Faraj M Suwan. English Department, University of Tripoli, Tripoli, Libya. Email address: email@example.com
Wassim Jamal Essid. English Department, University of Tripoli, Tripoli, Libya. Email address: firstname.lastname@example.org
This study is an attempt to explore the relationship between motivation and language learning strategies (LLSs) use. It examined this relationship by studying the motivation and LLSs use of 76 Libyan English majors via the distribution of three questionnaires (see Appendices). The results showed that motivation is related to the frequency and use of language learning strategies. In addition, the results of the current study demonstrated that variances in motivational orientation (instrumental or integrative) significantly affect the employment of LLSs.
Keywords: Instrumental Motivation; Integrative Motivation; Language Learning Strategies; Motivation
Motivation of language learners is believed to have an effect on strategy use in several studies. Politzer and McGroarty (1985) pointed out that the purpose of the English language learning is a central theme in any discussion of language learning strategies. Oxford (1989) suggested that learners learn target languages for various reasons and goals and this could have an effect on their choice of learning strategies. Oxford and Nyikos (1989: 295) maintained that motivation had a “pervasive influence on the reported use of specific kinds of strategies…”, while Nyikos and Oxford (1993), reporting on a study of university language learners in the USA who were studying a language to fulfil a requirement, reported that the students who were interested in having good grades focused on formal, rule related processing strategies and academic study strategies, rather than on strategies which improve skills for authentic and communicative language use.
The extensive body of research on strategies suggests a relationship between motivation, use of strategies and learning success. Oxford and Crookall (1989: 411) found that in contrast to unmotivated learners, highly motivated ones used strategies frequently and that students who thought they were good language learners employed more strategies than those who regarded themselves as less successful learners. Oxford (1994) argues that the main motive for learning the language (motivational orientation) was important in the selection of strategies.
In their study of foreign language undergraduates, Gardner and MacIntyre (1993) asserted that substantially motivated learners employed learning strategies more frequently than those who were comparatively less motivated. These results were also confirmed by McIntyre and Noels’s (1996) study.
The findings reported by Gardner and MacIntyre (1994) and McIntyre and Noels (1996) seem compatible with what Oxford and Nyikos (1989) found when they examined the use of LLSs by 1,200 students learning various languages in a Midwestern American university. They concluded that “The degree of expressed motivation to learn the language was the most powerful influence on strategy choice.” (Oxford and Nyikos, 1989: 294). Oxford and Shearin (1994) state that it is of utmost importance to understand learners’ motivation which directly influences the use of LLSs.
In a study conducted on 24 Japanese third-year college students learning English as a second language in the UK to gauge their use of learning strategies and the effects of motivation, proficiency, and personality on these strategies, Tamada (1996) found that variations in motivational orientation (instrumental or integrative) significantly affected the utilisation of LLSs.
The survey carried out by Hassanpur (1999) on 102 Shiraz University Science students revealed that integratively-motivated students use more memory and cognitive strategies than instrumentally-motivated ones. Moreover, the integratively motivated learners reported to employ the four remaining strategies types more frequently than those with instrumental motivation, but the difference was not significant at the 0.05 level.
In an investigation of 46 Taiwanese undergraduate and graduate students of English as a Foreign Language in the US to examine the effect of motivation on the use of LLS , Chang and Huang (1999) found that the total number of learning strategies were associated with motivational level. The results also revealed that instrumentally-motivated students utilised more memory and affective strategies, while learners with integrative motivation exploited higher range of cognitive and metacognitive learning strategies. Compensation strategies were employed almost similarly by the two groups.
Sadighi and Zarafshan (2006) conducted a study to explore the effects of attitude, motivation, and years of study on the use of language learning strategies by 126 Iranian EFL university students. Concerning the variable motivation, integratively-motivated students used more strategies than instrumentally-oriented ones.
