Search

Flipped learning has become a popular approach in various educational fields, including second language teaching. In this approach, the conventional educational process is reversed so that learners do their homework and prepare the material before going to class. Class time is then devoted to practice, discussion, and higher-order thinking tasks in order to consolidate learning. In this article, we meta-analysed 56 language learning reports involving 61 unique samples and 4,220 participants. Our results showed that flipped classrooms outperformed traditional classrooms, g = 0.99, 95% CI (0.81, 1.17), z = 10.90, p < 0.001. However, this effect had high heterogeneity (about 86%), while applying the Trim and Fill method for publication bias made it shrink to g = 0.58, 95% CI (0.37, 0.78). Moderator analysis also showed that reports published in non-SSCI-indexed journals tended to find larger effects compared to indexed ones, conference proceedings, and university theses. The effect of flipped learning did not seem to vary by age, but it did vary by proficiency level in that the higher proficiency the higher the effects. Flipped learning also had a clear and substantial effect on most language outcomes. In contrast, whether the intervention used videos and whether the platform was interactive did not turn out to be significant moderators. Meta-regression showed that longer interventions resulted in only a slight reduction in the effectiveness of this approach. We discuss the implications of these findings and recommend that future research moves beyond asking whether flipped learning is effective to when and how its effectiveness is maximized.

This article presents a conceptual replication of Hashimoto and Egbert (https://doi.org/10.1111/lang.12353), a study that featured multivariate models where lexical sophistication variables accounted for word difficulty (yes-no recognition) better than frequency alone among learners of English as a second or foreign language from North America. This current study (n[subscript words] = 88; n[subscript people] = 128) conceptually replicated Hashimoto and Egbert with data from three Asian university English-for-academic-purposes sites. Methodological differences included a more conservative lexical sophistication operationalization process and avoidance of stepwise regression. Like the original study, the replication's findings favored multivariate models over frequency, which predicted 36% of word difficulty's variance alone. In a multiple regression model accounting for word difficulty, R[superscript 2] = 0.52, frequency accounted for 17% of the predicted variance with age of acquisition (AoA: 18%) and word naming reaction time (WN_RT: 16%) also being significant predictors. This replication also extended the testing approach by using a mixed-effect model, involving person and site intercepts as random effects. The model's ability to predict word difficulty fell, marginal R[superscript 2] = 0.22, conditional R[superscript 2] = 0.40, but frequency, AoA, and WN_RT remained the strongest predictors. Taken together, this replication successfully supports the original study's more-than-frequency conclusion while highlighting the need for further research into the area.

Decades of research have established that most English Language Teaching (ELT) contexts rely on textbooks and corresponding materials to drive the education process. Textbook analysis as a vital quality control check of these products has also become a popular trend in applied linguistics and "second language" (L2) research. In the main, ELT textbooks have been conceptualized in past literature as supporting target language proficiency attainment while also giving the teacher everything required to conduct a lesson. Textbook analysis has subsequently checked products' utility and quality in relation to such proficiency development. Over time, the scope of textbook analyses has expanded to include issues such as cultural representations in these products to address how the products help students become better at English in a multicultural and globalized world. While teachers and researchers can reference numerous well-known books on these phenomena, a concise summary of how textbooks function within ELT contexts and the defining features of textbook analysis research appears to be lacking. This brief report meets this need and is useful to stakeholders in the ELT community, such as teachers and program managers, who might not have the time nor the resources to consult such extensive sources of information.

In this focused methodological synthesis, the sample construction procedures of 110 second language (L2) instructed vocabulary interventions were assessed in relation to effect size-driven sample-size planning, randomization, and multisite usage. These three areas were investigated because inferential testing makes better generalizations when researchers consider them during the sample construction process. Only nine reports used effect sizes to plan or justify sample sizes in any fashion, with only one engaging in an "a priori" power procedure referencing vocabulary-centric effect sizes from previous research. Randomized assignment was observed in 56% of the reports while no report involved randomized sampling. Approximately 15% of the samples observed were constructed from multiple sites and none of these empirically investigated the effect of site clustering. Leveraging the synthesized findings, we conclude by offering suggestions for future L2 instructed vocabulary researchers to consider "a priori" effect size-driven sample planning processes, randomization, and multisite usage when constructing samples.

