233 Studies in Second Language Learning and Teaching Department of English Studies, Faculty of Pedagogy and Fine Arts, Adam Mickiewicz University, Kalisz SSLLT 12 (2). 2022. 233-259 http://dx.doi.org/10.14746/ssllt.2022.12.2.4 http://pressto.amu.edu.pl/index.php/ssllt Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA Julia Goetze Pennsylvania State University, State College, USA https://orcid.org/0000-0002-4856-760X jzg5860@psu.edu Meagan Driver Michigan State University, Lansing, USA https://orcid.org/0000-0002-6712-4521 driverme@msu.edu Abstract The positive psychology movement (Seligman, 1998) has contributed to the proclamation of a positive turn in second language acquisition (SLA) (MacIntyre et al., 2016). Within the context of individual differences, self-efficacy (Bandura, 1997), an individual’s judgment of their capability to achieve goals, has gained particular interest in language learning (e.g., Lake, 2013). The present study meta-analyzes a body of research that has investigated the relationship be- tween second language (L2) self-efficacy and L2 achievement by exploring 1) reporting practices in this domain, 2) the strength and direction of the relation- ship, and 3) the effects of moderator variables on the self-efficacy-achievement link. A comprehensive literature search uncovered 37 studies, which contrib- uted to a total of 40 independent samples (N = 23,050). The average observed effect in the sample was r = .46. A moderator analysis showed systematic varia- tions in the effect size for learners’ first language, target language, proficiency level, and both self-efficacy and achievement type. We discuss our findings with respect to theoretical constructs and methodological practices and suggest im- plications for L2 pedagogy and future research into self-efficacy in SLA. Keywords: positive psychology; individual differences; L2 achievement; self-efficacy Julia Goetze, Meagan Driver 234 1. Introduction For nearly three decades, self-efficacy has seen a steady line of interest in SLA. In fact, since the positive turn in the field (MacIntyre et al., 2016; MacIntyre & Mercer, 2014), studies addressing positive affect in the foreign language (FL) classroom, including enjoyment (e.g., Dewaele & MacIntyre, 2014; Jin & Zhang, 2018; Zhang & Tsung, 2021), motivation (e.g., Dörnyei, 2020; Le-Thi et al., 2020) and second or foreign language (L2) grit (e.g., Alamer, 2021; Teimouri et al., 2020), have flourished and garnered increased attention with respect to lan- guage learning outcomes. As one of the most influential variables in positive psychology, self-efficacy has been explored across a range of contexts (e.g., tar- get languages and proficiency levels), age groups (e.g., children, adolescents, and adults), language skills (e.g., reading, writing, listening and speaking), and classroom participants (e.g., students and teachers). Encouragingly, findings have shown the benefits of self-efficacy with respect to learners’ L2 achieve- ment (e.g., Ghonsooly & Elahi, 2010; Hetthong & Teo, 2013), learning strategies (e.g., Balci, 2017; Gahunga, 2009; Jee, 2015; Ma et al., 2018; Mizumoto, 2013; Wang et al., 2012), and attitudes towards L2 learning (e.g., Bai et al., 2020; Mu- rad Sani & Zain, 2011). Bandura’s (1997) and Pajares’s (1997) seminal works on self-efficacy proved to be powerful driving forces for scholars in SLA and have sparked an abundance of research into the relationship between self-efficacy and achieve- ment. Still, the only research synthesis to date investigates self-efficacy and Eng- lish proficiency only (Wang & Sun, 2020), leaving the broader contributions of research across all languages unexamined. Given the theoretical implications of self-efficacy for individual tasks (Bandura, 1997), the various linguistic contexts and learner populations that have been addressed, the plethora of existing self- efficacy and achievement instruments, and the often inconsistent reporting standards of psychometric properties of instruments in SLA (Larson-Hall & Plon- sky, 2015), a comprehensive meta-analysis of the overall effect of self-efficacy on L2 achievement would be beneficial for furthering our understanding of self- efficacy as well as for developing theory and practice within the framework of positive psychology in SLA. The present study addresses this gap by means of a systematic meta-analysis in accordance with now commonly accepted method- ologies in SLA (e.g., Norris & Ortega, 2006; Oswald & Plonsky, 2010; Plonsky & Oswald, 2012), including a moderator analysis of variables, such as study con- texts, learner characteristics, and instrumentation. Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 235 2. Literature review 2.1. Positive psychology in SLA Positive psychology investigates the traits and processes that allow people to grow and flourish (Seligman & Csikszentmihalyi, 2000) and has encouraged scholars to explore positive emotions and experiences, such as flow (Csikszent- mihalyi, 2000) and resilience (Pan & Chan, 2007), which support people in lead- ing full, happy, and emotionally stable lives. Many scholars in education have adopted methods from positive psychology to investigate a range of positive emotions with respect to learning processes and achievement (e.g., Pekrun et al., 2002), a trend that has produced a number of meta-analyses (e.g., Lei & Cui, 2016; Marques et al., 2017; Möller et al., 2009; Möller et al., 2020; Petscher, 2010). For example, in a series of path meta-analyses of 118 studies (N = 213,121), Möller and colleagues (2020) found strong effects for the relationship between self-concept – “a self-description judgement that includes an evalua- tion of