Sedaghat (2001) investigated the influence of attitude, motivation, and proficiency level of 109 Iranian female EFL learners on the use of listening comprehension strategies. As for the factor of motivation, the sole significant difference was found to be in the social domain. Integratively motivated learners utilised more social strategies than instrumentally motivated ones. An explanation for the results of this study might be that integratively-oriented learners tend to integrate and adapt themselves in the target language culture. Consequently, they seek ways to communicate with members of the target language; therefore, they exploit social strategies more than other strategies.
Kaylani (1996) examined the effects of gender and motivation on the use of LLSs by (12th grade) high school students in Jordan. Her study revealed that there was a strong relationship among gender, motivation and the strategies that the participants employed. Females and more motivated students appeared to be high strategy users. It should be noted that Kaylani’s (1996) study and the current study vary in the students’ learning level. Kaylani’s subjects were high school students while the subjects of this thesis are university English majors who are assumed to be more aware of the learning process and of the strategies they need to achieve this goal.
Yang’s (1999) study in which he examined the relationship between the learners’ self-perceived motivation and their use of LLSs revealed a positive correlation between the level of motivation and the use of LLSs.
MacLeod (2002) found that strategy use was not influenced by neither instrumental nor integrative orientation, but, rather, by motivational intensity.
Schmidt et al (1996) found that students with high levels of determination, instrumental motivation, and sociability reported using active cognitive and organizing strategies. In a later, large-scale study of heritage language learners, Schmidt and Watanabe (2001) found that, while motivation itself influenced strategy use, the strongest predictor was motivational intensity, followed by value (reasons for learning another language) and cooperativeness. Cognitive and metacognitive strategies were the most influenced by levels of motivation. Schmidt and Watanabe (2001) maintain that if one believes in the value of learning another language, for either instrumental or intrinsic reasons, one can logically be expected to use a variety of cognitive and metacognitive strategies to achieve that goal.
In a study which examined the effects of gender, years of study, proficiency, motivation and learning style on the use of language learning strategies by 196 low, mid and high proficiency EFL learners from two universities in Iran, Rahimi et al. (2004: 45- 46) found that motivation have the second strongest linear relationship with learners’ overall strategy use after proficiency. Their results showed significant differences (p < .05) among the three motivational groups. They found that highly motivated students were high strategy users, whereas the other two groups were moderate strategy users. Moreover, the students’ use of the six strategy categories was influenced by their motivational intensity. Highly motivated learners reported using all strategy categories more frequently than the mid-level motivation group who in turn utilised these strategies more frequently than the low motivation group.
It is worth mentioning that the results of the above mentioned studies are, for a large part, in harmony with each other. The findings of several studies (Politzer & McGroarty, 1985; Oxford & Nyikos, 1989; Oxford, 1994; Oxford, & Shearin, 1994) indicate that motivation is the most powerful factor in the selection and use of LLS. However, Rahimi et al (2004) found that proficiency had a stronger effect on the use of LLSs than motivation. They argue that this finding might be ascribed to their study’s EFL context in which the learners’ explicit knowledge is not effectively exploited in real-life situations or transferred into contextualised language use resulting in a decrease in their motivation (particularly intrinsic) in general.
Finally, according to findings of previous studies, the researchers expect to find a relationship between motivation and LLS. More specifically, the researchers anticipate that there will be a positive relationship between the motivation of Libyan university English majors and their use of language learning strategies.
Having made corroborative use of qualitative information in the preliminary study, the methodology employed in this study is exclusively quantitative to measure and analyze the hypothesized relationships between the study variables. In addition to an English placement test (Oxford placement test) and a background information questionnaire (Appendix 1), the quantitative analysis involved asking closed-ended questions via the distribution of two questionnaires (Appendix 2 and 3) which were piloted and modified as required before being distributed to a total of 76 students. Data generated in this way arguably affords ‘‘a good deal of precision and clarity’’ (McDonough and McDonough, 2004, p. 171) and allows quick and simple answers (Oppenheim, 2001).
