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Do university students’ thinking styles matter in their preferred teaching approaches?
Personality and Individual Differences 37 (2004) 1551–1564 www.elsevier.com/locate/paid
Do university students’ thinking styles matter in their preferred teaching approaches? Li-fang Zhang
*
Faculty of Education, The University of Hong Kong, Pokfulam Road, Hong Kong Received 8 May 2003; received in revised form 14 January 2004; accepted 19 February 2004 Available online 27 March 2004
Abstract This study pioneered the research on the role of university students’ thinking styles in their preferred teaching approaches. Three hundred and forty-eight (111 male and 237 female) students from a large comprehensive university in Beijing, P.R. China, responded to the Thinking Styles Inventory (Revised) and the Preferred Teaching Approach Inventory. Results indicated that regardless of age, gender, university class level, and academic discipline, students with different thinking styles had significantly different preferences for particular teaching approaches. It was contended that both conceptual change and information transmission are necessary for effective teaching. Theoretically, the study contributed to the styles literature in general and to the literature on the relationships between styles and approaches of teaching and learning in particular. Practical implications of the present findings are discussed in the context of students’ teaching evaluations, teachers’ teaching, and university administrators’ personnel management. Ó 2004 Elsevier Ltd. All rights reserved. Keywords: Thinking styles; Preferred teaching approaches
1. Introduction Styles refer to people’s preferred ways of using the abilities that they have (Sternberg, 1997). After decades of theorizing and researching on styles, many theoretical models and frameworks on styles have been postulated. Among these existing works, two theories that are the most promising for improving the effectiveness of teaching and learning are Biggs’s theory of learning approaches and Sternberg’s theory of mental self-government. *
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Biggs (1979) proposed three learning approaches: surface, which involves a reproduction of what is taught to meet the minimum requirements; deep, which involves a real understanding of what is learned; and achieving, which involves using a strategy that will maximize one’s grades. Each approach is composed of two elements: motive and strategy. Motive describes why students learn, while strategy describes how students go about their learning. The Study Process Questionnaire (SPQ, Biggs, 1992) is designed to assess university students’ learning approaches. Good reliability and validity data have been obtained with this instrument among the majority of populations tested around the world. However, whereas some studies supported that the SPQ assesses three approaches to learning (e.g., Bolen, Wurm, & Hall, 1994), other studies supported a two-factor (surface and deep) model (e.g., Niles, 1995; Watkins & Dahlin, 1997). The two-factor model is consistent with the model proposed by Marton (1976) who used a phenomenographic method in studying students’ learning approaches. The theory of mental self-government (Sternberg, 1988, 1994, 1997) concerns people’s thinking styles, which apply to different types of activities, including teaching and learning. Central to this theory is the notion that people need to govern or manage their everyday activities. People choose styles of managing these activities with which they feel comfortable. The theory describes 13 thinking styles that fall along five dimensions of mental self-government: (a) functions (including the legislative, executive, and judicial styles), (b) forms (including the hierarchical, oligarchic, monarchic, and anarchic styles), (c) levels (including the global and local styles), (d) scopes (including the internal and external styles), and (e) leanings (including the liberal and conservative styles). A brief description of each of the 13 thinking styles can be found in Appendix A (for details, see Sternberg, 1997). These thinking styles are, in principle, value-free, for the same thinking style can serve one person beautifully in one situation, but may fail the same person miserably in another situation. However, in their repeated studies, Zhang and her colleagues (e.g., Zhang, 2000, 2001a, 2002a, 2002b; Zhang & Huang, 2001; Zhang & Postiglione, 2001; Zhang & Sternberg, 2000) have found that most of the thinking styles in Sternberg’s theory can be classified into two groups. The first group, known as Type I thinking styles, is composed of thinking styles that are more creativitygenerating and that denote higher levels of cognitive complexity, including such styles as the legislative, judicial, hierarchical, global, and liberal styles. The second group, known as Type II thinking styles, consists of thinking styles that suggest a norm-favoring tendency and that denote lower levels of cognitive complexity, including such styles as the executive, local, monarchic, and conservative styles. The remaining four thinking styles (i.e., anarchic, oligarchic, internal, and external) belong to neither the Type I group nor the Type II group. However, they may manifest the characteristics of the styles from both groups, depending on the stylistic demand of the specific task. For example, whether one prefers to work alone (internal style) or one prefers to work with others (external style), one can work on tasks that require either Type I thinking styles or Type II thinking styles. Also for instance, one could use the anarchic style in a sophisticated way––such as dealing with different tasks as they arise, but without losing one’s sight of the whole picture of the main issue. Under this circumstance, the anarchic style manifests the characteristics of Type I thinking styles. On the contrary, one also could use the anarchic style in a simple-minded way––such as dealing with tasks as they come along without knowing how each task contributes to his/her ultimate goal. Under this circumstance, the anarchic style manifests the characteristics of Type II thinking
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styles. In Zhang’s recent work (Zhang, 2003a), these four styles have been labeled as ‘‘Type III thinking styles’’. The theory of mental self-government has been operationalized through several inventories, including the Thinking Styles Inventory (TSI, Sternberg & Wagner, 1992) and the Thinking Styles in Teaching Inventory (TSTI, Grigorenko & Sternberg, 1993). Both inventories have been tested in cross-cultural contexts, including Hong Kong, mainland China, the Philippines, and the United States. Results indicated that both inventories have reasonably good reliability and validity (see Zhang & Sternberg, 2001 for a detailed review). The two inventories also have been assessed for their heuristic and predictive value in educational settings. For example, it has been found that students’ thinking styles do not only significantly contribute to their academic achievement, but also play a critical role in such aspects as students’ self-esteem, personality, and career interest. Moreover, teachers’ characteristics have a strong impact upon the thinking styles they use in teaching (i.e., teaching styles) (see Zhang & Sternberg, 2002 for a comprehensive review). Given that both learning approaches and thinking styles have heuristic and predictive value in educational settings and that both constructs fall within the styles literature (Sternberg, 1997), we conducted two studies (Zhang, 2000; Zhang & Sternberg, 2000) to examine the relationships between learning approaches and thinking styles among students. Both studies showed that students who reported a deep approach to learning tended to use Type I thinking styles, and that students who reported a surface approach to learning tended to use Type II thinking styles. Furthermore, the investigation of the relationships between styles and approaches in learning has been extended to the study of the relationships between styles and approaches in teaching (see Zhang, 2001b). As previously noted, Sternberg’s theory applies to different types of activities, including teaching and learning. The Thinking Styles in Teaching Inventory (TSTI, Grigorenko & Sternberg, 1993) assesses thinking styles as manifested in teaching––that is, teaching styles. The TSTI assesses two types of teaching styles: Type I styles that facilitate creativity and that encourage the development of cognitive complexity, and Type II styles that require conformity and that accommodate cognitive simplicity. In their investigation of approaches to teaching of first year university science teachers, Trigwell, Prosser, and Taylor (1994); (also Prosser & Trigwell, 1999) have found parallels with students’ approaches to learning. They proposed that there are two approaches to teaching. One is information transmission (also known as teacher-focused). Teachers adopting this approach to teaching tend to be content-oriented and to emphasize the reproduction of correct information. The other teaching approach is conceptual change (also known as student-focused). Teachers adopting this approach are learning-oriented and concerned with students’ conceptual change. These two approaches to teaching are measured by Trigwell and Prosser’s (1996) Approaches to Teaching Inventory (ATI). After examining the relationships between teaching styles (as measured by the TSTI) and teaching approaches (as measured by the ATI) among Hong Kong in-service teachers, Zhang (2001b) concluded that teachers who reported a conceptual change/student-focused teaching approach tended to use Type I teaching styles, and that teachers who reported a knowledge transmission/teacher-focused teaching approach tended to use Type II teaching styles. Thus, this finding between styles and approaches in teaching is consistent with that between styles and approaches in learning (see Zhang, 2000; Zhang & Sternberg, 2000).
