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The book Practical Language Testing, authored by Glenn Fulcher (2010), is an epitome of comprehensive and detailed documentation on the relevance of the appropriate techniques, knowledge, and conceptual frameworks required to interpret and develop language assessments. It is also a systematic, helpful reference for researchers and educators that address assessment selection and design concerns, offering instructors guidance on picking the proper test for a particular educational setting and assisting in interpreting the scores generated by such tests. The book lays the groundwork for instructors to establish a thoughtful awareness of test scenarios to furnish the most efficient language assessment for their learners. The book's language is highly lucid and user-friendly to both experts and novices. The book finds an appropriate amalgamation between practical applications and theoretical underpinnings to empower practitioners in comprehending the objectives of effective assessment and its function in facilitating good learning and teaching. On account of the fact that the referenced book has the potential to make a substantial contribution and have significant implications for teachers, test designers, and other stakeholders, the current article attempts to provide a review of the book and emphasize the critical concepts in each chapter.

To date, with the everyday growth of technology and the increase of online classes, busy modern teachers seek to lighten their burdens and boost their learners’ autonomy. Thus, this multi-method action research aimed to probe the differences between receiving computer-generated and direct corrective feedback (CF) on the syntactic accuracy and complexity of female adolescent Iranian EFL learners’ writing. Two intact classes took part in the study; one group (Group C) received CF from an AWE (Automated Writing Evaluation) tool, called Ginger software, and the other group (Group T) received CF from their teacher. Subject-verb agreement and verb form errors were considered to measure the syntactic accuracy while the average sentence length and verb form variation were regarded as the syntactic complexity. Moreover, via a questionnaire, the students’ perceptions of the kind of CF they had received were taken into account to see which one was more effective. Findings obtained from MANOVA revealed that both groups made significant improvements regarding syntactic accuracy. Group C produced more complex outputs after being exposed to the treatment while Group T didn’t make such progress. The results obtained from the questionnaire also indicated that both groups found the CF satisfactory. However, Group C held more positive attitudes. Not only was the Ginger application effective in decreasing the number of students’ writing errors but also it motivated them to be better writers and write more. The study further points to the likely merits of technology-enhanced feedback in improving EFL learners' writing ability in general, and their written syntactic accuracy/complexity in particular.

PhD examination is a unique type of assessment with examiners playing a key role in it. Despite extensive research on various modes of academic genre, research on the examiners’ language representing oral review genre is yet underrepresented. One important way to identify this genre is to unpack the metadiscursive features that constitute this type of academic discourse. Using a metadiscourse framework, developed by Hyland (2005), this study investigates the metadiscursive markers that constitute Iranian and International examiners’ language of PhD dissertation evaluation. The data include the transcriptions of Iranian and International examiners’ evaluative discourse in eight PhD dissertation defenses, taken place in Iran and the US (MICASE corpus), representing English for Academic Purposes. The results indicate that the examiners use a variety of interactional as well as interactive metadiscourse markers to convey the effective and appropriate evaluation of the PhD dissertations at hand. Further breakdown of the metadiscourse devices and the comparison of the two sets of data are provided. The results unpack an aspect of oral academic review as a specific genre with implications for both EAP-user examiners and PhD candidates to become aware of the discursive features of the examiners language.

As conceptual models of language learning, use, and processing mature, it is both natural and necessary for the statistical models we apply to follow suit. One statistical approach with great potential in the field Applied Linguistics and L2 studies is structural equation modeling (SEM). SEM is introduced in this paper as a powerful and highly flexible family of analyses. In doing so, the paper outlines (a) the types of variables and possible modeled relationships that SEM is equipped to address and (b) statistical considerations for applying SEM in L2 research, and (c) a number of additional and key considerations for those interested in delving deeper into SEM (e.g., goodness of fit indices, model modification procedures, etc.). This paper also describes the potential of SEM to contribute to construct validation (e.g., convergent and discriminant validity). Throughout the paper, a plethora of examples pertaining to applications of SEM in L2 research are provided.

