Shahrekord University
On the Interplay of Field Independence/Dependence, Impulsivity/Reflectivity, Multiple Intelligences, and Reading Performance
A Thesis Proposal
Supervisor:
Dr. Mahmood Hashemian
Advisor:
Dr. Ali Akbar Jafarpour
By:
Maryam Adibpour
Faculty of Letters & Humanities
English Department
September 2012
1. Introduction
Certainly, variety is an ever-existing axiom in nature. In human beings, similar to other organisms, different genotypes have created variety in characteristics. Humans have different cognitive characteristics as well as different physical ones. The notion of cognitive styles and multiple intelligences (MI) substantially contributes to the description of a small part of our cognitive differences. Apparently, these cognitive differences lead to different performance in many aspects including learning an L2. Hence, learning an L2 is affected by one’s cognitive styles and multiple intelligences in line with one’s other cognitive features.
Reviewing the literature on the interplay of cognitive styles and language learning, one finds a large body of research investigating the relationship between cognitive style and success in different aspects of language learning (e.g., Alavi & Kaivanpanah, 2009; Hessami Azizi, 1994; Jamieson, 1992; Salmani-Nodoushan, 2007; Soozandehfar & Souzandehfar, 2011; Yousefi, 2011) and to a lesser extent studies examining the relationship between multiple intelligences and language learning (e.g., Akbari & Hosseini, 2007; Seifoori & Zarei, 2011; Rahimi & Qannadzadeh, 2010; Razmjoo, 2008) with both showing controversy in the results. The focus of this study is to conduct a research to quell controversies and yield clear insight into the issue matter.
The notion of cognitive style, which has become so popular among researchers since its emergence, refers to “the link between personality and cognition that influences how we learn things in general and the particular approach we adopt dealing with problems” (Salmani-Nodoushan, 2007). Messick (1976, p.5) describes them as “consistencies in the manner or form of cognition” whose influence “extends to almost all human activities that implicate cognition” (cited in Cao, 2006, p. 1). In fact, they are relatively stable indicators of how learners perceive, interact with, and react to the learning environment (Keefe, 1979).
Among different cognitive styles, the focus of this study is on the two cognitive styles of field independence/dependence (FI/FD) and reflectivity/impulsivity (R/I). FI/FD has received the attention of researchers much more than R/I and has been investigated in a large body of research (e.g., Bush & Andrulis, 1975; Hessami Azizi, 1994; Salmani-Nodoushan, 2007; Soozandehfar, 2011). FD refers to a cognitive style in which an individual considers the whole of a learning task containing many items, whereas FI refers to a cognitive style in which an individual is able to concentrate on particular items (Brown, 2000, cited in Salmani-Nodoushan, 2007, p. 83) and separates some aspects of experience from its background (Soozandehfar, 2011); thus, the word field in this dichotomy refers to the background. Meanwhile, R refers to the tendency to reflect on the solution to a problem accurately where several alternatives are possible and take time to reach a decision, and I refers to the tendency to make a decision very quickly with little concern for accuracy (Jamieson, 1992). Reviewing literature on the relation of FI/FD and R/I to language learning skills, one easily notices too much incongruence in the results. The present study is aimed at examining the relation of the cognitive styles introduced to the language skill of reading. The rationale based upon which the language skill of reading has been selected from among other language skills is the access to a reading scale which enjoys the possibility of measuring learners’ performance on holistic and analytic reading tasks. Such a scale lets the researcher to focus on certain abilities involved in reading instead of an overall range of abilities affecting reading performance. So, it offers a more accurate insight into the nature of relationships among the study variables.
The other central theme of this study is MI. The theory of MI proposed by Gardner (1983) considers intelligence as a composite of different abilities or aptitudes (Akbari & Hosseini, 2007). Firstly, Gardner (1983) divided human intelligences into eight categories: linguistic, logical-mathematical, musical, spatial, bodily-kinesthetic, interpersonal, intrapersonal, and naturalist intelligences. Later on, other categories like existential, social, emotional, sexual, economic, and creative intelligences were added. Here, based upon the fact that the Multiple Intelligences Developmental Assessment Scales (MIDAS; Shearer, 1996), measuring eight intelligences, has been used to measure MI, just the eight intelligences proposed first will be considered. These eight intelligences have been defined by Karamikabir (2011, p. 8) as follows:
1. Linguistic intelligence involves “sensitivity to spoken and written language, the ability to learn languages, and the capacity to use language to accomplish certain goals.”
