 
Editor’s Note: This excellent research is exciting information for teachers and learners of foreign languages. Language Learning Strategy Use for 
Study  Findings  
1  BarYam (2003)  By the recent changes in the education system and the new challenges and demands, there has been the need for awareness of the necessity to improve the preparation of students for productive functioning.  
2  Russell (2001)  Learners have increasing opportunities to take their learning from place to place in the form of eportfolios and learning records, and to make choices about how, when, and where they participate in education.  
3  Jonassen, Peck & Wilson, (1999)  Classroom teaching with minimal equipment allows the teachers to tailor their approach to the immediate needs of learners. With the use of digital technologies, all of the pedagogical activities such as presenting explanations, guiding discussions, asking questions, etc. require forethought and an explicit representation of what learners and teachers will do.  
4  Mann (1998)  New technological options are challenging and changing the very nature of teaching as faculty migrate from being deliverers of information to facilitators and students are also undergoing a transformation from passive recipients to participants in an active learning environment.  
5  Kearsley (1995)  The primary type of communication between a faculty member and students in a traditional classroom is lecture and discussion. Students’ role in a traditional classroom include notetaking, summarizing, and questioning. In an online environment, the role of both the faculty member and students change. In online courses, students have the opportunity to interact with electronic media presentations and stimulations.  
6  Harasim (1995)  The results of a study that surveyed 240 teachers and learners that used the internet for educational purposes revealed that of the 176 responses to a question about differences between learning in a computermediated environment and a traditional classroom, 90 percent indicated that there were differences. Many of the stated differences involved changes in the roles of both teachers and students.  
2.2 Summary of Studies on Elearners’ & Tlearners’ Language Learning Strategy  
Study  Findings  
1  Azemi (2004)  There is no doubt elearners also come in different styles and strategies in ways they take in and process information. Based on different personalities, proficiencies and styles, they use different strategies to take benefit from the course.  
2  LessardClouston (1997)  In an electronic course as learners work rather independently, the strategies to be applied are mostly selfdeveloped and the responsibility of the selection of the appropriate strategies relevant to the given context is upon learners’ shoulder. Learning preferences affect the way students approach any task and the way they function under different conditions and different learning environments.  
3  Fedderholdt (1997)  There is no doubt a language learner who is aware of a wide range of learning strategies, and their use in the appropriate context will be able to improve his/her language skills in a better way.  
4  Oxford & Lever (1996)  As the learners increase their competence in the target language, they will be able to apply learning strategies to help them use known language in new contexts, identify key words and phrases in speech and in simple written texts, and use word lists and dictionaries, as well as in more general learning in other areas of the curriculum.  
5  Winston & Mayer  Language learning strategies are “behaviors and thoughts that a learner engages in during learning and that are intended to influence the learner’s encoding processes. Thus the goal of any particular learning strategy maybe to affect the learner’s motivational or affective state, or the way in which the learner selects, acquires, organizes, or integrates new knowledge”.  
6  Oxford & Crookall (1989)  Strategies should be chosen so that they mesh and support each other and so that they fit the requirements of the language task, the learners’ goals, and learners’ styles of learning. Selfdeveloped strategies like instructional ones should enable students to take charge of their own learning and lead to autonomy, independency, and selfdirection. 
This study was conducted with 200 undergraduate computer software learners. The sample population was taken from two universities. The first group of 100 learners was computer software students studying at Shiraz Virtual University who were exposed to an elearning program, and the second one was a 100learner group of the same major studying at Shiraz University going through a traditional course. All learners were native speakers of Persian selected from different intakes, from freshmen to seniors.
Two instruments were used in this study. The first one was the Oxford Placement Test (OPT), adopted from Allen (1985) consisting of 100 items on vocabulary, structure, and reading comprehension. The test was used to assess the general English language proficiency of the learners. The second one was Strategy Inventory for Language Learning (SILL), developed by Oxford (1990b) consisting of 50 likerttype items including 6 subscales. This questionnaire was used to assess the frequency with which language learners use each learning strategy. For the sake of simplicity and avoidance of misunderstanding, the translation of the items adopted from Hasanpour (1999) was used.
Oxford Placement Test (OPT) consists of 100 items which provides a practical way of grading students and assessing their level of general English proficiency in areas of vocabulary, structure, and reading comprehension, and was adopted from Allen (1985). The participants were supposed to choose the correct answer from among the three choices. Every correct answer received one point and the maximum possible score was equal to100.