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In the studies mentioned above, we have discussed extensively the implications of these findings for the process of teaching and learning. However, these discussions were all based on the respective research participants’ self-report of their own styles and approaches. To further enhance the effectiveness of teaching and learning, there is a need for establishing a dialogue between teachers’ teaching styles (and approaches) and students’ learning styles (and approaches). There are many ways to do so, one of which is to understand the kind of teaching styles/ approaches that students prefer that their teachers use. The present study initiates such an endeavour by investigating the relationships between university students’ thinking styles and the teaching approaches they prefer that their teachers use. Specifically, there were three objectives to this study. First, the study intends to ascertain the reliability and validity of the newly constructed Preferred Teaching Approach Inventory (Zhang, 2003b). Second, the study aims at revealing the profile of students’ preferred teaching approaches. Third, it intends to determine if it is possible to use students’ thinking styles to predict the teaching approaches that university students prefer that their teachers adopt. It was predicted that students who tended to use Type I thinking styles prefer that their teachers adopt the conceptual change/student-focused approach to teaching (either ‘conceptual change’ or ‘student-focused’ will be used to refer to ‘conceptual change/student-focused’ hereafter), but not the information transmission/ teacher-focused approach (either ‘information transmission’ or ‘teacher-focused’ will be used to refer to ‘information transmission/teacher-focused’ hereafter). It was also predicted that students who tended to use Type II thinking styles prefer that their teachers use the information transmission approach to teaching, but not the conceptual change approach. These predictions were based primarily on the ‘matching hypothesis’. According to the matching hypothesis, students would actively search for the learning environment in which their ways of using their abilities (i.e., thinking styles according to Sternberg) will be accommodated. Based on the definitions of the types of thinking styles and those of the two teaching approaches, whereas the conceptual change teaching approach tends to accommodate Type I thinking styles, the information transmission teaching approach tends to accommodate Type II thinking styles. As for Type III styles, since they may manifest the characteristics of either Type I or Type II styles, Type III styles may be accommodated by either the conceptual change teaching approach or the information transmission teaching approach. Therefore, Type III thinking styles may be significantly related to either the conceptual change approach or the information transmission approach.
2. Method 2.1. Participants Three hundred and forty-eight (111 male and 237 female) students from a large comprehensive university in Beijing volunteered to participate in this research. With both the mean and the median being 20 years, the participants’ ages ranged from 17 to 35 years. Among the participants, there were 48 freshmen, 160 sophomores, 117 juniors, and 23 seniors. Furthermore, the participants were pursuing their Bachelor’s degrees in the following academic areas: the Chinese language, economics, education, life science, and physics.
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2.2. Measures Two self-report inventories were administered to the participants. The first was the Thinking Styles Inventory––Revised (TSI-R, Sternberg, Wagner, & Zhang, 2003). The second was the Preferred Teaching Approach Inventory (Zhang, 2003b). The TSI-R is a modified version of Sternberg and Wagner’s (1992) Thinking Styles Inventory (TSI) based on the theory of mental self-government. Consisting of 65 statements, the inventory assesses the 13 thinking styles delineated in the theory, with each 5 statements contributing to the assessment of one of the thinking styles. For each statement, the participants rated themselves on a 7-point Likert type scale, with 1 indicating that the statement does not at all represent the way they normally carry out their tasks, and 7 denoting that the statement characterizes extremely well the way they normally carry out their tasks. Here are two examples: (1) ‘‘When faced with a problem, I use my own ideas and strategies to solve it’’ (legislative style); and (2) ‘‘I like to figure out how to solve a problem following certain rules’’ (executive style). The TSI has been translated and back-translated between Chinese and English in 1996. Both the Chinese and English versions of the inventory have been used in numerous studies. Reasonable reliability and good validity data have been demonstrated in all existing studies. However, previous research indicated that lower scale reliabilities were usually obtained with three of the 13 scales: local, monarchic, and anarchic. A careful examination of the item-scale reliabilities from previous data sets indicated that 7 items needed to be re-written: 2 from the local scale, 3 from the monarchic scale, and 2 from the anarchic scale. In the present study, a Chinese version of the TSI-R was used. Cronbach’s alphas were 0.74, 0.65, 0.74, 0.65, 0.67, 0.83, 0.76, 0.75, 0.65, 0.70, 0.51, 0.73, and 0.78, respectively for the legislative, executive, judicial, global, local, liberal, conservative, hierarchical, monarchic, oligarchic, anarchic, internal, and external styles. The alpha coefficients for the local and the monarchic scales have been improved dramatically: from low to mid 0.50s to nearly 0.70. The alpha coefficient for the anarchic scale only showed slight improvement. The validity of the TSI-R was supported by the results from an exploratory factor analysis with an oblique rotation. The way that the scales clustered makes substantive sense. The first factor was dominated by loadings of Type I thinking styles, whereas the second factor by those of Type II thinking styles. The third factor was dominated by loadings of a pair of contrasting styles: the internal and external styles. Finally, the fourth factor was dominated by loadings of a second pair of contrasting styles: the global and local styles. These four factors accounted for 68% of the variance in the data. Table 1 presents the detailed statistics obtained from this factor analysis. The Preferred Teaching Approach Inventory (PTAI, Zhang, 2003b) was particularly designed for the present study. Adapted from Prosser and Trigwell’s (1996) Approach to Teaching Inventory, the PTAI is a self-report test consisting of 16 items. The 16 items fall into 2 scales (with 8 items in each): conceptual change and information transmission. Each scale is further divided into 2 subscales, with one containing 4 intention items, and the other containing 4 strategy items. Therefore, the four subscales are conceptual change/student-focused/intention (CCSFI), conceptual change/student-focused/strategy (CCSFS), information transmission/teacher-focused/ intention (ITTFI), and information transmission/teacher-focused/strategy (ITTFS). Each item is a statement describing students’ preference for their teachers’ teaching approach. The respondents
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Table 1 Factor loadings: TSI-R scales and PTAI subscales (N ¼ 348) Scale
TSI-R Factor 1
Legislative Executive Judicial Global Local Liberal Conservative Hierarchical Monarchic Oligarchic Anarchic Internal External % Variance C. variance Eigenvalue
PTAI Factor 2
Factor 3
Factor 4
0.88 0.80 0.58 0.46
)0.39
0.49 )0.81
0.75 0.87 0.42 0.30
0.58 0.50
0.37 0.86 31.75 31.75 4.13
17.37 49.12 2.26
)0.56 )0.38 0.54 )0.92 10.99 60.11 1.43
Subscale CCSFI CCSFS ITTFI ITTFS % Variance C. variance Eigenvalue
Factor 1
Factor 2 0.87 0.88
0.89 0.90 41.51 41.51 1.66
37.45 78.96 1.50
)0.58
7.93 68.05 1.03
Note. Variables with factor loadings of less than j0:30j are omitted. C. variance ¼ cumulative variance.
are instructed to rate themselves on a 7-point Likert scale, with 1 indicating that they absolutely disagree that the statement describes the way they prefer that their teachers conduct their teaching and assessment, and 7 suggesting that they absolutely agree that the statement describes the way they prefer that their teachers conduct their teaching and assessment. Examples of the items in the inventory are ‘‘It is important that my teachers try to develop a conversation with students about the topics that we are studying’’ (CCSFS), and ‘‘It is important that the subjects my teachers teach be completely described in terms of specific objectives relating to what students have to know for formal assessment items’’ (ITTSI). 2.3. Data analysis To ascertain the reliability and validity of the PTAI, estimates of internal consistency for the 4 subscales (and the 2 overall scales) of the PTAI were obtained with Cronbach’s alphas. Furthermore, an exploratory factor analysis was conducted to examine the validity of the PTAI. To prepare for the achievement of the remaining two objectives, I tested the possible significant differences in either thinking styles or preferred teaching approaches based on the participants’ age, gender, university class level, and academic discipline, using t-test and multivariate analysis of variance. No significant difference was identified based on any of the variables examined. Therefore, in the remaining statistical analyses, there was no need for controlling these variables. Two further statistical procedures were performed to achieve the remaining two objectives of this research. First, to identify the profile of students’ preferred teaching approaches, a bar graph for the summaries of the 4 subscale means was drawn. Second, to investigate the predictability of students’ thinking styles for their preferred teaching approaches, stepwise multiple regression
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procedures were conducted, with students’ thinking styles being the independent variables and their preferred teaching approaches as the dependent variables.
