the role of learning environments in thinking styles

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The role of learning environments inthinking stylesJieqiong Fana & Li-fang Zhanga

a Faculty of Education, The University of Hong Kong, Hong Kong.Published online: 02 Aug 2013.

To cite this article: Jieqiong Fan & Li-fang Zhang (2014) The role of learning environments inthinking styles, Educational Psychology: An International Journal of Experimental EducationalPsychology, 34:2, 252-268, DOI: 10.1080/01443410.2013.817538

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The role of learning environments in thinking styles

Jieqiong Fan* and Li-fang Zhang

Faculty of Education, The University of Hong Kong, Hong Kong

(Received 31 August 2012; final version received 17 June 2013)

The present study examined the association between students’ perceived generallearning environment and their thinking styles (a specific term for ‘intellectualstyles’). Seven hundred and fifty-two undergraduates in Shanghai responded tothe Thinking Style Inventory-Revised II and the Inventory of Students’Perceived Learning Environment. Results indicated that students’ perceivedlearning environment statistically predicted their thinking styles beyond gender,grade, major, and socio-economic status. Specifically, constructivist-orientedteaching, as well as peer morale and identities, were mainly associated withthinking styles that are characterised by cognitive complexity, nonconformity,autonomy and low degrees of structure (known as Type I styles), while cleargoals and coherence of curricula mainly statistically predicted thinking stylesthat are characterised by cognitive simplicity, conformity, authority, and highdegrees of structure (known as Type II styles). Student–student cooperation, thenature of assessment and assignments and learning facilities also statisticallycontributed to thinking styles to varying extents. The implications andlimitations of the present findings are discussed.

Keywords: thinking style; learning environment

Introduction

Intellectual styles

Intellectual style, broadly defined as people’s preference for processing informationand dealing with tasks (Zhang & Sternberg, 2005), has been frequently used toexplain performance beyond ability and personality (Pashler, McDaniel, Rohrer, &Bjork, 2009; Zhang, 2006). ‘Intellectual style’ is an encompassing term that includesvarious style constructs (e.g. cognitive styles, learning styles and thinking styles).Based on both theoretical conceptualisation and empirical evidence, Zhang andSternberg (2005) classified all styles into three types. Type I styles (e.g. the field-inde-pendent style and the deep learning approach) tend to be creativity-generating andcognitively complex. These styles were often found to be related to more adaptivedevelopmental outcomes, such as openness and mental health. Type II styles (e.g. thefield-dependent style and the surface learning approach) tend to be norm-favouringand cognitively simplistic. These styles were usually related to less desirableattributes, such as neuroticism and pessimism. Type III styles (e.g. internal andexternal) manifest either Type I or Type II characteristics depending on the specificcontext involved. Therefore, Type III styles are value-differentiated.

*Corresponding author. Email: [email protected]

Educational Psychology, 2014Vol. 34, No. 2, 252–268, http://dx.doi.org/10.1080/01443410.2013.817538

� 2013 Taylor & Francis

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Researchers have made great efforts to explore antecedents of intellectual stylesso that styles that benefit students’ development can be cultivated. As one of theproximal environments where students reside, learning environments undoubtedlyshould be examined. Although intellectual styles are not merely developed inlearning environments, the examination of the relationships of learningenvironments to thinking styles can provide empirical data that could inform themalleability of styles and identify some possible environmental factors thatcontribute, at least partially, to the development of intellectual styles.

Learning environments

Learning environment is generally identified as ‘the social, psychological, andpedagogical contexts in which learning occurs and which affect student achievementand attitudes’ (Fraser, 1998, p. 3). The view on the nature of the effective learningenvironment for students’ high-quality learning has been changing along with thedevelopment of various learning theories. After behaviourism and cognitivism,constructivism has become more and more influential in education in thecontemporary era (Phillips, 2000; Tobin & Tippins, 1993).

Generally speaking, constructivism views learning as a process of activeknowledge construction (Brooks & Brooks, 1993; Loyens & Gijbels, 2008; Steffe &Gale, 1995). That means, firstly, that learners play an active role in learning processes.Secondly, knowledge is constructed by learners themselves with their own interpreta-tions of contradictory situations and through integrating new knowledge with priorexperiences, suggesting that knowledge is relative and subjective. Although there aresome variations of constructivism, such as cognitive constructivism, radicalconstructivism, and social constructivism, they still share a consensus that learning isa process of active knowledge construction. Based on this core belief, manyeducational principles were proposed. Among them, four educational principles arefrequently addressed in the literature.