3.2.1.1 Validity and Reliability of the Proficiency Test
Due to the fact that the OPT is a standard test of proficiency, its validity and reliability were assumed to be satisfactory. To ensure the content validity of the test, the comments of three experts were sought. Each strongly confirmed the appropriateness of the test in regard to subject matter content and the general objective of measuring learners’ English proficiency in areas of vocabulary, structure, and reading comprehension.
In order to estimate how reliable the use of Oxford Placement Test is, the internal consistency of the test was computed based on KR21 formula. As recommended by Raatz and KleinBraley (1995), the formula measures internal consistency in an acceptable way. The reliability index for the OPT in this study was found to be .94 with 40 learners through a pilot study, which is considered a high positive reliability. The obtained results are shown in Table 3.1.
Test Type  Number of Items  Mean  V  Std  KR21 
OPT  100  41.8  395  19.87  0.94 
Strategy Inventory for Language Learning (SILL) is a 50item likerttype questionnaire, developed by Oxford (1990b) which consists of 6 subscales; that is, memory, cognitive, compensation, metacognitive, affective, and social strategies. Students were asked to indicate their response (1,2,3,4, or 5) ranging from ‘always or almost always true of me’ to ‘never or almost never true of me’ to strategy description related to six major strategy groups according to the extent to which they use each strategy.
19 are related to memory strategy
1023 are related to cognitive strategy
2429 are related to compensation strategy
3038 are related to metacognitive strategy
3944 are related to affective strategy
4550 are related to social strategy
The items were in the form of statements and the subjects selfrated themselves according to the following scheme:
1 means: never or almost never true of me
2 means: usually not true of me
3 means: somewhat true of me
4 means: usually true of me
5 means: always or almost always true of me
3.2.1.2 Validity and Reliability of the Questionnaire
The validity of the SILL has been widely and extensively confirmed, based on construct validity. SILL construct validity is partially shown in relationships between the SILL on the one hand and language performance on the other. This evidence is probably the strongest support possible for the assertion of the construct validity of the SILL. A number of ESL/EFL studies have demonstrated this relationship. The content validity is reported to be reasonable based on independent raters (Oxford, 1986; Oxford and BurryStock, 1995).The viewpoints of three experts were taken into consideration in regard to the validity of the questionnaire.
In terms of reliability of the questionnaire, it is worth pointing out that acceptable reliabilities were found for the SILL by many researchers who had used the instrument. Oxford and Nyikos (1989) reported Cronbach Alpha of .96 for SILL which is extremely high considering 1 as its maximum. Phillips’s (19912) data had a reliability of .87 with 141 students.
Although internal consistency of the SILL was tested worldwide, the questionnaire was tested and revised following a pilot study with 60 learners comparable to the participants of the study. In order to check the internal consistency of the SILL for the current study, the Cronbach Alpha Coefficient was calculated. The resulting data for each strategy type is presented in Table 3.4.
Strategy Type  Cronbach Alpha 
Memory  .88 
Cognitive  .88 
Compensation  .86 
Metacognitive  .86 
Affective  .87 
Social  .86 
Since these reliabilities are respectable, it could be concluded that the SILL can be administrated with confidence and the measurement error is minimal.
The procedures of data collection including the administration of the instruments and scoring procedures are presented as follows:
The required data were collected in two sessions in each university. First, the 100item OPT was given to 100 elearners. The necessary instruction as how to complete the test was given. The learners were supposed to complete each part of the test normally in about 35 minutes. However, there was no time pressure for subjects, most of them completed each part in about 3040 minutes as expected. The results obtained from the test indicated the level of proficiency of learners in general English. The same test was given to tlearners and the same procedure was run. Then, they were given the SILL in another session. The learners were asked to indicate their choices which determined how often they tend to use language learning strategies, and which strategies they tend to use most often. There was no time restriction, but it took about 1015 minutes to complete the questionnaire for each subject. The results were analyzed to examine how language learning strategies were used by elearners and tlearners in their language learning process.
The correct answer for each item in the OPT was supposed to be chosen from among the three choices. Every correct choice received one point. The maximum possible score for each part was equal to 50 and the total score obtained from the whole test containing two parts was equal to 100.
Each of the items in the SILL was answered on five point likertscales, ranging from ‘always or almost always true of me’ to ‘never or almost never true of me’. A subject’s endorsement in ‘always or almost always true of me’ was equated with 5; ‘usually true of me’ with 4; ‘somewhat true of me’ with 3; ‘usually not true of me’ with 2; and ‘never or almost never true of me’ with 1.
