatively, and taking on the challenges of the complexity of a task is inherent. To illustrate, performing tasks in new ways (i.e., using the liberal style) often involves the risk of failure because there is no guarantee for success in taking up something new.
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Likewise, prioritizing tasks may also encounter resistant forces because one’s learning and work environment may not appreciate priorities. Yet, if the environment rewards such thinking styles (i.e., the use of such thinking styles are effective in dealing with the tasks at hand), an individual would become more assured of his or her abilities. Such self-assurance would, in turn, help the individual to better deal with the emotions—in particular, frustration, anger, and depressotypic feelings—typically encountered when he or she challenges the well-established rules (i.e., using creativity-generating styles). This logical argument, however, accords with the fact that our regression analyses used the thinking style scales as the independent variables and the emotion scales as the dependent variables. Such a discussion does not imply a causal relation between the two constructs. It is possible that an individual’s high capacity for dealing with negative feelings such as frustration, anger, and depression enables him or her to use creativitygenerating styles more often. A further caution is that people’s intellectual styles are malleable (Zhang & Sternberg, 2006). In an institution in which Type II styles are highly appreciated, using these styles may allow students to become more aware of and better at dealing with their emotions. Last, the statistically significant results were more likely to be reflective of the true differences in emotions partially because of thinking styles and because these findings are consistent with previous ones that suggested that intellectual styles are important in emotions. In particular, the main result of the present study supports the past general finding that Type I styles are more conducive to the development of people’s abilities to deal with negative emotions and to the enhancement of positive emotions (e.g., Campbell & Douglas, 1972; Deng et al., 2000; Hayden et al., 2006). Given these reasons, despite the fact that only 6 of the 13 thinking styles were statistically significant in predicting students’ emotions, researchers should conclude that thinking styles—along with factors such as culture, age, gender, and school environment—are significant in students’ emotions. Readers would want to know how I would interpret some of the apparently contradictory findings. For example, theoretically, the same style (i.e., the anarchic style) would be related to negative emotions (i.e., anger, frustration) in the same direction, whether positive or negative. However, although the zero-order correlation procedure revealed a positive relation between the anarchic style and the anger scale, regression results indicated that the anarchic style was a negative contributor to the frustration scale. One possible explanation is that although anger and frustration are related because both are negative emotions, they could differ significantly. As a result, they are related to the same thinking style (i.e., the anarchic style) in different fashions. However, it should be noted that the correlation coefficient between the anarchic style and anger was .27 and significant only at the .05 statistical level. By the same token, the anarchic style was the third predictor for the frustration scale, after the hierarchical and liberal styles. These data indicate that the relations of the anarchic style to the two types of emotions are rather weak. Therefore, these findings should not be taken at face value. Such an explanation, of course, is only a post
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hoc conjecture. Further research needs to find out the complexity of the relations between particular thinking styles and each type of emotion. Limitations, Conclusions, and Implications This study has three limitations. First, the research sample could be biased because the participants were from merely two academic disciplines. Thus, the results may not apply to students in other disciplines. Second, the Chinese version of the IMEI was tested for the first time among university students in Hong Kong. Although the psychometric properties of the inventory are generally good, further testing needs to determine the efficacy of the inventory in assessing the emotions of university students in Hong Kong. Third, inherent in this study might be a cultural bias because the IMEI is grounded in a theory intended for university students in the United States. Given the many differences between the American and Chinese higher education systems, the factors that interact with thinking styles to contribute to the development of students’ positive emotions (or effective management of negative emotions) may be more complex than those I described here. With these limitations, the study can be viewed as only exploratory, and its results should be considered tentative rather than definitive. Regardless of these limitations, the significance of this study can be derived from two major findings. First, the present study has obtained initial evidence for the IMEI among a sample of university students in Hong Kong. Further investigation of the reliability and validity of the inventory for measuring the emotions of university students in Hong Kong, as defined in Chickering’s theory, is necessary because the present study was only the first of its kind, and because the internal reliability for one of the scales (i.e., attraction) was relatively low. Nevertheless, the initial reliability and validity data determined in this study denote that the inventory may become a potential assessment tool for university counselors in Hong Kong in helping students to understand and manage their emotions. Second and more important, although the relational patterns of emotions to the Type II and the anarchic styles were not clear, it is obvious that Type I thinking styles and the external thinking style were strongly and positively associated with (and some even significantly predicted) students’ emotions. Furthermore, it was established that the oligarchic style was strongly and negatively associated with (and significantly predicted) students’ emotions. This general finding aligns with Zhang’s (2002a, 2008) finding that Type I thinking styles positively contributed to students’ psychosocial development, including their sense of purpose (Zhang, 2002a) and sense of identity (Zhang, 2008). The present findings have advanced our understanding of the significant function of thinking styles in psychosocial development. As I reviewed earlier, the importance of thinking styles goes beyond its role in student learning. Previous studies have shown that thinking styles are related
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to attributes such as self-esteem (Zhang & Postiglione, 2001), career personality types (Zhang, 2000), cognitive development (Zhang, 2002b), and personality traits (Zhang & Huang, 2001). Studies that investigated other style constructs found similar results. For example, I found that the field-dependence versus field-independence construct was significantly related to attributes such as moral maturity (e.g., Schleifer & Douglas, 1973) and sense of identity (e.g., Bhatnager & Rastogi, 1986), as well as emotions (Campbell & Douglas, 1972; Deng et al., 2000). On the basis of repeated empirical evidence for the intricately entwined link between intellectual styles and other human attributes—including that between thinking styles and students’ emotions—researchers would argue that thinking styles and emotions should be considered as two integral parts of a holistic student development at a scientific level. Moreover, at a practical level, researchers would argue that the present findings, like many of the earlier ones, call for joint ventures between teaching faculty and student development educators to achieve their goal of fostering students’ well-rounded development. Teaching faculty could support students in developing their capacity for dealing with emotions by promoting a wide range of thinking styles—in particular, Type I styles and the external style—and discouraging students from taking on too many tasks without any priority (i.e., avoiding using the oligarchic style). Meanwhile, student development educators could facilitate students’ effective use of thinking styles by helping them to understand and manage their emotions better. AUTHOR NOTE Li-fang Zhang is an associate professor and the associate dean (Research Higher Degrees) in the Faculty of Education at the University of Hong Kong. Her recent book with Robert J. Sternberg is titled The Nature of Intellectual Styles (Routledge, 2006). Her research interests include intellectual styles, giftedness, personality, and student development in higher education. REFERENCES Bagley, C., & Mallick, K. (1998). Field independence, cultural context and academic achievement: A commentary. British Journal of Educational Psychology, 68, 581–587. Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck Depression Inventory-II (2nd ed.). San Antonio, TX: Psychological Corporation. Bhatnager, P., & Rastogi, M. (1986). Cognitive style and basic ideal disparity in males and females. Indian Journal of Current Psychological Research, 1, 36–40. Biggs, J. B. (1978). Individual and group differences in study processes. British Journal of Educational Psychology, 48, 266–279. Campbell, S. B., & Douglas, V. I. (1972). Cognitive styles and responses to the threat of frustration. Canadian Journal of Behavioral Science, 4(1), 30–42. Cattell, R. B., Cattell, A. K., & Cattell, H. E. (1978). 16 personality factor questionnaire. Champaign, IL: Institute for Personality and Ability Testing.
