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Motivation and affect as two salient variables in L2 development are no longer seen as the stable individual difference factors they were once believed to be. Influenced by process-oriented approaches and by increasing understanding of how the complex dynamic system theory (CDST) works, researchers have been emphasizing the holistic, non-modular, dynamic and changeable nature of motivation and affect to-date. Accordingly, this study utilized the principles underlying the CDST perspective to examine the interrelationships between Iranian EFL learners’ motivational and affective factors mediated by working memory and gender over an academic semester. To this end, 445 pre-intermediate male and female students completed the motivation questionnaire and L2 Enjoyment Scale four times with one-month intervals during an academic semester and Working Memory Scale once in the beginning of the term. Relationships that emerged indicated both motivational and affective stability and fluctuation over a semester of instruction at one month intervals. The findings also illustrated how these factors are inseparable from students’ learning context. Implications of study and directions for further research were also discussed.

This cross-cultural study aims to examine how Iranian and American motivational speakers employ metadiscourse devices as a convincing tool to interact with their audience. To this end, eight motivational speeches in English and Persian were randomly selected from 2015 to 2021, and analyzed for the use of stance (i.e., hedges, boosters, attitude markers, and self-mentions) and engagement (i.e., reader-pronouns, directives, questions, shared knowledge, and personal asides) expressions. The findings showed that self-mention and attitude markers were the most frequently used stance markers in English and Persian corpus, respectively. Moreover, hedges found to be the least frequently used stance markers in the two corpora. With regard to the use of engagement markers, results showed that reader pronoun is the most frequently used engagement markers, and shared knowledge and personal asides were the least frequently used engagement markers in both languages. Finally, the results of chi-square test showed statistically significant differences in the use of stance and engagement expressions in the two languages, confirming cultural septicity nature of metadiscourse markers, and that speakers of different languages employ interactional devices according to their context.

The 5E Learning Cycle Model (Bybee, 1990) is an instructional design model which has roots in inquiry-based learning and constructivism and has received much support in non-EFL-related literature as a way to improve 21st-century skills, such as critical thinking and creativity, among students and to prepare them for an amazing occupational future. However, little work has been done on the model concerning English language students; hence, this study dealt with the effect of 5E-based online activities on English language students’ critical thinking and creativity. The study utilized a mixed method grounded theory method approach. A sample of 60 adult English language students studying in a pre-IELTS class at a private language academy took part in the study during a 12-session semester, in addition to an extra session at the beginning of the semester, in which they received instruction with regard to the platforms to be used, namely Easyclass and Nearpod. Student interviews and self-reflections, teacher interviews, self-reflections, and field notes were applied to extract qualitative data, and student self-assessment checklists were used to gain quantitative data. The analysis of the quantitative and qualitative data via an independent sample t-test, inductive thematic analysis, and grounded theory demonstrated that the employment of 5E-based online activities culminated in the improvement of EFL learners’ critical thinking and creativity. The findings have theoretical and practical implications not only for 21st-century language practitioners’ education and competencies but also for curriculum development.

Predicting students’ performance in a course is one of the major aims of educational data mining systems. In the present study, two and three-layer artificial neural networks (ANN) and neuro-fuzzy systems (NFS) were used to predict Iranian EFL learners’ final scores and compare them with scores given by their instructor. Sixty-six students’ scores in an English reading comprehension course comprising of five sub-scores of midterm (out of 40), quiz (out of 60), final (out of 50), class participation (out of 5) and bonus (out of 2) were used for training the systems. Two and three-layer ANNs and an NFS were trained to predict students’ final scores using training data. Researchers compared the students’ final scores given by their instructor and those achieved through the ANNs and NFS. The results showed that the NFS could predict and deliver scores that were closer to the linear sum of students’ scores. Moreover, three-layer ANN had a better performance than the two-layer ANN. According to these results, data mining techniques could deliver an accurate estimate of students' abilities in a particular course.

The Collaborative for Academic, Social, and Emotional Learning (CASEL) defines self-awareness competence as the ability to assess one's emotions, values, and skills realistically. Utilizing this definition as a theoretical framework, this qualitative study aimed to explore EFL teachers' perceptions and strategies regarding self-awareness competence in the classroom. To accomplish this goal, 19 EFL teachers from Iran were recruited through convenience sampling and took part in one semi-structured written interview and four focus group interviews to exchange their perspectives and strategies for developing their self-awareness competence. Adopting the routine analytical steps in grounded theory, i.e., open, axial, and selective coding, the study identified three key components for the participants’ self-awareness perceptions: knowing one’s emotions, having a growth mindset, and having a realistic sense of self-perception. The participants also outlined two primary categories of self-reflection strategies - practical and cognitive - to enhance their self-awareness competence. It was found that reflective practices were essential tools for cultivating the self-awareness competence of EFL teachers. Additionally, the study unveiled that EFL teachers' attitudes and strategies toward self-awareness competence were harmonious. Ultimately, the findings demonstrated promising prospects for future EFL teachers to enhance their personalized reflective strategies.

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.

Following the COVID-19 outbreak, educational institutes around the world including Iran transitioned from the face-to-face method to an online modality to sustain education. Adapting to this abrupt transition was challenging for teachers, especially those working in remote and low-resource schools. To have a profounder understanding of Emergency Remote Teaching (ERT) in rural secondary schools, in this qualitative study, the researchers explored the technological tools, teaching platforms, and assessment strategies employed by 12 Iranian English teachers during the pandemic. The analysis of the data, collected through semi-structured interviews and e-observations, revealed that the participants mostly, but not exclusively, used SHAD application as their online platform and used different technological tools for creating pedagogic content such as screen recorder, video editors, and PowerPoint. The teachers also adopted different methods for delivering teaching including flipped method, live broadcasts, pre-recorded teaching materials, voices, and images. They used Google forms, Digi forms, and video calls for evaluating the students; nevertheless, they chiefly deployed these tools for designing traditional exam types. The implications and limitations of the study are discussed.