3. Results 3.1. PTAI scale reliabilities Cronbach’s alphas were 0.56, 0.69, 0.57, and 0.54, respectively for the conceptual-change/ intention, conceptual-change/strategy, information-transmission/intention, and informationtransmission/strategy subscales. The alpha coefficients for the two overall teaching approach scales were both 0.73. These alpha coefficients were similar in magnitude to those reported in Trigwell and Prosser’s (1996) study and to those in Zhang’s (2001b) study. In both previous studies, teachers’ self-reported teaching approaches were assessed by the Approaches to Teaching Inventory, from which the PTAI was adapted. Given the small number of items (4 items in each subscale), the heterogeneity of the items within each subscale, as well as the similarity between the present alpha coefficients and those obtained in the 2 aforementioned studies, the present alpha coefficients are considered sufficient to allow the remaining statistical analyses. 3.2. PTAI validity The results from the exploratory factor analysis followed by an oblique rotation are also summarized in Table 1. The first factor was dominated by loadings of the two subscales in the information transmission teaching approach, while the second factor was loaded with the two subscales from the conceptual change teaching approach. The two factors accounted for 79% of the variance in the data. 3.3. Profile of preferred teaching approaches The bar graph (see Fig. 1) of the summaries of the means for the 4 teaching approach subscales revealed the following order of students’ preferences––from the strongest to the weakest: a conceptual change strategy, a conceptual change intention, an information transmission intention, and an information transmission strategy. In general, students indicated a stronger preference for the conceptual change teaching approach than for the information transmission approach. 3.4. Predicting preferred teaching approaches from thinking styles Results from multiple-regression analyses indicated that significant predictive relationships were obtained for all four teaching approach subscales. Of the 13 thinking styles, nine styles contributed to these significant predictions: the legislative, judicial, anarchic, global, local, liberal, conservative, internal, and external thinking styles. The amount of variance in students’ preferred teaching approaches explained by their thinking styles were 21% for conceptual change intention, 21% for conceptual change strategy, 17% for information transmission intention, and 24% for
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Fig. 1. Students’ preferrred teaching approaches ðN ¼ 348Þ.
information transmission strategy. Table 2 presents the detailed statistics from these multiple regressions. Specifically, the following predictive relationships were identified. First, the liberal, internal, and external thinking styles positively predicted a conceptual change intention. Second, the anarchic, global, and judicial styles positively predicted a conceptual change strategy, whereas the conservative style negatively predicted a conceptual change strategy. Third, the conservative and
Table 2 Contributions of thinking styles to preferred teaching approaches (N ¼ 348) PTAI subscale 2
R bStyle 1 bStyle 2 bStyle 3 bStyle 4 F dfa
CCSFI
CCSFS
ITTFI
ITTFS
0.21 0.18Liberal 0.31Internal 0.21External
0.21 0.27Anarchic 0.16Global )0.19Conservative 0.16Judicial 13.95 4, 217
0.17 0.39Conservative 0.13External
0.24 0.27Conservative 0.28Global 0.27Local )0.15Legislative 16.99 4, 217
19.59 3, 219
Note: ITTFI ¼ Information transmission/teacher-focused (intention). ITTFS ¼ Information transmission/teacher-focused (strategy). CCSFI ¼ Conceptual change/student-focused (intention). CCSFS ¼ Conceptual change/student-focused (strategy). * p < 0:05. ** p < 0:001. *** p < 0:01. a Listwise cases exclusion was used.
22.88 2, 219
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external styles positively contributed to the prediction of an information transmission intention. Finally, the conservative, global, and local styles positively contributed to the prediction of the information transmission strategy, whereas the legislative style negatively did so.
4. Discussion The present study had three objectives. The first was to obtain the reliability and validity of the Preferred Teaching Approach Inventory. The second was to identify the profile of university students’ preferred teaching approaches. The third was to examine the contribution of students’ thinking styles to their preferred teaching approaches. All three objectives have been achieved. Results indicated that the PTAI (sub)scales possesses reliabilities that are comparable with those obtained in previous studies using the Approach to Teaching Inventory that is based on the same theoretical model. Moreover, results from factor analysis also confirmed the two approaches to teaching in Trigwell and Prosser’s (1996) work as well as in Zhang’s (2001b) work. These present psychometric data indicate that the PTAI possesses convergent validity with the Approach to Teaching Inventory. Therefore, it should be asserted that the PTAI is valid for assessing university students’ preferred teaching approaches. As previously noted, research participants’ preferred teaching approaches as shown in the bar graph of the PTAI subscale means indicated that as a whole group, students were in favor of a teaching approach that could help them make conceptual change over one that could help them obtain information. However, when thinking styles were taken into account, this preference for the conceptual change teaching approach did not show up as a stronger one any more. Instead, results from multiple regression analyses demonstrated that students with different types of thinking styles preferred different types of teaching approaches. Across the four sets of significant predictive findings, the three types of styles predicted students’ preferred teaching approaches in the following fashion: Regarding Type I thinking styles, three styles (including the judicial, global, and liberal styles) positively predicted the conceptual change teaching approach, while one style (the legislative style) negatively predicted the information transmission teaching strategy. Such finding regarding the predictive relationships of Type I thinking styles to teaching approach lent strong support to the hypothesis of the study. However, one identified significant relationship was not anticipated: the positive significant relationship between the global style and the information transmission strategy. A post hoc explanation could be that students with the global thinking style were more open to various teaching approaches. That is, apart from having a strong preference for the conceptual change teaching strategy, students with the global thinking style also had a strong preference for the information transmission teaching strategy. Regarding Type II thinking styles, the conservative and local styles positively predicted the information transmission approach. Meanwhile, the conservative thinking style negatively predicted the conceptual change strategy. These findings lent full support to the prediction about the relationships between Type II thinking styles and students’ preferred teaching approaches. As for Type III styles, three of the thinking styles (i.e., internal, external, and anarchic styles) positively contributed to the prediction of the conceptual change teaching approach. Simultaneously, the external thinking style also positively contributed to the prediction of a preferred
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information transmission intention. It should be recalled that no specific prediction was made regarding the relationships between thinking styles and preferred teaching approaches due to the instability of the Type III thinking styles with respect to the characteristics they may manifest depending on the stylistic demands of a given task. Results indicated, though, that students with Type III thinking styles were essentially in favor of the conceptual change teaching approach, with the external style students also expressing a strong preference for the information transmission intention. These findings pertaining to the predictive relationships of students’ thinking styles to their preferred teaching approaches were more likely to be true than to have been found by chance. There are at least two reasons to support this claim. First, the obtained predictive relationships lent support to the earlier predictions that were primarily based on the popular ‘‘matching hypothesis’’, according to which, students would actively select learning environments in which their ways of using their abilities (i.e., thinking styles) can be accommodated (Holland, 1973; Jung, 1923; Nganwa-Bagumah & Mwamwenda, 1991; Saracho & Spodek, 1994). Teaching approaches can be construed as one type of learning environment. Thus, students with different thinking styles tend to prefer that their teachers use different teaching approaches. Second, the present findings are consistent with previous findings obtained from studies of the relationships between styles and approaches manifested in both teaching and learning, using the same theoretical models. For example, among students, Type I thinking styles were significantly related to the deep approach to learning, whereas Type II thinking styles were significantly related to the surface approach to learning (e.g., Zhang, 2000; Zhang & Sternberg, 2000). Likewise, among teachers, Type I thinking styles were significantly correlated with the conceptual change teaching approach, whereas Type II thinking styles were significantly correlated with the information transmission teaching approach (e.g., Zhang, 2001b). The present study, as expected, has found that students with Type I thinking styles preferred that their teachers use the conceptual change teaching approach and that students with Type II thinking styles preferred that their teachers use the information transmission teaching approach. Furthermore, Type III thinking styles were related to the conceptual change teaching approach.