competence and the feelings of self-worth associated with the judge- ment in question” in a specific field (Pajares & Schunk, 2005, p. 105) – and K-12 achievement in mathematics (β = .57) and first language (L1) (β = .46), respec- tively. In another study, Marques et al. (2017) explored the relationship between hope and academic achievement through a meta-analysis of 45 studies (N = 9,250) carried out with K-12, undergraduate and graduate students. Their find- ings revealed a moderate, positive relationship (k = 24, mean ρ = .24, SD = .10) (95% CI [.20, .26]), with a stronger link for K-12 students (k = 8, mean ρ = .28, SD = .10) (95% CI [.24, .32]) than for undergraduate and graduate students (k = 16, mean ρ = .19, SD = .06) (95% CI [.14, .23]). These suggested links between positive affect and academic achievement lay the foundation for exploring the association in content-specific contexts, such as the world language classroom (i.e., including but not limited to English as second and foreign language classrooms). The positive turn in second language acquisition (SLA) (MacIntyre et al., 2016; MacIntyre & Mercer, 2014) has acknowledged the relevance of positive psychology for improving the FL learning experience by supporting learners’ L2 motivation, perseverance, and resilience as well as by fostering meaningful com- munication and interaction between learners and teachers. As a result, this area of inquiry has seen an influx of research on enjoyment (e.g., Dewaele & Alfaw- zan, 2018), L2 grit (e.g., Alamer, 2021; Teimouri et al., 2020), and self-efficacy, as detailed in the following section. Notably, L2 motivation has probably gar- nered the most attention (e.g., Lake, 2013; Papi et al., 2019). As an example, Al- Hoorie (2018) explored the relationship between the L2 motivational self sys- tem (L2MSS; Dörnyei, 2005, 2009) – specifically the ideal L2 self, the ought-to L2 Julia Goetze, Meagan Driver 236 self, and the L2 learning experience – and L2 achievement through a meta-anal- ysis of 39 samples (N = 32,078). The findings revealed that all three components of the L2MSS were significant predictors of intended effort (rs = .61, .38, and .41, respectively), the measure for subjective learning outcomes, though weaker correlations were found between motivation and L2 achievement (rs = .20, -.05, and .17). This study highlighted the need for meta-analyses that examine the effects of other positive affective variables on L2 achievement and how certain moderators might explain variability of findings. 2.2. Self-efficacy and language achievement In perhaps one of the most cited definitions of the term, Bandura (1986) de- scribes self-efficacy as “people’s judgements of their capabilities to organize and execute courses of action required to attain designated types of performances” (p. 391). Simply put, it refers to individuals’ beliefs that they hold the necessary skills to complete a particular task (Chao et al., 2019). These ability-related be- liefs regulate achievement by influencing the goals a learner sets out to reach and the amount of effort dedicated to their performance (Bandura, 1986, 1997; Pajares, 1997). Beyond the regulation of achievement-related cognitive pro- cesses, self-efficacy has also been found to regulate types of affective feeling states in SLA. For example, multiple studies have shown that a perceived lack of competence was related to both weak self-efficacy beliefs and the presence of negative emotions, such as anxiety (e.g., Hiver, 2013; Song, 2016). In contrast, Cheng and associates (Cheng et al., 1999) found that perceived competence was related to strong self-efficacy beliefs and the presence of positive emotions, such as self-confidence. Worth noting is Wyatt’s (2018) recent argument that self-confidence should not be treated as an emotional variable. Instead, self- confidence is characterized as a “lay term” (p. 122) for self-efficacy beliefs, thereby calling into question the nature of self-confidence and its relation to self-efficacy. Indeed, the majority of existing studies in SLA have adopted an emotional understanding of self-confidence and clearly differentiate it from cog- nitive self-efficacy beliefs. Thus, the present work addresses self-efficacy, specif- ically, and does not treat self-confidence as a synonymous term. Numerous studies have shown a positive correlation between L2 self-effi- cacy and L2 achievement (e.g., Bai & Wang, 2020; Golparvar & Khafi, 2021; Kar- bakhsh & Safa, 2020), suggesting that learners with high levels of self-efficacy are more likely to persevere even during the most challenging tasks, thus achiev- ing higher levels of language learning success (Duckworth, 2013). Many scholars in SLA have also explored skill-specific self-efficacy, including reading (e.g., Al Khamisi et al., 2016; Balci, 2017; Chuang et al., 2018; Kitikanan & Sasimonton, Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 237 2017), writing (e.g., Raoofi & Maroofi, 2017; Sahril & Weda, 2018), speaking (e.g., Asakereh & Dehghannezhad, 2015; Kitikanan & Sasimonton, 2017) and lis- tening (e.g., Kitikanan & Sasimonton, 2017; Phakiti et al., 2013), as well as con- tent-specific self-efficacy for grammar (e.g., Mustapha et al., 2013) and vocabu- lary learning (e.g., Wu et al., 2012; Wu et al., 2013). For example, Al Khamisi et al. (2016) explored the relationship between reading self-efficacy and reading achievement for 636 primary and secondary English as a foreign language (EFL) students. Correlations showed that learners with higher self-efficacy had greater success on reading tests at both academic levels (elementary: r = .541, p < .001; secondary: r = .518, p < .001). Similarly, Kitikanan