2. Logical-mathematical intelligence involves the capacity to “analyze problems logically, carry out mathematical operations, and investigate issues scientifically.”
3. Musical intelligence involves “skill in the performance, composition, and appreciation of musical patterns.”
4. Spatial intelligence is concerned with the ability to “recognize and use patterns of wide space and more confined areas.”
5. Bodily-kinesthetic intelligence entails “the potential of using one’s whole body or parts of the body to solve problems.”
6. Interpersonal intelligence involves “the capacity to understand the intentions, motivations, and desires of other people, and have good relationships with others.”
7. Intrapersonal intelligence involves “the ability to understand one’s own feelings, fears, and motivation.”
8. Naturalist intelligence involves “the ability to think about, recognize, and categorize the natural world.”
MI and its relationship to language learning have been investigated in several studies (e.g., Marefat, 2007; Rahimi & Qannadzadeh, 2010; Razmjoo, 2008; Seifoori & Zarei, 2011; Yeganehfar, 2005). To the best of the present researcher’s knowledge, few studies have embarked on the relationship between MI and reading ability. Considering this and the considered rationale behind measuring reading mentioned before, this study will examine the relationship between MI and reading ability.
All in all, the present study is aimed at investigating the relationship between language learners’ FI/FD, R/I, MI, and their reading performance.
2. Literature Review
Cognitive psychologists and educators have long been eager to understand individual differences in cognition and their impact on learning and instruction (Altun & Kakan, 2006). Reviewing literature, one sees a large body of research investigating the factors related to language proficiency and language achievement (e.g., Alptekin & Atkan, 1990; Besson & Schon, 2001; Bongaerts, van Summeren, Planken, & Schils, 1997; Dornyei, 2005; Johnson, Prior, & Artuso, 2000; Kok, 2010; Milovanov, Pietila, Tervaniemi, & Esquef, 2009; Oflaz, 2011; Slevc & Miyake, 2006; Tallal & Gabb, 2006). Amongst the most popular factors researched are age, sex, aptitude, hemispheric dominance, motivation, anxiety, extroversion, learning strategies, FI/FD, I/R, ambiguity tolerance, and intelligences. From among the above, FI/FD has long been long been fascinating to researchers. Various studies have been done to investigate the effect of FI/FD on different aspects of language learning (e.g., Alavi & Kaivanpanah, 2009; Blanton, 2004; Hessami Azizi, 1994; Nilforooshan & Afghari, 2007; Salmani-Nodoushan, 2007; Yousefi, 2011).
In 1994, Hessami Azizi investigated whether test-takers’ FI/FD affected their performance on reading comprehension tests, and he found a statistically significant difference between the test-takers’ FI/FD and their performance on the reading comprehension tests.
In another research carried out in 2004, Blanton examined the influence of students’ cognitive style on performance on three forms of standardized reading comprehension test: timed multiple-choice, constructed response, and untimed multiple-choice tests. She found a significant mean difference between the timed multiple-choice test scores of the FI/FD students, but not between the means of the scores for the constructed response and the untimed multiple-choice test scores.
In 2007, Salmani-Nodoushan, investigating the effect of FI/FD on learners’ overall and task-specific performance on task-based reading comprehension, found that cognitive style leads to significant difference in the participants’ performance of true-false, sentence completion, outlining, scanning, and elicitation tasks.
In addition the effect of FI/FD on L2 writing performance considering general, narrative, and argumentative writing has been investigated in 2007 by Nilforooshan and Afghari. The results of their study showed a significant difference between the two groups of FI/FD writing skill in general and the narrative writing in particular, but no significant difference between their argumentative writing.
The role of FI/FD in lexical inferencing has also been investigated. Alavi and Kaivanpanah (2009) examined whether lexical inferencing ability, which requires attention to textual details and identification of the links between textual elements, is affected by L2 learners’ cognitive style of FI/FD. Considering both short and extended contexts, they distributed two passages and 23 sentences, in which the unknown words were underlined, to 112 learners were supposed to provide a synonym, a translation, or an explanation for the underlined words. The results of their study showed that having similar performance on short contexts, the FI participants outperformed the FD ones in extended contexts.
In the same line, Yousefi (2011) carried out research so as to examine the relationship between FI/FD and listening skills. The results showed the existence of a relationship between FD and listening skill, but no relationship between FI and listening skill.
Compared with FI/FD, the notion of I/R has received much less attention from researchers. Ehrman and Oxford (1990) suggested these two cognitive styles to be different measures of the same construct. In 1992, Jamieson examined the claim and found no significant relationship between FI/FD and I/R leading to consider them two measures of the same construct. In addition he investigated the relationship between these two cognitive styles and ESL success and concluded no relationship.