5. Significance and implications The present study has made four major contributions. The first relates to the revision of the Thinking Styles Inventory, resulting in dramatic improvement of the internal consistency of the local scale and that of the monarchic scale. Second, the study has obtained the psychometric properties of the newly constructed Preferred Teaching Approach Inventory. The PTAI has demonstrated comparable (sub)scale alpha coefficients with those obtained by Trigwell and Prosser (1996). By the same token, the PTAI has shown convergent validity with Trigwell and Prosser’s (1996) Teaching Approach Inventory. Third, by examining the relationships of students’ thinking styles to their preferred teaching approaches, the present study has extended previous works on the relationships between thinking styles and learning/teaching approaches. As has been noted previously, existing research has focused on the relationships between students’ thinking styles and students’ learning approaches and those between teachers’ teaching styles and teachers’ teaching approaches. This
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study focuses on the relationships between students’ thinking styles and their preferred teaching approaches. Fourth, the study has enriched the literature on styles. Existing literature has documented studies that demonstrated the roles of thinking styles in many aspects of student learning and development as well as in teachers’ teaching approaches. The present study has revealed that thinking styles also contributed to students’ preferences in their teachers’ teaching approaches. Apart from having made these theoretical contributions, the study also has practical implications for the university setting. There are good reasons for each of the three major parties (i.e., teachers, students, and university administrators) at the university setting to be aware of the predictive power of students’ thinking styles for their preferred teaching approaches. Teachers should be aware of this predictive relationship since this finding is signifying that to be effective in teaching, teachers should use both student-centered and teacher-centered approaches to teaching since only the use of both can accommodate the diverse thinking styles among students. In the past few decades, being influenced by the notion of constructivism, scholars and educators have been advocating for the conceptual-change teaching approach. However, whereas the conceptual-change teaching approach can help teachers to achieve many meaningful educational objectives, it does not always allow useful and efficient transmission of knowledge. It can be easily argued that for many reasons, knowledge transmission is a necessary part of teaching. Most notably, one’s life time is limited, which makes it impossible for one to learn everything through being in a learning environment that solely aims at facilitating conceptual change. Much wellestablished knowledge can be gained through being in a learning environment that focuses on didactic teaching in addition to student-centered teaching. This need for both teacher-centered and student-centered approaches is consistent with Pask’s (1976) (also Pask & Scott, 1972) notion of versatile learner. Versatile learners vary their learning approaches according to the characteristics of the tasks. Similarly, effective teachers (i.e., versatile teachers) should vary their teaching approaches according to the characteristics of their students, including their thinking styles. Effective teachers should use both teaching approaches so that students, no matter what their thinking styles are, could have the opportunity to study and grow intellectually in a learning environment that is both accommodating (i.e., a learning environment in which teachers use the teaching approaches that students prefer) and challenging (i.e., a learning environment in which teachers use the teaching approaches that do not match students’ thinking styles). Students should be aware of this predictive relationship for two reasons. First, an understanding of this relationship may encourage students to make a conscientious effort in enhancing teaching by either adjusting their own ways of learning to teachers’ ways of teaching or communicating with their teachers regarding their preferred teaching approaches. Second, an understanding of this predictive relationship may facilitate students to make a more balanced evaluation of their teachers’ teaching. Much research has indicated that teaching effectiveness is multifaceted (e.g., French, 1974; Herrmann, 1996; Phillips, 1999). Furthermore, many factors affect the way students rate their teachers’ teaching (e.g., Abrami, Leventhal, Perry, & Breen, 1976; Hale, 1980; Phillips, 1999). Very often, these evaluations could be fairly subjective. The present finding of the predictive relationship is suggesting that when students evaluate their teachers’ teaching, they should realize that their own thinking styles do affect their preferences for their teachers’ teaching approaches. Thus, their evaluation of the effectiveness of their teachers’ teaching approaches could very well be biased. Thus, it is important that they take their own
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thinking styles into account when making teaching evaluations. When students perceive their teachers as doing a poor teaching job, it might be a case of mismatch between their own thinking styles with their teachers’ teaching approaches. Finally, this predictive relationship should draw the attention of university administrators, in particular, decision makers for personnel issues. Too often, students’ teaching evaluation is used as one of the key criteria of university teachers’ teaching performance. However, there is much research evidence revealing that students’ teaching evaluation may be biased against (or for) teachers since it can be influenced by so many factors. The present finding indicates that students’ thinking styles statistically contributed to their preferences for teaching approaches. Thus, it is very possible that students with different thinking styles rate the same teacher’s teaching very differently. It is imperative, therefore, that students’ teaching evaluations be used critically, with at least students’ thinking styles being taken into consideration, especially when students’ teaching evaluations are used for personnel decision making, or for such an exercise as a promotion procedure. Acknowledgements Research for this article was supported by the Committee on Research and Conference Grants as administered by The University of Hong Kong. Appendix A Thinking styles in the theory of mental self-government Dimension
Thinking style
Key characteristics
Function
Legislative
One prefers to work on tasks that require creative strategies; One prefers to choose one’s own activities One prefers to work on tasks with clear instructions and structures; One prefers to implement tasks with established guidelines One prefers to work on tasks that allow for one’s evaluation; One prefers to evaluate and judge the performance of other people
Executive
Judicial
Form
Hierarchical
Monarchic Oligarchic
One prefers to distribute attention to several tasks that are prioritized according to one’s valuing of the tasks One prefers to work on tasks that allow complete focus on one thing at a time One prefers to work on multiple tasks in the service of multiple objectives, without setting priorities
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Appendix A (continued) Dimension
Level
Thinking style
Key characteristics
Anarchic
One prefers to work on tasks that would allow flexibility as to what, where, when, and how one works
Global
One prefers to pay more attention to the overall picture of an issue and to abstract ideas One prefers to work on tasks that require working with concrete details
Local Scope
Internal External
Leaning
Liberal Conservative
One prefers to work on tasks that allow one to work as an independent unit One prefers to work on tasks that allow for collaborative ventures with other people One prefers to work on tasks that involve novelty and ambiguity One prefers to work on tasks that allow one to adhere to the existing rules and procedures in performing tasks
References Abrami, P. C., Leventhal, L., Perry, R. P., & Breen, L. J. (1976). Course evaluation: How? Journal of Educational Psychology, 68(3), 300–304. Biggs, J. B. (1979). Individual differences in study processes and the quality of learning outcomes. Higher Education, 8, 381–394. Biggs, J. B. (1992). Why and how do Hong Kong students learn? Using the Learning and Study Process Questionnaires, Education paper no. 14, Faculty of Education, The University of Hong Kong. Bolen, L. M., Wurm, T. R., & Hall, C. W. (1994). Factorial structure of the Study Process Questionnaire. Psychological Reports, 75(3), 1235–1241. French, L. G. (1974). Predictability of students’ evaluations of college teachers from component ratings. Journal of Educational Psychology, 66(3), 373–385. Grigorenko, E. L., & Sternberg, R. J. (1993). Thinking Styles in Teaching Inventory. Yale University, Unpublished test. Hale, N. S. (1980). A study of differences in student perception of male and female faculty members’ teaching effectiveness as measured by student evaluation of classroom teaching. Dissertation Abstracts International (Section A): Humanities and Social Sciences, 40(8A), 4382. Herrmann, N. (1996). Supervisor evaluation: From theory to implementation. Academic Psychiatry, 20(4), 205–211. Holland, J. L. (1973). Making vocational choices: A theory of careers. Englewood Cliffs, NJ: Prentice-Hall. Jung, C. (1923). Psychological types. New York: Harcourt Brace. Marton, F. (1976). What does it take to learn? Some implications on an alternative view of learning. In N. J. Entwistle (Ed.), Strategies for research and development in higher education (pp. 200–222). Amsterdam: Swets and Zeitlenger. Nganwa-Bagumah, M., & Mwamwenda, T. S. (1991). Effects on reading comprehension tests of matching and mismatching students’ design preferences. Perceptual and Motor Skills, 72(3), 947–951. Niles, F. S. (1995). Cultural differences in learning motivation and learning strategies: A comparison of overseas and Australian students at an Australian university. International Journal of Intercultural Relations, 19(3), 369–385. Pask, G. (1976). Styles and strategies of learning. British Journal of Educational Psychology, 46, 128–148.