and Sasimonton (2017) inves- tigated skill-specific self-efficacy (i.e., listening, speaking, reading, and writing) and achievement for 32 Thai EFL university students, finding strong positive cor- relations between self-efficacy for each skill and overall achievement (raverage = .615; 95% CI [.34; .79]). The authors thus proposed that developing self-efficacy in even just one skill might improve learners’ overall L2 achievement. Despite this general positive trend, some researchers of skill-specific self- efficacy and L2 achievement have observed merely weak relationships between the two variables. For example, Sahril and Weda (2018) examined writing self- efficacy and achievement with 50 Indonesian EFL university students and found a weak positive correlation (r = .057, p < .001). Similarly, Liem and associates (2008) found a small positive correlation (r = .180, p < .001) when investigating general L2 self-efficacy and achievement in a group of 1,475 high school EFL learners in Singapore. In a study of general self-efficacy and speaking achievement, Oliver et al. (2005) also reported a very small positive correlation (r = .09, p >.05) for 275 Australian elementary school students studying a range of foreign languages. While all of these studies provide important insights, the variation of ef- fect sizes across studies is noteworthy and motivates the current study, which aims to contribute to a more comprehensive and nuanced understanding of the relationship between L2 self-efficacy and L2 achievement in SLA. 3. The current study The current study is motivated by three goals. First, we perform a thorough and systematic literature search and analysis to examine existing trends in reporting practices in the L2 self-efficacy and achievement domain. Second, we report on both the direction and size of the relationship between learner self-efficacy and achievement. Lastly, we examine our sample for systematic variation of effects and investigate a number of moderator variables. In order to meet these goals, the present meta-analysis addresses the following research questions: Julia Goetze, Meagan Driver 238 1) What reporting practices are used in studies exploring L2 self-efficacy and L2 achievement? (RQ1) 2) What is the direction and magnitude of the relationship between L2 self- efficacy and L2 achievement? (RQ2) 3) What is the moderating effect of L1/L2 proficiency level, learner age, in- stitutional context (e.g., primary school, university), self-efficacy type (e.g., general, skill-specific), and achievement measure on the relation- ship between L2 self-efficacy and L2 achievement? (RQ3) 4. Methods 4.1. Study identification and inclusion criteria In order to identify relevant studies to answer our research questions, a set of inclusion criteria was applied. To be eligible, a study had to (1) present a meas- ure of both L2 self-efficacy and L2 achievement, (2) report quantitative results, either as a Pearson correlation or a statistic that can be converted into an r index (e.g., t or F), and (3) be published in or after 1997, to include the studies pub- lished since both Bandura’s (1997) and Pajares’s (1997) influential works and the emergence of positive psychology. Using the defined parameters and combinations of defined keywords in English: (1) self-efficacy, beliefs, self-esteem, mindset, self-concept, talent; (2) performance, achievement, outcomes; and (3) language learning, second lan- guage learning, foreign language learning, heritage language learning, we con- ducted a comprehensive search in two library-housed databases (ERIC, LLBA), and one public database (Google Scholar). We also conducted an ancestry search by reviewing the bibliographies of relevant studies and the publication lists of prominent researchers in self-efficacy and positive psychology in SLA, identifying a total of 640 publications. Some studies were later excluded due to: (1) an absence of our target var- iables, (2) research designs that included neither L2 self-efficacy nor achieve- ment instruments, (3) a qualitative methods or case study design, (4) missing data, such as correlations, means, and standard deviations, and (5) a self-effi- cacy construct unrelated to language learning, such as computer self-efficacy (Ale et al., 2017) or technological self-efficacy (Abdallah & Mansour, 2015), which measure beliefs regarding one’s capability to use technology or digital tools in order to achieve one’s goal. After applying all eligibility criteria, 37 stud- ies published between 1999 and 2019 in 15 different countries were included in the final analysis, with a total N of 23,050 and sample sizes ranging from 32 to 11,036 (M = 581.9; SD = 1770.8). Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 239 4.2. Coding procedures Each study was coded for a number of features according to a systematic coding scheme, which was adapted from an existing coding scheme of a recent meta-anal- ysis of L2 anxiety (Teimouri et al., 2019). Specifically, we recorded study features according to five categories: (1) bibliographic details (e.g., authors), (2) study design (e.g., methods), (3) participant sample (e.g., target language), (4) instruments (e.g., self-efficacy scale), and (5) quantitative findings (e.g., effect sizes). To pilot the cod- ing scheme, we each rated five studies from the sample and resolved any ambigui- ties in our results and coding scheme. The final coding scheme can be found in Ap- pendix A. Next, each author coded half of the studies. Twenty percent of the sample was coded by both authors, establishing high inter-rater reliability (100%). 