Constructivist learning

Like many scholars, De Corte (1995, 2000) believed that learning is a process ofknowledge construction rather than simple transmission or reproduction ofknowledge and emphasised that teachers should create a powerful environment thatwould encourage students’ high-quality thinking. Collis and Winnips (2002) alsopointed out that it is important to make sense of the subject matter and helpstudents construct their mental models, which could be applicable to new fields andsituations. Similarly, Moreno and Mayer (1999) stressed the significance of helpingstudents understand the deep structure and process underlying the subject matter.Thus, the major focus of teachers and educators should be showing students how toconstruct knowledge by teaching instead of just teaching students to memoriseinformation. Meanwhile, students should be provided with abundant opportunitiesto experience the process of knowledge construction in a variety of helpfulactivities, including case studies, interest groups, internships and seminars.

Student autonomy

The second important point of constructivism is that learners play an active role inthe learning process. As Vermunt (2003) stated, making students be responsible for

Educational Psychology 253

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the learning process could facilitate the development of their self-directed learningand independent thinking. De Corte (1995, 2000) also supported the view that theencouragement of students’ self-regulation in studying is an important factor in aneffective learning environment. Thus, it is important for teachers and educators toallow student autonomy in their learning, to make them participate in the teachingprocess, and to cultivate students’ habit of self-study.

Interaction and cooperation

The third important point of constructivism is that teachers are no longer sages.They are just facilitators, so are peers. According to Vygotsky’s (1978) theory on‘scaffolding’, which is one of the foundations of constructivism, appropriate helpfrom teachers and peers is beneficial to student development. This kind of appropri-ate help can be largely facilitated by the interaction between teachers and studentsand the cooperation among students (Pontecorvo, 1993). Interaction and cooperationare also conducive to students’ initiatives in learning processes and to their criticalreflection of knowledge (De Corte, 1995, 2000; Van Merriënboer & Paas, 2003).Therefore, an effective learning environment should provide a good condition whereinteraction with teachers and cooperation with peers are encouraged.

Clear goals and coherence of curricula

Many criticisms on the efficacy of constructivism are about its minimal instructionstrategy. However, this understanding is a misinterpretation of constructivism(Tobias & Duffy, 2009). Actually, clear learning goals for students are consideredas a driver for learning and they are helpful in the process of knowledgeconstruction (Tobias & Duffy, 2009). Furthermore, if courses proceed in a way thatis oriented by the learning goal and if they make sense to students, it can be seenas a good demonstration of a process of knowledge construction. As Broekkamp,van Hout-Wolters, Rijlaarsdam, and van den Bergh (2002) pointed out, clear goalsand coherence of curricula had a great influence on students’ learning process, suchas learning strategies. Actually, the learning environment factor concerning cleargoals and coherence of curricula has been frequently included in learningenvironment inventories (e.g. Entwistle, McCune, & Hounsell, 2003; Kember &Leung, 2009; Ramsden, 1991; Wierstra, Kanselaar, Linden, & Lodewijks, 1999)Therefore, it is reasonable to see clear goals and coherence of curricula as essentialcharacteristics of effective learning environments.

Influenced by constructivism, considerable instructional modals or teachingstrategies are developed, including student/learner-centred approach, cooperativelearning, problem-based learning (PBL), situated learning, portfolio-based learning,experiential and inquiry-based teaching (Baeten, Dochy, & Struyven, 2008; Lave &Wenger, 1991; Loyens, Rikers, & Schmidt, 2009; Savery & Duffy, 1996; Slavin,2003). Ample studies have been conducted based on these instructional models orteaching strategies to see whether or not they are effective for student learning.

Most studies used academic achievement as the outcome variables in examiningthe effectiveness of learning environments with some constructivist features (e.g.Carpenter & Fennema, 1992; Knapp, 1995; Neale, Smith, & Johnson, 1990; Slavin,2003). For example, achievement was found to be enhanced by self-regulatedlearning (Harris, Santangelo, & Graham, 2008; Mason, 2004). Weinberger and