In order to investigate the answers to the proposed questions, the results obtained from the OPT and the SILL were analyzed and the following statistical analyses were run on the data:
Independent Samples Ttest: Independent Samples Ttest was used to compare the mean scores for two different groups (elearners vs. tlearners); that is, to investigate whether there is a significant difference in the mean scores for the two groups of tlearners and
elearners.
Pearson Correlation Coefficient: Correlation analysis was used to describe the strength and direction of the linear relationship between the variables.
Oneway ANOVA: Oneway ANOVA was used to indicate the mean differences for the three proficiency levels (low, intermediate, high) on applying language learning strategies within each group.
Standard Multiple Regression: Standard Multiple Regression was used to indicate whether the continuous variable can predict a particular outcome; that is, to explore whether language learning strategy use predicts proficiency level of the learners and the other way round.
In order to find the answers to the proposed research questions, the results obtained from the test and the questionnaire were subjected to the relevant descriptive and inferential statistics.
Findings of the Descriptive Statistics for Elearners’ and Tlearners’ Scores on the OPT and the SILL:
Table 4.1 shows descriptive statistics for the scores of the subjects on the OPT. The table provides a summary of minimum, maximum and mean scores, as well as standard deviations.
StatisticLearners  N  Min  Max  Mean  Std 
Elearners  100  14.00  81.00  46.91  14.97 
Tlearners  100  18.00  82.00  48.10  16.34 
Table 4.2 shows descriptive statistics for the scores of the subjects on the SILL. As clear, the table provides some information on minimum score, maximum score, mean, and standard deviation for the same number of population in each group based on their preferences for language learning strategies.
Strategy Statistic  Memory  Cognitive  Compensation  Metacognitive  Affective  Social  
E  T  E  T  E  T  E  T  E  T  E  T  
N  100  100  100  100  100  100  100  100  100  100  100  100 
MIN  1.78  1.66  1.82  2.00  1.35  1.66  2.00  2.16  1.66  1.66  2.00  1.50 
MAX  4.66  4.83  4.50  4.66  4.50  4.50  4.55  4.78  4.83  4.66  4.71  4.66 
MEAN  3.13  3.26  3.17  3.06  3.27  3.26  3.28  3.54  3.09  3.17  3.17  3.12 
STD  0.61  0.70  0.55  0.66  0.64  0.70  0.66  0.62  0.68  0.61  0.72  0.72 
Findings of the Inferential Statistics for Elearners’ and Tlearners’ Scores on the OPT and the SILL
The first research question:
The probable existing difference between the two groups of learners (elearners vs. tlearners) in terms of their preferences for language learning strategies was examined through the application of an Independent Samples Ttest. The results are summarized in Table 4.3.
Levene’s Test for  Ttest for  
F.  Sig.  t  df  Sig.  
LLSs Average  Equal Variances Assumed  .229  .633  1.176  198  .241 
Equal Variances Not Assumed  1.176  197.95  .241 
As shown in Table 4.3 the average scores of the two groups were compared. As the table indicates, the existing significance value (.241) is larger than the significance level (.05). In other words, there are no significant differences between the two groups of learners (elearners vs. tlearners) in terms of their preferences for language learning strategies.
The second research question:
Figure 4.1 shows the frequency distribution of language learning strategy use comparing the two groups of learners.
In the frequency of occurrence in strategy 1, memory strategy, a slight difference between the two groups’ preferences could be seen than can be ignored. It shows that elearners’ and tlearners’ preferences for memory strategy have been more or less the same.
As opposed to strategy 1, a considerable difference between the two groups in applying strategy 2, cognitive strategy, could be observed. As shown, elearners have used cognitive strategy more frequently than the learners in tgroup. Taking a glance on the strategy frequency of occurrence in the existing groups, one can amazingly find out that cognitive strategy in the egroup is the most frequent strategy whereas in the tgroup it is the least frequent one.
Comparing the two groups regarding the third strategy, compensation strategy, one can infer that the frequency of occurrence is more or less the same. It means that both elearners and tlearners have had the same trends applying this type of strategy in their process of language learning.
There is a substantial difference between the two groups’ preferences for the fourth strategy, metacognitive strategy. As could be observed, tlearners’ application of metacognitive strategy seems to be greater than elearners’.
The difference in regard to application of the fifth strategy, affective strategy, is considerable with respect to the two groups of learners. As clear, elearners tended to use affective strategy less frequently than the learners in the tgroup.
As the Figure 4.1 implies, the frequency of occurrence of the sixth strategy, social strategy, in both groups is exactly the same. It means that surprisingly both elearners and tlearners tended to use social strategy exactly in the same manner.