The researchers translated all the questionnaires into Arabic to avoid misunderstanding the meaning of the instruments’ items by the participants. The translation of the questionnaires into Arabic was approved by two members of staff at the English Department in the University of Tripoli.
In addition to the participants name and year of study, the background information questionnaire contains items about the length of time learners spent in learning English before they entered the university, type of schooling, and time spent in an English speaking country (see appendix 1).
The motivation questionnaire which was piloted and amended in the preliminary study includes 45 items in total (see appendix 2) distributed over 7 subscales measuring Integrative Motivation (3 items), Instrumental Motivation (12 items), Attitudes towards studying English (6 items), Parental Encouragement (4 items), Intrinsic Motivation (7items), Extrinsic Motivation (5 items), and Effort (8 items).
The modified Strategy Inventory for Language Learning (SILL) contains a total of 53 items (see appendix 3) classified into six strategy categories measuring memory strategies (Part A ), cognitive strategies (Part B), compensation strategies (Part C), metacognitive strategies (Part D), affective strategies (Part E), and social strategies (Part F).
Seventy six Libyan students (n=76) majoring in English at the department of English, Faculty of Arts, Assawani Branch, in the University of Tripoli participated in the study. All participants were native speakers of Arabic. Of these 22 students were third year English majors and 54 students were fourth year English majors. There were 26 males and 50 females. Data were collected in three separate lectures on the 18th, 22nd and the 23rd of October 2018 and subjects received no monetary compensation for their participation. All the participants have spent their lives in Libya and had more or less the same normal Libyan state education. Only two female students were found to have stayed in English speaking countries for more than 10 years. The responses obtained from these two participants will be treated with caution during the analyses of the data.
The participants had an overall proficiency mean score of 49 with a standard deviation of 11.79 which places them in the elementary level, but according to frequency analysis, the results indicated that the majority of students are within the intermediate level (53.9 % and Mean = 55.37). Only 2.6 % (Mean= 92.00) of the subjects are within the advanced proficiency category (these were the two females who had stayed in English speaking countries for more than 10 years). Others are either within the beginners level (21.1%, Mean= 34.00) or within the elementary level (22.4%, Mean= 43.47). Thus, according to these results, the proficiency of the majority of Libyan university English majors can be considered intermediate.
The researchers obtained the consent of the Dean of Faculty of Arts to use three lectures on three separate days (the 18th, 22nd and the 23rd of October 2018) for the administration of the instruments and also to invite English majors to participate in the study. The aims of the instruments, their structure and content, and how they were to be completed were explained to the participants. The researchers asked the participants to give their answers as truly as possible and emphasized that they had no predetermined expectations and that no response would be deemed as better than another. The subjects were also assured that all the information collected will be confidential and will only be used for research purposes. Moreover, they were assured that their identities will be anonymous and that their personal information will be treated in strict confidence and will not be revealed. It should be noted that in Libya, unlike other Arabic countries, mixed gender classes are normal, so males and females study together in the same classroom.
The questionnaires were read aloud to the participants before they started to record their responses to ensure that they understood each item accurately. The researchers were assured that students understood all the instructions and items because students did not ask questions about any of them.
On the 18th of October 2018, participants were invited to participate in the study on the 22nd and 23rd of February. On the 22nd of February they filled in the background information questionnaire and responded to the questionnaire measuring motivation. On the 23rd of October 2018, the subjects recorded their answers for the modified SILL.
The administration and the completion of the questionnaires took 100 minutes on two separate days. Students spent 20 minutes on the background information questionnaire, 40 minutes on the motivation questionnaire, 40 minutes on the strategy inventory. The responses to questionnaires were reviewed separately during their collection to insure that each student has responded to all the items. If a response was not provided, the participant was encouraged to helpfully give his/her answer. Since the instruments were completed in class, the return rate was 100%.
The next section describes and discusses the analysis of reliability of the study instruments.