254 J. Fan and L. Zhang

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McCombs (2001) also found that learner-centred pedagogy was beneficial forstudent academic performance. After a review of studies on cooperative learning,Slavin (2003) found that cooperative learning with elements of group goals andindividual accountability had great positive influence on student achievement acrosssubjects and schools. However, the positive effect of constructivist learningenvironments on academic achievement was not always detected (e.g. Dethlefs,2003; Kirschner, Sweller, & Clark, 2006; Klein & Schnackenberg, 2000). Forexample, Albanese and Mitchell (1993) reviewed studies on PBL in medicalprogrammes and found that in some studies, PBL graduates had better performanceon clinical examinations and faculty evaluations than peers who were trainedtraditionally, while in some other studies, PBL did not show its superiority totraditional teaching methods. In fact, some studies even found that students in PBLclasses had lower scores when basic science examinations were used as indicatorsfor academic achievement. In a collaborative, project-based engineering coursedesigned by Dinsmore, Alexander, and Loughlin (2008), students’ improvement ondeclarative knowledge was found, but no improvement was found on proceduralknowledge and principled knowledge. The inconsistent results from studies concern-ing the effects of the constructivist learning environment may be one of reasonswhy educational principles based on constructivism have been criticised andquestioned. However, these inconsistent results may largely have to do with the factthat different studies use different measures of academic achievement which madethe findings from these studies unfit for comparision. Furthermore, it is possible thatacademic achievement is a questionable indicator for the effectiveness of theconstructivist learning environment because its validity depends on the nature ofassessments and examinations. For this reason, some scholars (e.g. Loyens &Gijbels, 2008; Ozkal, Tekkaya, Cakiroglu, & Sungur, 2009) called for the expansionof the range of outcomes examined in studies. Recently, researchers began to exam-ine learning environmental effects on students’ conceptions of learning, academicefficacy, and some practical skills. Positive contributions of constructivist learningenvironments to the aforementioned student learning and developmental outcomeswere demonstrated (e.g. Dorman & Adams, 2004; Lin, 2004; Loyens et al., 2009;Tolhurts, 2007). Nonetheless, studies that examined the effects of learning environ-ments on learning outcomes beyond academic performance are still quite limited.Therefore, in the present study, intellectual styles were involved to further explorethe effectiveness of constructivist learning environments on student development.

Learning environments and intellectual styles

There are a handful of studies that explored the influence of some aspects oflearning environments on student intellectual styles (e.g. Baeten et al., 2008;Gijbels, Segers, & Struyf, 2008; Gordon & Debus, 2002; Luk, 1998). Among thesestudies, most of them assessed intellectual styles based on Biggs’ (1978) theory oflearning approaches (one model of intellectual styles) and several other studies werebased on Witkin’s (1962) theory of field-dependence/independence (also a model ofintellectual styles). However, findings from these studies are also inconsistent. Onthe one hand, some studies supported the positive effects of constructivist learningenvironments on the deep learning approach. For example, Wilson and Fowler(2005) compared a conventional course and an action course (with project workand learning group) and found that in the action-designed course, students who


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were initially deep learners maintained their learning approach at the end of thecourse, while students who were surface learners at the beginning of the coursechanged their learning styles to the deep learning approach. Gordon and Debus(2002) also found similar changes when teaching methods were modified by coop-erative group PBL pedagogy. Nijhuis, Segers, and Gijselaers (2008) also demon-strated that clear goals, independent learning, and proper workload were positivelyrelated to the deep learning approach.

On the other hand, some other studies failed in supporting the argument that con-structivist learning environments have positive effects on cultivating students’ deeplearning approach (Klinger, 2006; McParland, Noble, & Livingston, 2004). In fact,some studies even found that courses designed according to constructivist principlesincreased surface learning among students (Gijbels et al., 2008; Groves, 2005).

The inconsistency of findings also exists in studies centred on the style constructof field dependence/independence. For example, Luk (1998) found that, in a self-directed learning environment created by a distance education programme, studentsbecame more field independent. Cathcart (1990) also found that LOGO instructiondesigned based on constructivist principles had a positive relationship with students’field independence. However, another study (Azadi, 2009) that compared problemsolving method and lecturing in classes failed in proving the unique contribution ofconstructivist learning environments to the development of students’ fieldindependence.

Many factors may be responsible for the inconsistent findings in theaforementioned studies. In addition to the discrepancies of learning subjects, learn-ing contents, and learning outcomes involved in different studies, some scholars(Baeten et al., 2008; Rikers, van Gog, & Paas, 2008) also referred to the power ofthe long-standing general educational environment, suggesting that the effectivenessof particular course or programme examined in most studies would be offset by theinfluence of many other factors in the general learning environment. Therefore, thepresent study examined comprehensively the potential influence of the generallearning environment instead of a specific course. That is to say, the study assessedstudents’ general impression of all courses they had taken and examined environ-mental factors outside the classroom as well. In addition, existing studies thatexplored the influence of learning environments on intellectual styles only involvedtwo style models (i.e. learning approach and field dependence/independence). Thesemodels essentially specified two opposite styles that fall along one dimension (i.e.deep learning vs. surface learning; and field dependence vs. field independence),which made it impossible for these studies to conduct a comprehensive examinationof the effects of learning environments on intellectual styles. Therefore, Sternberg’s(1997) theory of mental self-government, which involves three traditions (i.e.cognition-centred, personality-centred, and activity-centred) of style studies, wasadopted in the present study to assess intellectual styles.