The third research question:
The above raised question comprises two parts. In order to provide answer for each part, first the relationship between all learners’ English language proficiency level (including elearners’ & tlearners’), and their language learning strategy use was investigated; Then, such relationship was examined separately within each group. Table 4.4 provides the actual value of the Pearson Correlation Coefficient between the variables along with the pvalue.
LLSs  Language Proficiency  
 Pearson Correlation Sig. (2tailed)  1  .621** 
 Pearson Correlation Sig. (2tailed)  . 621**  1 
** Correlation is significant at the .01 level (2tailed)
As the Table 4.4 shows, the correlation is ‘.621’ and pvalue is ‘.000’. Thus, it can be concluded that the correlation is significant. On the other hand, there is a high correlation between language proficiency and language learning strategy use. The following tables demonstrate how the relationship between the variables is manifested in each group.
As Table 4.5 implies, the correlation is ‘.616’ and the pvalue is ‘.000’. The existing result indicates that the correlation is significant at the ‘1.01’ level (2teiled). It means that there is a linear correlation between the proficiency level of the learners and their language learning strategy use in egroup. Table 4.6 represents Pearson Correlation Coefficient between the variables in tgroup.
LLSs  Language Proficiency  
 Pearson Correlation Sig. (2tailed)  1  .616** 
 Pearson Correlation Sig. (2tailed)  .616**  1 
** Correlation is significant at the .01 level (2tailed)
Table 4.6 also shows a significant correlation at the ‘1.01’ level (2tailed). The index representing the correlation is recorded as ‘.625’ which demonstrates a high correlation between the proficiency level of the learners and their language learning strategy use in tgroup.
LLSs  Language Proficiency  
 Pearson Correlation Sig. (2tailed)  1  .625** 
 Pearson Correlation Sig. (2tailed)  . 625**  1 
** Correlation is significant at the .01 level (2tailed)
The fourth research question:
Table 4.7 gives the actual value of the Pearson Correlation Coefficient along with the pvalue demonstrating the existing relationship between elearners’ English language proficiency and their preferences for subcategories of language learning strategies.
Lg. Prof.  Str.1  Str.2  Str.3  Str.4  Str.5  Str.6  
Lg.Prof  Pearson  1  .330**  . 475**  . 342**  . 503**  .373**  543** 
Str.1  Pearson  .330**  1  .447**  .457**  . 393**  .323**  . 413** 
Str.2  Pearson  .475**  .447**  1  .424**  . 456**  .327**  . 597** 
Str.3  Pearson  .342**  .457**  .424**  1  .491**  .290**  .511** 
Str.4  Pearson  .503**  .393**  .456**  .491**  1  .362**  .629** 
Str.5  Pearson  .373**  .323**  .327**  .293**  .362**  1  .508** 
Str.6  Pearson  543**  .413**  .597**  .511**  .629**  .508**  1 
** Correlation is significant at the .01 level (2tailed)
As could be inferred from the table, the direction of the relationship between language proficiency and each subcategory of language learning strategy is positive. The positive correlation represents that high scores on one variable are associated with high scores on the other. Then, there is a direct relationship between the variables.
The size of value of correlation usually can range from ‘1.00’ to ‘1.00’. This value will indicate the strength of the relationship between language proficiency and the use of each subcategory. A correlation of 0 indicates no relationship, a correlation of ‘1.0’ indicates a perfect positive correlation and a value of ‘1.0’ indicates a perfect negative correlation (Pallant, 2005).
Table 4.8 gives the actual value of the Pearson Correlation Coefficient between tlearners’ English language proficiency and their preferences for subcategories of language learning strategy.
Lg. Prof.  Str.1  Str.2  Str.3  Str.4  Str.5  Str.6  
Lg.Prof  Pearson  1  .434**  .531**  .369**  .312**  .482**  529** 
Str.1  Pearson  .434**  1  .546**  .357**  .371**  .469**  .486** 
Str.2  Pearson  .531**  .546**  1  .618**  .272**  .541**  .583** 
Str.3  Pearson  .369**  .357**  .618**  1  .179**  .430**  .386** 
Str.4  Pearson  .312**  .371**  .272**  .179**  1  .329**  .411** 
Str.5  Pearson  .482**  .469**  .541**  .430**  .329**  1  .570** 
Str.6  Pearson  529**  .486**  .583**  .386**  .411**  .570**  1 
** Correlation is significant at the .01 level (2tailed)
As presented in Table 4.8, a strong positive correlation in all cases could be observed between language proficiency of the learners and their application of each strategy type. Then, it could be claimed that a direct relationship exists between language proficiency and application of subcategories of language learning strategies.