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Chickering, A. (1969). Education and identity. San Francisco: Jossey-Bass. Chickering, A., & Reisser, L. (1993). Education and identity (2nd ed.). San Francisco: Jossey-Bass. Ciarrochi, J., Deane, F. P., Wilson, C. J., & Rickwood, D. (2002). Adolescents who need help the most are the least likely to seek it: The relationship between low emotional competence and low intention to seek help. British Journal of Guidance & Counselling, 30, 173–188. Costa, P. T., Jr., & McCrae, R. R. (1992). The NEO-PI-R: Professional manual. Odessa, FL: Psychological Assessment Resources. Deng, Z., Li, D., & Zhang, Q. (2000). Cognitive styles, scholastic attainments with the Cattell’s 16PF: A correlative approach. Psychological Science China, 23, 234–235. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125, 276–302. Erikson, E. H. (1959). Identity and the life cycle. Psychological Issues Monograph (Vol. 1). New York: International Universities Press. Eysenck, H. J., & Eysenck, S. B. G. (1964). Manual of the Eysenck Personality Inventory. London: Hodder and Stoughton. Fan, W. Q. (2006). Thinking styles among university students in Shanghai: Comparing traditional and hypermedia instructional environments. Unpublished doctoral dissertation, University of Hong Kong. Gadzella, B. M. (1999). Differences among cognitive-processing styles groups on personality traits. Journal of Instructional Psychology, 26, 161–166. Globerson, T., & Zelniker, T., eds. (1989). Cognitive style and cognitive development. Human development (Vol. 3, edited). Norwood, NJ: Ablex. Gregorc, A. F. (1979). Learning/teaching styles: Potent forces behind them. Educational Leadership, 36, 234–236. Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill. Hayden, E. P., Klein, D. N., Durbin, C. E., & Olino, T. M. (2006). Positive emotionality at age 3 predicts cognitive styles in 7-year-old children. Development and Psychopathology, 18, 409–423. Hilliard, R. I. (1995). How do medical students learn: Medical student learning styles and factors that affect these learning styles. Teaching and Learning in Medicine, 7, 201–210. Holland, J. L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Prentice-Hall. Hood, A. B. (Ed.). (1986). The Iowa Student Development Inventories (1st ed.). Iowa City, IA: HITECH Press. Hood, A. B. (Ed.). (1997). The Iowa Student Development Inventories (2nd ed.). Iowa City, IA: HITECH Press. Hood, A. B., & Jackson, L. M. (1997). The Iowa Managing Emotions Inventory. In A. B. Hood (Ed.), The Iowa student development inventories (2nd ed.; pp. 22–31). Iowa City, IA: HITECH Press. Jong, P. J. D., Merckelbach, H., & Nijman, H. (1995). Hemisphere preference, anxiety, and covariation bias. Personality and Individual Differences, 18, 363–371. Jung, C. (1923). Psychological types. New York: Harcourt Brace. Kagan, J. (1965). Individual differences in the resolution of response uncertainty. Journal of Personality and Social Psychology, 2, 154–160. Kaufman, J. C. (2001). Thinking styles in creative writers and journalists. Dissertation Abstracts International (Section B): The Physical Sciences and Engineering, 62(3B), 1069. Kirton, M. J. (1976). Adaptors and innovators: A description and measure. Journal of Applied Psychology, 61, 622–629.
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Kogan, N. (1980). A style of life, a life of style (review of cognitive styles in personal and cultural adaptation). Contemporary Psychology, 25, 595–598. Mansfield, E. A. (1998). Working memory development in adolescents: A neo-Piagetian investigation. Dissertation Abstracts International (Section A): Humanities and Social Sciences, 58(8-A), 3001. Mayer, J. D., Salovey, P., Caruso, D. R., & Sitarenios, G. (2001). Emotional intelligence as a standard intelligence. Emotion, 1, 232–242. Messick, S. (1996). Bridging cognition and personality in education: The role of style in performance and development. European Journal of Personality, 10, 353–376. Mischel, W., & Ayduk, O. (2004). Willpower in a cognitive-affective processing system: The dynamics of delay of gratification. In R. F. Baumeister & K. D. Vohs (Eds.), Handbook of self-regulation: Research, theory, and applications (pp. 99–129). New York: Guilford Press. Mischel, W., & Shoda, Y. (1999). Integrating dispositions and processing dynamics within a unified theory of personality: The cognitive-affective personality system. In L. A. Pervin & O. P. John (Eds), Handbook of personality: Theory and research (2nd ed.; pp. 197–218). New York: Guilford Press. Morgan, H. (1997). Cognitive styles and classroom learning. Westport, CT: Praeger Publishers. Mortenson, S. T. (2006). Cultural differences and similarities in seeking social support as a response to academic failure: A comparison of American and Chinese college students. Communication Education, 55, 127–146. Riding, R., & Cheema, I. (1991). Cognitive styles: An overview and integration. Educational Psychology, 11, 193–215. Riding, R. J., & Wigley, S. (1997). The relationship between cognitive style and personality in further education students. Personality and Individual Differences, 23, 379–389. Saleh, A. I. (1998). The nexus of brain hemisphericity, personality types, temperaments, learning styles, learning strategies, gender, majors, and cultures. Dissertation Abstracts International (Section A): Humanities and Social Sciences, 58(8-A), 3004. Schleifer, M., & Douglas, V. I. (1973). Moral judgments, behavior and cognitive style in young children. Canadian Journal of Behavioral Science, 5, 133–144. Spangler, G., Pekrun, R., Kramer, K., & Hofmann, H. (2002). Students’ emotions, physiological reactions, and coping in academic exams. Anxiety, Stress, and Coping, 15, 413–432. Sternberg, R. J. (1988). Mental self-government: A theory of intellectual styles and their development. Human Development, 31, 197–224. Sternberg, R. J. (1997). Thinking styles. New York: Cambridge University Press. Sternberg, R. J., & Wagner, R. K. (1992). Thinking Styles Inventory. Unpublished manuscript, Yale University, New Haven, Connecticut. Sternberg, R. J., Wagner, R. K., & Zhang, L. F. (2003). Thinking Styles Inventory— Revised. Unpublished manuscript, Yale University, New Haven, Connecticut. Torrance, E. P. (1988). SOLAT (style of learning and thinking) manual. Bensenville, IL: Scholastic Testing Service. Torrance, E. P., Taggart, B., & Taggart, W. (1984). Human information processing survey. Bensenville, IL: Scholastic Testing Service. Westreich, A. H., Ritzler, B., Duncan, J. (1997). Relationship between cognitive style and defensive style. Perceptual and Motor Skills, 84, 1011–1023. White, D. B. (1986). An assessment and validation of Chickering’s seven vectors of student development. Unpublished doctoral dissertation, University of Iowa, Iowa City. White, D. B., & Hood, A. B. (1989). An assessment of the validity of Chickering’s theory of student development. Journal of College Student Development, 30, 354–361.
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Winston, R. B., Jr., Miller, T. K., & Prince, J. S. (1987). Student developmental task and lifestyle inventory. Athens, GA: Student Development Associates. Witkin, H. A. (1962). Psychological differentiation: Studies of development. New York: Wiley. Zhang, L. F. (2000). Are thinking styles and personality types related? Educational Psychology, 20, 271–283. Zhang, L. F. (2002a). The role of thinking styles in psychosocial development. Journal of College Student Development, 43, 696–711. Zhang, L. F. (2002b). Thinking styles and cognitive development. The Journal of Genetic Psychology, 163, 179–195. Zhang, L. F. (2003). Contributions of thinking styles to critical thinking dispositions. The Journal of Psychology, 137, 517–544. Zhang, L. F. (2004a). Do university students’ thinking styles matter in their preferred teaching approaches? Personality and Individual Differences, 37, 1551–1564. Zhang, L. F. (2004b). Thinking styles: University students’ preferred teaching styles and their conceptions of effective teachers. The Journal of Psychology, 138, 233–252. Zhang, L. F. (2005). Validating the theory of mental self-government in a non-academic setting. Personality and Individual Differences, 38, 1915–1925. Zhang, L. F. (2008). Thinking styles and identity development among Chinese university students. American Journal of Psychology, 121(2), 255–271. Zhang, L. F., & Higgins, P. (2008). The predictive power of socialization variables for thinking styles among adults in the workplace. Learning and Individual Differences, 18, 11–18. Zhang, L. F., & Huang, J. F. (2001). Thinking styles and the five-factor model of personality. European Journal of Personality, 15, 465–476. Zhang, L. F., & Postiglione, G. A. (2001). Thinking styles, self-esteem, and socio-economic status. Personality and Individual Differences, 31, 1333–1346. Zhang, L. F., & Sachs, J. (1997). Assessing thinking styles in the theory of mental selfgovernment: A Hong Kong validity study. Psychological Reports, 81, 915–928. Zhang, L. F., & Sternberg, R. J. (2005). A threefold model of intellectual styles. Educational Psychology Review, 17, 1–53. Zhang, L. F., & Sternberg, R. J. (2006). The nature of intellectual styles. Mahwah, NJ: Erlbaum.