4.3. Analysis To answer RQ1, we first identified all self-efficacy and achievement instruments. Next, we conducted frequency counts and examined the reporting tendencies for reliability and validity of instruments for each variable. By examining the psychometric proper- ties, we followed the foundational principle of the methodological reform movement (Marsden & Plonsky, 2018), which aims for more rigorous reporting practices in the field of SLA through robust description and evaluation procedures. To calculate the magnitude and direction of the relationship between self- efficacy and achievement (RQ2), we employed a fixed-effect model. That is, we as- sumed the existence of one common effect size across all studies in our sample and calculated both the weighted overall mean according to each study’s sample size, and the 95% confidence intervals for each effect. The fixed-effect model was chosen a priori due to our small sample size. More specifically, after visually inspecting our coded studies, we assumed only a moderate amount of heterogeneity across our sample. That is, while the studies were not identical with regards to design features, such as their use of data collection instrument or participant recruitment proce- dure, we deemed them moderately homogenous in terms of participant character- istics, such as target language and institutional context. This assumption was later con- firmed (I2 = 68.647, p < .001), and we investigated the systematic variation of effect sizes within our model (Borenstein et al., 2010) in our moderator analysis (RQ3). To address our last research question, we used the categorical variables in our coding scheme to form and analyze subsamples. Before running the anal- yses, we examined our data set for heterogeneity, calculating the goodness-of- fit statistic (Q) and checking for the existence of systematic variation among the observed effects in the sample (I2). All analyses were performed using Compre- hensive Meta-Analysis (CMA) Version 3 (Borenstein et al., 2013). Julia Goetze, Meagan Driver 240 5. Results The results concerning our first research question, which aimed to explore re- porting practices, are summarized in Tables 1 and 2. Self-efficacy was measured by a total of 33 unique instruments, with two studies that did not provide details on their instrument. The most commonly referenced questionnaires were the Motivated Strategies for Learning Questionnaire (MSLQ; Pintrich et al., 1991), the Questionnaire of English Self-Efficacy (QESE; Wang, 2004; Wang et al., 2013), and the Self-Efficacy Questionnaire (SEQ; Sedighi et al., 2004). However, only a minor- ity of our sample (k = 14; 36%) adapted any of these three instruments. Fifteen studies uniquely adapted instruments from other sources, and eight studies de- signed new instruments. Of the 39 times that studies reported on a measurement for L2 self-efficacy, reliability was reported 37 times (95%) in the form of Cronbach’s alpha coefficients, with the exception of two studies that, respectively, conducted a test-retest correlation and split-half test of internal consistency. With respect to language achievement measures, our analysis found 39 different measures representing three main methods for assessing L2 achieve- ment: language tests (k = 22), course grades (k = 7), and Grade Point Average (GPA) (k = 3). Seven samples implemented a range of other methods, including student self-reported exam grades, teacher ratings of student achievement, and task-based assessment (Table 2). As shown in Table 2, 28 samples (72%) re- ported means, and 26 studies (66%) reported both the means and standard de- viation for their instrument. Of the 22 samples implementing a language test, reliability coefficients were reported only eight times (36%): five reported Cronbach’s alpha, one reported KR-20, one reported inter-rater reliability, and one reported test-retest correlation. The five samples reporting Cronbach’s al- pha yielded an average reliability of .93 (SD = .03). Table 1 Reliability analyses (Cronbach’s alpha) of L2 self-efficacy instruments Instrument K # reporting reliability # not reporting reliability Min. Max. Mean SD MSLQ 6 6 0 .85 .97 .91 .05 QESE 5 4 1 .84 .96 .92 .06 SEQ 3 3 0 .74 .87 .82 .07 Novel instrument 8 8 0 .78 .95 .89 .06 Other 15 15 0 .63 .96 .86 .09 All SE instruments 39 37 2 .63 .97 .88 .08 Note. MSLQ – Motivated Strategies for Learning Questionnaire (Pintrich et al., 1991); QESE – Question- naire of English Self-Efficacy (Wang, 2004; Wang et al., 2013); SEQ – Self-Efficacy Questionnaire (Sedi- ghi et al., 2004) Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 241 Table 2 Reporting practices for L2 achievement assessments Assessment type K # reporting Mean # reporting SD # reporting reliability Cronbach’s alpha Mean SD Language test 22 17 16 8 .93 .03 Course grade 7 7 7 0 - - GPA 3 3 3 0 - - Other 7 3 1 0 - - All achievement measures 39 28 26 8 .93 .03 The second research question targeted the magnitude and direction of the relationship between self-efficacy and achievement. We first computed the weighted average mean of all 40 effects in our sample: r = .464 (95% CI [.454, .474]; p < .001), and then examined their distribution for outliers, which we define as any result with a standardized residual larger than 3 in absolute value. This resulted in the exclusion of 13 values, which increased our result slightly to r = .475 (95% CI [.464, .486]; p < .001). Additionally, the Q statistic changed from 1303.27 to 82.93, and the I2 statistic changed from 97.01 to 68.65. This indicated a reduction of sampling error and a sizeable amount of real and systematic variation in the data, thus jus- tifying a moderator analysis. Table 3 provides a summary of our statistical model. An