3. Analyses of Reliability
Although reliability had already been checked in the preliminary study, we thought it advisable to confirm it. This section presents and explains the analyses of reliability of the participants’ responses on various five point Likert-scales, for the two questionnaires measuring motivation and language learning strategy use (see Appendices 2 and 3). Using SPSS 16, these analyses were conducted as it is believed indispensable to prove the reliability of scores on which data description and analysis are based. As a consequence, the researchers preclude “the accumulation of results based on relatively invalid or unreliable measures” (Wilkinson et al., 1999:6).
The section is organized into two subsections. Each section firstly reports on the overall reliability of the instrument in question following its administration to 76 participants, then on the analyses of reliability of each of its component subscales.
3.1 Reliability of the Motivation Questionnaire
After the administration of the motivation questionnaire to the 76 subjects, the researchers entered the data into an SPSS data file and reversed the negative items (items 32, 33, 34, 35, 36, 3and 7).Then, the investigators analysed the data to test the overall reliability of the instrument. Cronbach’s alpha coefficient for internal consistency was therefore calculated for the 45 items in the motivation questionnaire. The overall reliability of the motivation scale appeared to have good internal consistency, α = 0.82.
After establishing the overall reliability of the motivation questionnaire analyses were made of the instrument subscales. As outlined above, the modified version of the motivation questionnaire used in this study consisted of 45 items which are divided into seven subscales, as shown in Table 1 below:
TABLE 1: MOTIVATION QUESYIONAIRE SUBSCALES
|Subscale||Number of Items|
|Attitudes towards studying English||6|
It was these seven subscales on which analyses of reliability were carried out. The approach to analysis included the examination of the overall reliability index of each of the seven motivation subscales and discussion of those scales, the scores of which were considered to be unreliable.
It can be seen in Table 2 that the reliability index for the seven subscales ranged from a minimum of 0.25 for the Integrative Motivation subscale to 0.82 for the Instrumental Motivation subscale.
Table 2. RELIABILITY INDEX OF MOTIVATION SUBSCALES
|Attitudes towards studying English||0.62|
As has been summarised in table 1 the scores on only four of the seven subscales of the motivation subscale when administered to the 76 participants in this study, can be considered reliable. Three of those four, Instrumental, Parental Influence, and Effort can be regarded straightforwardly as internally consistent as their corresponding Cronbach’s alpha coefficients were above 0.72. The Attitudes towards studying English subscale however, while broadly satisfactory, should be treated cautiously as it just reached the level of 0.62 for overall reliability. Hence, the researchers inspected the values of Item Deleted statistics and found that the deletion of item 30 would increase alpha by .016 which improves the overall reliability of the subscale to reach 0.64.
The three remaining subscales, Integrative, Intrinsic and Extrinsic must be considered unreliable because they failed to reach a satisfactory level of reliability. However, the reliability of these subscales could be increased by the removal of certain items.
The inspection of the Item-Total Statistics for the Integrative Motivation subscale revealed that the deletion of item 2 “I study English because it will help me understand English art, literature and culture” increases Cronbach’s alpha by 0.39. The researchers have also checked the participants’ responses to this item to find out whether students gave a low rating for this item which might have affected its correlation with other items of the integrative subscale, but it was found that students’ scores varied according to the five point Likert scale. Thus, item 2 was removed to improve the subscale’s reliability α = 0.64.
The Intrinsic Motivation subscale has an internal consistency α = 0.39, but none of the items would substantially affect the overall reliability if they were deleted. The worst offender is item 20, and removing this item would increase alpha by only 0.063 resulting in an unacceptable overall reliability of .45 (George and Mallery, 2003: 231).