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Pask, G., & Scott, B. C. E. (1972). Learning strategies and individual competence. International Journal of ManMachine Studies, 4, 242–253. Phillips, S. B. (1999). Student evaluation of faculty instruction: Inflated results and student feedback. Dissertation Abstracts International (Section A): Humanities and Social Sciences, 60(5A), 1478. Prosser, M., & Trigwell, K. (1999). Understanding learning and teaching: The experience in higher education. Buckingham: The Society for Research into Higher Education and Open University Press. Prosser, M., & Trigwell, K. (1996). Approach to Teaching Inventory. University of Sydney, Unpublished test. Saracho, O. N., & Spodek, B. (1994). Matching preschool children’s and teachers’ cognitive styles. Perceptual and Motor Skills, 78, 683–689. Sternberg, R. J. (1988). Mental self-government: A theory of intellectual styles and their development. Human Development, 31, 197–224. Sternberg, R. J. (1994). Thinking styles: Theory and assessment at the interface between intelligence and personality. In R. J. Sternberg & P. Ruzgis (Eds.), Intelligence and personality (pp. 169–187). New York: Cambridge University Press. Sternberg, R. J. (1997). Thinking styles. New York: Cambridge University Press. Sternberg, R. J., & Wagner, R. K. (1992). Thinking Styles Inventory. Yale University, Unpublished test. Sternberg, R. J., Wagner, R. K., & Zhang, L. F. (2003). Thinking Styles Inventory––Revised. Yale University, Unpublished test. Trigwell, K., & Prosser, M. (1996). Congruence between intention and strategy in science teachers’ approaches to teaching. Higher Education, 32, 77–87. Trigwell, K., Prosser, M., & Taylor, P. (1994). Qualitative differences in approaches to teaching first year university science. Higher Education, 27, 75–84. Watkins, D. A., & Dahlin, B. (1997). Assessing study approaches in Sweden. Psychological Reports, 81, 131–136. Zhang, L. F. (2000). Relationship between thinking styles inventory and study process questionnaire. Personality and Individual Differences, 29, 841–856. Zhang, L. F. (2001a). Thinking styles, self-esteem, and extracurricular experiences. International Journal of Psychology, 36(2), 100–107. Zhang, L. F. (2001b). Approaches and thinking styles in teaching. Journal of Psychology, 135(5), 547–561. Zhang, L. F. (2002a). Thinking styles and cognitive development. The Journal of Genetic Psychology, 163(2), 179–195. Zhang, L. F. (2002b). Thinking styles and modes of thinking: Implications for education and research. The Journal of Psychology, 136(3), 245–261. Zhang, L. F. (2003a). Contributions of thinking styles to critical thinking dispositions. The Journal of Psychology, 137(6), 517–544. Zhang, L. F. (2003b). Preferred Teaching Approach Inventory. The University of Hong Kong, Unpublished test. 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., & Sternberg, R. J. (2000). Are learning approaches and thinking styles related? A study in two Chinese populations. The Journal of Psychology, 134(5), 469–489. Zhang, L. F., & Sternberg, R. J. (2001). Thinking styles across cultures: Their relationships with student learning. In R. J. Sternberg & L. F. Zhang (Eds.), Perspectives on thinking, learning, and cognitive styles (pp. 197–226). Mahwah, NJ: Lawrence Erlbaum. Zhang, L. F., & Sternberg, R. J. (2002). Thinking styles and teacher characteristics. International Journal of Psychology, 37(1), 3–12.
Do university students’ thinking styles matter in their preferred teaching approaches? Li-fang Zhang
*
Faculty of Education, The University of Hong Kong, Pokfulam Road, Hong Kong Received 8 May 2003; received in revised form 14 January 2004; accepted 19 February 2004 Available online 27 March 2004
Abstract This study pioneered the research on the role of university students’ thinking styles in their preferred teaching approaches. Three hundred and forty-eight (111 male and 237 female) students from a large comprehensive university in Beijing, P.R. China, responded to the Thinking Styles Inventory (Revised) and the Preferred Teaching Approach Inventory. Results indicated that regardless of age, gender, university class level, and academic discipline, students with different thinking styles had significantly different preferences for particular teaching approaches. It was contended that both conceptual change and information transmission are necessary for effective teaching. Theoretically, the study contributed to the styles literature in general and to the literature on the relationships between styles and approaches of teaching and learning in particular. Practical implications of the present findings are discussed in the context of students’ teaching evaluations, teachers’ teaching, and university administrators’ personnel management. Ó 2004 Elsevier Ltd. All rights reserved. Keywords: Thinking styles; Preferred teaching approaches
1. Introduction Styles refer to people’s preferred ways of using the abilities that they have (Sternberg, 1997). After decades of theorizing and researching on styles, many theoretical models and frameworks on styles have been postulated. Among these existing works, two theories that are the most promising for improving the effectiveness of teaching and learning are Biggs’s theory of learning approaches and Sternberg’s theory of mental self-government. *
Tel./fax: +852-2859-2522. E-mail address: [email protected] (L.-f. Zhang).
0191-8869/$ - see front matter Ó 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2004.02.012
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Biggs (1979) proposed three learning approaches: surface, which involves a reproduction of what is taught to meet the minimum requirements; deep, which involves a real understanding of what is learned; and achieving, which involves using a strategy that will maximize one’s grades. Each approach is composed of two elements: motive and strategy. Motive describes why students learn, while strategy describes how students go about their learning. The Study Process Questionnaire (SPQ, Biggs, 1992) is designed to assess university students’ learning approaches. Good reliability and validity data have been obtained with this instrument among the majority of populations tested around the world. However, whereas some studies supported that the SPQ assesses three approaches to learning (e.g., Bolen, Wurm, & Hall, 1994), other studies supported a two-factor (surface and deep) model (e.g., Niles, 1995; Watkins & Dahlin, 1997). The two-factor model is consistent with the model proposed by Marton (1976) who used a phenomenographic method in studying students’ learning approaches. The theory of mental self-government (Sternberg, 1988, 1994, 1997) concerns people’s thinking styles, which apply to different types of activities, including teaching and learning. Central to this theory is the notion that people need to govern or manage their everyday activities. People choose styles of managing these activities with which they feel comfortable. The theory describes 13 thinking styles that fall along five dimensions of mental self-government: (a) functions (including the legislative, executive, and judicial styles), (b) forms (including the hierarchical, oligarchic, monarchic, and anarchic styles), (c) levels (including the global and local styles), (d) scopes (including the internal and external styles), and (e) leanings (including the liberal and conservative styles). A brief description of each of the 13 thinking styles can be found in Appendix A (for details, see Sternberg, 1997). These thinking styles are, in principle, value-free, for the same thinking style can serve one person beautifully in one situation, but may fail the same person miserably in another situation. However, in their repeated studies, Zhang and her colleagues (e.g., Zhang, 2000, 2001a, 2002a, 2002b; Zhang & Huang, 2001; Zhang & Postiglione, 2001; Zhang & Sternberg, 2000) have found that most of the thinking styles in Sternberg’s theory can be classified into two groups. The first group, known as Type I thinking styles, is composed of thinking styles that are more creativitygenerating and that denote higher levels of cognitive complexity, including such styles as the legislative, judicial, hierarchical, global, and liberal styles. The second group, known as Type II thinking styles, consists of thinking styles that suggest a norm-favoring tendency and that denote lower levels of cognitive complexity, including such styles as the executive, local, monarchic, and conservative styles. The remaining four thinking styles (i.e., anarchic, oligarchic, internal, and external) belong to neither the Type I group nor the Type II group. However, they may manifest the characteristics of the styles from both groups, depending on the stylistic demand of the specific task. For example, whether one prefers to work alone (internal style) or one prefers to work with others (external style), one can work on tasks that require either Type I thinking styles or Type II thinking styles. Also for instance, one could use the anarchic style in a sophisticated way––such as dealing with different tasks as they arise, but without losing one’s sight of the whole picture of the main issue. Under this circumstance, the anarchic style manifests the characteristics of Type I thinking styles. On the contrary, one also could use the anarchic style in a simple-minded way––such as dealing with tasks as they come along without knowing how each task contributes to his/her ultimate goal. Under this circumstance, the anarchic style manifests the characteristics of Type II thinking
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styles. In Zhang’s recent work (Zhang, 2003a), these four styles have been labeled as ‘‘Type III thinking styles’’. The theory of mental self-government has been operationalized through several inventories, including the Thinking Styles Inventory (TSI, Sternberg & Wagner, 1992) and the Thinking Styles in Teaching Inventory (TSTI, Grigorenko & Sternberg, 1993). Both inventories have been tested in cross-cultural contexts, including Hong Kong, mainland China, the Philippines, and the United States. Results indicated that both inventories have reasonably good reliability and validity (see Zhang & Sternberg, 2001 for a detailed review). The two inventories also have been assessed for their heuristic and predictive value in educational settings. For example, it has been found that students’ thinking styles do not only significantly contribute to their academic achievement, but also play a critical role in such aspects as students’ self-esteem, personality, and career interest. Moreover, teachers’ characteristics have a strong impact upon the thinking styles they use in teaching (i.e., teaching styles) (see Zhang & Sternberg, 2002 for a comprehensive review). Given that both learning approaches and thinking styles have heuristic and predictive value in educational settings and that both constructs fall within the styles literature (Sternberg, 1997), we conducted two studies (Zhang, 2000; Zhang & Sternberg, 2000) to examine the relationships between learning approaches and thinking styles among students. Both studies showed that students who reported a deep approach to learning tended to use Type I thinking styles, and that students who reported a surface approach to learning tended to use Type II thinking styles. Furthermore, the investigation of the relationships between styles and approaches in learning has been extended to the study of the relationships between styles and approaches in teaching (see Zhang, 2001b). As previously noted, Sternberg’s theory applies to different types of activities, including teaching and learning. The Thinking Styles in Teaching Inventory (TSTI, Grigorenko & Sternberg, 1993) assesses thinking styles as manifested in teaching––that is, teaching styles. The TSTI assesses two types of teaching styles: Type I styles that facilitate creativity and that encourage the development of cognitive complexity, and Type II styles that require conformity and that accommodate cognitive simplicity. In their investigation of approaches to teaching of first year university science teachers, Trigwell, Prosser, and Taylor (1994); (also Prosser & Trigwell, 1999) have found parallels with students’ approaches to learning. They proposed that there are two approaches to teaching. One is information transmission (also known as teacher-focused). Teachers adopting this approach to teaching tend to be content-oriented and to emphasize the reproduction of correct information. The other teaching approach is conceptual change (also known as student-focused). Teachers adopting this approach are learning-oriented and concerned with students’ conceptual change. These two approaches to teaching are measured by Trigwell and Prosser’s (1996) Approaches to Teaching Inventory (ATI). After examining the relationships between teaching styles (as measured by the TSTI) and teaching approaches (as measured by the ATI) among Hong Kong in-service teachers, Zhang (2001b) concluded that teachers who reported a conceptual change/student-focused teaching approach tended to use Type I teaching styles, and that teachers who reported a knowledge transmission/teacher-focused teaching approach tended to use Type II teaching styles. Thus, this finding between styles and approaches in teaching is consistent with that between styles and approaches in learning (see Zhang, 2000; Zhang & Sternberg, 2000).
