Language Learning Strategy Use and Self-efficacy in Relation to Language Achievement: The Case of Bahir Dar University Students

Haile Abraha ¹
Mulugeta Teka ²

Abstract: The purpose of this research was determining the level of EFL students’ language learning strategy use and investigating the relationship of language achievement with language learning strategy use and perceived self-efficacy. The target population for the study consisted of 73 English major students of the Bahir Dar University. As the size of population was manageable, comprehensive sampling was employed to involve all undergraduate students from Year I to Year III. Two standardized questionnaires and document analysis were the instruments used to gather data. Different statistical techniques were employed to analyze the data. First, the overall SILL mean (M= 3.27) represents that the participants used learning strategies at a medium level. Among the six clusters of strategies, the most-preferred strategies were cognitive (M=3.57) which involved repeating, analyzing, and summarizing information. Second, a strong positive correlation was found between language learning strategy use, self-efficacy and language achievement. Third, language learning strategy use tended to influence learners’ language achievement more than self-efficacy does. Fourth, in the effort made to investigate differences in language learning strategy use and self-efficacy due to achievement level difference, significant statistical difference was not found. Based on the findings and the discussions, conclusions and educational implications were forwarded.

¹ Haile Abraha is a lecturer of English in the Ethiopian Institute of Textile, Bahir Dar University.
Email: haileab65@gmail.com
² Mulugeta Teka is assistant professor of TEFL in the Department of English Language and Literature, Faculty of Humanities, Bahir Dar University.
Email: mulugetateka2010@gmail.com

Introduction

Research on language learning strategies is based on the assumption that learning strategies are teachable (Chamot & Kupper, 1989; O’Malley & Chamot, 1990; Oxford, 1990) and it often intends to display how the use of strategies is related to effective language learning, beyond showing the ways language learners apply learning strategies. With the advent of cognitive psychology, research on language learning strategies came into play focusing on learner characteristics and the process of acquiring a second language (Wenden, 1987) instead of on teaching methods.

The advent of cognitivist theory in the field of educational psychology led to a major shift in the field of language learning and teaching with higher emphasis being put on learners and learning process rather than on teachers and teaching. This shift entailed an effort to make language learners independent and autonomous so that they can manage language learning by themselves, thereby placing an increasing burden of responsibility on the shoulders of learners for their own learning.

In general education, learning strategies are the behaviors and thoughts that a learner engages in during learning that are intended to influence the learner’s encoding process (Weinstein & Mayer, 1986). However, in the field of foreign or second language education, language learning strategies (henceforth LLSs) are the specific actions, behaviors, steps, or techniques that language learners (often intentionally) use to improve their progress in developing language skills (Oxford, 1990). Oxford (1990) also extends her definition of language learning strategies as specific methods or techniques used by individual learners to facilitate the comprehension, retention, retrieval and application of information for each topic, language learning and acquisition.

In the literature we find learning strategy defined by different scholars of the field. For example, Chamot (1987) defines learning strategies as techniques, approaches or deliberate actions that students take in order to facilitate the learning and recall of both linguistic and content area information. According to Wenden and Rubin (1987), language learning strategies are strategies that contribute to the development of the language system which the learner constructs and affect learning directly. For O’Malley and Chamot (1990) they are the special thoughts and behaviors that individuals use to help them comprehend, learn, or retain new information. Cohen (1998) refers to language learning strategies as processes which are consciously selected by learners and which may result in action taken to enhance the learning or use of a second or foreign language, through the storage, retention, recall, and application of information about that language.

Even though there are different classifications of LLSs, (Rubin’s, O’Malley’s, Oxford’s, etc) Oxford’s (1990) classification of language learning strategies is easily understood and readily accepted that her taxonomy is used throughout this research paper. Oxford developed a taxonomy which divides language learning strategies into two main groups: direct and indirect strategies. Language learning strategies that directly involve the target language are called direct strategies. All direct language strategies require mental processing of the language, but the three groups of direct strategies (memory, cognitive and compensation) do this processing differently and for different purposes. Strategies that support the language learning process in an indirect way are called indirect strategies (metacognitive, affective and social strategies).