Original manuscript received July 24, 2007 Final version accepted October 31, 2007
Leaning
Scope
Level
Form
Legislative Executive
Function
Hierarchical Monarchic Oligarchic Anarchic Global Local Internal External Liberal Conservative
Judicial
Thinking style
Dimension
Work on tasks that require creative strategies; one prefers to choose one’s own activities. Work on tasks with clear instructions and structures; one prefers to implement tasks with established guidelines. Work on tasks that allow for one’s evaluation; one prefers to evaluate and judge the performance of other people. Distribute attention to several tasks that are prioritized according to one’s valuing of the tasks. Work on tasks that allow complete focus on one thing at a time. Work on multiple tasks in the service of multiple objectives, without setting priorities. Work on tasks that would allow flexibility as to what, where, when, and how one works. Pay more attention to the overall picture of an issue and to abstract ideas. Work on tasks that require working with concrete details. Work on tasks that allow one to work as an independent unit. Work on tasks that allow for collaborative ventures with other people. Work on tasks that involve novelty and ambiguity. Work on tasks that allow one to adhere to the existing rules and procedures in performing tasks.
Key characteristics
APPENDIX A Thinking Styles in the Theory of Mental Self-Government
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Concrete random
Mode of thinking Personality type
e
Adaptation Impulsivity Convergent thinking Field dependent Executive, local, monarchic, conservative
Concrete sequential
Analytic Sensing, judging
Surface Conventional
Type II
Oligarchic, anarchic, internal, external
Achieving Realistic, investigative, social, enterprising Integrative Thinking, feeling, introversion, extraversion Abstract random, abstract sequential
Type III
Note. Theoretical foundations: aBiggs’s theory of student learning (J. B. Biggs, 1978); bHolland’s theory of career personality types (J. L. Holland, 1973); cTorrance’s construct of brain dominance (E. P. Torrance, 1988); dJung’s theory of personality types (C. Jung, 1923); eGregorc’s model of mind styles, (A. F. Gregorc, 1979); fKirton’s model of decision-making styles (M. J. Kirton, 1976); gKagan’s model of reflectivity-impulsivity conceptual tempo (J. Kagan, 1965); hGuilford’s model of structure of intellect (J. P. Guilford, 1967); iWitkin’s construct of field-dependence/independence (H. A. Witkin, 1962); jSternberg’s theory of mental self-government (R. J. Sternberg, 1988).
g
Decision-making style Conceptual tempo h Structure of intellect i Perceptual style j Thinking style
f
Mind style
d
Innovation Reflectivity Divergent thinking Field independent Legislative, judicial, global, hierarchical, judicial
Holistic Intuitive, perceiving
c
b
Deep Artistic
Type I
Learning approach Career personality type
a
Style type/construct
APPENDIX B Three Types of Intellectual Styles
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Thinking Styles and Emotions LI-FANG ZHANG University of Hong Kong
ABSTRACT. This study aimed to explore the relationship between thinking styles and emotions among university students in Hong Kong. Participants were 99 2nd-year students (23 men and 76 women) who responded to the Thinking Styles Inventory–Revised (TSI-R), based on R. J. Sternberg’s (1988) theory of mental self-government, and to the Iowa Managing Emotions Inventory (IMEI), based on A. Chickering’s (1969) theory of psychosocial development. Results indicated not only that thinking styles were associated with emotions but also that thinking styles had predictive power for emotions beyond age. The author discusses implications of these findings for faculty members and studentdevelopment educators. Keywords: Chinese university students, emotions, thinking styles
INTELLECTUAL STYLES IS AN ALL-ENCOMPASSING TERM for constructs such as cognitive styles, learning styles, thinking styles, and teaching styles and refers to people’s preferred ways of processing information and dealing with tasks (Zhang & Sternberg, 2006). It has been established that intellectual styles matter in various domains of a student’s life, including his or her academic achievement (Bagley & Mallick, 1998; Mansfield, 1998), cognitive development (Globerson & Zelniker, 1989; Westreich, Ritzler, & Duncan, 1997), career development (Hilliard, 1995; Morgan, 1997), and personality traits (Deng, Li, & Zhang, 2000; Saleh, 1998). I considered the present study to be related to the final line of the aforementioned investigations (i.e., research on the relation between intellectual styles and personality traits). In literature, some scholars consider constructs such as anxiety, assertiveness, depression, frustration, happiness, and optimism as personality traits (e.g., Costa & McCrae, 1992; Eysenck & Eysenck, 1964). Other scholars, however, refer to such constructs as emotional competence (e.g., Ciarrochi, Deane, The author is grateful to the Committee on Research and Conference Grants, administered by the University of Hong Kong, for funding this project. The author’s special thanks go to all the research participants. Address correspondence to Li-fang Zhang, Faculty of Education, The University of Hong Kong, Pokfulam Road, Hong Kong; [email protected] (e-mail). 497 497
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Wilson, & Rickwood, 2002), emotional intelligence (e.g., Mayer, Salovey, Caruso, & Sitarenios, 2001), mental health (Beck, Steer, & Brown, 1996), subjective wellbeing (Diener, Suh, Lucas, & Smith, 1999), emotions, (Mortenson, 2006; Spangler, Pekrun, Kramer, & Hofmann, 2002) or emotionality (e.g., Hayden, Klein, Durbin, & Olino, 2006). This study adopts the term emotions to achieve consistency with those used in the theoretical framework on which one of the inventories employed in this study stands: the emotions dimension defined in Chickering’s (1969; Chickering & Reisser, 1993) theory of psychosocial development. Furthermore, this construct will be examined against thinking styles, one of the specific style constructs under intellectual styles. Intellectual Styles and Emotions Researchers have investigated the relation between intellectual styles and emotions for more than three decades. However, unlike research on the more general cognitive–affective personality system (e.g., Mischel & Ayduk, 2004; Mischel & Shoda, 1999), research on intellectual styles and emotions has been unfruitful. Campbell and Douglas (1972) conducted the earliest study in which researchers examined children’s responses to and level of optimism toward the threat of frustration in relation to their intellectual styles, on the basis of Witkin’s (1962) field-dependent/independent styles and Kagan’s (1965) reflective and impulsive styles. Compared with children who scored higher on field dependence and impulsivity, children who scored higher on field independence and reflectivity displayed higher levels of optimism toward frustration. I conducted a systematic search on the PsycINFO database (2007), entering two sets of terms in their maximum possible combinations. The first set included emotions, emotional competence, emotional intelligence, emotionality, mental health, and subjective well-being. The second set included cognitive styles, intellectual styles, learning styles, and thinking styles. This search resulted in five additional entries. These studies, however, were all published after the mid 1990s. The first study was conducted in the Netherlands. Jong, Merckelbach, and Nijman (1995) found that among 70 undergraduate students, those with a holistic mode of thinking (i.e., right-brained dominance) demonstrated higher levels of anxiety than did those with the analytic mode of thinking (i.e., left-brained dominance). Riding and Wigley (1997) examined Riding and Cheema’s (1991) two stylistic dimensions (verbal–imagery, analytic–wholistic) against psychoticism. The authors concluded that the wholistic style was highly associated with psychoticism. Gadzella (1999) conducted a third study and administered the Human Information Processing Survey (Torrance, Taggart, & Taggart, 1984) and the 16 Personality Factor Questionnaire (Cattell, Cattell, & Cattell, 1978) to 55 students enrolled in undergraduate psychology classes at a Midwestern university. Results