Besides FI/FD and I/R, MI is amongst the factors whose relationship to language learning and proficiency have been investigated. Razmjoo (2008) planned a study to examine the strength of the relationship between language proficiency and nine types of intelligences. He concluded that no significant relationship exists between language proficiency and MI as a whole and each of the nine intelligence types in particular. Additionally, the results indicated that none of the nine types could be considered as the predictor for language proficiency, and there was no significant difference between the males and females regarding the nine types of intelligence.
In another study, Akbari and Hosseini (2007) investigated the existence of possible relationships between the use of language learning strategies and MI. The results indicated significant relationships between the use of the strategies and MI. However, musical intelligence did not correlate with any aspect of strategy use, and kinesthetic intelligence was found to correlate with only memory learning strategies.
In 2005, Yeganehfar conducted a study to investigate the relationship between MI and writing skill. Interestingly, the results showed a significant correlation between the participants’ writing skill and their spatial and linguistic intelligences.
Similarly, Marefat (2007) made an attempt to examine the relationship between students’ MI profile and their writing skill. She concluded that kinesthetic, existential, and interpersonal intelligences made the biggest contribution to predicting writing scores.
In another study by Rahimi and Qannadzadeh (2010), the relationship between quantitative usage of logical connectors, in terms of both token and type, in Iranians’ EFL essay writing and their logical/mathematical and linguistic intelligences was examined. The results showed that the EFL students with higher logical/mathematical intelligence tended to use more logical connectors in their writings. Surprisingly, it was revealed that linguistic intelligence was less significant to the token rate of logical connectors in EFL essay-writing than logical intelligence.
By reviewing the literature on of FI/FD, I/R, and MI, one notices a great amount of incongruence in the results of the studies on the relation of FI/FD and I/R to language learning skills and a dearth of study on the relation of MI to the reading skill. Hence, the present study is designed to shed light on the interplay of FI/FD, R/I, MI and reading performance ability.
3. Statement of the Problem
Although L2 learners’ cognitive profile, including FI/FD, I/R and MI, can affect their performance in various aspects of language learning, it seems a neglected issue in L2 teaching.
It seems that teachers generally consider L2 proficiency the only source of score variance and largely ignore the effect of the aforementioned factors, which can create error variance. Not only testing, but also teaching is affected negatively as a result of the general ignorance about the possible effects of FI/FD, I/R, and MI on L2 performance. The mentioned cognitive characteristics are not considered in devising lesson plans, and this contributes to the inefficiency of L2 pedagogy.
Taking into account the consequences of the lack of insight about the effect of the aforementioned cognitive differences on L2 performance and the fundamental importance of the language skill of reading to L2 learners, the present researcher tries to shed some light on the interplay of FI/FD, I/R, MI, and reading performance.
In addition, taking into account the issue of MI from an alternative perspective, one finds that MI are, in fact, human beings’ genetically controlled characteristics which are, like other characteristics, distributed normally in normal populations. Thus, a better approach may be describing and categorizing human beings’ characteristics rather than intelligences. Besides MI, the cognitive styles of FI/FD and I/R can be considered as human beings’ characteristics.
In an attempt to describe and categorize human beings’ characteristics, one can investigate patterns of relationships among human beings’ characteristics as well as examining brain locations responsible for them. The combination of these two approaches can shed some light on the nature of unknown patterns ruling human beings’ characteristics and may lead to insights in harmony with the Human Genome Project. Considering the above, the present study will hopefully shed some light on the relationship between FI/FD, I/R, and MI in addition to the other purposes.
3.1. Research Questions
This research is an attempt to find the answer to the following questions:
1. Is there any relationship between L2 learners’ ID/FD and their reading performance?
2. Is there any relationship between L2 learners’ I/R and their reading performance?
3. Is there any relationship between L2 learners’ MI and their reading performance?
3.2. Research Hypotheses
Accordingly, the following null hypotheses are formulated:
• H01: There is no relationship between L2 learners’ FI/FD and their reading performance.
• H02: There is no relationship between L2 learners’ I/R and their reading performance.
• H03: There is no relationship between L2 learners’ MI and their reading performance.
1. Methodology
4.1. Participants
In the first stage of this study, a total population of 80 male and female M.A. students, majoring in TEFL, aged 23-32, from Shahrekord University and University of Isfahan will be selected. In order to homogenize the participants in terms of proficiency, the Oxford Placement Test (OPT), with reasonable measures of validity and reliability will be used to screen the participants. The participants who score lower than 50% of the total possible score will be excluded from the study.