The theory of mental self-government describes 13 thinking styles that fall alongfive dimensions: function, form, level, scope and leaning. The 13 styles were recon-ceptualised into three types corresponding to the three types of intellectual styles(Zhang, 2002). Specifically, the legislative, judicial, global, liberal, and hierarchicalstyles were classified as Type I styles; the executive, local, conservative, and monar-chic styles were classified as Type II styles; and the oligarchic, anarchic, internal,and external styles were classified as Type III styles (see details in Appendix).


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The present study

The present study aimed at investigating the contributions of the general universitylearning environment perceived by students to their thinking styles in a statisticalsense. University learning environment was selected because university years havebeen shown to be a critical period of time during which many changes andchallenges happen. During this transitional period, in order to adapt themselves touniversity learning environments, university students may have to developthemselves in many ways, including cognitively (Tanner, Arnett, & Leis, 2009).

In literature, it has been shown that a constructivist learning environment usuallyaims at encouraging students to experience the process of knowledge constructionthrough explorations and to be autonomous in their learning. These objectives arein line with the characteristics of Type I styles that manifest autonomy, initiativeand creativity; and meanwhile, they are contrary to the characteristics of Type IIstyles that are instruction-conforming and conservative. Therefore, it washypothesised that statistically, constructivist learning environments would positivelycontribute to Type I thinking styles (Hypothesis 1) and negatively contribute toType II thinking styles (Hypothesis 2). As the nature of Type III styles iscontext-dependent, no specific hypothesis concerning Type III styles was made.

Methodology

Participants

Seven hundred and fifty-two undergraduate students in Shanghai participated in thisstudy. Among them, 419 were males and 333 were females. Five hundred and nineof them were sophomores and 243 of them were seniors. Concerning academicmajors, 225 students were from humanities and social sciences while 527 were fromscience and engineering.

Inventories

The participants responded to the Thinking Style Inventory-Revised II (TSI-R2,Sternberg, Wagner, & Zhang, 2007) and the Inventory of Students’ PerceivedLearning Environment (ISPLE) particularly designed for this study. They alsoprovided some demographic information, including gender, grade, major,hometown, and socioeconomic status (SES).

The TSI-R2 consists of 65 items. Each of the five items assess one of the 13thinking styles based on Sternberg’s (1997) theory of thinking styles (e.g. forlegislative style, ‘When faced with a problem, I use my own ideas and strategies tosolve it’; and for executive style, ‘I like to figure out how to solve a problemfollowing certain rules’). Participants were asked to rate themselves on a 7-pointscale, with 1 indicating that the statement does not describe them at all and 7indicating that the statement characterises them extremely well.

To our best knowledge, existing inventories assessing learning environments weredesigned to assess learning environments within particular courses and they merelydealt with limited range of dimensions of learning environments. In order to assessstudents’ perceptions of various learning dimensions in their general learning environ-ment, the present researchers developed a comprehensive inventory ISPLE especiallyfor this study. The contents of the inventory concern all of the four common featuresof a constructivist learning environment (summarised in Section “Learning environ-


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ments”). Furthermore, the dimensions of the inventory were developed based onEntwistle et al.’s (2003) conceptual model of teaching-learning environments and onseveral existing inventories, including Student Engagement Questionnaire (Kember &Leung, 2009), the Experiences of Teaching and Learning Questionnaire (Entwistleet al., 2003), College Student Experience Questionnaire (Pace & Kuh, 2007), andInventory of Perceived Study Environment (Wierstra et al., 1999). Dimensions thatwere frequently found in the factor analysis of these inventories and fit into theconceptual model of Entwistle et al. (2003) were selected. In addition, dimensionsconcerning learning environments outside the classroom were added. Eventually,eight dimensions were identified: (1) constructivist-oriented teaching; (2) clear goalsand coherence of curricula; (3) student autonomy; (4) assessments and assignments;(5) teacher–student interaction; (6) student-student cooperation; (7) peer morale andidentities; and (8) learning facilities. Each dimension consists of four items (e.g. forconstructivist-oriented teaching, ‘The courses give me a sense of what goes on“behind the scenes” in the subject areas’; for student autonomy, ‘We are given somechoices over how we go about learning’; and for learning facilities, ‘There are a greatdeal of opportunities, such as extracurricular activities and lab internship, where Icould practice what I learned’). Because the ISPLE was a new inventory, both thereliability and the factor structure were examined.