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indicated that students with an analytic mode of thinking displayed higher levels of self-control than did students with a holistic mode of thinking, and that students comfortable with either the analytic or the holistic mode of thinking scored higher on the anxiety scale than did students with an integrative mode of thinking (i.e., whole-brained thinking). Deng et al. (2000) investigated the relations among field-dependence/ independence to assertiveness. Their results showed that the field independent participants scored significantly higher on assertiveness than did the field dependent ones. Hayden et al. (2006) examined the links of positive and negative emotions at age 3 to depressive attributional styles at age 7 years. Although little evidence was obtained for a relationship between negative emotions and depressive attributional styles, lower positive emotions at age 3 predicted greater helplessness in the interpersonal domain. There are at least two reasons to continue this investigation. First, the majority of the existing studies were based on style models that describe two bipolar styles (e.g., field-dependent versus field-independent; impulsive versus reflective). The present research adopted a style model much broader in scope in that it describes multiple stylistic dimensions: Sternberg’s (1988, 1997) theory of mental self-government. Second, the emotions examined against intellectual styles have been isolated and not those deemed important to a specific target group. The present study examines five types of emotions addressed in Chickering’s (1969; Chickering & Reisser, 1993) theory of psychosocial development targeted to university students: happiness, attraction, anger, depression, and frustration. These emotions were given special attention in Chickering’s work. According to him, these emotions are important to young university students because recognizing and effectively managing them would positively contribute to their formation of identity—a critical component of psychosocial development. Theory of Mental Self-Government and Its Research Sternberg (1988, 1997) has contended that just as there are different ways of governing a society, there are different ways in which people use their abilities, which are known as thinking styles. According to Sternberg, 13 thinking styles fall under five dimensions: function, form, level, scope, and leaning. Based on both empirical data and theoretical arguments (Kogan, 1980; Messick, 1996), Zhang (2003) reconceptualized the 13 thinking styles into three types. Type I thinking styles include the legislative, judicial, hierarchical, global, and liberal styles, and tend to be more creativity-generating and denote higher levels of cognitive complexity. Type II thinking styles include the executive, local, monarchic, and conservative styles, and suggest a norm-favoring tendency and denote lower levels of cognitive complexity. Type III thinking styles include
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the anarchic, oligarchic, internal, and external styles and may manifest the characteristics of either Type I or Type II thinking styles, depending on the stylistic demands of a task. In Appendix A, the main characteristics of each of the 13 thinking styles are described. The notion of three types of intellectual styles (Zhang & Sternberg, 2005) has been developed to accommodate additional style labels such as fieldindependent/dependent styles and reflective/impulsive styles. For example, along with Type I thinking styles, the field-independent and reflective styles were classified as Type I intellectual styles. Along with Type II thinking styles, the field-dependent and impulsive styles were classified as Type II intellectual styles. Moreover, along with Type III thinking styles, the feeling and integrative styles were classified as Type III intellectual styles. Individual styles from 10 theoretical models were organized into the three types of intellectual styles. In Appendix B, the specific styles in each of the three types of intellectual styles are listed (see Zhang & Sternberg, 2006, for definitions of individual styles). Much empirical evidence has supported the validity of Sternberg’s (1988) original theory and its reconceptualized notion of three types of thinking styles (Kaufman, 2001; Zhang, 2005). The most frequently used testing tool is the Thinking Styles Inventory (TSI; Sternberg & Wagner, 1992) and its revision, the Thinking Styles Inventory–Revised (TSI-R; Sternberg, Wagner, & Zhang, 2003). Research using these inventories suggests that thinking styles vary as a function of both personal characteristics (e.g., age, gender) and environmental characteristics (e.g., nature of academic discipline). This research also indicates that, in general, thinking styles make a difference in students’ academic achievement, cognitive development, and psychosocial development (Zhang & Sternberg, 2006). Chickering (1969)—and later, Chickering and Reisser (1993)—delineated psychosocial development, which we examined in the aforementioned research. Chickering’s Theory of Psychosocial Development and Its Research Theories of psychosocial development originated from Erikson’s (1959) work. Such theories address developmental issues or tasks that occur throughout one’s life, as well as one’s pattern of responses. Chickering (1969; Chickering & Reisser, 1993) proposed seven vectors (i.e., dimensions) of developmental tasks for university students in the United States: (a) developing competence, (b) managing emotions, (c) developing autonomy, (d) establishing identity, (e) freeing interpersonal relationships, (f) developing purpose, and (g) developing integrity. Since its publication, Chickering’s (1969) theory has been guiding much of the research on university students’ psychosocial development and has been operationalized through the Student Developmental Task and Lifestyle Inventory (SDTLI; Winston, Miller, & Prince, 1987) and the Iowa Student Development Inventory (ISDI; Hood, 1986, 1997).
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The ISDI is composed of seven inventories, each measuring one developmental task. In the managing emotions dimension, university students are portrayed as becoming more aware of their emotions and more able to integrate them as they advance through their education. Five types of both positive and negative emotions are especially pertinent to university students: happiness, attraction, anger, depression, and frustration. The Iowa Managing Emotions Inventory (IMEI; Hood & Jackson, 1997) assesses these emotions. Apart from being tested among students from two universities in Iowa during the process of its development (White, 1986; White & Hood, 1989), the IMEI has not been examined in any other study. Both existing studies, however, have obtained satisfactory internal scale reliability data, with Cronbach’s alphas ranging from the mid .70s to the mid .80s. Furthermore, the correlations among the various scales ranged from the low .60s to the mid .70s. These high interscale correlations indicated that the levels of differentiation among the five scales could be improved. These studies have also yielded a moderate amount of evidence for the external construct validity of the IMEI. For example, students who demonstrated higher levels of ability to manage their emotions (as this inventory measured) tended to rate themselves higher on dimensions such as personal development and social development; they also tended to rate themselves higher on critical thinking and on their ability to understand diverse philosophies and cultures. Students who evaluated themselves as being more capable of managing their emotions also tended to earn higher grade point averages. I adopted the IMEI because it has good reliability and validity data and was designed to assess a wide range of emotions among university students. I also adopted this inventory because I expect significant relations between these emotions and the thinking styles defined in the theory of mental self-government, on the basis of past finding that intellectual styles and emotions were closely associated with each other. The Present Study There were two objectives of this study: to validate the IMEI among university students in Hong Kong and, more important, to explore the predictive power of thinking styles for students’ emotions. Given that past research indicated that Type I intellectual styles (e.g., fieldindependent style and reflective style) were associated with positive emotions and that Type I thinking styles were related to attributes that are perceived as being more positive (e.g., higher levels of self-esteem and cognitive development; Zhang & Sternberg, 2006), it was predicted that in general, Type I thinking styles would be statistically predictive of a higher capacity for managing one’s emotions. Regarding Type II and Type III styles, I did not make specific hypotheses because there was no foundation for making them. Furthermore, because