Jones (1998) believes that Oxford has developed a system of language learning strategies that is more comprehensive and detailed than earlier classification models. However, as Oxford herself concedes, there is no agreement on the basic definitions of the terms ‘direct’ and ‘indirect’, nor on “exactly what strategies are; how many strategies exist; how they should be defined, demarcated, and categorized”. And all these types of strategies are important to good language learning. Thus, it is acknowledged that an understanding and awareness of learner strategies on the part of both teacher and students may provide valuable insights into the process of language learning. This, in turn, may enable individual learners to adopt or further develop a range of effective language learning strategies, and may encourage teachers to incorporate their active use in regular class. Oxford (1990) argues that strategies are very important for language learning because they are tools for active, self-directed involvement, which is essential for developing communicative competence.
Self-efficacy is another factor that can influence language achievement. The concept of self-efficacy, introduced and developed by Albert Bandura (1977), is based on the social cognitive theory, which states that individuals act based on multiple influences from both the internal and external worlds. Among those internal influences, self-efficacy, which is a form of self-evaluation, describes how cognitive functioning affects new behavior patterns. While self-esteem is related to an individual’s perception of self-worth, self-efficacy refers to an individual’s perception of competence and capability in completing certain tasks (Bandura, 1997). Bandura (1977, p. 193) states: “An efficacy expectation is the conviction that one can successfully execute the behavior required to produce the outcomes”.

In line with this, what the literature tells us about success is that, if a person believes that he/she will be successful, success is more likely to occur (Bandura, 1977; Mills, Pajares & Herron, 2006; Seeger, 2009; Gahungu, 2007). If success is not expected at all, the individual will avoid the activity or not expend full effort and thus will not be successful. Therefore, the first step to be successful in different aspect is to develop the conviction “I can do it”. The rest can be done on the extent of effort that we exert for the activity.

Self efficacy beliefs affect language learning in many ways as they influence task choice, effort, persistence, resilience, and achievement. Compared with students who doubt their learning capabilities, those who feel efficacious for learning or performing a task more readily work harder, persist longer when they encounter difficulties, and achieve at a higher level. Self-efficacy being at the root of self-esteem, motivation and self-regulation (Bandura, 1992), the development of an individual’s self-efficacy likely determines one’s confidence and engagement in solving a problem because of their experience with an approach to problem solving that has or has not worked in the past. Zimmerman (1990) also asserts that the development of an individual’s self-efficacy is closely associated with effective use of learning strategies. Students with high levels of self-efficacy are persistent and diligent about their work and willing to engage in classroom activities. Thus this increased engagement means better use of learning strategies which leads to increased learning and achievement.

Problem Statement

Numerous research reports show that language learning strategy use and self-efficacy can be some of the factors which facilitate learners’ achievement. For instance, regarding language learning strategies, Bremner (1999) and Green & Oxford (1995) explain that there is a relationship between the frequent use of language learning strategies and achievement in language learning. The difference between successful and less successful learners, according to Abrahm and Vann (1987), depends on the type and number of LLSs they use. Similarly, Chamot, Barnhardt, El-Dinary and Robbins (1999) stated that the difference between more effective learners and less effective learners lies in “the number and range of strategies used, in how the strategies were applied to the task, and in whether they were appropriate for the task” (p.166). Some studies, however, only partially supported the claim that there is a positive association between the number of strategies used and language proficiency (e.g., Abraham & Vann, 1987; Khaldieh, 2000); some studies even indicated just the opposite (e.g., Chen, 1990; Phillips, 1991). Other researchers even found that, similar to successful learners, unsuccessful learners also actively use and apply a great number and variety of strategies, but in a different manner (Abraham & Vann, 1987; Chamot et al., 1988; Chamot & Kupper, 1989; Vandergrift, 1997; Vann & Abraham, 1990). Different explanations have been forwarded about these controversial or opposing findings.

Various studies also demonstrated that self-efficacy has a very direct effect on several aspects of an individual’s work. Research supports the idea that a high level of self-efficacy leads to accepting a challenging goal (Vancouver, Thompson & Williams, 2001) and a firmer commitment to achieving those goals (Bandura, 1989). However, very few studies have tried to compare the influence of learners’ general self-efficacy and language learning strategy use on EFL learners’ achievement in our context.

Based on the conceptual explanation of self-efficacy and language learning strategy use described above, the researchers try to show what language learning strategies EFL major students use, what type of relationship exists among learners’ general self-efficacy, language learning strategy use and achievement and to what extent learners’ general self-efficacy and language learning strategy use can contribute to students’ achievement in English courses in Bahir Dar University.

Research Questions

1. What language learning strategies are used by EFL students? What are the most frequently used and the least frequently used LLSs?
2. Is there a significant relationship among language learning strategy use, learners’ self-efficacy and learners’ academic achievement in English courses?
3. Which independent variable (language learning strategy use or self-efficacy) better predicts students’ academic achievement in English courses?
4. Is there a significant difference in the type of language leaning strategy use between high and low achievers?