Since the overall reliability index of the Intrinsic Motivation subscale did not reach an acceptable level of internal consistency even after the elimination of item 20, the researchers examined the internal consistency of the subscale at the item level to determine the overall satisfactoriness of the subscale. Hughes (1989) suggests an item-total correlation of 0.30 as the criterion necessary for an item to be regarded as relating satisfactorily to the subscale as a whole. However, only two of its seven items met the criterion of .30 item-total correlation (item 28 “I study English because I have a desire to learn it” and item 31 “I like the English lectures”). Five items, with a minimum value of 0.001 did not meet that criterion (item 19 “I study English because the textbooks and the materials used in class are interesting”, item 20 “I study English because learning English is a challenge that I enjoy”, item 21 “I study English because the class tasks and activities are enjoyable”, item 27 “I study English because I feel superior when I speak it”, and item 36 “The English lectures are boring”). Thus, the researchers conclude that the participants have rather different attitudes to these intrinsic aspects of learning.
To eliminate the five poorly correlating items in an attempt to improve the reliability index would minimize the subscale to two items, thus rendering it impractical. Further, the overall reliability index was considered too low for the practical application of the Spearman Brown prophesy formula. Thus it was concluded that the Intrinsic Motivation subscale was not internally consistent.
The Extrinsic Motivation subscale appeared to have a poor internal consistency of α = 0.57, but considering Alpha if Item Deleted statistics reveals that the deletion of item 26 (“I study English because it is my parents’ wish”) increases alpha by .083, reflecting an acceptable degree of reliability α = 0.65. So this item was removed leaving the Extrinsic subscale with an internal consistency α = 0.65. It is worth mentioning that responses to item 26 differed from responses to the other subscale items because while item 26 asks about an extrinsic aspect before students enrolled at university to study English other items of the subscale are related to benefits after their graduation (item 22: “I study English because it is a requirement asked for by most well-known employers”, item 22: “I study English because it is a requirement asked for by most well-known employers”, item 24: “I study English because being able to speak English will add to my social status” and item 25: “I study English because it will have financial benefits for me”). Item 23 (“I study English because I need to pass the examinations”) is also related to the immediate benefit of passing exams.
As has been demonstrated here, and is summarized on Table 3, after revision the scores on only six of the seven subscales of the motivation questionnaire, when administered to the 76 subjects in this study, can be considered reliable. Four of those six, Instrumental Motivation, Parental Influence, Extrinsic Motivation and Effort, can be regarded straightforwardly as internally consistent as their Cronbach’s alpha coefficients are either 0.65 or above. The Integrative Motivation and Attitudes towards studying English subscales however, while broadly satisfactory, should be treated cautiously as they just met the criterion level of 0.64 for overall reliability.
TABLE 3. RELIABILITY OF MOTIVATION SUBSCALES AFTER REMOVAL OF ITEMS
|Attitudes towards studying English||0.64|
On the other hand, the remaining Intrinsic Motivation subscale must be considered unreliable. Five items from seven on the Intrinsic Motivation subscale failed to reach a satisfactory level of reliability and coherence. Consequently, the Intrinsic Motivation subscale was discarded and was not considered in further analyses and discussion of the data.
The researchers have calculated mean ratings for each subscale across all the items that appeared to have an acceptable reliability. It should be mentioned that when calculating the overall mean for motivation as a whole, the researchers have left out the discarded items and all of the intrinsic subscale.
3.2 Reliability of the SILL
Following the administration of the modified version of SILL to the 76 subjects, an analysis was made of the overall reliability of the instrument (Cronbach alpha for internal consistency). The overall reliability was found to be 0.92. This was considered quite acceptable and compatible with the coefficients in the range of 0.93 to 0.98 obtained by various forms of the SILL and reported in Green and Oxford (1995: 264).
The researchers now move to the analyses of reliability of scores of the six SILL subscales.
As outlined above, the modified version of the SILL used in this study consisted of fifty three items which are divided into six subscales, as shown in Table 4 below:
TABLE 4: SUBSCALES OF THE SILL
|Memory (10 items)||Metacognitive (9 items)|
|Cognitive (14 items)||Affective (6 items)|
|Compensation (7 items)||Social (7 items)|
When the internal consistency was tested by applying Cronbach’s alpha to the six SILL subscales separately, the reliability index ranged from a minimum of 0.65 for the Memory subscale to 0.84 for the Social subscale (see Table 5).
