محسن محمودی دهکی

Rooted in the Cognitive Load (CL) and Dual Coding theories, this sequential explanatory study examined the CL levels experienced by 36 available Iranian pre-intermediate English as a Foreign Language (EFL) learners in auditory and visual Phonemic Awareness Tasks (PATs). The PATs focused on 'th' sound variations that were specifically challenging for Persian speakers of English. Participants were divided into two equal groups. The first group underwent auditory and visual PATs (i.e., picture sorting and word discrimination). The second group faced auditory PATs only (i.e., rhyme recognition and sound isolation) structured around voiced and voiceless ‘th’ sounds. In the qualitative phase, 8 participants were randomly interviewed to discover the potential reasons behind various levels of CL measured in certain PATs. A Virtual Reality (VR) cognitive pupillometry analysis was performed for two groups in an immersive VR environment using VR Head-Mounted Displays (VR-HMDs) and Tobii Nexus software, followed by thematic analysis. GazeMetrics strategies were employed to validate and ensure the reliability of the data collection process. The quantitative results demonstrated (a) no critical differences regarding the CL experienced by the participants in each group concerning voiced vs. voiceless’ th’ PATs and (b) higher levels of CL (increased pupil diameter, decreased blink rates, and increased gaze pattern or fixation duration) among participants in the auditory PATs group compared to the ones in the auditory and visual PATs group. Besides, qualitative findings identified the following factors as the most probable causes of the observed differences in CL levels among participants: (a) segmental differences, (b) phonological transfer, (c) phonological fossilization, (d) working memory constraints, (e) cognitive flexibility, and (f) task delivery methods. This study contributes to cognitive phonology, phonological processing, perceptual-motor language functions, and English material development.

The upheaval time of COVID-19 highlighted the importance of an effective way of teaching English to the front-line healthcare workers such as medical doctors and researchers with different digital-divide status, particularly in non-English-speaking countries because they were first-hand users of critical pandemic-related information in mostly-English articles published online by scientific journals. This study attempted to investigate the pedagogical effects of utilizing the two main User-Generated Content (UGC) platforms in E-learning, namely LMS vs. LXP, on the results of the Electronic Ministry of Health Language Examinations (E-MHLE) among Iranian English for Medical Purposes (EMP) learners across their digital-divide status (digital natives vs. digital immigrants) during the COVID-19 pandemic. A series of focus-group E-interviews were conducted to determine the reasons behind the lowest scores among the participants and to find out possible suggestions for success in high-stake E-tests. To this end, 272 EMP learners who were users of LMS and LXP were conveniently selected from a university of medical science to participate in this sequential explanatory mixed-method research. The results of descriptive and inferential statistics showed that the LXP group outperformed the LMS one in the results of E-MHLE. Moreover, the digital natives obtained higher scores than the digital immigrants in both groups but the difference was not significant in the LXP. The findings of the E-interviews were thematically analyzed and discussed. The findings of this study might offer practical and realistic benefits to the whole EMP community, particularly policymakers for the post-COVID-19 era. 

Languages as living and dynamic structured systems were influenced at the very first moments of the COVID-19 pandemic as they became medicalized by the use and practice of various jargons and technical terms. Meanwhile, homebound individuals around the world started to create a COVID-19 pandemic-related lexical-overload of neologisms (Coroneologisms or Corona coinages) in different languages which started to spread across the globe by mass media, and some of them even entered the official databases of the well-known dictionaries and Wikipedia corpora. This study was a scrutinized attempt to explore the English vs. Persian (Farsi) Coroneologisms across various Extensible Markup Language (XML) corpora and a huge body of E-resource discourses (websites, social media, and news channels and forums) based on embedded mixed-method design to provide a comprehensive insight into their types, structures, and meanings. To provide a better understanding of how and why particular Coroneologisms were created in terms of social, cultural, or political contributing factors, they were investigated based on the reflections of a series of sociolinguistic focus-group E-interviews with 184 volunteer English and Persian native speakers. This study might provide implications for sociolinguistics, corpus-based language studies, lexicographers, designers of corpora, etymologists, and discourse analysts in English and Persian.