Data analyses

Estimates of internal consistency and confirmatory factor analysis were conductedto ascertain the psychometric properties of the ISPLE. The reliability of the TSI-R2was also estimated by Cronbach’s alpha coefficients. MANOVA and correlationswere conducted to examine the relationships between demographic factors (i.e.gender, grade, major, hometown, and SES) and the key variables (i.e. the perceivedgeneral learning environment and thinking styles). Multiple regressions wereconducted to predict thinking styles from learning environments with relevantdemographic factors being controlled.

Results

Psychometric properties of the inventories

The reliabilities of the TSI-R2 and the ISPLE

The Cronbach’s alpha coefficients of 13 scales of the TSI-R2 were .80 (legislative),.72 (executive), .79 (judicial), .68 (global), .76 (local), .87 (liberal), .80 (conserva-tive), .82 (hierarchical), .75 (monarchic), .80 (oligarchic), .71 (anarchic), .76(internal) and .83 (external). The Cronbach’s alpha coefficients of eight scales ofthe ISPLE were .75 (constructivist-oriented teaching), .69 (clear goals andcoherence of curricula), .64 (student autonomy), .67 (assessments and assignments),.75 (teacher–student interaction), .79 (student–student cooperation), .76 (peer moraleand identities), and .63 (learning facilities). These data suggested that thereliabilities of both the TSI-R2 and the ISPLE were acceptable.

The factor structure of the ISPLE

The model fit indices for eight-factor model of the ISPLE were as follows:Chi-square (df = 436, N= 752) = 2046.27, p< .001, RMSEA= .070, SRMR= .050,


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GFI = .85, AGFI = .82, NFI = .95, NNFI = .96, CFI = .96, PGFI = .71, andCN= 211.13. The factor loading of each item is shown in Table 1. These resultsshowed that, although there was room for improving the ISPLE, the eight-factorsolution was generally acceptable.

The role of learning environments in students’ thinking styles

The MANOVA yielded the following statistically significant relationships betweensome demographic factors and the key variables: gender (F= 1.78, p< .05) andgrade (F= 3.08, p< .001) made statistical differences in students’ thinking styles,while students from different majors had different perceptions of their learningenvironment (F= 2.16, p< .05). The results of subgroup comparisons based on gen-der, grade, and major were presented in Table 2.

Specifically, male students scored significantly higher in the liberal, anarchic,and internal styles than female students, while seniors scored significantly higherin the global, conservative, oligarchic, and anarchic styles than sophomores.Only one difference in the perceptions of learning environment was found basedon majors – that students from science and engineering perceived their peers asbeing more proactive in learning than students from humanities and socialsciences. In addition, results from correlations showed that SES was positivelyrelated to two dimensions of students’ perceived learning environment: construc-tivist-oriented teaching (r= .09, p< .05) and student–student cooperation (r= .09,p< .05). Meanwhile, SES was also related to five thinking styles: legislative(r= .08, p< .05), judicial (r= .08, p< .05), global (r= .10, p< .01), local (r=�.09,p< .05), and hierarchical (r= .11, p< .01). Because gender, grade, major and SESwere found to have statistically significant relationships with the key variables,they were put under control in multiple regressions of thinking styles onlearning environments.

Results from multiple regressions showed that six of eight dimensions oflearning environment uniquely contributed to students’ thinking styles in a statisticalsense (Table 3). The amount of variance in thinking styles that was explained bylearning environments ranged from 6% to 31%. Specifically, five dimensions of theconstructivist learning environment statistically predicted thinking styles that arecharacterised by cognitive complexity, nonconformity, autonomy, and low degreesof structure (i.e. Type I styles), where constructivist-oriented teaching, peer moraleand identities, and learning facilities were major contributors. Meanwhile, fivedimensions of the learning environment statistically predicted thinking styles thatare characterised by cognitive simplicity, conformity, authority, and high degrees ofstructure (i.e. Type II styles), where clear goals and coherence of curricula,assessments and assignments and learning facilities were major contributors. Inaddition, five learning environment dimensions also statistically predicted Type IIIstyles (i.e. oligarchic, anarchic, internal and external styles), where student–studentcooperation was the major contributor.

Discussion

Results indicated that learning environments were significantly related to students’thinking styles. Specifically, the hypothesis about the positive relationships betweenthe constructivist learning environment and Type I thinking styles was supported


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Table1.

Standardisedparameter

estim

ates

fortheeight-factor

model

oftheISPLE(N

=752).

Factors

Item

sConstructivist-oriented

teaching

Clear

goalsandcoherenceof

curricula

Student

autono

my

Assessm

entsand

assignments

Teacher-student

interaction

Student-student

cooperation

Peermoraleand

identities

Learning

facilities

1.55

9.70

17.68

25.72

2.63

10.55

18.61

26.61

3.54

11.55

19.51

27.63

4.55

12.67

20.60

28.49

5.63

13.67

21.66

29.65

6.64

14.75

22.74

30.69

7.67

15.78

23.65

31.55

8.49

16.64

24.53

32.53


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Table2.

