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Language Learning Strategy Use for
EFL E-Learners and Traditional Learners:
A Comparative Study

Behnaz Ashraf Ganjooei, Ali Rahimi

Iran

Abstract

The present study is comparative research aimed at investigating language learning strategies used by EFL e-learners and traditional learners. To this end, it sought to compare and contrast the mentioned groups with respect to their preferences for language learning strategies, the frequency with which e-learners and t-learners use each language learning strategy type, the relationship between learners’ English language proficiency level in each group with their language learning strategy use in general and in regard to subcategories of learning strategies, and the manifestation of differences in learners’ use of strategies in each level of proficiency. Furthermore, the study attempted to investigate whether language learning strategy use can predict the proficiency level of the learners and the other way round. Two hundred (200) Iranian undergraduate EFL learners arranged in two groups participated in this study. The first group of 100 learners was selected from Shiraz Virtual University who were exposed to an e-learning program, and the second one was a 100-learner group going through a traditional course studying at Shiraz University. The study was conducted with a placement test (OPT), adopted from Allen (1985), and a questionnaire (SILL), developed by Oxford (1990b). The test was used to assess the learners’ English language proficiency level, and the questionnaire was applied to estimate the frequency with which language learners use learning strategies. The data obtained through the application of the test and the questionnaire were subjected to descriptive and inferential statistics and the following analyses were run on the data: Independent Samples T-test, Pearson Correlation Coefficient, One-way ANOVA, and Standard Multiple Regression. The findings indicated that the type of education system has no contribution to language learning strategy use. No significant differences were observed with respect to the frequency with which the learners use each strategy type. It was also revealed that the effective use of strategies and the way learners usually go about learning is highly influenced by their level of proficiency in both groups. Finally, it was found that the use of learning strategies is predictable by learners’ level of proficiency and the other way round.

Keywords:  Language Learning Strategy, Language Proficiency, E-learners, T-learners

1. Introduction

Over the last twenty years, there has been a prominent shift within the field of teaching and learning with greater emphasis being put on learners and learning rather than on teachers and teaching. Due to recent changes in the education system and new challenges and demands, there has been the need for awareness of the necessity to improve the preparation of students for productive functioning in the continually changing and highly demanding environment (Bar-Yam, 2003). The formal education consists of systematic instruction, teaching, and training by professional teachers. This consists of the application of pedagogy and the development of curricula. In such known traditional form of education, teachers draw on many different disciplines for their lessons. Informal education also includes knowledge and skills learned and defined during the course of life, including education that comes from experience in practicing a profession. Non-traditional education may be used to refer to all forms of education for all age groups and levels outside of traditional settings. It is rooted in various philosophies that are, commonly, fundamentally different from those of traditional compulsory education. A non-traditional type of education is a home-based learning and often emphasizes the value of small class size, close relationships between students and teachers, and a sense of community. The ways learners learn, remember, and process information has been the primary concern of researchers in recent years. In more recent studies, it is claimed that technology is an increasingly influential factor which changes the face of the education. Educational technology offers tools that practitioners can apply to their own concerns and incorporates a variety of contexts including face-to-face, self-directed, blended and distance learning modes, as well as a range of theories of learning and roles of technology. The practitioners of e-learning continue to seek guidance on pedagogically sound, learner-focused and accessible learning activities, and learning contexts are increasingly rich in electronic and mobile technologies (Beethman, 2003).

In the case of language learning strategies, Littlewood (1996) holds the opinion that, as the amount of information to be processed in a course of study is rather high, and learners have to perform the tasks and process the new input, they usually apply some language learning strategies intentionally or even unconsciously. The application of language learning strategies is considered very important to a language learner’s development. “The term strategies in second language learning sense, has come to be applied to the conscious moves by second language speakers intended to be useful either in learning or using second language” (Cohen, 1998, p.1). Oxford & Nyikos (1989) believe that selection of appropriate language learning strategies enables learners to take responsibility for their own learning by enhancing learner autonomy, independence, self-direction, and necessary attributes for life-long learning. According to Littlewood (1996), learners need to keep on learning even if the formal classroom is not available. Being successful at learning nurtures learners’ need to be autonomous and seeks individualized approaches to learning objectives.

Furthermore, learners’ goals, language proficiency, level of motivation, personality traits, and general learning styles are among basic factors which influence the choice and use of language learning strategies (Wenden & Rubin, 1987; O’Malley & Chamot, 1990; Chamot & O’Malley, 1994; Oxford, 1996; Cohen, 1998).