overview of all effects can be found in Appendix B. Table 3 Overall correlation between L2 self-efficacy and L2 achievement K N Mr 95% CI Q I2 Lower Upper L2 achievement 27 18,265 .475 .464 .486 82.927* 68.647* Note. * = p < .001 Additionally, a funnel plot of the relationship between effect size and stand- ard error (Figure 1) was created to examine the presence of publication bias in our sample. The plot includes both actual (i.e., hollow) and imputed (i.e., solid black) data points and suggests a slight publication bias in favor of studies that report strong, positive correlations between L2 self-efficacy and achievement. The moderator analysis (Table 4) was conducted with 27 independent samples and calculated subgroup effects based on seven categories: age, learner L1, target language, institutional context, proficiency level, self-efficacy type, and achievement measure. The analysis for age showed weaker correla- tions for high-school age teenagers (16-18) and learners over 20 than for early high-school (15) and early college age students (19-20). However, the majority of primary studies did not report age as a learner characteristic, leading to small subsamples that warrant cautious interpretation. Julia Goetze, Meagan Driver 242 Note. Solid black point represents imputed data Figure 1 Funnel plot of effect sizes and sampling errors With respect to the learners’ L1 and proficiency level, a similar pattern of underreporting was found. Regarding learners’ L1, some languages, such as Thai (r = .68), showed stronger relationships between L2 self-efficacy and achieve- ment than others, for example Japanese (r = .31). In terms of proficiency level, the analysis indicated a gradual increase in relationship strength when moving from beginner (r = .44) to advanced levels (r = .62). The analysis of self-efficacy type revealed the strongest relationship for speaking self-efficacy (r = .56) and the weakest relationship for vocabulary self- efficacy (r = .33). Other skill-specific types (i.e., reading and writing self-efficacy), as well as general L2 self-efficacy (i.e., no skill or content-specific subtype), all showed findings similar to the overall mean effect of r = .475. Regarding achieve- ment measure, learners’ GPA yielded a stronger correlation (r = .62) than course grades or language tests, which both returned the same effect (r = .47). The analyses for other moderators did not indicate such ranges in effect sizes. For example, findings for target language revealed only a slightly higher effect for English (r = .53) than for non-English languages (r = .47), and institu- tional contexts showed similar effects across all subgroups (r = .47-.50). St an da rd er ro r Funnel plot of standard error by Fisher’s Z Fisher’s Z Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 243 Table 4 Results of the moderator analysis K N Mr 95% CI Lower Upper Age 15 2 2,184 .501 .468 .531 16 1 200 .290 .158 .412 18 1 78 .440 .241 .603 19 1 53 .530 .303 .700 20 2 349 .582 .507 .647 21 6 1,594 .408 .366 .448 Not reported 14 13,807 .477 .465 .490 L1 Arabic 3 857 .533 .483 .580 Chinese 2 1,212 .457 .411 .501 English 1 128 .530 .393 .644 Japanese 2 171 .307 .163 .438 Malaysian 2 320 .401 .304 .489 Persian 1 100 .560 .409 .681 Thai 2 83 .678 .539 .781 Multiple 1 304 .530 .444 .606 Not reported 13 15,090 .473 .460 .485 Target language English 23 17,296 .472 .460 .483 Non-English 4 969 .525 .478 .570 Institutional context Secondary 7 13,806 .474 .461 .487 Post-secondary 17 3,583 .471 .447 .495 Language institute 3 876 .500 .449 .548 Proficiency level Beginner 1 78 .440 .241 .603 Intermediate 4 696 .518 .461 .570 Advanced 1 32 .615 .339 .794 Multiple 5 842 .487 .433 .537 Not reported 16 16,617 .472 .461 .484 Self-efficacy type General 17 15,943 .474 .462 .486 Skill – vocabulary 1 120 .330 .160 .481 Skill – reading 4 889 .479 .427 .529 Skill – speaking 1 100 .560 .409 .681 Skill – writing 4 1,213 .483 .439 .525 Achievement measure Language test 17 16,677 .473 .461 .485 Course grade 5 783 .473 .417 .526 GPA 1 32 .615 .339 .794 Other 2 220 .442 .328 .543 Multiple 2 553 .530 .467 .588 Julia Goetze, Meagan Driver 244 6. Discussion RQ1 explored reporting practices in L2 self-efficacy and achievement research. The majority of studies reported both basic descriptive statistics and reliability coefficients of their self-efficacy instruments, which all align with or exceed the average reliability estimates for instruments designed for SLA research (Plonsky & Derrick, 2016). Thus, we see rigorous reporting practices within this domain of research. With respect to language achievement measures, we found a weaker tradition of reporting practices. Only approximately one-third of the studies provided the reliability coefficient of their language achievement test. In terms of basic descriptives, only two-thirds reported both the mean and stand- ard deviation for their sample. As noted in previous meta-analyses (e.g., Teimouri et al., 2019) and reviews of SLA research practices (e.g., Larson-Hall & Plonsky, 2015; Plonsky, 2013, 2017), this lack of reporting is a common limitation of SLA research. Furthermore, nearly half of the studies used instructor- or institution- developed achievement tools, which often lack the psychometric properties that are essential for robust quantitative analysis in SLA (Brown et al., 2018). Altogether, these results highlight the need for greater validation of instruments and more rigorous reporting practices on language achievement measures in SLA (Marsden & Plonsky, 2018). RQ2 investigated the direction and magnitude of the relationship be- tween learners’ self-efficacy and their L2 achievement. The mean correlation