The fifth research question:
In order to investigate the probable differences among the means of three language proficiency levels on applying language learning strategies in each group, a one way Analysis Of Variance (ANOVA) was applied for each group of learners (elearners & tlearners) separately. Table 4.9 displays the results of the oneway ANOVA performed on the means of the three proficiency levels in the egroup.
Sum of Squares  df  Mean Square  F  Sig.  
Between Groups  6.450  2  3.225  19.01  .000 
Within Groups  16.452  97  .170  
Total  22.902  99 
As the table represents, there are significant differences among the means of the compared groups as a whole. In order to determine the exact mean differences, multiple comparisons needed to be performed. Posthoc Tests are useful means to find out where the differences lie. Table 4.10 shows posthoc results on the egroup.
Level  Mean df  Std. Error  Sig  95% Confidence Interval  
Lower Bound  Upper Bound  
 Mid  .437**  .120  .001  .725  .150 
High  .910  .148  .000  1.26  .557  
 Low  **.437**  .120  .001  .150  .725 
High  .473***  .111  .000  .738  .207  
 Low  .910**  .148  .000  .557  1.264 
Mid  .473**  .111  .000  .207  .738 
Correlation is significant at the .05 level (2tailed)
As Table 4.10 manifests, the significance values (.01 & .00) are less than the significance level (.05). Thus, it can be concluded that there are significant differences among the means of the three proficiency levels regarding their preferences for language learning strategies.
Sum of Squares  df  Mean Square  F  Sig.  
Between Groups  8.242  2  4.121  26.038  .000 
Within Groups  15.352  97  .158  
Total  23.594``  99 
To examine the probable differences among the means of three language proficiency levels on applying language learning strategies in tgroup a oneway ANOVA was run. The obtained results are shown in Table 4.11.
As could be realized from the table, there are significant differences among three proficiency levels on applying language learning strategies. Posthoc Tests applied to manifest where exactly the differences lie. The results on Posthoc Tests are shown in Table 4.12
Level  Mean df  Std. Error  Sig  95% Confidence Interval  
Lower Bound  Upper Bound  
 Mid  .419**  .104  .000  .667  .170 
High  .916  .127  .000  1.21  .612  
 Low  **.419**  .104  .001  .170  .667 
High  .497***  .102  .000  .741  .253  
 Low  .916**  .127  .000  .612  1.21 
Mid  .497**  .102  .000  .253  .741 
** Correlation is significant at the .05 level (2tailed)
As shown in the table, the existing values in each category are less than the significance level. It means that the differences are significant. Thus, one can conclude that language learning strategies are applied differently by learners with different language proficiencies.
The sixth research question:
To answer the raised question, two Standard Multiple Regressions were performed. Once, language learning strategy use was regarded as independent variable and language proficiency as the dependent one. Then, language learning strategy use was considered as dependent variable and language proficiency as the independent one. The following tables provide the results obtained from Standard Multiple Regression.
Model  R  R Square  Adjusted  Std. Error 
1  .621a  .385  .382  12.294 
a. Predictors (Constant): Language Learning Strategy
b. Dependent Variable: Language Proficiency
The value of ‘.385’ as R square (coefficient of multiple determinations) indicates that the model explains ‘38.5’ percent of variance in language proficiency level. In order to make sure that the independent variable has been able to significantly predict the variance in the dependent variable, it is necessary to take a look on the ANOVA table.
Model  Sum of Squares  df  Mean Square  F  Sig. 
Regression  187  1  187  124.17  .000 
Residual  299  198  151  
Total  486  199 
a. Predictors (Constant): Language Learning Strategy
b. Dependent Variable: Language Proficiency
As it is evident, the resulting significance level is smaller than the pvalue. Then, it can be claimed that the coefficient of Multiple Regression is significant. In order to investigate if the independent variable contributed to the prediction of the dependent variable, the coefficients in regression analysis should be observed. Table 4.15 presents the related analysis.
 Unstandardized Coefficients  Standardized Coefficients 

 Collinearity Statistics  
B  Std. E.  Beta  Tolerance  VIF  
1 (constant  16.623  5.820  2.856  .005  
LLSs  20,022  1.797  .621  11.143  .000  1.000  1.000 
The Beta value of ‘.621’ means that language learning strategy use makes a strong contribution to explain the dependent variable, language proficiency.
Regarding the significance value, it could be observed that the resulting significance is less than ‘.05’, then it can be concluded that language learning strategy use is making a significant contribution to the prediction of the language proficiency level of the learners.
A converse procedure was followed to find out whether language proficiency level can predict language learning strategy use. In this case, language learning strategy use was considered as dependent variable and language proficiency as the independent one. The following tables demonstrate the results.