With respect to all the existing factors which affect language learning strategy use, it seems that the system of education under which the learners develop L2 communicative abilities influences the selection and use of learning strategies.

1.1 Objectives of the Study

The main objective of this study was to reveal the importance of language learning strategies used in the language learning process, and to investigate the way they are applied in two different contexts (electronic vs. traditional). Moreover, it aimed at studying the relationship between e-learners’ and traditional learners’ (hereafter, t-learners) language learning strategy use and their language proficiency level, and examine the probable differences.

1.2 Research Questions

Based on the objectives, this study sought answers to the following questions:     

1. Are there any significant differences between e-learners and t-learners in terms of their preferences for language learning strategies?
2. What is the frequency of occurrence of e-learners’ and t-learners’ use of language learning strategies?
3. What is the relationship between learners’ English language proficiency level and their language learning strategy use, and how is this manifested in each group (e-group vs. t-group)?
4. What is the relationship between learners’ English language proficiency level in each group and their preferences for subcategories of language learning strategies?

1. 5 Are there any significant differences in e-group’s and t-groups’ use of strategies in each level of proficiency (low, intermediate, high)?

5. Can language learning strategy use predict proficiency level of the learners and the other way round?

2. Literature Review

2.1 Review of Studies Related to Electronic vs. Traditional Teaching/Learning Process

3. Methodology

3.1 Participants

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 e-learning program, and the second one was a 100-learner 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.

3.2 Instruments

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 likert-type 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.

3.2.1 The Proficiency Test

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 KR-21 formula. As recommended by Raatz and Klein-Braley (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.

Table 3.1

Reliability of the OPT

3.2.2 The Questionnaire

Strategy Inventory for Language Learning (SILL) is a 50-item likert-type 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. 

1-9 are related to memory strategy

10-23 are related to cognitive strategy

24-29 are related to compensation strategy

30-38 are related to metacognitive strategy

39-44 are related to affective strategy

45-50 are related to social strategy

The items were in the form of statements and the subjects self-rated 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 Burry-Stock, 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 (1991-2) 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.

Table 3.4

Cronbach Alpha for Each Strategy Type

Since these reliabilities are respectable, it could be concluded that the SILL can be administrated with confidence and the measurement error is minimal.

3.3 Data Collection

The procedures of data collection including the administration of the instruments and scoring procedures are presented as follows:

3.3.1 Administration Procedures

The required data were collected in two sessions in each university. First, the 100-item OPT was given to 100 e-learners. 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 30-40 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 t-learners 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 10-15 minutes to complete the questionnaire for each subject. The results were analyzed to examine how language learning strategies were used by e-learners and t-learners in their language learning process.    

3.3.2 Scoring Procedures

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 likert-scales, 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.

3.4 Data Analysis

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:

1.         Independent Samples T-test: Independent Samples T-test was used to compare the mean scores for two different groups (e-learners vs. t-learners); that is, to investigate whether there is a significant difference in the mean scores for the two groups of t-learners and
   e-learners.

2.          Pearson Correlation Coefficient: Correlation analysis was used to describe the strength and direction of the linear relationship between the variables.

3.          One-way ANOVA: One-way ANOVA was used to indicate the mean differences for the three proficiency levels (low, intermediate, high) on applying language learning strategies within each group. 

4.          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.

4. Results

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 E-learners’ and T-learners’ 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.

Table 4.1

Descriptive Statistics for the Scores of the Subjects on the OPT

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.

Table 4.2

Descriptive Statistics for the Scores of the Subjects on the SILL

Findings of the Inferential Statistics for E-learners’ and T-learners’ Scores on the OPT and the SILL 

The first research question:

4.2.1 Are there any significant differences between e-learners and t-learners in terms of their preferences for language learning strategies?

The probable existing difference between the two groups of learners (e-learners vs. t-learners) in terms of their preferences for language learning strategies was examined through the application of an Independent Samples T-test. The results are summarized in Table 4.3.

Table 4.3

Independent Samples T-test for E & T-learners’ Preferences for LLSs

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 (e-learners vs. t-learners) in terms of their preferences for language learning strategies. 

The second research question:

4.2.2 What is the frequency of occurrence of e-learners’ and t-learners’ use of language learning strategies

Figure 4.1 shows the frequency distribution of language learning strategy use comparing the two groups of learners.

Figure 4.1 Frequency Distribution of E & T-learners’ Preferences for LLSs.

