arXiv Open Access 2025

LingoQ: Bridging the Gap between EFL Learning and Work through AI-Generated Work-Related Quizzes

Yeonsun Yang Sang Won Lee Jean Y. Song Sangdoo Yun Young-Ho Kim
Lihat Sumber

Abstrak

Non-native English speakers performing English-related tasks at work struggle to sustain EFL learning, despite their motivation. Often, study materials are disconnected from their work context. Our formative study revealed that reviewing work-related English becomes burdensome with current systems, especially after work. Although workers rely on LLM-based assistants to address their immediate needs, these interactions may not directly contribute to their English skills. We present LingoQ, an AI-mediated system that allows workers to practice English using quizzes generated from their LLM queries during work. LingoQ leverages these on-the-fly queries using AI to generate personalized quizzes that workers can review and practice on their smartphones. We conducted a three-week deployment study with 28 EFL workers to evaluate LingoQ. Participants valued the quality-assured, work-situated quizzes and constantly engaging with the app during the study. This active engagement improved self-efficacy and led to learning gains for beginners and, potentially, for intermediate learners. Drawing on these results, we discuss design implications for leveraging workers' growing reliance on LLMs to foster proficiency and engagement while respecting work boundaries and ethics.

Topik & Kata Kunci

Penulis (5)

Y

Yeonsun Yang

S

Sang Won Lee

J

Jean Y. Song

S

Sangdoo Yun

Y

Young-Ho Kim

Format Sitasi

Yang, Y., Lee, S.W., Song, J.Y., Yun, S., Kim, Y. (2025). LingoQ: Bridging the Gap between EFL Learning and Work through AI-Generated Work-Related Quizzes. https://arxiv.org/abs/2509.17477

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2025
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