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age and gender have been found to be significantly related to thinking styles (e.g., Zhang & Sachs, 1997) in examining the relation between thinking styles and emotions, this study took age and gender into account. Method Participants Participants were 99 university students (23 men and 76 women) in their 2nd year at the Chinese University of Hong Kong. The participants ranged from 18–50 years old, with a mean age of 22 years (SD = 1.83 years) and a median age of 21 years. Studying toward their bachelor’s degree in either education or the arts, students from three sessions of an introductory educational psychology course participated in the research in exchange for extra credit. Instruments The participants responded to two self-report tests: the TSI-R (Sternberg, Wagner, & Zhang, 2003) and the IMEI (Hood & Jackson, 1997). Consisting of 65 statements, the TSI-R assesses the 13 thinking styles described in Sternberg’s theory, with all five statements measuring 1 of the 13 thinking styles. For each statement, the participants rated themselves on a 7-point response scale, with 1 indicating that the statement does not at all represent the way in which they normally carry out their tasks, and 7 indicating that the statement characterizes extremely well the way in which they normally carry out their tasks. Two sample questions are (a) “When faced with a problem, I use my own ideas and strategies to solve it” (i.e., legislative style); and (b) “I like to figure out how to solve a problem following certain rules” (i.e., executive style). The TSI-R has been used in more than a half dozen studies, including Zhang’s (2004a) study of university students in Beijing, Zhang’s (2004b) study of university students in Hong Kong, Fan’s (2006) study of university students in Shanghai, Zhang’s (2005) study of Chinese business personnel in mainland China, and Zhang and Higgins’s (2008) study of business personnel in Great Britain. These studies obtained good psychometric data for the inventory. In the present study, Cronbach’s alphas are .73, .66, .72, .60, .61, .83, .81, .70, .64, .76, .64, .72, and .78, respectively, for the legislative, executive, judicial, global, local, liberal, conservative, hierarchical, monarchic, oligarchic, anarchic, internal, and external styles. These alpha coefficients are comparable in magnitude to those reported in the aforementioned studies. An exploratory factor analysis yielded a two-factor solution. The first factor was dominated by loadings of Type I thinking styles. The second factor was dominated by loadings of Type II thinking styles. Last, loadings of Type III thinking styles were split between the first two factors. These results reveal good validity of the TSI-R because the
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first two factors are consistent with the characteristics of three types of thinking styles. Furthermore, they support the validity data from previous studies of samples from not only the West (e.g., the United Kingdom, the United States) but also Asia (e.g., Hong Kong, mainland China). The IMEI (Hood & Jackson, 1997) measures Chickering’s managing emotions dimension. Composed of 60 statements, this inventory pertains to five types of emotions: happiness, attraction, anger, depression, and frustration. For each statement, the respondents rated themselves on a 5-point response scale, with 1 indicating that the statement does not describe themselves at all regarding how they feel or act in various situations, and 5 indicating that the statement represents extremely well how they feel or act in various situations. Some of the statements are positively scored; others are reversely scored. For example, the statement “I try to understand my own anger” is a positively scored anger item (i.e., higher scores on this item indicate higher capacity for dealing with anger). The statement “I rarely look beyond my feelings of anger for causes,” however, is a reversely scored anger item (i.e., higher scores on this item indicate lower capacity for dealing with anger). The present study employed a Chinese version of the inventory. Linguistic equivalency was obtained via the back-translation technique. As we discussed previously, the two existing studies obtained reasonably good internal scale reliability data and proved that the inventory possesses good external validity, although its interscale correlations had much room for improvement. Cronbach’s alpha coefficients for the present data are .68, .78, .70, .75, and .52, respectively, for anger, depression, frustration, happiness, and attraction. Although the first four alpha coefficients were similar in magnitude to those in the two existing studies, the alpha coefficient for the attraction scale was substantially lower than that reported in previous studies. The Pearson product–moment correlations ranged from .31 to .72, and the majority fell below .40. These interscale correlation coefficients suggest better differentiation among the five scales than those obtained in the United States. Data Analysis I conducted preliminary statistical analyses to examine possible significant group differences in the two main variables based on gender and age. I found no gender difference in the thinking style and emotion scales. However, I identified age differences in several scales across the two inventories. For example, older students tended to score higher on the legislative, judicial, and internal thinking styles and indicated better capability for dealing with frustration. Two statistical analyses followed. First, I used a zero-order correlation procedure to explore the basic relations between thinking styles and emotions. Second, I used hierarchical multiple regressions in which thinking styles were the independent variables, emotions were the dependent variables, and age was
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the control variable because of its significant correlations with several of the thinking styles. These regressions aimed to test the predictive power of thinking styles for emotions when I took students’ ages into consideration. Results Zero-Order Correlation Coefficients Between Thinking Styles and Emotions Zero-order correlation coefficients suggest significant relation between thinking styles and emotions. Of the 65 correlation coefficients (13 styles by 5 types of emotions), 22 (34%) were statistically significant. From the perspective of thinking styles, the hierarchical style was most frequently involved in the statistically significant relations. The hierarchical style was significantly correlated with all of the emotion scales except the attraction scale. From the perspective of emotions, anger and frustration resulted in the largest number of statistically significant correlations. Anger related to 6 of the 13 styles, with 4 Type I styles (all but the global style) and 2 Type III styles (anarchic, external). Frustration was related to 7 thinking styles, with 4 Type I styles (again, all but the global style), and 3 Type II styles (conservative, executive, monarchic). I identified three general patterns of correlations when I took all 22 statistically significant correlations into account. First, Type I styles were positively associated with the ability to deal with emotions. Second, the anarchic and external styles (two Type III styles) also had a positive relation with the ability to deal with emotions. Last, significant correlations involving Type II styles were inconsistent; the executive and monarchic styles were positively associated with frustration, but the conservative style was negatively associated with the ability to handle both frustration and depression. It is important to mention that although statistically significant, the majority of the correlations are weak and that the links of emotions to some styles are at best tenuous. Detailed statistics are presented in Table 1. Predicting Emotions From Thinking Styles, Controlling for Age Results from hierarchical multiple-regressions indicated that statistically significant predictive relations were obtained for all five types of emotions. Across the five emotion scales, 6 of the 13 thinking styles were involved in the statistically significant predictions. The anger scale was positively predicted by the hierarchical style, with 9% of the variance in the former being explained by the latter beyond age. The depression scale was positively predicted by the hierarchical style but negatively predicted by the oligarchic style. The 2 styles accounted for 17% of the variance in the depression scale beyond age. The frustration scale was positively predicted by the hierarchical and liberal styles but negatively predicted by the anarchic style. The 3 styles contributed to 20% of the
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TABLE 1. Zero-Order Correlation Coefficients for Thinking Styles and Emotions (N = 99) Scale
Anger
Depression
Frustration
Happiness
Legislative Executive Judicial Global Local Liberal Conservative Hierarchical Monarchic Oligarchic Anarchic Internal External
.31** .06 .22* –.02 .20 .27* –.16 .28* .07 .12 .27* .09 .26*
.16 .08 .18 –.06 .03 .17 –.22* .33** –.04 –.13 .04 .02 .15
.26* .23* .27* –.09 .11 .31** –.22* .32** .25* .08 .07 .03 .22*
.11 .14 .22* .02 –.03 .18 –.10 .25* –.05 .02 .01 –.10 .27*
Attraction .05 .17 .26* –.09 .10 .09 .05 .14 .08 .01 .06 –.12 .08
*
p < .05. **p < .01.