4.2. Materials
To ensure the homogeneous entry behavior of the participants in terms of proficiency, OPT will be used in this study.
In order to identify the participants’ cognitive style of FI/FD, GEFT will be used. GEFT is a nonverbal measure, developed by Witkin, Oltman, Raskin, and Karp in 1971. They reported a reliability coefficient of .82 for it. Regarding validity, previous studies (Cano, Garten, & Raven, 1992; Panek, Funk, & Nelson, 1980) have reported adequate validity for this scale.
To identify the participants’ cognitive style of I/R, the Matching Familiar Figures Test (MFFT), which is a nonverbal scale, will be used. MFFT, developed by Kagan (1965), consists of 20 items. Each item consists of one standard picture with eight similar variants. The learner’s task is to select the drawing that exactly corresponds to the standard one. Meanwhile, the tester records the total number of errors and the latency of the first response to each item individually. Based upon accuracy and latency, the participants are classified into four groups of reflective, impulsive, slow and inaccurate, as well as fast and accurate (Al-Salimi, 2010). MFFT is reported to be highly reliable. Conducting test-retest reliability, Buela-Casel (2003) reported the reliability coefficient of .85 for latency and .77 for errors (cited in Al-Salimi, 2010, p. 149), and Al-Salimi (2010) reported the reliability coefficient of .88 for latency and .78 for errors. Regarding validity, previous studies (Al-Salimi, 2010; El-Faramawy, 1986; Frare, 1986) have reported adequate validity for this scale.
In order to find out the participants’ performance on the holistic and analytic reading tasks, Task-Based Reading Test (TBRT) will be administered. TBRT, developed by Salmani-Nodoushan (2003), consists of three modules: a) the electronics module (TBRT-EM), b) the accounting module (TBRT-AM), and c) the general module (TBRT-GM). Each module is made up of five passages that have the maximum correspondence to the IELTS General Training Reading Module (UCLES, 2000) in terms of textual features. TBRT-EM and TBRT-AM are designed based upon the content areas students majoring in electronics and accounting study in their academic courses, whereas TBRT-GM is designed in accordance with general content areas. Considering the study participants’ major, TBRT-GM should be used for the present research. Like other modules, TBRT-GM consists of 40 items measuring performance on five reading tasks: true-false task, sentence-completion task, outlining task, writer’s-view task, and skimming task. True-false, outlining, and elicitation tasks, consisting of 12, six, and five items each are holistic tasks, whereas sentence completion and scanning tasks, consisting of eight and nine items each, are considered as analytic tasks. Validating TBRT against the 1990 version of the IELTS, Salmani-Nodoushan (2007) reported the correlation coefficient between them to be 0.871. Additionally, TBRT enjoys a reliability coefficient of 0.871.
In order to identify the MI profiles of the participants, MIDAS will be used. MIDAS, developed by Shearer (1996), is a scale consisting of 119 Likert-type questions that taps eight types of MI.
4.3. Procedure
Firstly, in order to homogenize the participants, OPT will be administered. Secondly, so as to identify the participants’ cognitive styles of FI/FD and I/R as well as their MI profile, GEFT, MFFT, and MIDAS will be separately administered. Then, to identify the participants’ performance on the holistic and analytic reading tasks, TBRT will be administered. Finally, the collected data will be analyzed using Pearson correlation, multiple regression analysis, and independent t test.
4.4. Data Analysis
After the required data are collected, using the Statistical Package for Social Sciences (SPSS), the present researcher will run Pearson correlation, multiple regression, and independent t test to analyze the data.
5. Significance of the Study
The findings of this study can be beneficial to L2 pedagogy. According to Jamieson (1992), learner characteristics are considered to play a role in L2 learning. Looking at previous studies, it is found that both FI/FD and I/R as well as MI profiles affect L2 learners’ proficiency. Kang (1999) mentions that students can achieve their learning power by being aware of style areas in which they feel comfortable, and trying on the development of these areas, they manage to foster their intellectual growth (cited in Kheirzadeh & Kassian, 2006, p. 188)
In addition, teachers should apply in the classroom the insights that they gain regarding cognitive differences and their effect on L2 development. Yielding deep insight into L2 learners’ cognitive profiles and their effect can improve the efficacy of pedagogical programs involving to a considerable extent. According to Kang (1999), teachers should identify strong style patterns in their classes and devise lesson plans which accommodate individual learning style preferences.”