between these variables was r = .475, and self-efficacy accounted for approxi- mately 22% of the variance in learners’ achievement, signifying a medium effect in SLA (Plonsky & Oswald, 2014). Within the context of the positive turn in SLA, it is insightful to interpret our result in comparison to meta-analytical findings of other prominent psychological constructs, such as motivation, which has been paradigmatically categorized as playing a positive role in student learning. Somewhat surprisingly, Al-Hoorie’s (2018) recent meta-analysis of the L2 moti- vational self system and L2 achievement found smaller mean correlations be- tween learners’ L2 achievement and their L2 ideal self (r = .20), ought-to self (r = -.05), and learning experience (r = .17). Considering the close relationship be- tween learners’ ideal selves and self-efficacy beliefs (Lake, 2013), one might have expected a similar effect size for both variables. Instead, finding a larger positive effect for learner beliefs raises questions about the complexity of the relationship between learner beliefs and motivations in the context of L2 achievement. While studies in the positive psychology paradigm in SLA have pre- dominantly examined a host of emotional variables (Driver, 2021), our findings furthermore highlight the potential of examining the role of cognitive variables and their interaction in student thriving and learning success in future studies. Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 245 It is also helpful to interpret our result in comparison to meta-analytic findings in neighboring disciplines. In psychology, Multon and associates (1991) found a more moderate effect of r = .38 (95% CI [.36, .41]) through their meta- analysis of self-efficacy beliefs and general academic outcomes, while Huang’s (2016) findings in education regarding the effect of self-efficacy on general achievement goals align more closely with our result (r = .48; 95% CI [.38, .46]). The similarity of Huang’s finding raises questions regarding the underlying the- oretical assumptions of the self-efficacy and achievement relationship in SLA (Wyatt, 2018), considering Huang’s conceptualization of achievement goals as beliefs about achievement objectives rather than as a measurable performance outcome. Put differently, Huang’s study examined the relationship between two separate beliefs, rather than between a belief (e.g., self-efficacy) and an out- come (e.g., achievement measure), arguably capturing more accurately Ban- dura’s (1977) theorization of the relationship between self-efficacy and achieve- ment (Figure 2). In contrast, most studies in our sample employed self-efficacy definitions by Bandura (1986, 1997) but used correlational designs to investigate the link to outcomes, thereby conflating multiple cognitive and behavioral con- structs into one variable. Therefore, our estimate of the mean effect must be interpreted with caution, as neither the different types of beliefs nor the behav- iors of participants were controlled for in the primary studies. Learner Behavior Outcome Figure 2 Representation of the self-efficacy and achievement relationship (Ban- dura, 1977) RQ3 examined the effects of moderating variables. The results of this anal- ysis showed a number of differences in effects sizes with respect to learner char- acteristics, language, and target skill (e.g., speaking vs. writing). However, con- sidering the overall small sample size of this moderator analysis (N = 27) and the resulting limited number of studies in each analytical subcategory, caution should be taken when interpreting these findings. Perhaps most notable were the findings for L2 proficiency, which showed strongest effects for advanced students and weakest for beginners. For self-effi- cacy to positively impact L2 achievement, learners must not only believe in their abilities, but these beliefs must also have a direct effect on how learners engage with a task, that is, through increased levels of attention and awareness, imple- mentation of task-appropriate learning strategies, or stronger feelings of L2 grit, Self-efficacy beliefs Outcome beliefs Julia Goetze, Meagan Driver 246 all of which have been seen to result in better learning outcomes (e.g., Teimouri et al., 2020). Higher proficiency learners likely have more experience with how posi- tive beliefs can motivate learning processes that lead to greater L2 achievement, as well as the linguistic resources to bridge the gap between simply believing in the ability to complete a task and actually successfully accomplishing the task. Results also revealed differences across learners’ L1, which may be related to questions around L2 accessibility and the relative “prestige” and utility of the L1 in global settings. Self-efficacy effects were strongest for L1 Thai speakers and weakest for L1 Japanese speakers. Given the value of Japanese in the worldwide business market and the socioeconomic developments in Japan (Terasawa, 2017) that have increased access to the L2 (i.e., English), L1 Japanese speakers may be motivated by factors other than self-efficacy and have less urgency to meet achievement objectives than other L1 speakers. In contrast, L1 Thai speakers en- counter fewer opportunities and encouragement to use L2 English in Thailand (Anyadubalu, 2010) but, at the same time, may also be more dependent on an L2 in order to enter into global discussions, economics, and business partnerships. Thus, some L1 speakers in regions with less access to L2 resources are likely to rely more heavily on their self-efficacy for affecting achievement, which aligns with the relative effects and L1 profiles in our findings (e.g., Arabic; Aljaffery, 