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Pragmatic testing depends on a variety of factors that can impact its dependability. This study intended to examine these factors using a two-phase approach. The first phase examined the impact of test methods, items, raters, and test-takers' characteristics on the variance in pragmatic test scores using generalizability theory, and the second phase explored potential rater bias using the Many-Facet Rasch model. Two test types, including a Written Discourse Completion Test (WDCT) and a Discourse Self-Assessment Test (DSAT), were administered to 110 English language students (98 female, 12 male) aged 17-24 at Vali-e-Asr University of Rafsanjan. Four raters scored the WDCT by using a standardized rubric developed by Lui (2004). The DSAT was self-assessed by test takers based on the same rubric. The findings revealed no significant difference between the WDCT and DSAT test types. However, items and the interaction between items and test takers emerged as substantial contributors to the variance of the scores. This highlights the importance of item calibration and rater training to mitigate bias in pragmatic testing. Finally, the implications were discussed.
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This study investigates the syntactic differences between texts authored by native (NES) and non-native English-speaking (NNES) professional architects on ArchDaily, the world's most visited architecture website. We focused on established indices of syntactic complexity hypothesized to differentiate between first-language (L1) and second-language (L2) writing. The corpus consisted of randomly selected texts on residential architecture by Iranian and British architects. Data analysis was conducted using Coh-Metrix Core Desktop Beta (2023), with results processed in SPSS. Preliminary MANOVA analysis revealed significant differences in the mean scores of the two groups, and follow-up analyses indicated that syntactic complexity indices, including left-embeddedness, minimal edit distance for words, and the number of modifiers per noun phrase, exhibited medium to large effect sizes in distinguishing the texts. Additionally, among the syntactic density indices, agentless passive voice, negation, gerund, and noun phrase density were most effective in differentiating native from non-native compositions. The findings revealed that while both NES and NNES architects demonstrate sophisticated writing skills, they exhibit distinct patterns of syntactic complexity in their professional discourse. NES architects tend towards richer modification and a more cohesive flow, while NNES architects lean towards longer, denser sentences. These differences, influenced by both linguistic proficiency and discourse-specific conventions, highlight the need for continued attention to clarity and readability in architectural communication and underscore the importance of considering both linguistic proficiency and discourse-semantic motivations when analyzing syntactic complexity in professional writing.
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This study employed a concurrent triangulation mixed-methods design to examine the impact of backward design (BD), central design (CD), and forward design (FD) on the speaking proficiency and engagement of 75 intermediate-level Iranian EFL learners, aged 18–21, selected through convenience sampling at Arak University, Iran. Participants attended nine weekly 105-minute sessions over one semester, with intermediate proficiency verified by the Oxford Quick Placement Test. Pre-tests established baseline speaking abilities, and participants were divided into three groups of 25: BD group (BDG), CD group (CDG), and FD group (FDG). Data were gathered using IELTS speaking pre- and post-tests, a student engagement scale (SES), and semi-structured interviews. The BDG focused on defining learning outcomes and using assessments such as observations and recorded speeches to track progress and adjust instruction. The FDG prioritized structured activities targeting specific speaking skills, using formative and summative assessments to evaluate mastery. The CDG adopted a learner-centric approach, incorporating personas, scenarios, and open educational resources to create collaborative, engaging activities emphasizing social context and emotional growth. Post-intervention results revealed CD as the most effective in enhancing speaking proficiency and engagement, followed by BD, with FD being the least effective. These findings underscore CD’s strength in fostering interactive, meaningful learning experiences for Iranian EFL learners. The study suggests that curriculum developers and educators should prioritize learner-centered approaches, such as CD, to improve EFL speaking outcomes and engagement.
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The widespread integration of technology into education has led to significant reliance on online assessment. Despite its prevalence, concerns about the fairness of online assessment persist. While this issue has attracted considerable attention, empirical investigations, particularly those exploring teachers' perceptions of fairness in online assessment, remain scarce. Additionally, existing frameworks for assessing fairness in an online context seem inadequate. To address these concerns, the current study investigated Iranian English as a Foreign Language (EFL) teachers' perceptions of fairness in online assessment. Moreover, the study aimed to develop a valid scale to measure the fairness of assessment practices in the online context. Employing a mixed-methods approach, the study conducted a structured interview with 20 EFL teachers, and the resulting data were transcribed and analyzed qualitatively. Ten major codes or themes derived from the data were access, knowledge, personal factors, clear criteria, item quality, safety, policies, teaching quality, assessment type, and administration. The codes were subsequently classified into three overarching categories: student level, teacher level, and organizational level. Then, based on the interview findings and the existing literature, an online assessment fairness questionnaire was developed and administered to a sample of 100 EFL teachers, whose results verified five core factors of online assessment fairness. The study's findings offer a novel understanding of teachers' perspectives on the fairness of online assessment and the factors that contribute to its fairness or unfairness.
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Although several studies have examined the effectiveness of Artificial Intelligence (AI) tools in enhancing L2 speaking , it remains unclear whether learners with low and high levels of anxiety benefit similarly from AI-based instruction. The present study examined the extent to which learners with varying levels of anxiety, specifically high and low, benefit from an AI-based speaking assistant, Character AI. This r esearch involved 30 intermediate EFL learners from a language institute, who were identified and labeled as high -anxiety (HA) and low-anxiety (LA) groups based on their anxiety scores. Following a sequential explanatory mixed-methods design, the initial phase involved administering the Oxford Placement Test (OPT) to determine participants' language proficiency, followed by a pre-test that served as a benchmark of their speaking proficiency before exposure to the Character AI app. Over the course of the study, participants engaged with Character AI for speaking practice and feedback. The results showed that Character AI-based support was beneficial for promoting FL speaking by fostering enhanced interaction and oral communication. It was also observed that learners with lower initial anxiety levels demonstrated greater improvements in speaking, implying that anxiety may moderate the benefits of AI-driven educational technologies. The qualitative findings underscore the potential of AI technologies as robust tools in L2 speaking, facilitating personalized, interactive, and learner-centric learning experiences. The present outcomes provide substantial insights into the interactions between psychological factors, technological integration, and language acquisition within the English as a Foreign Language (EFL) framework.
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Critical Incidents (CIs) have become central to language teacher development by promoting reflective practice, a key element of teacher education. This study examines critical incidents (CIs) in English as a Foreign Language (EFL) classes in public high schools. Researchers conducted semi-structured interviews with 10 teachers and 15 students across 7 public schools, analyzing narratives using thematic analysis within a complexity theory framework. Three themes emerged: Teaching high and lows, classroom management issues, and language proficiency. Teachers felt challenged by the frequent number of CIs, associating their management skills and immunity with their response to these events, and viewed Iranian public schools as particularly susceptible. Similarly, students highlighted both the negative and positive aspects of CIs and noted cultural diversity and language skills as key factors. The study's findings align with complexity theory by highlighting the dynamic, interconnected, and adaptive nature of teaching and learning in public schools. The emergent patterns of emotional responses, classroom management strategies, and language proficiency interactions reflect the principles of sensitivity to initial conditions, self-organization, and co-evolution.