This study sought to determine the impact of self-regulation and emotional labor on reflective action among Iranian EFL teachers in online EFL classes using structural equation modeling. To achieve this, a combination of cluster sampling and stratified random sampling of 500 people was recruited. The participants were administered with the English version of Dutch questionnaire of emotional labor, Teacher Self-Regulation Scale and Teaching Reflection Inventory. After collecting data using three distinct questionnaires pertaining to latent variables, SEM analysis was conducted using IMB SPSS version 28.0 and Amos version 24.0 to analyze the path model relationships. To this end, a hypnotical model was proposed, evaluated, and specified to fit the data. The confirmatory factor analysis was employed to assess the hypothetical model by employing goodness of fit indices and analyzing all the convergences between the latent variables and the related sub-scales. According to the criteria for a good model's fitness, all of the model's values are above 0.90, indicating that the model has good fitness. And it was concluded that there was statistically significant relationships between the variables of the study.

English cartoons have become increasingly popular as a resource for language learners worldwide. While the literature has primarily focused on their impact on English language skills and sub-skills in EFL education, less attention has been given to their influence on cognitive and affective aspects such as emotion regulation and self-efficacy. This study employed a mixed-methods approach with a pre-test/post-test quasi-experimental design to explore the impact of watching English cartoons on the emotion regulation and self-efficacy of adolescent Iranian EFL learners. 120 Iranian learners, aged 12 to 18, were recruited from English institutes in Tehran and randomly assigned to either the experimental or control group. The experimental group watched two 30-minute episodes of selected American-produced animated cartoons per week for eight weeks, totaling 16 episodes, while the control group did not. The MANCOVA analysis revealed significant differences in self-efficacy and emotion regulation between the experimental and control groups, indicating that exposure to English cartoons positively influences learners' emotional responses and self-efficacy. Thematic analysis of the interview data highlighted positive evaluations of the experience, identifying five themes: enhancement of language skills, positive emotions leading to increased motivation, the prominence of comedy, contribution to sustained learning, and varying effects on self-efficacy. These findings hold valuable theoretical and practical implications for the field.

The present study scrutinized the probable significant correlation between Iranian language learners’ emotional intelligence (EQ) and reading proficiency. Moreover, the significant predicting role of the participants’ EQ for their reading comprehension proficiency was investigated. To this end, 196 Iranian B.A. English language teaching students at Islamic Azad university of Neyshabur attended the study. They formed unequal proportion of gender. The study followed a quantitative descriptive design, in which the significant correlation between the variables and the significant predicting role of EQ were investigated. As the normality of data was proved through Kolmogrow-smirnow test, the parametric statistical analyses, including descriptive statistics, Pearson correlation coefficient, independent sample T-test, and linear regression analyses were employed. The data collection instruments were an ETS TOEFL reading comprehension test and Bar On’s (1997) inventory of emotional quotient. The findings demonstrated significant positive correlation coefficients between the participants’ reading proficiency and overall EQ as well as most of its subcategories. Three highest positive significant correlation coefficients were seen among the participants’ reading proficiency level, happiness, problem-solving, and emotional self-awareness successively. The results of linear regression analysis also reflected that EQ significantly predicted the participants’ reading proficiency. No significant differences were found between the genders concerning EQ. The findings laid emphasis on the influential importance of psychological non-linguistic factors in improving linguistic competence of language learners. Language teachers should be acutely conscious of the highly influential role of psychological paradigms in boosting language learning process of language learners.

Cognitive diagnostic models (CDMs) have received much interest within the field of language testing over the last decade due to their great potential to provide diagnostic feedback to all stakeholders and ultimately improve language teaching and learning. A large number of studies have demonstrated the application of CDMs on advanced large-scale English proficiency exams, such as IELTS, TOEFL, MELAB, and ECPE. However, too little attention has been paid to the utility of CDMs on elementary and intermediate high-stakes English exams. The current study aims to diagnose the reading ability of test takers in the B1 Preliminary test, previously known as the Preliminary English Test (PET), using the generalized deterministic input, noisy, “and” gate (G-DINA; de la Torre, 2011) model. The G-DINA is a general and saturated model which allows attributes to combine in both compensatory and non-compensatory relationships and each item to select the best model. To achieve the purpose of the study, an initial Q-matrix based on the theory of reading comprehension and the consensus of content experts was constructed and validated. Item responses of 435 test takers to the reading comprehension section of the PET were analyzed using the “G-DINA” package in R. The results of attribute profiles suggested that lexico-grammatical knowledge is the most difficult attribute, and making an inference is the easiest one.