Methodology

Participants

All first, second and third year English major students of the Bahir Dar University who are 73 in number (36 males and 37 females) participated in the study. As the number of population was manageable, the researchers employed comprehensive sampling.

Instruments

In order to obtain valuable information from the respondents, questionnaires and document analysis were used as data gathering tools. To ensure the validity of the research results, two standardized questionnaires and the respondents’ documents were employed.

Strategy Inventory for Language Learning (SILL)

The application of language learning strategies is an internal process that takes place in the learner’s mind. Therefore, among the available self-report questionnaires, the researchers decided to use Oxford's (1990) Strategy Inventory for Language Learning (SILL) version 7.0, which is a 5-point Likert scale that measures the frequency of strategy use from 1 (never or almost never) to 5 (always or almost always) and that consists of 50 items categorized into six groups including cognitive, memory, compensation, metacognitive, affective, and social dimension. The SILL is ‘perhaps the most comprehensive classification of learning strategies to date’ (Ellis 1994, 539) and the most wildly employed strategy scale across many cultural groups. The SILL has been extensively checked for reliability and validated in multiple ways. Reliability of the SILL is high across many cultural groups (Oxford and Burry-stock 1995). For these reasons, this inventory, being a standardized one, was chosen for this study. A pilot study was carried out among 43 first-year graduate students. The Cronbach’s alpha, calculated to estimate the reliability of the questionnaire, was 0.81 for the SILL.

General Self-Efficacy Scale (GSE)

In order to assess the self-efficacy of the respondents, another questionnaire named as general self-efficacy scale (GSE) was used. This scale is a unidimensional 10-item psychometric scale that is designed to assess optimistic self-beliefs to cope with a variety of difficult demands in life. This scale, originally developed by Jerusalem and Schwarzer in 1981, has been chosen for this study because it has been extensively checked for reliability and validated in multiple ways. Reliability of the GSE is high across many cultural groups. In samples from 23 nations, Cronbach’s alphas ranged from .76 to .90, with the majority in the high .80s. As to its validity, criterion-related validity is documented in numerous correlation studies where positive coefficients were found with different constructs.

Document Analysis

To gather data on the third variable of this study, students’ Grade Point Average (GPA) was considered. This information had to be obtained from students’ records in the Humanities Faculty Registrar Unit. So as to investigate the difference in LLSs use as the function of achievement, the students were categorized into three groups based on their English course results as high, medium and low achievers. The classification was made based on the advice taken from Cohen, Manion and Morrison (2007), which states that the top 30% of the total samples should be taken as high achievers and the lowest 30% as low achievers. Based on this classification, the top 30% (N=23) students having GPA > 2.83 were considered as high achievers, the lowest 30% (N=22) students with GPA < 2.50 were considered to be low achievers, and the remaining 40% (N=28) students whose GPA is between 2.50 and 2.82 were considered as medium achievers. One participant was added to the high achievers’ group because of overlapping score at the cut-off point that divided the top 30% and the middle 40% of the participants.

Data Analysis Techniques

The purpose of this study was to investigate the relationship between language learning strategy use and perceived general self-efficacy with language achievement. First, descriptive statistics (mean, standard deviation and frequency) were employed to analyze the data obtained by administering SILL questionnaire. After each respondent’s mean scores on each strategy cluster had been computed, each participant’s level of strategy use was categorized based on the reporting scale developed by Oxford (1990): ‘high strategy user’ (3.50 - 5.00), ‘moderate strategy user’ (2.50 – 3.49), and ‘low strategy user’ (1.00 – 2.49). Then, frequency count followed for comparison purpose. Pearson product moment correlation analysis was employed to reveal whether there was a significant relationship among language learning strategy, self-efficacy use and achievement. In order to identify which independent variable contributes more to language achievement, the regression analysis was employed. Finally, in order to find out if there is a significant difference among the achievement groups in the extent of LLS use and level of perceived general self-efficacy, one-way ANOVA was employed

Results

In order to give an introduction and general information about the variables, the descriptive statistics is shown here under in Table 1. The overall SILL mean in the present study was 3.27, with a standard deviation of .495. According to Oxford’s (1990) classification, whereas 28.8% of the respondents were high users, 67.1% of them were moderate users and 4.1% of them were poor users, the range of the overall SILL (3.27) represents moderate use; i.e., the participants used learning strategies at a medium level based on their perceptions on the strategy questionnaire.
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Table 1: Language Learning Strategy Use: frequency, percentage, mean and S.D. (N=73)