2015). Similarly, given the “prestige” of English as a global language, L1 English speakers may also receive less support for learning an L2 and rely more heavily on their own self-beliefs for realizing L2 achievement goals. In addition, we found slightly weaker effects for L2 learners of English than for non-English languages, which strengthens our argument. L2 learners of English likely find primary motiva- tions (e.g., ought-to L2 self; Ushioda & Dörnyei, 2011) from outside sources based on the global instrumentality of the English language. In contrast, learners of other languages likely see fewer motivations and obligations from their society to learn the L2, resulting in a stronger connection between self-efficacy and achievement. Interestingly, results also indicated weaker effects for learners’ beliefs about their L2 vocabulary knowledge than general or skill-specific self-efficacy (e.g., reading, writing, or speaking), suggesting that learners’ beliefs in their abil- ity to complete open-ended rather than narrowly focused tasks (i.e., on vocab- ulary or grammar) may have a greater impact on achievement. The strongest effect was found for speaking self-efficacy. Because speaking requires learners to produce language without the opportunity to review and revise before the final product (as is the case with both reading and writing), self-efficacy in this area suggests that learners have a strong belief in their ability to spontaneously and accurately organize and communicate their thoughts. Thus, speaking self- efficacy may encompass self-beliefs in a wider number of task-related abilities, leading to stronger effects for ultimate L2 achievement. Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 247 Finally, the positive effects of self-efficacy were uniform in relation to lan- guage tests and course grades, which suggests both as acceptable metrics of achievement in this domain. However, the much larger effect for GPA raises con- cerns about the weak ecological validity of GPA as a measure of achievement. Still, the subsample for this moderator was small and this finding should be taken with caution. Other moderators revealed either no differences (i.e., insti- tutional context) or no clear variation patterns (i.e., age). Though a smaller ef- fect size was seen for the 16-year-old age group, the self-efficacy-achievement connection for 15-year-olds was similar to the average effect size for college- aged learners (i.e., ages 18-21), and, due to underreporting of this learner char- acteristic, it is not clear if studies explored other age groups within the second- ary or primary school context. The question whether or not the effects of L2 self- efficacy may be more beneficial for adults in comparison to younger learners, or perhaps for contextually younger students compared to older students, who tend to be closer to a graduation and perhaps reap fewer benefits of believing in their abilities, will require more research exploring a wider range of age groups, as well as robust reporting practices. 7. Limitations, directions for further research, and pedagogical implications Some important limitations need to be considered when interpreting the findings of our study. First, small subsamples in our moderator analysis can only provide scant evidence for the role that our selected variables play in the systematic vari- ation of the effect size. Second, we did not include unpublished studies or those published in languages other than English in our final sample, which may have introduced multiple biases into our analysis that possibly resulted in an overesti- mation of the strength of the observed relationship (Cooper, 2016). Lastly, we also excluded two studies that implemented advanced statistical methods, such as β- coefficients in structural equation modeling (SEM) to report on the relationship for self-efficacy and achievement. As a result, we are not able to provide evidence for existing trends or effect size variation for different analytical approaches. We encourage future studies to carefully examine the theoretical under- pinnings of the self-efficacy and achievement relationship. Bandura’s (1986) fre- quently used definition distinguishes self-efficacy beliefs from beliefs about out- comes, which some scholars have defined as self-confidence (e.g., Karademas, 2006), thereby adding not only a behavioral, but also an emotional component to the theoretical conceptualization of the relationship. The use of conceptual frameworks that allow for the holistic examination of self-efficacy in relation to other psychological dimensions, such as emotions, behaviors, and motivations, simultaneously within cultural, societal, and institutional contexts (e.g., Ushioda, Julia Goetze, Meagan Driver 248 2014) would move future studies away from cross-sectional bivariate analyses of variables toward system modeling that is able to capture variable change over time. The moderator analysis also revealed the need for research with popula- tions learning other second or foreign languages than English and with K-12 learners. Additionally, our findings suggest that SLA would benefit from future studies that focus specifically on skill-specific self-efficacy beliefs. Lastly, we rec- ommend more rigorous reporting practices in line with field-specific standards and reaffirm calls to improve the reporting of statistical and psychometric fea- tures of measurement tools, especially for L2 achievement. In terms of FL pedagogy, the findings suggest that increased self-efficacy in the target language is beneficial for language learning, regardless of age or con- text. Given this positive relationship, educators might