variance in the frustration scale beyond age. The happiness scale was positively predicted by the external and hierarchical styles but negatively predicted by the anarchic style. The unique contribution of the 3 styles to the variance in happiness over age was 18%. Last, the attraction scale was positively predicted by the judicial styles and its unique contribution was 6%. See Table 2 for other details from these regression procedures. Discussion This study aimed to achieve two objectives: to validate the Chinese version of the IMEI (Hood & Jackson, 1997) for a sample of university students in Hong Kong and, more important, to understand the relations between university students’ thinking styles and their capacity for being aware of and managing their emotions, in particular, how their thinking styles contributed to their capacity when researchers take age and gender into consideration. Both objectives were achieved. The IMEI scales yielded reliabilities that are comparable to those obtained in the two existing studies of university students in the United States. It should be noted that the internal scale reliability for the attraction scale (α = .52) was substantially lower than that yielded by the U.S. data sets. This low internal scale consistency could have resulted from several possibilities; most notably, the notion of attraction might operate differently in the American culture and the
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TABLE 2. Contributions of Thinking Styles to Emotions Beyond Age (N = 99) Variable summary Variable Anger Age Hierarchical Depression Age Hierarchical Oligarchic Frustration Age Hierarchical Liberal Anarchic Happiness Age External Anarchic Hierarchical Attraction Age Judicial
Model summary
β weight
R
F
df
.11 .30**
.02a .11b
2.109a 4.76b*
1, 77 2, 76
.11 .41*** –.26*
.04a .15b .21c
3.02a 6.50b** 6.49c**
1, 75 2, 74 1, 77
.15 .41** .34** –.30*
.05a .14b .20c .25d
3.79a 5.93b** 5.82c** 5.90d***
1, 73 2, 72 3, 71 4, 70
.14 .33* –.36* .27*
.01a .08b .14c .19d
1.10a 3.66b* 3.97c* 4.13d**
1, 76 2, 75 3, 74 4, 73
.09 .24*
.02a .08b
1.31a 4.01b*
1, 76 2, 75
2
Note. List-wise cases exclusion was used. aPredictors were constant and age. bPredictors were constant, age, and the first style predictor. cPredictors were constant, age, the first style predictor, and the second style predictor. dPredictors were constant, age, the first style predictor, the second style predictor, and the third style predictor. * p < .05. **p < .01. ***p < .001.
Chinese culture. Thus, future studies using the Chinese version of this inventory are recommended to further modify and test the items in the attraction scale. Out of the many possible revisions of the items in the attraction scale, understanding the meaning of attraction among American students and among Chinese students is fundamental. I can discuss the validity of the inventory from three perspectives. The first pertains to the way in which the IMEI scales were correlated with one another. On the one hand, the moderate strength of the correlation coefficients among the scales suggests that the five scales assess an overarching construct: emotions. On the other hand, this moderate magnitude indicates that the correlations among the scales are low enough to be distinguished from one another. Second, the validity of the inventory is evident through the fact that the older students scored in the more favorable direction than did the younger ones on three of
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the five scales: anger, depression, and frustration. Chickering’s theoretical underpinnings expected this significant difference in emotions related to age. As they mature, students become more aware of and better at integrating their emotions. In the third perspective to determine the validity of the inventory, researchers observe how the emotion scales were related to the thinking styles. The way in which the two constructs were related to each other in the present data is largely supportive of the research hypothesis of this study. As expected, Type I thinking styles demonstrated the strongest predictive power for students’ ability to recognize and manage their emotions. From this perspective, researchers determine external validity of the IMEI. Apart from exploring the general relations between emotions and thinking styles by calculating zero-order correlation coefficients among the scales in the two inventories, I tested the predictive power of thinking styles for emotions, taking into consideration the effects of age on the two main variables. Putting together the two sets of the resultant statistics, I found that although most thinking styles (except the global, local, internal styles) are associated with emotions, only fewer than half (6 of 13) were significant predictors for emotions. Although the positive contributors to students’ abilities to cope with emotions are three of the five Type I styles (hierarchical, liberal, judicial) and a Type III style (the external style), the negative contributors are two Type III styles (anarchic, oligarchic). Researchers could argue that given that only 6 of the 13 thinking styles significantly contributed to the variance in emotions beyond age, these significant results might have been obtained by statistical chance. I would maintain that such an argument would be ill grounded. For at least three reasons, researchers should argue that the statistically significant regression results were more likely to reflect true variations in emotions as a function of thinking styles than to have been obtained by statistical chance. First, because there is no semantic resemblance between the statements in the TSI-R and in the IMEI, the statistically significant relations found between the two constructs cannot be considered coincidental. Second, the way in which thinking styles contributed to the variance in emotions (i.e., Type I styles positively contributed to positive emotions or to better control of negative emotions) is supportive of the predictions made earlier. It is more important that these results make substantive sense. For example, both the liberal and hierarchical styles predicted students’ scores on the frustration scale in a favorable direction. An individual with a liberal thinking style prefers to engage in tasks that involve novelty and ambiguity. An individual with a hierarchical thinking style tends to distribute attention to several tasks that are prioritized according to his or her valuing of the tasks. In both of these thinking styles, the propensity for taking risks, working creatively, and taking on the challenges of the complexity of a task is inherent. To illustrate, performing tasks in new ways (i.e., using the liberal style) often involves the risk of failure because there is no guarantee for success in taking up something new.
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Likewise, prioritizing tasks may also encounter resistant forces because one’s learning and work environment may not appreciate priorities. Yet, if the environment rewards such thinking styles (i.e., the use of such thinking styles are effective in dealing with the tasks at hand), an individual would become more assured of his or her abilities. Such self-assurance would, in turn, help the individual to better deal with the emotions—in particular, frustration, anger, and depressotypic feelings—typically encountered when he or she challenges the well-established rules (i.e., using creativity-generating styles). This logical argument, however, accords with the fact that our regression analyses used the thinking style scales as the independent variables and the emotion scales as the dependent variables. Such a discussion does not imply a causal relation between the two constructs. It is possible that an individual’s high capacity for dealing with negative feelings such as frustration, anger, and depression enables him or her to use creativitygenerating styles more often. A further caution is that people’s intellectual styles are malleable (Zhang & Sternberg, 2006). In an institution in which Type II styles are highly appreciated, using these styles may allow students to become more aware of and better at dealing with their emotions. Last, the statistically significant results were more likely to be reflective of the true differences in emotions partially because of thinking styles and because these findings are consistent with previous ones that suggested that intellectual styles are important in emotions. In particular, the main result of the present study supports the past general finding that Type I styles are more conducive to the development of people’s abilities to deal with negative emotions and to the enhancement of positive emotions (e.g., Campbell & Douglas, 1972; Deng et al., 2000; Hayden et al., 2006). Given these reasons, despite the fact that only 6 of the 13 thinking styles were statistically significant in predicting students’ emotions, researchers should conclude that thinking styles—along with factors such as culture, age, gender, and school environment—are significant in students’ emotions. Readers would want to know how I would interpret some of the apparently contradictory findings. For example, theoretically, the same style (i.e., the anarchic style) would be related to negative emotions (i.e., anger, frustration) in the same direction, whether positive or negative. However, although the zero-order correlation procedure revealed a positive relation between the anarchic style and the anger scale, regression results indicated that the anarchic style was a negative contributor to the frustration scale. One possible explanation is that although anger and frustration are related because both are negative emotions, they could differ significantly. As a result, they are related to the same thinking style (i.e., the anarchic style) in different fashions. However, it should be noted that the correlation coefficient between the anarchic style and anger was .27 and significant only at the .05 statistical level. By the same token, the anarchic style was the third predictor for the frustration scale, after the hierarchical and liberal styles. These data indicate that the relations of the anarchic style to the two types of emotions are rather weak. Therefore, these findings should not be taken at face value. Such an explanation, of course, is only a post