Model  R  R Square  Adjusted  Std. Error 
1  .621a  .385  .382  .381 
a. Predictors (Constant): Language proficiency
b. Dependent Variable: Language Learning Strategy
As shown in the table, R square index is ‘.385’, indicating that ‘38.5’ percent of variance in the learners’ language learning strategy scores is explained by the independent variable, language proficiency, which is considered a respectable result. In order to assess the statistical significance of the result, it is necessary to consider the ANOVA table.
Model  Sum of Squares  df  Mean Square  F  Sig. 
Regression  18.04  1  18.04  124.17  .000a 
Residual  28.77  198  .145  
Total  46.82  199 
a. Predictors (Constant): Language Learning Strategy
b. Dependent Variable: Language Proficiency
The ANOVA table provides evidence to prove if the coefficient of Multiple Regression demonstrated by R square is significant or not. As could be understood from the Table 4.17, the reported significance (.000) is less than the pvalue (.0005). In order to find out to what extent the independent variable has been able to predict the variance in the dependent variable, the coefficient analysis needed to be performed. Table 4.18 presents coefficients in regression analysis.
 Unstandardized Coefficients  Standardized Coefficients 

 Collinearity Statistics  
B  Std. E.  Beta  Tolerance  VIF  
1 (constant  2.288  .086  26.492  .000  
LP  .019  .002  .621  11.143  .000  1.000  1.000 
The Beta value under standardized coefficients indicates the power of contribution to explain the dependent variable. By the resulting Beta value of ‘621’, it can be claimed that learners’ language proficiency scores can reasonably predict their scores on language learning strategy use. As displayed, the language proficiency has a significance level below ‘.05’. This means that this variable can predict the variance in language learning strategy scores.
The results obtained from the data collected through the test (OPT) and the questionnaire (SILL) can be discussed as the following. The foregoing discussion includes a review of the findings and the related studies in the domain.
Language learning strategies which are considered as effective means for productive learning are used more or less the same way by learners under different educational systems; that is, learners exposed to an elearning program whose education is more selfdirected and lacks essential instruction as how to fit the assumed framework to the current teaching/learning issues, engage in the learning process as those who were instructed how to develop awareness for a comprehensive learning. As a result, the choice and use of language learning strategies is not significantly influenced by the type of education system.
This finding contradicts BarYam’s (2003) beliefs stating that the system of education under which the learners develop L2 communicative abilities influences the selection and use of learning strategies.
The findings of the study also stand in contrast with Harasim’s (1995) findings who reported the results of a study that surveyed 240 teachers and learners that used the internet for educational purposes. Of the 176 responses to a question about differences between learning in a computermediated environment and a traditional classroom, 90 percent reported that there were differences.
The result accords with Oxford and Lever’s (1996) assertion that an important aim of language learning in any system is making students familiar with strategies which they can apply to the learning of any language. As the learners increase their competence in the target language, they will be able to apply learning strategies to help them go toward progress.
Fedderholdt (1997) believes that acquisition of strategies is considered very important to a language learner’s development. No doubt a language learner who is aware of a wide range of learning strategies, and their use in the appropriate context will be able to improve his/her language skill in a better way. On the other hand, Azemi (2004) asserts that elearners also come in different styles and strategies in ways they take in and process information. Based on different personalities, proficiencies, and styles, learners use different strategies to benefit from the course.
The results of the study indicate that there are no considerable differences with respect to the frequency with which the learners use each strategy type. According to Oxford (1990a) the frequency of occurrence and the type of language learning strategy applied by the learners are mostly influenced by factors such as motivation, gender, cultural background, attitudes and beliefs, type of task, age, L2 stage, and learning style but not by the type of educational system. Moreover, many scholars stressed that successful learners who cater their foreign language learning strategy use to their proficiency level demands (under any type of education system) use language learning strategies more appropriately (Oxford & Nyikos, 1989; O’Malley & Chamot, 1990; Ellis, 1994).
Based on the findings, it’s worth pointing out that language learning strategy use is highly influenced by the proficiency level of the learners in both groups. The learners with high English proficiency seemed to use more learning strategies in their language learning process rather than those with low proficiency level.
Such finding is in accordance with Yang’s (1994) results who discussed that perceived proficiency levels have a significant effect on students’ use of learning strategies. The better students perceive their language proficiency, the more often they use various learning strategies to assist them in learning a second/foreign language. Chamot and Kupper (1989) also asserted that learners with high proficiency know how to use appropriate strategies to reach their learning goals, while learners with low proficiency are less expert in their strategy use and choice. Oxford and Nyikos (1989, p.291) concurred saying “better language learners generally use strategies appropriate to their own stage of learning …”, that is to say that affective strategy use changes as the demands at language proficiency dictate.