Table 1 presents the descriptive statistics for the use of strategy categories in descending order by frequency of use. Mean scores for all the strategy categories except cognitive ones fell in the medium range of 2.5–3.49 (Oxford 1990, 291), which indicates that the participants used almost each strategy category at medium frequency. As displayed in Table 1, cognitive strategies (M = 3.57, SD = 0.68) were the most frequently used strategies. While 60.3% of the respondents were high users, 37% of them were moderate users and 2.7% of them were poor users. When the overall mean cognitive strategies (M = 3.57) is considered, the range represents high use. This was followed by metacognitive (M = 3.49, SD = 0.62), of which range fell in medium use and 57.2% of the respondents were high users, 37% of them were moderate users and 5.5% of them were poor users. The third most frequently used cluster of strategies was memory (M = 3.48, SD = 0.76), of which range fell in medium use and 50.7% of the respondents were high users, 43.8% of them were moderate users and 5.5% of them were poor users. The fourth most frequently used cluster of strategies was affective (M = 3.27, SD = 0.75) and compensation strategies (M = 3.08, SD = 0.63), and social strategies (M = 2.94, SD = 0.63) were the least frequently used by participants in this study.

To examine whether or not relationships exist among the six clusters of learners’ language learning strategy use, overall results were statistically compared using Pearson Product Moment correlations. Before this analysis, a one-sample Kolmogorov–Smirnov test was run to investigate the normality of the sample in the study. The result showed that the significance level of the sample for all three variables was above .05, suggesting normality of the sample and thus allowing the parametric statistical procedures to be conducted. Since the results of Kolmogorov–Smirnov test suggested normality, parametric correlational analysis, namely Pearson product-moment correlation, was conducted to answer the second question of the study. Results of the analysis presented in Table 2 showed that the six categories of strategies had significant positive correlations with one another (p < 0.05) except the correlation between metacognitive and compensation strategies, which was positive but not significant (r= .207, p > .05).

Table 2: Interrelationship among Language Learning Strategy Uses: Pearson correlation (N=73)

**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

However, as displayed in Table 2, the researchers did not want to examine the correlation and regression analyses between these six clusters of language learning strategies and students general self- efficacy and achievement for the very reason that such analyses require a larger sample size – a minimum of 50 + (M * 8), i.e., 50 plus (the number of predictor variables times 8) as Tabachnick and Fidell (2007) recommend. This means that there should be at least 98 participants (50 + (6 strategy clusters x 8)). Therefore, the overall strategy use and the self-efficacy were configured as independent (predictor) variables and the students’ achievement was configured as a dependent (outcome) variable because the actual sample involved in this study (N= 73) being larger than the minimally required sample (50 + (M x 8)= 66) would allow the analysis. Towards this end, the mean scores and the correlation coefficients were computed, as shown in Table 3 below.

The overall mean score of strategy use was computed by summating the responses of each participant to all 50 items of the scale (SILL) and dividing by the number of items (50). Then each participant’s mean score was again summated and divided to find the average score. The mean score of students’ general self-efficacy was computed by summating the responses of each participant to all 10 items of the scale (GSE) and dividing by the number of items (10). Then each participant’s mean score was again summated and divided to find the average score. Similarly, the mean score of the participants’ achievement was obtained by summating each participant’s GPA and dividing by the number of participants (73).

Table 3: Relationship among LLS use, Self-efficacy and Achievement: Pearson Correlation

**. Correlation is significant at the 0.01 level (2-tailed)

Accordingly, Table 3 depicts that the overall SILL mean in the present study was 3.27, with a standard deviation of 0.495, which represents moderate use; i.e., the participants used learning strategies at a medium level based on their perceptions on the strategy questionnaire. Similarly, the mean score of participants’ general self-efficacy in the present study was 3.09, with a standard deviation of 0.582, which may indicate that the participants were moderately efficacious on a one-to-five scale. Moreover, Table 3 reveals that general self-efficacy, language learning strategy use and achievement had a significant positive correlation with each other (r = .48, between language learning strategy use and achievement; r = .42, between general self-efficacy beliefs and achievement; and r = .32, between language learning strategy use and self-efficacy). As a result, it can be concluded that the independent variables had a power of predicting the dependent variable.