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 e-learners’ and t-learners’ 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, e-learners have used cognitive strategy more frequently than the learners in t-group. Taking a glance on the strategy frequency of occurrence in the existing groups, one can amazingly find out that cognitive strategy in the e-group is the most frequent strategy whereas in the t-group 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 e-learners and t-learners 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, t-learners’ application of metacognitive strategy seems to be greater than e-learners’.

The difference in regard to application of the fifth strategy, affective strategy, is considerable with respect to the two groups of learners. As clear, e-learners tended to use affective strategy less frequently than the learners in the t-group.

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 e-learners and t-learners tended to use social strategy exactly in the same manner.

The third research question:

4.2.3 What is the relationship between learners’ English language proficiency level and their language learning strategy use, and how is this manifested in each group (e-group vs. t-group)?

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 e-learners’ & t-learners’), 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 p-value.

Table 4.4

Pearson Correlation between E & T-learners’ LP and their LLSs Use

                 ** Correlation is significant at the .01 level (2-tailed)

As the Table 4.4 shows, the correlation is ‘.621’ and p-value 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 p-value is ‘.000’. The existing result indicates that the correlation is significant at the ‘1.01’ level (2-teiled). It means that there is a linear correlation between the proficiency level of the learners and their language learning strategy use in e-group. Table 4.6 represents Pearson Correlation Coefficient between the variables in t-group.

Table 4.5

Pearson Correlation between E-groups’ LP and their LLSs Use

** Correlation is significant at the .01 level (2-tailed)

Table 4.6 also shows a significant correlation at the ‘1.01’ level (2-tailed). 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 t-group.

Table 4.6

Pearson Correlation between T-groups’ LP and their LLSs Use

** Correlation is significant at the .01 level (2-tailed)

The fourth research question:

4.2.4 What is the relationship between learners’ English language proficiency level in each group and their preferences for subcategories of language learning strategies?

Table 4.7 gives the actual value of the Pearson Correlation Coefficient along with the p-value demonstrating the existing relationship between e-learners’ English language proficiency and their preferences for subcategories of language learning strategies.

Table 4.7

Pearson Correlation between E-groups’ LP and Subcategories of LLSs

** Correlation is significant at the .01 level (2-tailed)

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 t-learners’ English language proficiency and their preferences for subcategories of language learning strategy.

Table 4.8

Pearson Correlation between T-groups’ LP and Subcategories of LLSs

** Correlation is significant at the .01 level (2-tailed)

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:

4.2.5 Are there any significant differences in e-groups’ and t-groups’ use of strategies in each level of proficiency (low/intermediate/high)?

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 (e-learners & t-learners) separately. Table 4.9 displays the results of the one-way ANOVA performed on the means of the three proficiency levels in the e-group.

Table 4.9

`One-way ANOVA on the Means of Proficiency levels in E-group

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. Post-hoc Tests are useful means to find out where the differences lie. Table 4.10 shows post-hoc results on the e-group.

Table 4.10

Post-hoc Tests on the Means of Proficiency Levels in E-group

          Correlation is significant at the .05 level (2-tailed)

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.        

Table 4.11

One-way ANOVA on the Means of Proficiency Levels in T-group

To examine the probable differences among the means of three language proficiency levels on applying language learning strategies in t-group a one-way 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. Post-hoc Tests applied to manifest where exactly the differences lie. The results on Post-hoc Tests are shown in Table 4.12  

Table 4.12

Post-hoc Tests on the Means of Proficiency Levels in T-group

          ** Correlation is significant at the .05 level (2-tailed)

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:

4.2.6 Can language learning strategy use predict proficiency level of the learners and the other way round?

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.

Table 4.13

Model Summary in Multiple Regression (b)

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.

Table 4.14

ANOVA in Regression Analysis (b)

a. Predictors (Constant): Language Learning Strategy
b. Dependent Variable: Language Proficiency

As it is evident, the resulting significance level is smaller than the p-value. 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.

Table 4.15

Coefficients in Regression Analysis (a)

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.

Table 4.16

Model Summary in Multiple Regression (b)

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.  

Table 4.17

ANOVA in Regression Analysis (b)

     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 p-value (.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.

Table 4.18

Coefficients in Regression Analysis (a)

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.

4.3 Discussion

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 e-learning program whose education is more self-directed 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 Bar-Yam’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 computer-mediated 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 e-learners 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 e-learners and t-learners, 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.

5. Conclusion

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 T-test 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 (e-learners & t-learners) 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 e-learners and t-learners 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 one-way 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.

References

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About the Authors

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