Abstract
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.
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