Nursing students' attitude and perception toward machine translation for learning English medical terminologies

Norah Banafi ()

International Journal of Education and Practice, 2023, vol. 11, issue 4, 739-748

Abstract: Nursing students must learn English medical terminologies since they must read and follow them to deliver patient care. Arab students highly use machine translation (MT) to understand those terminologies. Therefore, this study aimed to reveal the attitude and perception towards MT for learning English medical terminologies among undergraduate nursing students in Saudi Arabia. This study used an exploratory study design and comprised all final-year nursing students of the undergraduate nursing program in Abha (n=80) and Muhayil (n=80) female campuses of King Khalid University (KKU), Saudi Arabia. Those students (N=160) were administered a self-structured online questionnaire, and 132 responded to the questionnaire. More than 95% agreed that MT tools were easy to use, fast, and saved time. Though, 81.1% required more training in using MT tools. Furthermore, 97.7% perceived that MT helped them learn English medical terminologies. More than 90% reported that MT helped them understand and memorize English medical terminologies. Most nursing students stated that MT boosted their confidence (94.7%) and improved the quality of learning (96.2%) concerning English medical terminologies. Nursing students of KKU presented a positive attitude and perception toward MT for learning English medical terminologies. Saudi nursing schools should provide adequate training in using MT tools to enhance their students' learning of English medical terminologies, which would help them in clinical practice.

Keywords: Attitude; English medical terminologies; Machine translation; Nursing students; Saudi Arabia. (search for similar items in EconPapers)
Date: 2023
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