Table 4: Contribution of LLS use and Self-efficacy to Achievement: Regression Analysis

Table 4 displays the regression analysis results. In the regression model the two independent variables (language learning strategy use and self-efficacy) were entered as predictors and achievement was entered as an outcome variable to answer which independent variable better predicts students’ academic achievement in English courses. It is observed in Table 4 that the correlation between the independent variables (self-efficacy and overall LLS use) and the dependent variable (language achievement) was good (R=.555), the R Square coefficient was .308 while the adjusted value of R-square (.288) indicated that 28.8 percent of the variance in language achievement could be predicted from self efficacy and LLS use. Therefore, it can be seen from the result that almost 29 percent of students’ achievement in English courses could be attributed to their self-efficacy and LLS use.

It was reported in the model summary that the students’ self-efficacy and LLS use could predict the learners’ achievement. It can be said that the independent variables significantly predicted students’ achievement (F=15.571, p < .001). Table 4 shows not only that the predictors as a group had a significant influence on learners’ language achievement, but also how much each predictor variable had a significant influence on language achievement. It was clearly indicated in Table 4 that the overall language learning strategy use contributed to language achievement (β = .382, t= 3.626, p > .05). In the same way, learners’ self-efficacy was found to have a significant contribution to language achievement (β =.295, t=2.795, p < .05). By comparing the beta weights, it can be inferred from the findings that LLS use (β = .382, t= 3.626, p > .05) had greater influence on achievement than self-efficacy did (β =.295, t=2.795, p < .05).
To address the last research question, significant variation in strategy use mean across the entire SILL as well as in the six categories of the SILL in relation to achievement level was determined by using ANOVA. This technique was preferred to the other possible one, Chi-Square test, because the results of test of normality (i.e., Kolmogorov–Smirnov test) allowed the application of parametric test. Then, the Scheffe post-hoc test was used to see where any significant differences among the groups lay. The ANOVA tests revealed that achievement level had a significant effect on frequency of strategy use across the entire SILL (F 2,70 = 12.024, p < .05), as well as in three of the six strategy categories ( p <.05). Such a positive variation suggested greater strategy use for a higher achievement levels.

Table 5: Summary of Variations in Use of Six Strategy Categories for Students with Different Achievement Levels

As shown in Table 5, the higher level students reported using three learning strategies more frequently than the lower level students did. The post-hoc Scheffe test indicated that for the cognitive and compensation strategy categories, high-level and mid-level students used these strategies significantly more often than low-level students, and the same was true for overall use the strategies. For the social strategy categories, high-level students used these strategies significantly more often than low-level students. However, the ANOVA test revealed that the differences among the three achievement groups in use of metacognitive, memory and affective strategy categories were not significant (p >.05).

Discussion

The participants reported using the entire SILL and five of the six strategy categories of the SILL in the medium frequency. In general, EFL learners in foreign language settings reported at the medium frequency for the overall mean strategy use on the SILL. This finding is consistent with Tang and Tian’s ( 2015), Lai’s (2009), Park’s (1997), Yang’s (1992), and Wharton’s ( 2000) findings. However, when we compare this finding with those of studies conducted in a second language context settings (e.g., Phillips, 1991; Griffiths, 2003; Goh & Kwah, 1997), the overall mean strategy use of the EFL learners in this study was much lower. This can be attributed to the contextual factor. English as a foreign language is taught in school, and it is not used by people in society. In such setting, the role the language plays in communication is limited and so is the availability of authentic input and interaction opportunities. Therefore, learners are less motivated to master the language by using a variety of LLS.

The most-preferred strategies were cognitive (M=3.57) which involved repeating, analyzing, and summarizing information. Oxford (1990, p.68) emphasized that cognitive strategies are typically found to be the most popular strategies with language learners and essential in learning a new language because these strategies not only require but also allow for direct and immediate manipulation or use of input. The results are in conflict with the data collected by some researchers like Chen (2002), Liao (2000), and Yang (1992) who found that EFL learners in Taiwan rely heavily on compensation strategies that help them to overcome deficiencies in knowledge when using English. In favor of this, Oxford (1990, 90) argues that compensation strategies are important for beginning and intermediate language learners and useful for expert language users who fail to hear something clearly, or who are faced with a situation in which the meaning is expressed indirectly or unclearly. This speculation is supported by the finding concluded by Oxford (1990, 49) that ‘less proficient learners need these compensatory production strategies even more, because they run into knowledge roadblocks more often than do individuals who are skilled in the language’.