consider using methods that have been shown to promote self-efficacy, such as the flipped classroom model (Namaziandost & Çakmak, 2020), and project-based learning (Shin, 2018). Both of these methods have shown positive effects on learners’ self-efficacy and motivation, and may have a positive influence on their future achievement objec- tives. Educators should consider preparing classroom activities, particularly relat- ing to speaking, that feed into students’ self-efficacy and nurture students’ beliefs about their abilities to complete tasks in the L2, which will depend on learners’ experiences with the language and their existing knowledge and skills. As our find- ings suggest, practitioners may find that materials designed to raise L2 self-effi- cacy are particularly beneficial for students at higher L2 levels. Importantly, the methods used in a majority of studies in our sample were not intended to repli- cate the classroom learning experience, and pedagogical implications should be considered with other well-founded pedagogical methods from SLA. 8. Conclusion The goal of this meta-analysis was to systematically examine the relationship between L2 self-efficacy and achievement. 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System, 96, 102410. https://doi.org/10. 1016/j.system.2020.102410 Julia Goetze, Meagan Driver 258 APPENDIX A Descriptions of variables used in the coding scheme (adapted from Teimouri et al., 2019) Variable Description Bibliographic information Author(s) Name(s) of researchers who conducted and published the study Publication year Year in which the study was published Publication title Title of the article or chapter Publication venue Title of the journal or volume in which the study was published Participant sample Sample size Number of participants Age Average age or age range of participants Nationality Nationality of participants L1 L1 of participants Target language Language of interest for self-efficacy and achievement measures Academic level Educational level (elementary, middle, or high school, university, language institute, tutor- ing/private lessons) of participants Proficiency level Proficiency level (beginner, intermediate, advanced, multiple) of participants Language learning experience Average number of months/years of experience that participants had with learning the lan- guage Study design Design Experimental or observational Methodology Quantitative, qualitative, or mixed methods Context Target language context (L2, FL, heritage, combined L2/FL, study abroad) Setting Setting in which the research took place (classroom, lab, combined classroom/lab, computer- or mobile-assisted learning, distance learning) Country Country in which the research took place Self-efficacy instrument Terminology Terminology used to refer to self-efficacy (e.g., L2 self-efficacy) Type General or skill-specific Definition Definition used for self-efficacy and whether the definition was adapted from previous work or newly-formulated Variable role Dependent or independent variable, or not applicable Instrument type Whether the instrument was adapted from previous work or newly-developed; if adapted, origi- nal publication from which the instrument was adapted N of items Number of items in the instrument Items type Whether or not the instrument was a Likert-scale questionnaire and, if so, the range of the Likert scale Mean Reported mean for the self-efficacy measure Standard deviation Standard deviation for the self-efficacy measure Reliability Whether or not a reliability measure was reported Reliability index Reported reliability index (e.g., Cronbach’s alpha) Reliability estimate Observed reliability coefficient L2 achievement instrument Type Type of achievement measure (e.g., language test, course grade, self-perceived competence, GPA) Mean Reported mean for the achievement measure Standard deviation Standard deviation for the achievement measure Reliability Whether or not a reliability measure was reported Reliability index Reported reliability index (e.g., Cronbach’s alpha) Reliability estimate Observed reliability coefficient Results Type of analysis Type of analysis run between self-efficacy and L2 achievement (e.g., Pearson correlation, re- gression) Effect size (r) Observed correlation between self-efficacy and L2 achievement Is learning really just believing? A meta-analysis of self-efficacy and achievement in SLA 259 APPENDIX B Effect sizes in the studies under review Primary study N M 95% CI Lower Upper Alrabai (2018) 221 .549* .450 .635 Asakereh & Dehghannezhad (2015) 100 .560* .409 .681 Bai et al. (2019) 1092 .530* .486 .571 Balci (2017) 78 .440* .241 .603 Chao et al. (2019) 1092 .470* .422 .515 Fukuda (2018) 97 .304** .111 .475 Hetthong & Teo (2013) 51 .712* .543 .826 Hsieh (2008) 249 .590* .503 .666 Hsieh & Kang (2010) 192 .468* .350 .572 Hsieh & Schallert (2008) 500 .530* .464 .590 Jee (2015) 92 .272** .071 .452 Khodadad & Kaur (2016) 240 .423* .313 .522 Kitikanan & Sasimonton (2017) 32 .615* .339 .794 Ma et al. (2018) 11,036 .472* .457 .486 McCollum (2003) 128 .530* .393 .644 Mizumoto (2013) 303 .570* .489 .641 Al Khamisi et al. (2016) – Study 1 260 .541* .449 .622 Al Khamisi et al. (2016) – Study 2 376 .518* .440 .588 Raoofi & Maroofi (2017) 304 .530* .444 .606 Shah et al. (2011) 120 .563* .427 .674 Shang (2010) 53 .530* .303 .700 Templin (1999) 74 .310** .088 .503 Wang et al. (2012) – Study 1 474 .380* .300 .455 Wang et al. – Study 3 476 .360* .279 .436 Woodrow (2011) 738 .430* .369 .487 Wu et al. (2013) 120 .330* .160 .481 Weighted average*** 18,265 .475* .464 .486 Note. * p < .001; ** p < .01; *** Weighted means with 95% confidence intervals of final sample (k = 27)