Differences

inthekeyvariablesbasedon

gender,grade,

andmajor

(N=752).

IVDV

Wilk

s’lambda

FSig.

Partialetasquared

Scale

Mean

Mean

tSig.

Males

Fem

ales

Gender

TS

.97

1.78

.043

.03

Liberal

4.77

4.26

6.72

.000

Anarchic

4.24

3.91

4.56

.000

Internal

4.73

4.37

5.33

.000

Sophomores

Seniors

Grade

TS

.95

3.08

.000

.06

Global

4.28

4.48

�2.98

.003

Conservative

4.54

4.78

�3.26

.001

Olig

archic

4.69

4.88

�2.41

.016

Anarchic

4.03

4.24

�2.98

.003

Hum

anities

andsocial

sciences

Science

andengineering

Major

LE

.98

2.16

.029

.02

Peermoraleandidentities

4.53

4.80

�3.52

.000

Notes:IV

=independ

entvariable;DV=depend

entvariable;TS=thinking

styles;LE=learning

environm

ent.

Table

3.Predictingthinking

styles

from

thelearning

environm

ent(N

=752).

TS

Type

ITy

peII

Type

III

Legislativ

eJudicial

Global

Liberal

Hierarchical

Executiv

eLocal

Conservative

Monarchic

Olig

archic

Anarchic

Internal

External

R2Total

.25

.20

.12

.19

.22

.17

.17

.10

.13

.22

.11

.10

.33

R2dem

o.04

.03

.05

.07

.01

.01

.02

.02

.02

.03

.04

.04

.02

R2LE

.21

.18

.07

.12

.21

.16

.15

.08

.11

.19

.07

.06

.31

β.20 c

onst⁄⁄

⁄.18 c

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⁄.14 p

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.12 a

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.12 c

onst⁄

.16 s

-s⁄⁄

.12 c

lear⁄

.15 c

lear⁄⁄

.10 a

ssess⁄

.16 s

-s⁄⁄

⁄.17 a

ssess⁄⁄

⁄.14 c

onst⁄

.34 s

-s⁄⁄

⁄

.22 facil⁄⁄

⁄.09 p

eer⁄

.12 p

eer⁄⁄

.17 c

lear⁄⁄

⁄.26 facil⁄⁄

⁄.23 a

ssess⁄⁄

⁄.14 facil⁄⁄

.19 facil⁄⁄

⁄�.

19s-s⁄⁄

⁄.10 p

eer⁄

.12 facil⁄⁄

.09 facil⁄

.10 facil⁄

.09 p

eer⁄

.13 facil⁄⁄

F19.70⁄

⁄⁄15.41⁄

⁄⁄8.19

⁄⁄⁄

13.93⁄

⁄17.40⁄

⁄⁄12.07⁄

⁄⁄12.32⁄

⁄⁄6.66

⁄⁄⁄

9.14

⁄⁄⁄

16.68⁄

⁄⁄7.26

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6.59

⁄⁄⁄

29.70⁄

⁄⁄

df739

739

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739

739

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739

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Notes:TS=thinking

styles;R2Total=thecontribu

tionof

demog

raph

icfactors(gender,grade,

major

andSES)andthelearning

environm

entto

thinking

styles;R2dem

o=the

contribu

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raph

icfactors(gender,grade,

major

andSES)to

thinking

styles;R2LE=theun

ique

contribu

tionof

thelearning

environm

entto

thinking

styles;

const=

constructiv

ist-oriented

teaching

;clear=

cleargo

alsandcoherenceof

curricula;

assess=assessmentandassign

ment;s-s=stud

ent-stud

entcoop

eration;

peer=peer

moraleandidentities;facil=

learning

facilities;

⁄ p<.05;

⁄⁄p<.01;

⁄⁄⁄ p

<.001

.


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(Hypothesis 1). However, unlike what was expected (Hypothesis 2), the constructiv-ist learning environment was also positively related to Type II thinking styles.

With regard to Type I thinking styles, constructivist-oriented teaching, peermorale and identities, and learning facilities were three major statistical contributors.These results indicated that, first, if students perceived their teachers as stressing theprocess of knowledge building rather than knowledge accumulation and helpingstudents think critically on what they have learned, students were more comfortableto deal with unstructured tasks (legislative style), preferred to evaluate people andthings around them (judicial style), and tended to manage multiple tasks in a orderlyway (hierarchical style). There are two equally plausible ways to explain thisphenomenon. It is possible that teachers’ constructivist-oriented teaching encouragedstudents’ development of those Type I styles. It is also possible that students withType I thinking styles preferred to choose courses where teachers teach in aconstructivist way and, thus, they perceived much constructivist-oriented teaching.

