Summer PD with CERCLL: ML in Language Classroom

Translating Empathy: A Reflection on Machine Translation and Meaning-Making in the Language Classroom

Recently, I watched a compelling webinar hosted by CERCLL (Center for Educational Resources in Culture, Language and Literacy), titled “Translating Google Translate: Instructional Strategies for Machine Translation in the Language Classroom” by Emily Hellmich and Kimberly Vinall. The session explored how students actually use machine translation (MT) tools like Google Translate while completing writing tasks—and what implications this has for us as educators.

Rather than dismissing MT outright, the presenters advocate for a pedagogical stance that is both realistic and reflective, one that trains students to use these tools critically. Their research, based on screen recordings and retrospective interviews with learners of French, Spanish, and Mandarin, shows that students already rely on MT—but often in unexamined ways.

This reminded me of the importance of metalinguistic and emotional nuance, particularly in languages like Korean, where register, tone, and cultural subtext carry so much weight.

✍️ My Mini Experiment: Translating Empathy

Inspired by the webinar, I decided to conduct my own small experiment. I took a sentence I had written in English and ran it through Google Translate and Papago, then examined how each rendered the emotional tone.

Original sentence (English):

I can’t help but feel for people who love research and need to present to build their skills. To me, that is one of the main purposes of chapter presentations.

πŸ§ͺ Google Translate version:

연ꡬλ₯Ό μ’‹μ•„ν•˜κ³  μžμ‹ μ˜ κΈ°μˆ μ„ μŒ“κΈ° μœ„ν•΄ ν”„λ ˆμ  ν…Œμ΄μ…˜μ„ ν•΄μ•Ό ν•˜λŠ” μ‚¬λžŒλ“€μ„ 보면 μ•ˆνƒ€κΉŒμš΄ 마음이 λ“­λ‹ˆλ‹€. μ €λŠ” 그것이 각 μž₯의 ν”„λ ˆμ  ν…Œμ΄μ…˜μ˜ μ£Όμš” λͺ©μ  쀑 ν•˜λ‚˜λΌκ³  μƒκ°ν•©λ‹ˆλ‹€.

πŸ“ Back-translation:

When I see people who love research and need to present to build their skills, I feel sorry or sympathetic. I think that is one of the main purposes of chapter presentations.

✅ This version felt accurate, with "μ•ˆνƒ€κΉŒμš΄ 마음이 λ“­λ‹ˆλ‹€" capturing a gentle, empathetic tone.

πŸ§ͺ Papago version:

μ €λŠ” 연ꡬλ₯Ό μ‚¬λž‘ν•˜κ³  μžμ‹ μ˜ κΈ°μˆ μ„ λ°œμ „μ‹œν‚€κΈ° μœ„ν•΄ λ°œν‘œν•΄μ•Ό ν•˜λŠ” μ‚¬λžŒλ“€μ„ κ·Έλ¦¬μ›Œν•˜μ§€ μ•Šμ„ 수 μ—†μŠ΅λ‹ˆλ‹€. 이것이 챕터 λ°œν‘œμ˜ μ£Όμš” λͺ©μ  쀑 ν•˜λ‚˜μž…λ‹ˆλ‹€.

πŸ“ Back-translation:

I cannot help but miss people who love research and have to present in order to improve their skills.

❌ Here, the verb κ·Έλ¦¬μ›Œν•˜λ‹€ (“to miss or long for someone”) introduced a sentimental tone that misinterpreted my intended emotion of empathetic support. A subtle, but significant mistranslation.

πŸ›  Revision for Nuance

To refine the Korean for emotional accuracy, I settled on:

연ꡬλ₯Ό μ’‹μ•„ν•˜κ³  μžμ‹ μ˜ μ—­λŸ‰μ„ ν‚€μš°κΈ° μœ„ν•΄ λ°œν‘œλ₯Ό ν•΄μ•Ό ν•˜λŠ” μ‚¬λžŒλ“€μ„ 보면 마음이 μ§ ν•©λ‹ˆλ‹€. 이런 λ°œν‘œκ°€ λ°”λ‘œ μž₯별 λ°œν‘œμ˜ μ£Όμš” λͺ©μ  쀑 ν•˜λ‚˜λΌκ³  μƒκ°ν•©λ‹ˆλ‹€.

This version uses 마음이 μ§ ν•©λ‹ˆλ‹€, a Korean expression that gently conveys a tender ache or empathy. The phrasing maintains the emotional intent of my English, while sounding natural and appropriate for Korean learners or educators.

🧭 Instructional Reflections

This small experiment helped me appreciate some of the key takeaways from the CERCLL session:

  • Machine translation is already embedded in students' workflows. Rather than prohibit it, we can design tasks that ask students to engage with MT critically and reflectively.

  • Back translation is a powerful tool. It reveals meaning shifts and encourages awareness of nuance.

  • Different tools produce different emotional readings. This opens a door to discussion about voice, register, and cultural context—valuable not just for translation, but for any multilingual writing.

  • Empathy and meaning-making go hand in hand. Whether in English or Korean, precision in tone matters—especially in education, where students often present themselves publicly as learners.

🌐 Resource Links

  • πŸ“Ί CERCLL Webinar Slides

  • πŸ“– Hellmich & Vinall (2023). Student Use and Instructor Beliefs: Machine Translation in Language Education. Language Learning & Technology, 27(1), 1–27. https://hdl.handle.net/10125/73525

  • πŸ“„ Hellmich (2021). Machine Translation in Foreign Language Writing. ALSIC, 24(1)

If you're teaching in a multilingual classroom or navigating the push-pull of MT tools in student writing, I recommend watching the webinar—and trying a small translation experiment of your own. You may be surprised at what you uncover.

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