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hoc conjecture. Further research needs to find out the complexity of the relations between particular thinking styles and each type of emotion. Limitations, Conclusions, and Implications This study has three limitations. First, the research sample could be biased because the participants were from merely two academic disciplines. Thus, the results may not apply to students in other disciplines. Second, the Chinese version of the IMEI was tested for the first time among university students in Hong Kong. Although the psychometric properties of the inventory are generally good, further testing needs to determine the efficacy of the inventory in assessing the emotions of university students in Hong Kong. Third, inherent in this study might be a cultural bias because the IMEI is grounded in a theory intended for university students in the United States. Given the many differences between the American and Chinese higher education systems, the factors that interact with thinking styles to contribute to the development of students’ positive emotions (or effective management of negative emotions) may be more complex than those I described here. With these limitations, the study can be viewed as only exploratory, and its results should be considered tentative rather than definitive. Regardless of these limitations, the significance of this study can be derived from two major findings. First, the present study has obtained initial evidence for the IMEI among a sample of university students in Hong Kong. Further investigation of the reliability and validity of the inventory for measuring the emotions of university students in Hong Kong, as defined in Chickering’s theory, is necessary because the present study was only the first of its kind, and because the internal reliability for one of the scales (i.e., attraction) was relatively low. Nevertheless, the initial reliability and validity data determined in this study denote that the inventory may become a potential assessment tool for university counselors in Hong Kong in helping students to understand and manage their emotions. Second and more important, although the relational patterns of emotions to the Type II and the anarchic styles were not clear, it is obvious that Type I thinking styles and the external thinking style were strongly and positively associated with (and some even significantly predicted) students’ emotions. Furthermore, it was established that the oligarchic style was strongly and negatively associated with (and significantly predicted) students’ emotions. This general finding aligns with Zhang’s (2002a, 2008) finding that Type I thinking styles positively contributed to students’ psychosocial development, including their sense of purpose (Zhang, 2002a) and sense of identity (Zhang, 2008). The present findings have advanced our understanding of the significant function of thinking styles in psychosocial development. As I reviewed earlier, the importance of thinking styles goes beyond its role in student learning. Previous studies have shown that thinking styles are related
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to attributes such as self-esteem (Zhang & Postiglione, 2001), career personality types (Zhang, 2000), cognitive development (Zhang, 2002b), and personality traits (Zhang & Huang, 2001). Studies that investigated other style constructs found similar results. For example, I found that the field-dependence versus field-independence construct was significantly related to attributes such as moral maturity (e.g., Schleifer & Douglas, 1973) and sense of identity (e.g., Bhatnager & Rastogi, 1986), as well as emotions (Campbell & Douglas, 1972; Deng et al., 2000). On the basis of repeated empirical evidence for the intricately entwined link between intellectual styles and other human attributes—including that between thinking styles and students’ emotions—researchers would argue that thinking styles and emotions should be considered as two integral parts of a holistic student development at a scientific level. Moreover, at a practical level, researchers would argue that the present findings, like many of the earlier ones, call for joint ventures between teaching faculty and student development educators to achieve their goal of fostering students’ well-rounded development. Teaching faculty could support students in developing their capacity for dealing with emotions by promoting a wide range of thinking styles—in particular, Type I styles and the external style—and discouraging students from taking on too many tasks without any priority (i.e., avoiding using the oligarchic style). Meanwhile, student development educators could facilitate students’ effective use of thinking styles by helping them to understand and manage their emotions better. AUTHOR NOTE Li-fang Zhang is an associate professor and the associate dean (Research Higher Degrees) in the Faculty of Education at the University of Hong Kong. Her recent book with Robert J. Sternberg is titled The Nature of Intellectual Styles (Routledge, 2006). Her research interests include intellectual styles, giftedness, personality, and student development in higher education. REFERENCES Bagley, C., & Mallick, K. (1998). Field independence, cultural context and academic achievement: A commentary. British Journal of Educational Psychology, 68, 581–587. Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Beck Depression Inventory-II (2nd ed.). San Antonio, TX: Psychological Corporation. Bhatnager, P., & Rastogi, M. (1986). Cognitive style and basic ideal disparity in males and females. Indian Journal of Current Psychological Research, 1, 36–40. Biggs, J. B. (1978). Individual and group differences in study processes. British Journal of Educational Psychology, 48, 266–279. Campbell, S. B., & Douglas, V. I. (1972). Cognitive styles and responses to the threat of frustration. Canadian Journal of Behavioral Science, 4(1), 30–42. Cattell, R. B., Cattell, A. K., & Cattell, H. E. (1978). 16 personality factor questionnaire. Champaign, IL: Institute for Personality and Ability Testing.
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Chickering, A. (1969). Education and identity. San Francisco: Jossey-Bass. Chickering, A., & Reisser, L. (1993). Education and identity (2nd ed.). San Francisco: Jossey-Bass. Ciarrochi, J., Deane, F. P., Wilson, C. J., & Rickwood, D. (2002). Adolescents who need help the most are the least likely to seek it: The relationship between low emotional competence and low intention to seek help. British Journal of Guidance & Counselling, 30, 173–188. Costa, P. T., Jr., & McCrae, R. R. (1992). The NEO-PI-R: Professional manual. Odessa, FL: Psychological Assessment Resources. Deng, Z., Li, D., & Zhang, Q. (2000). Cognitive styles, scholastic attainments with the Cattell’s 16PF: A correlative approach. Psychological Science China, 23, 234–235. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125, 276–302. Erikson, E. H. (1959). Identity and the life cycle. Psychological Issues Monograph (Vol. 1). New York: International Universities Press. Eysenck, H. J., & Eysenck, S. B. G. (1964). Manual of the Eysenck Personality Inventory. London: Hodder and Stoughton. Fan, W. Q. (2006). Thinking styles among university students in Shanghai: Comparing traditional and hypermedia instructional environments. Unpublished doctoral dissertation, University of Hong Kong. Gadzella, B. M. (1999). Differences among cognitive-processing styles groups on personality traits. Journal of Instructional Psychology, 26, 161–166. Globerson, T., & Zelniker, T., eds. (1989). Cognitive style and cognitive development. Human development (Vol. 3, edited). Norwood, NJ: Ablex. Gregorc, A. F. (1979). Learning/teaching styles: Potent forces behind them. Educational Leadership, 36, 234–236. Guilford, J. P. (1967). The nature of human intelligence. New York: McGraw-Hill. Hayden, E. P., Klein, D. N., Durbin, C. E., & Olino, T. M. (2006). Positive emotionality at age 3 predicts cognitive styles in 7-year-old children. Development and Psychopathology, 18, 409–423. Hilliard, R. I. (1995). How do medical students learn: Medical student learning styles and factors that affect these learning styles. Teaching and Learning in Medicine, 7, 201–210. Holland, J. L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Prentice-Hall. Hood, A. B. (Ed.). (1986). The Iowa Student Development Inventories (1st ed.). Iowa City, IA: HITECH Press. Hood, A. B. (Ed.). (1997). The Iowa Student Development Inventories (2nd ed.). Iowa City, IA: HITECH Press. Hood, A. B., & Jackson, L. M. (1997). The Iowa Managing Emotions Inventory. In A. B. Hood (Ed.), The Iowa student development inventories (2nd ed.; pp. 22–31). Iowa City, IA: HITECH Press. Jong, P. J. D., Merckelbach, H., & Nijman, H. (1995). Hemisphere preference, anxiety, and covariation bias. Personality and Individual Differences, 18, 363–371. Jung, C. (1923). Psychological types. New York: Harcourt Brace. Kagan, J. (1965). Individual differences in the resolution of response uncertainty. Journal of Personality and Social Psychology, 2, 154–160. Kaufman, J. C. (2001). Thinking styles in creative writers and journalists. Dissertation Abstracts International (Section B): The Physical Sciences and Engineering, 62(3B), 1069. Kirton, M. J. (1976). Adaptors and innovators: A description and measure. Journal of Applied Psychology, 61, 622–629.