Second, results also indicated that students whose classmates and friends wereproactive in learning and interested in knowledge connection and application, had atendency to think critically (judicial style) and globally (global style) and to demon-strate open-mindedness (liberal style). There are also two equally plausible reasonswhy this phenomenon existed. It is possible that students were inspired by theirpeers and commit themselves in academic activities so that they practised thoseType I styles. Equally likely, students with Type I styles tended to choose proactivestudents to be their friends and, thus, they perceived high peer morale.

Third, the results also showed that sufficient places and resources on campus forstudents to further study beyond courses and practise their knowledge were foundto be positively related to students’ tendency to create their own ideas withoutinstruction (legislative style), to have their own judgement on things (judicial style),to try new things (liberal style), and to handle multiple tasks orderly (hierarchicalstyle). This positive relationship between learning facilities and the Type I thinkingstyles may indicate that learning facilities that provide abundant opportunities forstudents are conducive to the use of those Type I styles. Apart from the threeaforementioned learning environment dimensions (i.e., constructivist-orientedteaching, peer morale and identities and learning facilities), two other learningenvironment dimensions also statistically contributed to the use of Type I styles.First, the dimension of assessments and assignments oriented to deep understandingof learning materials was also found to be positively related to students’ preferencesfor novel tasks (liberal style). It is possible that students needed to adopt the liberalstyle in order to score well in such assessments and assignments. Second, cleargoals and coherence of curricula were associated with students’ use of the hierarchi-cal thinking style. This suggests that clear goals and coherence of curricula providea good demonstration for students about the process of knowledge building, whichmay in turn help students to develop a tendency to manage their life in a moreorganised way. Generally speaking, learning environments where students areencouraged to be fully engaged in active knowledge construction are highly relatedto students’ preferences for dealing with unstructured and creativity-generatingtasks, thinking critically, and managing life orderly.

Type II thinking styles were not related negatively to the constructivist learningenvironment as hypothesised. On the contrary, some learning environmentdimensions statistically predicted Type II thinking styles in a positive way. Themajor predictors for Type II styles were clear goals and coherence of curricula,


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assessments and assignments, and learning facilities. The statistically predictivepower of clear goals and coherence of curricula for Type II styles indicated that,students in a learning environment where teachers explained clearly about the aimsof courses and made sense of the teaching process to achieve these objectives had atendency to pay attention to details (local style) and to adhere to existing rules or touse familiar ways to deal with tasks (conservative style). It is possible that studentswith the local style or the conservative style prefer to choose courses that had cleargoals and coherent sessions, but it is also possible that clear instruction on bigpictures of the courses make students not bother to focus on general issues. Instead,they focused on details. Furthermore, students would tend to follow the process oflearning that teachers have planned for them rather than attempt novel ways. If thisis the case, teachers should provide appropriate levels of support because anoverdosage may make students step back and become ‘lazy’ to explore bythemselves. High scores in the dimension of assessments and assignments meansthe evaluation of performance requires deep understanding of the subjects ratherthan simply memorising facts. It is understandable that this dimension waspositively related to the liberal thinking style (Type I). However, meanwhile, it wasalso positively related to two Type II styles-preferences for focusing on details(local) and dealing with one task at a time (monarchic style). Such a result mayindicate that memorising facts to some extent is a necessary step in the process ofdeep understanding (Hess & Azuma, 1991). These Type II thinking styles seemhelpful for memorising. Therefore, assessments and assignments that require deepunderstanding of certain subject matters seem to provide opportunities for studentsto practise both Type I and Type II styles. In addition, it was also found thatlearning facilities was positively associated with Type II thinking styles as well asType I thinking styles. It is possible that the various available resources and facili-ties on campus provide abundant opportunities for students to practise a wide rangeof thinking styles. However, such an explanation is merely a post hoc speculation.In order to clarify the specific relationships between learning facilities and thinkingstyles, future research could further examine the nature of different types offacilities and the different ways in which students use these facilities rather thansimply looking at the availability of learning facilities.