TABLE 5: RELIABILITY INDEX FOR SILL SUBSCALES
As it can be seen in table 5 all subscales appeared to have good internal consistency. Moreover, the overall reliability was found to be 0.92. Thus the researchers concluded that the data are reliable enough to be analyzed.
The researchers have prepared the students’ responses for data analysis by adding up students responses to each strategy category and getting their averages by dividing by the total number of items in each category. The overall strategy scores were obtained by adding all sums of the six strategy categories and dividing by 53 (the number of the SILL items).
The next section will describe the results obtained from the responses to the study instruments and their analysis.
4. Results and Discussion
To test this hypothesis, the research first used a scatter plot to visually see if there appears any linear relationship between the students’ motivation overall scores and their overall average scores on the SILL. The fit line in Fig. 1 below shows a relatively rising trend between the two variables indicating a positive relationship. To verify that there is a positive relationship between the participants’ motivation and their strategy use, the researchers ran a statistical analysis using the Pearson product moment correlation coefficient (Pearson r) as the test to determine any associations between motivation and strategy use.
The results of Pearson correlation indicated that there is a moderate positive relationship between motivation and strategy use, r= .344, p= .002. In other words, the more participants are motivated, the more strategies they use. Thus, the hypothesis that there is a positive association between Libyan university English majors’ motivation and their strategy use was confirmed.
The result is consistent with the earlier extensive research on strategies (e.g., Oxford & Nyikos, 1989; Oxford, 1994; Gardner & MacIntyre,1993; McIntyre & Noels, 1996; Tamada, 1996; Chang & Huang, 1999; Yang, 1999; Schmidt & Watanabe. 2001; Rahimi & Saif, 2004) which suggests a relationship between motivation and use of strategies and demonstrated that motivation plays an important role in the selection and use of learning strategies.
The researchers also conducted a correlation analysis to determine the strength and type of relationships between motivation and use of separate strategy categories. Moderate significant positive relationships were only found between motivation and three strategy categories. The results showed that the use of Social strategies was more related to motivation (r= .497, p< .001) than Compensation strategies (r= .308, p= .007), and Metacognitive strategies (r= .274, p= .017). There were also positive but non-significant weak relationships between motivation and other types of strategies: (Memory strategies, r= .205, p= .075); (Cognitive strategies, r= .216, p= .061); (Affective strategies, r= .134, p= .250).
The researchers also divided the participants into groups of amotivated, minimally, moderately, and highly motivated students and compared the means of their overall strategy use. With a mean of 3.8 and a standard deviation of 0.46, highly motivated students appeared to employ strategies more than the moderately motivated (m= 3.5, SD= .57) and the minimally motivated ones (m= 3.6, SD= 0). These results support the findings of previous studies which revealed that highly motivated learners generally use all categories of strategies more frequently than those comparatively less motivated (Oxford & Crookall, 1989; Gardner& MacIntyre, 1993; McIntyre & Noels, 1996; Kaylani, 1996; Rahimi et al, 2004). The findings of the current study also support a number of previous studies demonstrating that the level of expressed motivation to learn a language has a significant effect on strategy use (Oxford & Nyikos, 1989; Ehrman & Oxford, 1988). From a social psychology perspective, motivation has been found as having a “pervasive influence on the reported use of specific kinds of strategies…” (Oxford and Nyikos, 1989: 295). Motivation was also found to be one of the most influential factors in language learning and is a key determinant of frequency and type of strategy use (Nyikos & Oxford, 1993). Thus, it would seem that more highly motivated students are likely to put in the time and effort required of consistent strategy application. In contrast, students who are not motivated discard employing a range of effective strategies or they become amotivated when their lack of strategy use hinders their language learning progress.