Benefits of knowing cognitive styles to learners are stated by Ngeow (1999, cited in Kheirzadeh & Kassaian, 2006, p. 188) as follows:
1. Learners who are conscious of their style make better use of their learning opportunities.
2. Learners learn better when provided with learning opportunities that enhance their learning preferences.
3. Learners work better with new learning styles if they are provided with given guided opportunities to practice them.
Understanding L2 participants’ cognitive profiles improves testing as well as teaching and learning. Considering the fact that L2 learners’ cognitive profiles are potential sources of score variance, L2 test developers can boost the reliability of language tests through controlling the effect of these extraneous factors.
Investigating the relationship between FI/FD, I/R, and MI as its minor purposes, the present study will hopefully contribute to give a better understanding of the relatedness of certain cognitive styles and will shed some light on the nature of unknown patterns ruling our characteristics.
In a nutshell, the present researcher hopes that the current study shares a part in improving teaching, learning, and testing, illuminating the relation of FI/FD, I/R, and MI to language learners reading performance, and providing a clearer image of the relationship between cognitive characteristics.
References
Akbari, R., & Hosseini, K. (2007). Multiple intelligences and language learning strategies. System, 36, 141-155.
Alavi, S. M., & Kaivanpanah, S. (2009). Examining the role of individual differences in lexical inferencing. Journal of Applied Sciences, 9(18), 2829-2834.
Alptekin, C., & Atakan, B. (1990). Field dependence-independence and hemisphericity as variables in L2 achievement. Second Language Research, 6(2), 135-149.
Al-Salimi, T. A. (2010). A comparison of creative thinking and reflective-impulsive creative style in grade 10 male students from rural and urban Saudi Arabia, Unpublished doctoral dissertation, Victoria University, Australia.
Altun, A., & Cakan, M. (2006). Undergraduate students’ academic achievements, field dependent/independent cognitive styles and attitude toward computers. Educational Technology and Society, 9(1), 278-297.
Besson, M., & Schon, D. (2001). Comparison between language and music. In R. J. Zatorre, & I. Peretz (Eds.), The Biological foundations of music (pp. 232-258). The New York Academy of Sciences.
Bongaerts, T., van Summeren, C., Planken, B., & Schils, E. (1997). Age and ultimate attainment in the pronunciation of a foreign language. Studies in Second Language Acquisition, 19(4), 447-465.
Brown, H. D. (2000). Principles of language learning and teaching (4th ed.). White Plains, NY: Addison Wesley Longman.
Buela-Casel, H. (2003). Psychometric properties of a Spanish adaptation of the matching familiar figures test (MFFT-20). European Journal of Psychological Assessment, 19(2), 151-159.
Bush, D. F., & Andrulis, R. S. (1975). Relationship between performance by adult males on matching familiar figures and hidden figures test. Perceptual and Motor Skills, 41, 530-544.
Cano, J., Garton, B. L., & Raven, M. R. (1992). Learning styles, teaching styles and personality styles of preservice teachers of agricultural education. Journal of Agricultural Education, 33(1), 46-52.
Cao, Y. (2006). Effects of field dependence-independence cognitive styles and cueing strategies on students’ recall and comprehension. Unpublished doctoral dissertation, Virginia Polytechnic Institute.
Dornyei, Z. (2005). The psychology of language learner. London: Lawrence Erlbaum Associates.
Ehrman, M. E., & Oxford, R. L. (1990). Cognition plus: Correlations of language learning success. Modern Language Journal, 79(1), 67-89.
El-Faramawy, H. A. (1986). The correspondence between teacher and student cognitive style and its implications for academic achievement and academic tendency. Unpublished doctoral dissertation, University of Wales, Cardiff, Wales.
Frare, F. (1986). Reflectivity-impulsivity related to creativity and critical thinking. Unpublished doctoral dissertation, Zagazig University, Cairo, Egypt.
Gardner, H. (1983). Frames of mind. NY: Basic Books.
Hessami Azizi, A. (1994). Test method, test taker’s cognitive style, and their effect on test performance. Unpublished master’s thesis, Tarbiat Madarres University, Iran.
Jamieson, J. (1992). The cognitive style of reflection/impulsivity and field independence/dependence. The Modern Language Journal, 76, 491-501.
Johnson, J., Prior, S., & Artuso, M. (2000). Field dependence as a factor in second language communication production. Language Learning, 50(3), pp. 529-567.
Kagan, J. (1965). Matching Familiar Figures test.