It was investigated that the use of language learning strategies can predict the proficiency level of the learners and the other way round. . Ellis (1994, p.555) also concluded that “the strategies that learners elect to use reflect their general stage of L2 development”.
To wrap up the discussion, it can be stated that both elearners and tlearners, needless to say, apply learning strategies in their process of language learning and the type of education system has no influence on applying learning strategies. Furthermore, no significant differences were observed with respect to the frequency with which the learners use each strategy type. The effective use of strategies and the way the learners usually go about learning is also highly influenced by their level of proficiency. Finally, the use of learning strategies is predictable by the learners' level of language proficiency. In this case, the level of proficiency can be predicted by the use of language learning strategies as well.
The findings of the study are summarized as follows based on the proposed research questions.
Concerning the first research question dealing with investigating the differences between learners exposed to two different education systems with respect to their preferences for language learning strategies, the obtained findings through Independent Samples Ttest revealed that the education system has little influence on the way learners usually go about applying language learning strategies. In other words, both groups of learners (elearners & tlearners) showed more or less the same trends while applying language learning strategies in their language learning process.
The second research question aimed at exploring the frequency with which elearners and tlearners use language learning strategies. No significant differences were observed in regard to the frequency of occurrence of learners’ use of strategies in each group after data were analyzed.
With respect to the third research question studying the probable existing relationship between learners’ English language proficiency level in each group and their language learning strategy use, it is worth mentioning that the efficient use of strategies is significantly influenced by learners’ level of proficiency in both groups. As such, the result obtained from the application of Pearson Correlation Coefficient manifested that learners with high language proficiency level showed more effective use of strategies whereas the learners with low level of proficiency usually failed to choose the appropriate learning strategies in their process of language learning.
The fourth research question dealt with studying the investigated relationship in the third posed question with respect to the subcategories of language learning strategies; that is, memory, cognitive, compensation, metacognitive, affective, and social strategy. It was revealed that there is a positive correlation between language proficiency level and application of subcategories of language learning strategies.
The fifth research question was after investigating whether there are differences in learners’ use of strategies in each level of proficiency. Analyzing the results from oneway Analysis Of Variance (ANOVA), one could claim that there were differences regarding language learning strategy use in each proficiency level, but contrasting each proficiency level two by two, no significant differences were observed.
The last attempt was to explore whether language learning strategy use is predictable by the level of proficiency and the other way round. Through the application of Standard Multiple Regression considering language learning strategy use as the independent variable, it was clarified that language proficiency level can be predicted by the way learners use of language learning strategies. The reverse procedure indicated the prediction of language learning strategy use by language proficiency level. Therefore, both language learning strategy use and language proficiency level can be predicted by each other.
Allen, E. D. (1985). Communicative Competence and Levels of Proficiency. Canadian Modern Language Review, 41(6), 99199.
Azemi, A. (2004). Hybride Elearning Achieving an Effective E learning Education Using Active Learning Methodology. Department of Engineering, the Pennsylvania State University. Delware Campus. Media, PA 19063.
BarYam, M. (2003). Changing the teaching and learning process in a complex education system. New England complex systems Institute.
Beethman, H. (2003). Embedding learning technologies: Lessons for academic developers. Educational Developments 4(4): 46.
Chamot, A. U. & Kupper, L. (1989). Learning strategies in foreign language instruction. Foreign Language Annals, 22 (1), 1324.
Chamot, A. U. & O’Malley, J. M. (1994). Language learner and learning strategies. In N. C. Ellis (Ed.), implicit and explicit learning of languages (pp. 371392). London: Academic.
Cohen, A. D. (1998). Strategies in learning and using a second language. London: Longman.
Ellis, R. (1994). The study of second language acquisition. Oxford: Oxford University Press.
Fedderholdt, K. (1997). Using Diaries to Develop Language Learning Strategies. Retrieved April 20, 1998 from: http://language.hyper.chubu.ac.ip/jalt/pub/tlt/98/apr/
Harasim, L. (1995). Learning networks: A field guide to teaching and learning online. Cambridge, MA: The MIT Press.
Hasanpour, M. (1999). Science student’s use of language learning strategies and its relation to motivation, attitude, and gender. Shiraz: Shiraz Azad University, M.A. Thesis.
Jonassen, D. H., Peck, K. & Wilson, B. G. (1999). Learning with technology: A constructivist perspective. Columbus, OH: Merrill/PrenticeHall.