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In the studies mentioned above, we have discussed extensively the implications of these findings for the process of teaching and learning. However, these discussions were all based on the respective research participants’ self-report of their own styles and approaches. To further enhance the effectiveness of teaching and learning, there is a need for establishing a dialogue between teachers’ teaching styles (and approaches) and students’ learning styles (and approaches). There are many ways to do so, one of which is to understand the kind of teaching styles/ approaches that students prefer that their teachers use. The present study initiates such an endeavour by investigating the relationships between university students’ thinking styles and the teaching approaches they prefer that their teachers use. Specifically, there were three objectives to this study. First, the study intends to ascertain the reliability and validity of the newly constructed Preferred Teaching Approach Inventory (Zhang, 2003b). Second, the study aims at revealing the profile of students’ preferred teaching approaches. Third, it intends to determine if it is possible to use students’ thinking styles to predict the teaching approaches that university students prefer that their teachers adopt. It was predicted that students who tended to use Type I thinking styles prefer that their teachers adopt the conceptual change/student-focused approach to teaching (either ‘conceptual change’ or ‘student-focused’ will be used to refer to ‘conceptual change/student-focused’ hereafter), but not the information transmission/ teacher-focused approach (either ‘information transmission’ or ‘teacher-focused’ will be used to refer to ‘information transmission/teacher-focused’ hereafter). It was also predicted that students who tended to use Type II thinking styles prefer that their teachers use the information transmission approach to teaching, but not the conceptual change approach. These predictions were based primarily on the ‘matching hypothesis’. According to the matching hypothesis, students would actively search for the learning environment in which their ways of using their abilities (i.e., thinking styles according to Sternberg) will be accommodated. Based on the definitions of the types of thinking styles and those of the two teaching approaches, whereas the conceptual change teaching approach tends to accommodate Type I thinking styles, the information transmission teaching approach tends to accommodate Type II thinking styles. As for Type III styles, since they may manifest the characteristics of either Type I or Type II styles, Type III styles may be accommodated by either the conceptual change teaching approach or the information transmission teaching approach. Therefore, Type III thinking styles may be significantly related to either the conceptual change approach or the information transmission approach.
2. Method 2.1. Participants Three hundred and forty-eight (111 male and 237 female) students from a large comprehensive university in Beijing volunteered to participate in this research. With both the mean and the median being 20 years, the participants’ ages ranged from 17 to 35 years. Among the participants, there were 48 freshmen, 160 sophomores, 117 juniors, and 23 seniors. Furthermore, the participants were pursuing their Bachelor’s degrees in the following academic areas: the Chinese language, economics, education, life science, and physics.
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2.2. Measures Two self-report inventories were administered to the participants. The first was the Thinking Styles Inventory––Revised (TSI-R, Sternberg, Wagner, & Zhang, 2003). The second was the Preferred Teaching Approach Inventory (Zhang, 2003b). The TSI-R is a modified version of Sternberg and Wagner’s (1992) Thinking Styles Inventory (TSI) based on the theory of mental self-government. Consisting of 65 statements, the inventory assesses the 13 thinking styles delineated in the theory, with each 5 statements contributing to the assessment of one of the thinking styles. For each statement, the participants rated themselves on a 7-point Likert type scale, with 1 indicating that the statement does not at all represent the way they normally carry out their tasks, and 7 denoting that the statement characterizes extremely well the way they normally carry out their tasks. Here are two examples: (1) ‘‘When faced with a problem, I use my own ideas and strategies to solve it’’ (legislative style); and (2) ‘‘I like to figure out how to solve a problem following certain rules’’ (executive style). The TSI has been translated and back-translated between Chinese and English in 1996. Both the Chinese and English versions of the inventory have been used in numerous studies. Reasonable reliability and good validity data have been demonstrated in all existing studies. However, previous research indicated that lower scale reliabilities were usually obtained with three of the 13 scales: local, monarchic, and anarchic. A careful examination of the item-scale reliabilities from previous data sets indicated that 7 items needed to be re-written: 2 from the local scale, 3 from the monarchic scale, and 2 from the anarchic scale. In the present study, a Chinese version of the TSI-R was used. Cronbach’s alphas were 0.74, 0.65, 0.74, 0.65, 0.67, 0.83, 0.76, 0.75, 0.65, 0.70, 0.51, 0.73, and 0.78, respectively for the legislative, executive, judicial, global, local, liberal, conservative, hierarchical, monarchic, oligarchic, anarchic, internal, and external styles. The alpha coefficients for the local and the monarchic scales have been improved dramatically: from low to mid 0.50s to nearly 0.70. The alpha coefficient for the anarchic scale only showed slight improvement. The validity of the TSI-R was supported by the results from an exploratory factor analysis with an oblique rotation. The way that the scales clustered makes substantive sense. The first factor was dominated by loadings of Type I thinking styles, whereas the second factor by those of Type II thinking styles. The third factor was dominated by loadings of a pair of contrasting styles: the internal and external styles. Finally, the fourth factor was dominated by loadings of a second pair of contrasting styles: the global and local styles. These four factors accounted for 68% of the variance in the data. Table 1 presents the detailed statistics obtained from this factor analysis. The Preferred Teaching Approach Inventory (PTAI, Zhang, 2003b) was particularly designed for the present study. Adapted from Prosser and Trigwell’s (1996) Approach to Teaching Inventory, the PTAI is a self-report test consisting of 16 items. The 16 items fall into 2 scales (with 8 items in each): conceptual change and information transmission. Each scale is further divided into 2 subscales, with one containing 4 intention items, and the other containing 4 strategy items. Therefore, the four subscales are conceptual change/student-focused/intention (CCSFI), conceptual change/student-focused/strategy (CCSFS), information transmission/teacher-focused/ intention (ITTFI), and information transmission/teacher-focused/strategy (ITTFS). Each item is a statement describing students’ preference for their teachers’ teaching approach. The respondents
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Table 1 Factor loadings: TSI-R scales and PTAI subscales (N ¼ 348) Scale
TSI-R Factor 1
Legislative Executive Judicial Global Local Liberal Conservative Hierarchical Monarchic Oligarchic Anarchic Internal External % Variance C. variance Eigenvalue
PTAI Factor 2
Factor 3
Factor 4
0.88 0.80 0.58 0.46
)0.39
0.49 )0.81
0.75 0.87 0.42 0.30
0.58 0.50
0.37 0.86 31.75 31.75 4.13
17.37 49.12 2.26
)0.56 )0.38 0.54 )0.92 10.99 60.11 1.43
Subscale CCSFI CCSFS ITTFI ITTFS % Variance C. variance Eigenvalue
Factor 1
Factor 2 0.87 0.88
0.89 0.90 41.51 41.51 1.66
37.45 78.96 1.50
)0.58
7.93 68.05 1.03
Note. Variables with factor loadings of less than j0:30j are omitted. C. variance ¼ cumulative variance.