Instrument measurement conducted with Rasch analysis is a common process in language assessment research. A recent systematic review of 215 studies involving Rasch analysis in language testing and applied linguistics research reported that 23 different software packages had been utilized. However, none of the analyses were conducted with one of the numerous R-based Rasch analysis software packages, which generally employ one of the three estimation methods: conditional maximum likelihood estimation (CMLE), joint maximum likelihood estimation (JMLE), or marginal maximum likelihood estimation (MMLE). For this study, eRm, a CMLE-based R package, was utilized to conduct a dichotomous Rasch analysis of a Yes/No vocabulary test based on the academic word list. The resulting parameters and diagnostic statistics were compared with the equivalent results from four other R-based Rasch measurement software packages and Winsteps. Finally, all of the packages were utilized in the analysis of 1000 simulated datasets to investigate the extent to which results generated from the contrasting estimation methods converged or diverged. Overall, the differences between the results produced with the three estimation methods were negligible, and the discrepancies observed between datasets were attributable to the software choice as opposed to the estimation method.

The present study involved the analysis of 81 second language instructed vocabulary acquisition (L2 IVA) studies over 2 phases. In Phase I, we categorized and coded the effect sizes of the studies. Observing that the basic between- and within-subject design dichotomy lacked the sensitivity to capture the heterogeneity of observed effects, we employed a more granular approach. In both between- and within-subject designs, treatment versus comparison contrasts best represented comparisons of most interest in L2 IVA experiments, with median effect sizes (g) of 0.62 (between-subject) and 0.25 (counterbalanced within-subject). In Phase II, the aggregated effect sizes observed in Phase I were utilized in a priori power simulations to suggest approximate sample sizes for common L2 IVA analyses. For conservatively powered between-subject designs, the simulations suggested sample sizes ranging from 292 to 492 participants. Counterbalanced within-subject designs required 95 to 203 subjects depending on the assumed correlation between the repeated measures. The overarching implication of these simulations suggests that future L2 IVA experiments require larger samples that reference effect sizes from previous research, and we offer 3 potential solutions to the problem of obtaining larger samples.

This report presents a review of the statistical practices of 30 journals representative of the second language field. A review of 150 articles showed a number of prevalent statistical violations including incomplete reporting of reliability, validity, non-significant results, effect sizes, and assumption checks as well as making inferences from descriptive statistics and failing to correct for multiple comparisons. Scopus citation analysis metrics and whether a journal is SSCI-indexed were predictors of journal statistical quality. No clear evidence was obtained to favor the newly introduced CiteScore over SNIP or SJR. Implications of the results are discussed.

Within English for Academic Purposes (EAP), writing instruction has often been of primary interest with a focus on curricula design and implementation. This especially holds true in East Asia where many universities operate EAP writing programmes. This study is located within this region, taking an inquiry stance in a small-scale case study of four EAP writing programmes. Through practitioner-as-researcher reflections and triangulating interviews from fellow colleagues within this professional context, we add to this discussion by uncovering three interrelated and hierarchical themes that have emerged from our data. At the university and inter-department organizational level, our data points to the need for universities housing these programmes to create a culture of collaboration where relevant academic expertise can directly inform the classroom (EAP writing) instruction. At the departmental level, our data suggests that standardization, especially in relation to intra-department testing, assignments, etc. is beneficial. Finally, at the classroom level, we posit, through the observations in the inquiry, that certain teaching methods are associated with different levels of proficiency. Teacher-led frameworks are more observed and suitable among lower proficiency language learners. Conversely, higher proficiency students expect and are better served by task-based or student-led approaches.