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Kogan, N. (1980). A style of life, a life of style (review of cognitive styles in personal and cultural adaptation). Contemporary Psychology, 25, 595–598. Mansfield, E. A. (1998). Working memory development in adolescents: A neo-Piagetian investigation. Dissertation Abstracts International (Section A): Humanities and Social Sciences, 58(8-A), 3001. Mayer, J. D., Salovey, P., Caruso, D. R., & Sitarenios, G. (2001). Emotional intelligence as a standard intelligence. Emotion, 1, 232–242. Messick, S. (1996). Bridging cognition and personality in education: The role of style in performance and development. European Journal of Personality, 10, 353–376. Mischel, W., & Ayduk, O. (2004). Willpower in a cognitive-affective processing system: The dynamics of delay of gratification. In R. F. Baumeister & K. D. Vohs (Eds.), Handbook of self-regulation: Research, theory, and applications (pp. 99–129). New York: Guilford Press. Mischel, W., & Shoda, Y. (1999). Integrating dispositions and processing dynamics within a unified theory of personality: The cognitive-affective personality system. In L. A. Pervin & O. P. John (Eds), Handbook of personality: Theory and research (2nd ed.; pp. 197–218). New York: Guilford Press. Morgan, H. (1997). Cognitive styles and classroom learning. Westport, CT: Praeger Publishers. Mortenson, S. T. (2006). Cultural differences and similarities in seeking social support as a response to academic failure: A comparison of American and Chinese college students. Communication Education, 55, 127–146. Riding, R., & Cheema, I. (1991). Cognitive styles: An overview and integration. Educational Psychology, 11, 193–215. Riding, R. J., & Wigley, S. (1997). The relationship between cognitive style and personality in further education students. Personality and Individual Differences, 23, 379–389. Saleh, A. I. (1998). The nexus of brain hemisphericity, personality types, temperaments, learning styles, learning strategies, gender, majors, and cultures. Dissertation Abstracts International (Section A): Humanities and Social Sciences, 58(8-A), 3004. Schleifer, M., & Douglas, V. I. (1973). Moral judgments, behavior and cognitive style in young children. Canadian Journal of Behavioral Science, 5, 133–144. Spangler, G., Pekrun, R., Kramer, K., & Hofmann, H. (2002). Students’ emotions, physiological reactions, and coping in academic exams. Anxiety, Stress, and Coping, 15, 413–432. Sternberg, R. J. (1988). Mental self-government: A theory of intellectual styles and their development. Human Development, 31, 197–224. Sternberg, R. J. (1997). Thinking styles. New York: Cambridge University Press. Sternberg, R. J., & Wagner, R. K. (1992). Thinking Styles Inventory. Unpublished manuscript, Yale University, New Haven, Connecticut. Sternberg, R. J., Wagner, R. K., & Zhang, L. F. (2003). Thinking Styles Inventory— Revised. Unpublished manuscript, Yale University, New Haven, Connecticut. Torrance, E. P. (1988). SOLAT (style of learning and thinking) manual. Bensenville, IL: Scholastic Testing Service. Torrance, E. P., Taggart, B., & Taggart, W. (1984). Human information processing survey. Bensenville, IL: Scholastic Testing Service. Westreich, A. H., Ritzler, B., Duncan, J. (1997). Relationship between cognitive style and defensive style. Perceptual and Motor Skills, 84, 1011–1023. White, D. B. (1986). An assessment and validation of Chickering’s seven vectors of student development. Unpublished doctoral dissertation, University of Iowa, Iowa City. White, D. B., & Hood, A. B. (1989). An assessment of the validity of Chickering’s theory of student development. Journal of College Student Development, 30, 354–361.
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Winston, R. B., Jr., Miller, T. K., & Prince, J. S. (1987). Student developmental task and lifestyle inventory. Athens, GA: Student Development Associates. Witkin, H. A. (1962). Psychological differentiation: Studies of development. New York: Wiley. Zhang, L. F. (2000). Are thinking styles and personality types related? Educational Psychology, 20, 271–283. Zhang, L. F. (2002a). The role of thinking styles in psychosocial development. Journal of College Student Development, 43, 696–711. Zhang, L. F. (2002b). Thinking styles and cognitive development. The Journal of Genetic Psychology, 163, 179–195. Zhang, L. F. (2003). Contributions of thinking styles to critical thinking dispositions. The Journal of Psychology, 137, 517–544. Zhang, L. F. (2004a). Do university students’ thinking styles matter in their preferred teaching approaches? Personality and Individual Differences, 37, 1551–1564. Zhang, L. F. (2004b). Thinking styles: University students’ preferred teaching styles and their conceptions of effective teachers. The Journal of Psychology, 138, 233–252. Zhang, L. F. (2005). Validating the theory of mental self-government in a non-academic setting. Personality and Individual Differences, 38, 1915–1925. Zhang, L. F. (2008). Thinking styles and identity development among Chinese university students. American Journal of Psychology, 121(2), 255–271. Zhang, L. F., & Higgins, P. (2008). The predictive power of socialization variables for thinking styles among adults in the workplace. Learning and Individual Differences, 18, 11–18. Zhang, L. F., & Huang, J. F. (2001). Thinking styles and the five-factor model of personality. European Journal of Personality, 15, 465–476. Zhang, L. F., & Postiglione, G. A. (2001). Thinking styles, self-esteem, and socio-economic status. Personality and Individual Differences, 31, 1333–1346. Zhang, L. F., & Sachs, J. (1997). Assessing thinking styles in the theory of mental selfgovernment: A Hong Kong validity study. Psychological Reports, 81, 915–928. Zhang, L. F., & Sternberg, R. J. (2005). A threefold model of intellectual styles. Educational Psychology Review, 17, 1–53. Zhang, L. F., & Sternberg, R. J. (2006). The nature of intellectual styles. Mahwah, NJ: Erlbaum.
Original manuscript received July 24, 2007 Final version accepted October 31, 2007
Leaning
Scope
Level
Form
Legislative Executive
Function
Hierarchical Monarchic Oligarchic Anarchic Global Local Internal External Liberal Conservative
Judicial
Thinking style
Dimension
Work on tasks that require creative strategies; one prefers to choose one’s own activities. Work on tasks with clear instructions and structures; one prefers to implement tasks with established guidelines. Work on tasks that allow for one’s evaluation; one prefers to evaluate and judge the performance of other people. Distribute attention to several tasks that are prioritized according to one’s valuing of the tasks. Work on tasks that allow complete focus on one thing at a time. Work on multiple tasks in the service of multiple objectives, without setting priorities. Work on tasks that would allow flexibility as to what, where, when, and how one works. Pay more attention to the overall picture of an issue and to abstract ideas. Work on tasks that require working with concrete details. Work on tasks that allow one to work as an independent unit. Work on tasks that allow for collaborative ventures with other people. Work on tasks that involve novelty and ambiguity. Work on tasks that allow one to adhere to the existing rules and procedures in performing tasks.
Key characteristics
APPENDIX A Thinking Styles in the Theory of Mental Self-Government
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Concrete random
Mode of thinking Personality type
e
Adaptation Impulsivity Convergent thinking Field dependent Executive, local, monarchic, conservative
Concrete sequential
Analytic Sensing, judging
Surface Conventional
Type II
Oligarchic, anarchic, internal, external
Achieving Realistic, investigative, social, enterprising Integrative Thinking, feeling, introversion, extraversion Abstract random, abstract sequential
Type III
Note. Theoretical foundations: aBiggs’s theory of student learning (J. B. Biggs, 1978); bHolland’s theory of career personality types (J. L. Holland, 1973); cTorrance’s construct of brain dominance (E. P. Torrance, 1988); dJung’s theory of personality types (C. Jung, 1923); eGregorc’s model of mind styles, (A. F. Gregorc, 1979); fKirton’s model of decision-making styles (M. J. Kirton, 1976); gKagan’s model of reflectivity-impulsivity conceptual tempo (J. Kagan, 1965); hGuilford’s model of structure of intellect (J. P. Guilford, 1967); iWitkin’s construct of field-dependence/independence (H. A. Witkin, 1962); jSternberg’s theory of mental self-government (R. J. Sternberg, 1988).
g
Decision-making style Conceptual tempo h Structure of intellect i Perceptual style j Thinking style
f
Mind style
d
Innovation Reflectivity Divergent thinking Field independent Legislative, judicial, global, hierarchical, judicial
Holistic Intuitive, perceiving
c
b
Deep Artistic
Type I
Learning approach Career personality type
a
Style type/construct
APPENDIX B Three Types of Intellectual Styles
Zhang 515
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