are instructed to rate themselves on a 7-point Likert scale, with 1 indicating that they absolutely disagree that the statement describes the way they prefer that their teachers conduct their teaching and assessment, and 7 suggesting that they absolutely agree that the statement describes the way they prefer that their teachers conduct their teaching and assessment. Examples of the items in the inventory are ‘‘It is important that my teachers try to develop a conversation with students about the topics that we are studying’’ (CCSFS), and ‘‘It is important that the subjects my teachers teach be completely described in terms of specific objectives relating to what students have to know for formal assessment items’’ (ITTSI). 2.3. Data analysis To ascertain the reliability and validity of the PTAI, estimates of internal consistency for the 4 subscales (and the 2 overall scales) of the PTAI were obtained with Cronbach’s alphas. Furthermore, an exploratory factor analysis was conducted to examine the validity of the PTAI. To prepare for the achievement of the remaining two objectives, I tested the possible significant differences in either thinking styles or preferred teaching approaches based on the participants’ age, gender, university class level, and academic discipline, using t-test and multivariate analysis of variance. No significant difference was identified based on any of the variables examined. Therefore, in the remaining statistical analyses, there was no need for controlling these variables. Two further statistical procedures were performed to achieve the remaining two objectives of this research. First, to identify the profile of students’ preferred teaching approaches, a bar graph for the summaries of the 4 subscale means was drawn. Second, to investigate the predictability of students’ thinking styles for their preferred teaching approaches, stepwise multiple regression
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procedures were conducted, with students’ thinking styles being the independent variables and their preferred teaching approaches as the dependent variables.
3. Results 3.1. PTAI scale reliabilities Cronbach’s alphas were 0.56, 0.69, 0.57, and 0.54, respectively for the conceptual-change/ intention, conceptual-change/strategy, information-transmission/intention, and informationtransmission/strategy subscales. The alpha coefficients for the two overall teaching approach scales were both 0.73. These alpha coefficients were similar in magnitude to those reported in Trigwell and Prosser’s (1996) study and to those in Zhang’s (2001b) study. In both previous studies, teachers’ self-reported teaching approaches were assessed by the Approaches to Teaching Inventory, from which the PTAI was adapted. Given the small number of items (4 items in each subscale), the heterogeneity of the items within each subscale, as well as the similarity between the present alpha coefficients and those obtained in the 2 aforementioned studies, the present alpha coefficients are considered sufficient to allow the remaining statistical analyses. 3.2. PTAI validity The results from the exploratory factor analysis followed by an oblique rotation are also summarized in Table 1. The first factor was dominated by loadings of the two subscales in the information transmission teaching approach, while the second factor was loaded with the two subscales from the conceptual change teaching approach. The two factors accounted for 79% of the variance in the data. 3.3. Profile of preferred teaching approaches The bar graph (see Fig. 1) of the summaries of the means for the 4 teaching approach subscales revealed the following order of students’ preferences––from the strongest to the weakest: a conceptual change strategy, a conceptual change intention, an information transmission intention, and an information transmission strategy. In general, students indicated a stronger preference for the conceptual change teaching approach than for the information transmission approach. 3.4. Predicting preferred teaching approaches from thinking styles Results from multiple-regression analyses indicated that significant predictive relationships were obtained for all four teaching approach subscales. Of the 13 thinking styles, nine styles contributed to these significant predictions: the legislative, judicial, anarchic, global, local, liberal, conservative, internal, and external thinking styles. The amount of variance in students’ preferred teaching approaches explained by their thinking styles were 21% for conceptual change intention, 21% for conceptual change strategy, 17% for information transmission intention, and 24% for
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Fig. 1. Students’ preferrred teaching approaches ðN ¼ 348Þ.
information transmission strategy. Table 2 presents the detailed statistics from these multiple regressions. Specifically, the following predictive relationships were identified. First, the liberal, internal, and external thinking styles positively predicted a conceptual change intention. Second, the anarchic, global, and judicial styles positively predicted a conceptual change strategy, whereas the conservative style negatively predicted a conceptual change strategy. Third, the conservative and
Table 2 Contributions of thinking styles to preferred teaching approaches (N ¼ 348) PTAI subscale 2
R bStyle 1 bStyle 2 bStyle 3 bStyle 4 F dfa
CCSFI
CCSFS
ITTFI
ITTFS
0.21 0.18Liberal 0.31Internal 0.21External
0.21 0.27Anarchic 0.16Global )0.19Conservative 0.16Judicial 13.95 4, 217
0.17 0.39Conservative 0.13External
0.24 0.27Conservative 0.28Global 0.27Local )0.15Legislative 16.99 4, 217
19.59 3, 219
Note: ITTFI ¼ Information transmission/teacher-focused (intention). ITTFS ¼ Information transmission/teacher-focused (strategy). CCSFI ¼ Conceptual change/student-focused (intention). CCSFS ¼ Conceptual change/student-focused (strategy). * p < 0:05. ** p < 0:001. *** p < 0:01. a Listwise cases exclusion was used.
22.88 2, 219
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external styles positively contributed to the prediction of an information transmission intention. Finally, the conservative, global, and local styles positively contributed to the prediction of the information transmission strategy, whereas the legislative style negatively did so.