The researchers also conducted a correlation analyses to explore the relationship between the types of motivation (integrative/instrumental) and use of the six strategy categories. The results showed positive significant relationships between Integrative motivation and only two strategy types, Compensation strategies (r= .314, p= .006) and Affective strategies (r= .261, p= .023). The rest of strategy types did not appear to be significantly related to integrative motivation. Instrumental motivation, on the other hand, appeared to be significantly related to 5 of the six strategy types. The use of Metacognitive strategies appeared to be more related to instrumental motivation than the other strategy types (r= .292, p= .011), followed by Social strategies (r= .283, p = .013), Memory strategies (r= .262, p= .022), Affective strategies (r= .230, p= .46) and finally cognitive strategies with an r of .226 and a p value of .050. Thus, the results of the current study suggest that instrumentally motivated students use more strategy types than integratively-motivated ones. This result supports Oxford’s (1994) claim that the main motive for learning the language (motivational orientation) was important in the selection of strategies.
These results, however, are not consistent with Hassanpur’s (1999) study which revealed that integratively-motivated students employ the six strategies types more frequently than those with instrumental motivation. These findings are not also compatible with Sadighi and Zarafshan’s (2006) study which indicated that integratively-motivated students used more strategies than instrumentally-oriented ones. On the other hand, the results of the current study support other studies (e.g. Tamada, 1996) demonstrating that variations in motivational orientation (instrumental or integrative) significantly affect the utilisation of LLSs.
Therefore, according to the results of the current study and the discussion above, the researchers can conclude that motivation is related to the frequency and use of language learning strategies.
5. Conclusions and Recommendations
This study examined the relationship between motivation and LLSs use through reviewing previous research, measuring and analysing the hypothetical relationships between motivation and LLSs use. It does so by investigating the motivation and LLSs use of Libyan university English majors. The findings revealed that motivation is related to the frequency and use of LLSs. Moreover, the analyses have also shown that differences in motivational orientations have a significant impact on the utilization of LLSs. Therefore, the researchers suggest that teachers should seek ways to motivate their students so that they feel enthusiastic and attempt to employ LLSs. They should also incorporate the training of students in using LLSs in their courses, so that their students can utilize them effectively.
The authors thank the students of the English Department at the Faculty of Arts in Assawani for their participation in the study.
Chang, S. F., and Huang, S. C. (1999). Language learning motivation and language strategies of Taiwanese EFL students. ERIC, No: ED 371589.
Ehrman, M. & Oxford, R. (1988). Effects of sex differences, career choice, and psychological type on adult language strategies. The Modern Language Journal, 72:3, 253-65.
Gardner, R. C., and MacIntyre, P. D. (1993). A student’s contributions to second language learning. Part II: Affective variables. Language Teaching, 26, 1-11.
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0 update (4th ed.). Boston: Allyn & Bacon.
Green, J. M. & Oxford, R. (1995). A closer look at learner strategies, L2 proficiency, and gender. TESOL Quarterly, 29:2, 261-97.
Hassanpur, M. (1999). Science Students’ Use of Language Learning Strategies and its Relation to Motivation, Attitude, and Gender. Unpublished master’s thesis, Shiraz Islamic Azad University, Shiraz.
Hughes, A. (1989). Testing for language teachers. Cambridge: Cambridge University Press.
Kaylani, C. (1996). ‘The Influence of Gender and Motivation on EFL learning Strategy Use in Jordan’. In R. L. Oxford (Ed.), Language learning strategies around the world: Cross-cultural perspectives (pp. 75-88). Honolulu: Second Language Teaching & Curriculum Center, University of Hawaii.
MacIntyre, P. D. (1994). Toward a social psychological model of strategy use. Foreign Language Annals, 27, 185-95.
MacLeod, P. (2002). Take two language learners: A case study of the learning strategies of two successful learners of English as a second language with instrumental motivation. Journal of Language and Linguistics, 1, pp. 1–13.