The major statistical predictor for Type III styles was student–studentcooperation. Results indicated that students who perceived more support andcooperation from classmates had a tendency to select their tasks based on others’ sug-gestions (oligarchic style) and to work with others (external style) rather than to dothings alone (internal style). This finding makes good sense because students whoexperienced more student cooperation would value others’ suggestions more andwould be more willing to work with others. Nonetheless, an alternative explanationcould be that students with the oligarchic style and the external styles rely more onothers, which leads them to interact with others more. Thus, they perceived more stu-dent–student cooperation than their counterparts. Students with the internal thinkingstyle would be more independent; so they would interact with others less, whichwould make them perceive less student–student cooperation than their counterparts.

Conclusions, implications and limitations

The present study demonstrated that the general constructivist learningenvironment played an important role in students’ thinking styles. Specifically,


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constructivist-oriented teaching as well as peer morale and identities in learningwere positively associated with thinking styles that are characterised by cognitivecomplexity, nonconformity, autonomy, and low degrees of structure (characteris-tics of Type I styles), while assessments and assignments oriented to deepunderstanding as well as learning facilities had positive associations with bothType I (creativity-generating styles) and Type II styles (norm-conforming styles).Clear goals and coherence of curricula had positive relationships with Type IIstyles while student–student cooperation played a statistically significant role inType III styles. Among these findings, the relationship of clear goals andcoherence of curricula to Type II styles needs to be further studied with thecontent and the amount of instruction being examined. In addition, the role thatlearning facilities play in both Type I and Type II styles also requires furtherstudies to explore the nature of different facilities and different ways by whichstudents use these facilities, so that we can improve our understanding of howlearning facilities are associated with different styles.

Generally speaking, the present study illustrated the connections betweenlearning environments and thinking styles. It provides the necessary information tofurther identify the antecedents of intellectual styles and encourages relevantresearch in examining the malleability of styles. Furthermore, the specific relation-ships between various dimensions of learning environment and students’ thinkingstyles provide some insight for teachers and university administrators by indicatingpossible directions they could work on if they want to cultivate specific stylesamong students. For example, if teachers aim at cultivating Type I styles amongstudents, they are encouraged to teach in a constructivist way, where they shouldfocus on the process of knowledge construction rather than merely knowledgetransmission. Teachers are also advised to create an academic atmosphere thatfacilitates students’ proactive learning and provides students with the opportunity toinfluence one another. If university administrators want to cultivate the variety ofstudents’ thinking styles, they are advised to provide abundant learning facilities fortheir students, for as an important dimension of learning environment, learningfacilities statistically predicted all three types of thinking styles. However, weshould be cautious if we want to apply the findings of this study into practicebecause there are several limitations in the present study.

First of all, the relationships found in this study are correlations rather thancausal relationships, which means the relationships between learning environmentsand thinking styles are probably because that some characteristics in learningenvironments facilitate students’ development of certain styles or may be becausestudents with certain styles prefer to be involved in learning environments withsome specific characteristics. Therefore, longitudinal or experimental studies areneeded to make compelling causal inferences and to further deepen our understand-ing on the effect of learning environments on thinking styles. Second, the sample ofthis study was from one com university in China, which limits the generalisation ofthe findings to other populations. Third, the ISPLE developed in this study still hasroom to be improved. The improvement and further examinations of the ISPLEmay benefit relevant research in future.

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Appendix

Descriptions of 13 thinking styles in the theory of mental self-government

DimensionThinkingstyles Key characteristics

Function Legislative(I)

One prefers to work on tasks that require creativestrategies; one prefers to choose one’s own activities.

Executive(II)

One prefers to work on tasks with clear instructionsand structures;one prefers to implement tasks with establishedguidelines.

Judicial (I) One prefers to work on tasks that allow for one’sevaluation; one prefers to evaluate and judge the performanceof other people.

Form Hierarchical(I)

One prefers to distribute attention to several tasks prioritisedaccording to one’s valuing of the tasks.

Monarchic(II)

One prefers to work on tasks that allow complete focuson one thing at a time.

Oligarchic(III)

One prefers to work on multiple tasks in the serviceof multiple objectives, without setting priorities.

Anarchic(III)

One prefers to work on tasks that would allow flexibilityas to what, where, when, and how one works.

Level Global (I) One prefers to pay more attention to the overall pictureof an issue and to abstract ideas.

Local (II) One prefers to work on tasks that require workingwith concrete details.

Scope Internal (III) One prefers to work on tasks that allow one to workas an independent unit.

External (III) One prefers to work on tasks that allow for collaborativeventures with other people.

Leaning Liberal (I) One prefers to work on tasks that involve novelty andambiguity.

Conservative(II)

One prefers to work on tasks that allow one to adhere to theexisting rules and procedures in performing tasks.

Note: Extracted from Zhang (2003, p. 630); I = Type I thinking style; II = Type II thinking style;III = Type III thinking style.


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the role of learning environments in thinking styles

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