College Translation Teaching in the Era of Artificial Intelligence: Challenges and Solutions

Abstract

AI-powered translation technology has greatly improved machine translation quality, posing three major challenges to college translation teaching: students’ perceived anxiety towards translation learning, their dependency on MT technology to complete translation tasks, and traditional teaching assessment methods being rendered ineffective. In response to these challenges, this article proposes that translation instructors pass on to students knowledge concerning MT to reduce their anxiety and turn stress into motivation and help them develop scientifically sound strategies for the use of MT technology to further reduce their anxiety while mitigating their excessive dependency on it. Furthermore, classroom teaching should be reformed by introducing “flipped learning” to ensure that these strategies are implemented under the supervision and guidance of the instructors. The teaching assessment should also be changed to regulate students’ use of the strategies outside the classroom, while at the same time eliminating the adverse effects brought about by MT technology on teaching assessment.