4. Discussion The present study had three objectives. The first was to obtain the reliability and validity of the Preferred Teaching Approach Inventory. The second was to identify the profile of university students’ preferred teaching approaches. The third was to examine the contribution of students’ thinking styles to their preferred teaching approaches. All three objectives have been achieved. Results indicated that the PTAI (sub)scales possesses reliabilities that are comparable with those obtained in previous studies using the Approach to Teaching Inventory that is based on the same theoretical model. Moreover, results from factor analysis also confirmed the two approaches to teaching in Trigwell and Prosser’s (1996) work as well as in Zhang’s (2001b) work. These present psychometric data indicate that the PTAI possesses convergent validity with the Approach to Teaching Inventory. Therefore, it should be asserted that the PTAI is valid for assessing university students’ preferred teaching approaches. As previously noted, research participants’ preferred teaching approaches as shown in the bar graph of the PTAI subscale means indicated that as a whole group, students were in favor of a teaching approach that could help them make conceptual change over one that could help them obtain information. However, when thinking styles were taken into account, this preference for the conceptual change teaching approach did not show up as a stronger one any more. Instead, results from multiple regression analyses demonstrated that students with different types of thinking styles preferred different types of teaching approaches. Across the four sets of significant predictive findings, the three types of styles predicted students’ preferred teaching approaches in the following fashion: Regarding Type I thinking styles, three styles (including the judicial, global, and liberal styles) positively predicted the conceptual change teaching approach, while one style (the legislative style) negatively predicted the information transmission teaching strategy. Such finding regarding the predictive relationships of Type I thinking styles to teaching approach lent strong support to the hypothesis of the study. However, one identified significant relationship was not anticipated: the positive significant relationship between the global style and the information transmission strategy. A post hoc explanation could be that students with the global thinking style were more open to various teaching approaches. That is, apart from having a strong preference for the conceptual change teaching strategy, students with the global thinking style also had a strong preference for the information transmission teaching strategy. Regarding Type II thinking styles, the conservative and local styles positively predicted the information transmission approach. Meanwhile, the conservative thinking style negatively predicted the conceptual change strategy. These findings lent full support to the prediction about the relationships between Type II thinking styles and students’ preferred teaching approaches. As for Type III styles, three of the thinking styles (i.e., internal, external, and anarchic styles) positively contributed to the prediction of the conceptual change teaching approach. Simultaneously, the external thinking style also positively contributed to the prediction of a preferred
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information transmission intention. It should be recalled that no specific prediction was made regarding the relationships between thinking styles and preferred teaching approaches due to the instability of the Type III thinking styles with respect to the characteristics they may manifest depending on the stylistic demands of a given task. Results indicated, though, that students with Type III thinking styles were essentially in favor of the conceptual change teaching approach, with the external style students also expressing a strong preference for the information transmission intention. These findings pertaining to the predictive relationships of students’ thinking styles to their preferred teaching approaches were more likely to be true than to have been found by chance. There are at least two reasons to support this claim. First, the obtained predictive relationships lent support to the earlier predictions that were primarily based on the popular ‘‘matching hypothesis’’, according to which, students would actively select learning environments in which their ways of using their abilities (i.e., thinking styles) can be accommodated (Holland, 1973; Jung, 1923; Nganwa-Bagumah & Mwamwenda, 1991; Saracho & Spodek, 1994). Teaching approaches can be construed as one type of learning environment. Thus, students with different thinking styles tend to prefer that their teachers use different teaching approaches. Second, the present findings are consistent with previous findings obtained from studies of the relationships between styles and approaches manifested in both teaching and learning, using the same theoretical models. For example, among students, Type I thinking styles were significantly related to the deep approach to learning, whereas Type II thinking styles were significantly related to the surface approach to learning (e.g., Zhang, 2000; Zhang & Sternberg, 2000). Likewise, among teachers, Type I thinking styles were significantly correlated with the conceptual change teaching approach, whereas Type II thinking styles were significantly correlated with the information transmission teaching approach (e.g., Zhang, 2001b). The present study, as expected, has found that students with Type I thinking styles preferred that their teachers use the conceptual change teaching approach and that students with Type II thinking styles preferred that their teachers use the information transmission teaching approach. Furthermore, Type III thinking styles were related to the conceptual change teaching approach.
5. Significance and implications The present study has made four major contributions. The first relates to the revision of the Thinking Styles Inventory, resulting in dramatic improvement of the internal consistency of the local scale and that of the monarchic scale. Second, the study has obtained the psychometric properties of the newly constructed Preferred Teaching Approach Inventory. The PTAI has demonstrated comparable (sub)scale alpha coefficients with those obtained by Trigwell and Prosser (1996). By the same token, the PTAI has shown convergent validity with Trigwell and Prosser’s (1996) Teaching Approach Inventory. Third, by examining the relationships of students’ thinking styles to their preferred teaching approaches, the present study has extended previous works on the relationships between thinking styles and learning/teaching approaches. As has been noted previously, existing research has focused on the relationships between students’ thinking styles and students’ learning approaches and those between teachers’ teaching styles and teachers’ teaching approaches. This
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study focuses on the relationships between students’ thinking styles and their preferred teaching approaches. Fourth, the study has enriched the literature on styles. Existing literature has documented studies that demonstrated the roles of thinking styles in many aspects of student learning and development as well as in teachers’ teaching approaches. The present study has revealed that thinking styles also contributed to students’ preferences in their teachers’ teaching approaches. Apart from having made these theoretical contributions, the study also has practical implications for the university setting. There are good reasons for each of the three major parties (i.e., teachers, students, and university administrators) at the university setting to be aware of the predictive power of students’ thinking styles for their preferred teaching approaches. Teachers should be aware of this predictive relationship since this finding is signifying that to be effective in teaching, teachers should use both student-centered and teacher-centered approaches to teaching since only the use of both can accommodate the diverse thinking styles among students. In the past few decades, being influenced by the notion of constructivism, scholars and educators have been advocating for the conceptual-change teaching approach. However, whereas the conceptual-change teaching approach can help teachers to achieve many meaningful educational objectives, it does not always allow useful and efficient transmission of knowledge. It can be easily argued that for many reasons, knowledge transmission is a necessary part of teaching. Most notably, one’s life time is limited, which makes it impossible for one to learn everything through being in a learning environment that solely aims at facilitating conceptual change. Much wellestablished knowledge can be gained through being in a learning environment that focuses on didactic teaching in addition to student-centered teaching. This need for both teacher-centered and student-centered approaches is consistent with Pask’s (1976) (also Pask & Scott, 1972) notion of versatile learner. Versatile learners vary their learning approaches according to the characteristics of the tasks. Similarly, effective teachers (i.e., versatile teachers) should vary their teaching approaches according to the characteristics of their students, including their thinking styles. Effective teachers should use both teaching approaches so that students, no matter what their thinking styles are, could have the opportunity to study and grow intellectually in a learning environment that is both accommodating (i.e., a learning environment in which teachers use the teaching approaches that students prefer) and challenging (i.e., a learning environment in which teachers use the teaching approaches that do not match students’ thinking styles). Students should be aware of this predictive relationship for two reasons. First, an understanding of this relationship may encourage students to make a conscientious effort in enhancing teaching by either adjusting their own ways of learning to teachers’ ways of teaching or communicating with their teachers regarding their preferred teaching approaches. Second, an understanding of this predictive relationship may facilitate students to make a more balanced evaluation of their teachers’ teaching. Much research has indicated that teaching effectiveness is multifaceted (e.g., French, 1974; Herrmann, 1996; Phillips, 1999). Furthermore, many factors affect the way students rate their teachers’ teaching (e.g., Abrami, Leventhal, Perry, & Breen, 1976; Hale, 1980; Phillips, 1999). Very often, these evaluations could be fairly subjective. The present finding of the predictive relationship is suggesting that when students evaluate their teachers’ teaching, they should realize that their own thinking styles do affect their preferences for their teachers’ teaching approaches. Thus, their evaluation of the effectiveness of their teachers’ teaching approaches could very well be biased. Thus, it is important that they take their own
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thinking styles into account when making teaching evaluations. When students perceive their teachers as doing a poor teaching job, it might be a case of mismatch between their own thinking styles with their teachers’ teaching approaches. Finally, this predictive relationship should draw the attention of university administrators, in particular, decision makers for personnel issues. Too often, students’ teaching evaluation is used as one of the key criteria of university teachers’ teaching performance. However, there is much research evidence revealing that students’ teaching evaluation may be biased against (or for) teachers since it can be influenced by so many factors. The present finding indicates that students’ thinking styles statistically contributed to their preferences for teaching approaches. Thus, it is very possible that students with different thinking styles rate the same teacher’s teaching very differently. It is imperative, therefore, that students’ teaching evaluations be used critically, with at least students’ thinking styles being taken into consideration, especially when students’ teaching evaluations are used for personnel decision making, or for such an exercise as a promotion procedure. Acknowledgements Research for this article was supported by the Committee on Research and Conference Grants as administered by The University of Hong Kong. Appendix A Thinking styles in the theory of mental self-government Dimension
Thinking style
Key characteristics
Function
Legislative
One prefers to work on tasks that require creative strategies; One prefers to choose one’s own activities One prefers to work on tasks with clear instructions and structures; One prefers to implement tasks with established guidelines One prefers to work on tasks that allow for one’s evaluation; One prefers to evaluate and judge the performance of other people
Executive
Judicial
Form
Hierarchical
Monarchic Oligarchic
One prefers to distribute attention to several tasks that are prioritized according to one’s valuing of the tasks One prefers to work on tasks that allow complete focus on one thing at a time One prefers to work on multiple tasks in the service of multiple objectives, without setting priorities
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Appendix A (continued) Dimension
Level
Thinking style
Key characteristics
Anarchic
One prefers to work on tasks that would allow flexibility as to what, where, when, and how one works
Global
One prefers to pay more attention to the overall picture of an issue and to abstract ideas One prefers to work on tasks that require working with concrete details
Local Scope
Internal External
Leaning
Liberal Conservative
One prefers to work on tasks that allow one to work as an independent unit One prefers to work on tasks that allow for collaborative ventures with other people One prefers to work on tasks that involve novelty and ambiguity One prefers to work on tasks that allow one to adhere to the existing rules and procedures in performing tasks
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