This study has also shown that the LLSs have reasonably good association or connection with achievement of the participants. The significance or p-value of each correlation coefficient displayed in the correlation table confirms the significant relationship among the clusters of strategies. When this result is compared to the previous research findings, we can see similarities as well as differences. For instance, it is consistent with the findings of some studies. The study of Borromand et.al (2012), revealed a strong relationship between the use of LLS’s and students’ academic achievement. Onurcesur (2001) also reported that all six categories of Oxford’s SILL significantly correlated with a Turkish university preparatory class students’ achievement in reading comprehension. Afshar and Movassagh (2014) similarly reported that a significant correlation was observed between Iranian university students’ language learning strategy use and university achievement, although the coefficient did not indicate a robust index.

The correlations which are found to be positive are also in congruence with the literature. Oxford (1990) suggested that “strategies in the classroom involve some kind of definite plan or conscious action on the part of the learner to achieve a goal.” (p.4) Many studies were conducted in different places to examine the relationship between LLSs and English language proficiency instead of achievement. For example, Wu (2008) and Lai (2009) found that Taiwanese students who had a higher proficiency in English used strategies more frequently than those with lower proficiency. Likewise, Abedini, Rahimi and Zare-ee (2011) reported a positive correlation between Iranian EFL Learners' language learning strategy use and their English language proficiency at tertiary level. Contrary to these, Chand (2014) reported that LLSs have very little association or connection with language proficiency among tertiary students in Fiji.

As to the observed relationship between learners’ self-efficacy and their language learning strategy use, there are some research findings that revealed a similar result. Shkullaku (2013) found a significant relationship between the students’ self-efficacy and academic performance among Albanian students. Abdullah (2006) also showed positive correlations between self-efficacy and academic performance in English language. Therefore, it is possible to say that this finding is consistent with the literature. Bandura (1989) argues that the perceived self-efficacy increases academic achievement in a direct and an indirect way, by influencing individuals’ goals as individuals with a high level of self-efficacy assign higher goals to themselves and exercise more effort and willingness to have them accomplished. Bandura (1995) elaborates that perceived self-efficacy fosters engagement in learning activities promoting the development of educational competencies and such beliefs affect level of achievement as well as motivation.In order to answer this question, regression analysis between the two independent variables (self-efficacy and LLS use) and the dependent variable (achievement) was computed. The result of the data analysis in Table 4 showed a value of (β=.382, t= 3.626, p>0.05) for the overall language learning strategy use and a value of (β=0.295, t=2.795, p<0.01) for self-efficacy. The result can be interpreted as the beta (β) value of 0.38 indicated that a change of one standard deviation in perceived use of language learning strategies would result in a change of the same level in achievement. In the same way, the beta (β) value of 0.29 indicated that a change of one standard deviation in perceived self-efficacy would result in a change of the same level in achievement. In short it can be concluded from this finding that, learners’ LLS use influenced achievement more than self-efficacy did.

In an attempt to identify the type of language learning strategies used by high, medium and low achievers, a comparison of LLS use in terms of achievement level was administered. The result revealed that there was a significant difference among the three achievement groups in their use of cognitive, compensation and social strategies as well as in their overall use of strategies. The result concluded by many studies (Alhaisoni 2012; Chien & Wei 1998; Oxford & Crookall 1989; Oxford & Nyikos 1989; Wharton 2000) supports the finding that learners with high proficiency in English used more learning strategies than learners with low proficiency. Despite the fact that the finding of this study is consistent with the results of previous studies, it contradicts with those same previous studies in that there were no significant differences in use of metacognitive and affective strategies among these groups. On the other hand, the results of the study are not consistent with the findings of the study carried out by Afshar, Ketabi and Tavakoli (2010), who found that good and poor Iranian EFL majors were not significantly different in their overall vocabulary learning strategy use. Yet, the two groups of good and poor learners were reported to differ from each other in the use of specific vocabulary learning strategies.

Conclusions and pedagogical implications

This paper examined the relationship of language learning strategy use, self-efficacy and language achievement. The results of the present study showed similar results with some previous research findings and inconsistency with some other studies were also exhibited. LLS use was found to have a major contribution for EFL learners’ success in language learning. LLS use is crucial in determining learners achievement in English courses, its importance should be considered as one of the factors affecting language achievement and treated accordingly. Despite the fact that the role of learners’ self-efficacy in determining language achievement is less important compared to the role of LLS use, its contribution is not deniable.

Cognizant of the power of LLS use and self-efficacy in predicting learners’ achievement, EFL instructors in universities should consider incorporating learner training into their normal course of instruction. Teachers as professionals should be responsible for the development of their students by creating self-efficacy belief within their students through feedback teachers provide for their students.

References