Kearsley, G. (1995). The nature and value of interaction distance learning. Paper prepared for the third distance education research symposium, May 1821, 1995.
LessardClouston, M. (1997). Review the Resources! [Review of R. R. Jordon’s English for Academic Purposes: A Guide and Resource Book for Teachers]. ESP News.
Littlewood, W. (1996). Autonomy: An anatomy and a framework. System, 24/4, 427435.
Mann, C. J. (1998). Teaching on the WEB, Computers, and Geoscience. vol. 24, No. 7, p.p. 693697, Elsevier Science Ltd. Great Britain.
O’Malley, J. M. & Chamot, A. U. (1990). Learning strategies in second language acqusition. Combridge: Cambridge University Press.
Oxford, R. L. (1986). Strategy Inventory for Language Learning. Various Versions. Tuscaloosa, AL: Oxford Associates.
Oxford, R. L. (1990a). Language learning strategies and beyond: A look at strategies in the context of styles. In S.S. Magnan (Ed.) Shifting the instructional focus to the learner. Middlebury, VT: Northeast Conference on the Teaching of Foreign Languages.
Oxford, R. L. (1990b). Language learning strategies: What every teacher should know. New York: Newbury House/Harper & Row. Now Boston: Heline & Heinle.
Oxford, R. L. (Ed.) (1996). Language learning strategies around the world: Crosscultural perspectives. Honolulu: University of Hawaii Press.
Oxford, R. L. & BurryStock, J. A. (1995). Assessing the use of language learning strategies worldwide with the ESL/EFL version of the Strategy Inventory for Language Learning (SILL). System, 23/1, 123.
Oxford, R. L. & Crookall, D. (1989). Research on language learning strategies: Methods, findings, and instructional issues. Modern Language Journal.
Oxford , R. L. & Leaver, B. L. (1996) . A synthesis of strategy instruction for language learners. In R.L. Oxford (Ed.). Language learning strategies around the world: Crosscultural Perspectives. Honolulu: University of Hawaii Press.
Oxford, R. L. & Nyikos, M. (1989). Variables affecting choice of language learning strategies by university students. The Modern Language Journal, 73, 3, 291 300.
Pallant, J. (2005). SPSS Survival Manual: A Step by Step Guide to Data Analysis Using SPSS for Windows. Buckingham: Open University Press.
Phillips, E. M. (1992). The effects of language anxiety on students’ oral test performance and attitudes. The Modern Language Journal, 76, 1426.
Raatz, E. & KleinBraley, C. (1995). Introduction to language testing and Ctests. In Coleman (Ed.), University language testing and the Ctest. Proceedings of a conference held at the University of Portsmouth in April 1995. retrieved January 26, 2008 from: http://www.uniduisburg.de/FB3/ANGLING/FORSCHUNG/HOWTODO.HTM
Russell, T. L. (2001). No Significant Difference Phenomenon: A Comparative Research Annotated Bibliography on Technology for Distance Education. International Distance Education Certification Center. Retrieved May 19, 2007 from: www.nonsignificantdifference.com (accessed 29 September 2006)
Weinstein, C. E. & Mayer, R. (1986). The teaching of learning strategies. In M. C. Wiltrock (Ed.), Handbook of research on teaching (3rd ed. p.p. 315327). New York: Macmillan.
Wenden, A. L. & Rubin, J. (Eds.) (1987). Learner Strategies in language learning. Englewood Cliffs, NJ: Prentice Hall.
Yang, N. D. (1994). Study of factors affecting EFL Learners use of learning strategies: An investigating of Taiwanese college students. Paper presented at the eleventh. National Conferences on TESOL Taipel, Taiwan.
Behnaz Ashraf Ganjooei obtained her B.A. in English Literature from Tehran Teacher Training University and her M.A. in TEFL from Bandar Abbas Branch, Azad University, in Iran (Persia). She has translated a book on Pragmatics and an autobiography. Her research interests include Principles of Translation, Literature, Psycholinguists, and Language Proficiency.
Ali Rahimi (Ph.D) is an assistant Professor in Applied Linguistics, at the University of Kashan, Iran (Persia). He obtained his Ph.D. from Shiraz University in Iran. He has written books on Principles of Translation, Critical Discourse Analysis, Teaching English Language Skills, The Art of Communication, and Reading Comprehension. He has published in international journals and presented articles at national and international conferences. His research interests include critical discourse analysis, social psychology, communication skills, psycholinguistics, and issues in linguistics and language proficiency.
Email: rahimijah@yahoo.com