Kang, S. (1999). Learning styles: Implications for ESL/EFL instruction. Forum, 37, 132-140.
Karamikabir, N. (2011). Gardner’s multiple intelligence and mathematical education. Procedia Social and Behavioral Sciences, 31, 773-781.
Keefe, J. W. (1979). Learning style: An overview. In Student learning styles: Diagnosing and prescribing programs (pp. 1-17). Reston, VA: National Association of Secondary School Principals.
Kheirzadeh, S., & Kassaian, Z. (2011). Field dependence/independence as a factor affecting performance on listening comprehension subskills: The case of Iranian EFL learners. Journal of Language Teaching and Research, 2(1), 188-195.
Kok, I. (2010). The relationship between students’ reading comprehension achievement and their attitudes toward learning English and their abilities to use reading strategies with regard to hemispheric dominance. Procedia Social and Behavioral Sciences, 3, 144-151.
Lynn Blanton, E. (2004). The influence of students’ cognitive style on a standardized reading test administered in three different formats. Unpublished doctoral dissertation, University of Central Florida.
Marefat, F. (2007). Multiple intelligences: Voices from an EFL writing class. Pazhuheshe-e Zabanha-ye Khareji, 32,145-162.
Messick, S. (1976). Personality consistencies in cognition and creativity. In S. Messick & Associates (Eds), Individuality in learning (pp. 4-22). San Francisco: Jossey-Bass.
Milovanov, R., Pietila, P., Tervaniemi, M., & Esquef, P. A. A. (2009). Foreign language pronunciation skills and musical aptitude: A study of Finnish adults with higher education. Learning and Individual Differences, 20, 56-60.
Ngeow, K. (1999). Classroom practice: Enhancing and extending learning styles through computers. In J. Egbert, & E. Hanson-Smith (Eds.), CALL, environment, research practice, and critical issues. Alexandia, VA: TESOL.
Nilforooshan, N., & Afghari, A. (2007). The effect of field dependence-independence as a source of variation in EFL learners’ writing performance. Iranian Journal of language Studies, 1(2), 103-118.
Oflaz, M. (2011). The effect of right and left brain dominance in language learning. Procedia Social and Behavioral Sciences, 15, 1507-1513.
Panek, P. E., Funk, L. G., & Nelson, P. K. (1980). Reliability and validity of the Group Embedded Figures Test across the life span. Percept Motor Skills, 50(3), 171-174.
Rahimi, A., & Qannadzadeh, J. (2010). Quantitative usage of logical connectors in Iranians’ EFL essay writing and logical and linguistic intelligences. Procedia Social and Behavioral Sciences, 5, 2012-2019.
Razmjoo, S. A. (2008). On the relationship between multiple intelligences and language proficiency. The Reading Matrix, 8(2), 155-174.
Salmani-Nodoushan, M. A. (2003). Text familiarity, reading tasks, and ESP test performance: A study on Iranian LEP and non-LEP university students, The Reading Matrix 3(1), 1-14.
Salmani-Nodoushan, M. A. (2007). Is field dependence or independence a predictor of EFL reading performance. TESL Canada Journal, 24(2), 82-108.
Seifoori, Z., & Zarei, M. (2011). The relationship between Iranian EFL learners’ perceptual learning styles and their multiple intelligences. Procedia Social and Behavioral Sciences, 29, 1606-1613.
Shearer, B. (1996). Multiple intelligences developmental assessment scales. Oxford: Greyen Press.
Slevc, L. R., & Miyake, A. (2006). Individual differences in second language proficiency: Does musical ability matter? Psychological Sciences, 17, 675-681.
Soozandehfar, S. M., & Souzandehfar, M. (2011). The effects of field-dependence/field independence cognitive styles and gender on second language speaking performance. California Linguistic Notes, 36(2), 1-21.
Tallal, P., & Gabb, N. (2006). Dynamic auditory processing, musical experience and language development. Trends in Neuroscience, 29(7), 382-390.
Witkin, H. A., Oltman, P. K., Raskin, E., & Karp, S. A. (1971). Group embedded figures test manual. Palo Alto, CA: Consulting Psychologist Press.
Yeganehfar, B. (2005). Investigating the relationship between proficiency in a foreign language and multiple intelligences. Unpublished master’s thesis, University of Allameh Tabatabaei, Tehran.
Yousefi, M. (2011). Cognitive style and EFL learners’ listening comprehension ability. Indonesia Journal of Applied Linguistics, 1(1), 70-79.
essay in here…