McDonough, J., McDonough, S., (2004). Research Methods for English Language Teachers. Arnold, London.
McIntyre, P.D. and K. Noels. (1996). Using social-psychological variables to predict the use of language learning strategies. Foreign Language Annals, 29, pp. 373–386.
McIntyre, P.D. and K. Noels. (1996). Using social-psychological variables to predict the use of language learning strategies. Foreign Language Annals, 29, pp. 373–386.
Nyikos, M. & Oxford, R. (1993). A factor analytic study of language learning strategy use: interpretations from information-processing theory and social psychology. The Modern Language Journal, 77:1, 11-22.
Oppenheim, A.N., (2001). Questionnaire Design, Interviewing and Attitude Measurement. Continuum, New York.
Oxford, R. (1989). “The best and the worst”: an exercise to tap perceptions of language-learning experiences and strategies. Foreign Language Annals, 22:5, 447-54.
Oxford, R. (1994). Language Learning Strategies: An Update. Center for Applied Linguistics. WWW Document Found at: http://www.cal.org/resources/digest/oxford01.html (Access Date: 12/ 01/ 2007).
Oxford, R. and Crookall, D. (1989). Research on language learning strategies: methods, findings, and instructional issues. The Modern Language Journal, 73, iv: 404-419.
Oxford, R. and Shearin, J. (1994). Language learning motivation: expanding the theoretical framework. The Modern Language Journal, 78, i, 12-25.
Oxford, R., and Nyikos, M. (1989). Variables affecting choice of language learning strategies by university students. Modern Language Journal, 73(3), 291-300.
Politzer, R. L. & McGroarty, M. (1985). An exploratory study of learning behaviors and their relationship to gains in linguistic and communicative competence. TESOL Quarterly, 19:1, 103-23.
Rahimi, M., Riazi, A. and Saif, S. (2004). An investigation into the factors affecting the use of language learning strategies by Persian EFL learners. A www document found at: http://www.aclacaal.org/Revue/vol-11-no2-art-rahimi-riazi-saif.pdf (Access date: 18/09/2009).
Sadighi, F and M. Zarafshan (2006). Effects of Attitude and Motivation on the Use of Language Learning Strategies by Iranian EFL University Students, Journal of Social Sciences & Humanities of Shiraz University, Vol. 23, No. 1, Spring 2006 (SER. 46) (Special Issue in English Language and Linguistics)
Schmidt, R. and Y. Watanabe, (2001). ‘Motivation, strategy use, and pedagogical preferences in foreign language learning’ in Z. Dörnyei and R. Schmidt (eds): Motivation and Second Language Acquisition. Honolulu, HI: University of Hawaii, Second Language Teaching Center. pp. 313–59.
Schmidt, R., D. Boraie, and O. Kassabgy. (1996). ‘Foreign language motivations: Internal structure and external connections’ in R. Oxford (ed.): Language Learning Motivation: Pathways to the New Century. Honolulu, HI: University of Hawaii, Second Language Teaching & Curriculum Center, pp. 9–70.
Sedaghat, M. (2001). The Effects of Attitude, Motivation (Instrumental and Integrative), and Proficiency Level on the Use of Listening Comprehension Strategies by Iranian Female EFL Students. Unpublished master’s thesis, Shiraz University, Shiraz.
Tamada, Y. (1996). The relationship between Japanese learners’ personal factors and their choices of language learning strategies. Modern Language Journal, 80(2), 120-131.
Wilkinson, L. & Task Force on Statistical Inference (1999). Statistical Methods in Psychology Journals: Guidelines and Explanations. American Psychologist, 54, 594-604. WWW document found at: http://www.personal.kent.edu/~dfresco/CRM_Readings/Wilkinson_1999.pdf
Yang, N.-D. (1999). The relationship between EFL learners’ beliefs and learning strategy use. System, 27, pp. 515–535.