디지털융복합연구 (Journal of Digital Convergence)

  • 제16권8호
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  • Pages.19-26
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  • 2018
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  • 2713-6434(pISSN)
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  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
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국내 대학생의 영어 듣기 및 읽기 능력 향상을 위한 챗봇 활용 연구

A Study on Chatbots for Developing Korean College Students' English Listening and Reading Skills

  • Kim, Na-Young (Department of General Education, Sehan University)
  • 투고 : 2018.05.14
  • 심사 : 2018.08.20
  • 발행 : 2018.08.28
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초록

본 연구는 챗봇의 활용이 국내 대학생의 영어 듣기 및 읽기 학습에 미치는 영향을 조사한 것으로, 실험 참가자의 영어 듣기 및 읽기 능력이 챗봇과의 채팅을 통해 실제로 상승하는지에 대한 여부를 알아보는 데 그 목적이 있다. 본 연구를 위해 총 46명의 참가자를 실험그룹과 통제그룹으로 나누어 16주 동안 실험을 진행하였으며, 실험 시작 전과 실험 종료 후 사전 사후 평가를 실시하여 챗봇 활용의 효과를 파악하였다. 본 연구의 주요 결과 및 시사점은 다음과 같다. 사전 사후 평가 결과 실험그룹과 통제그룹 모두에서 영어 듣기 및 읽기 능력이 유의미하게 상승한 것으로 나타났다. 특히 영어 듣기능력과 관련하여 실험그룹이 통제그룹보다 사후 평가에서 더 많은 상승폭을 보임으로써 듣기 능력 향상에 대한 챗봇 활용의 효과를 증명하였다. 본 연구는 4차 산업혁명 시대에 따라 영어 학습을 위한 챗봇 활용에 대한 시사점을 제시하는데 그 의의를 갖는다고 볼 수 있다.

In an effort to investigate the effects of chatbots on English listening and reading skills, 46 college students participated in the current study. Participants consisted of first-year students who enrolled in an English class at a university in South Korea. They were randomly divided into two groups: one experimental group (n=24) and one control group (n=22). During 16 weeks, the experimental group engaged in chats with a chatbot, named Elbot, while the control group did not. There were pre- and post-tests to confirm the effects of the chatbot usage. Major findings are as follows: First, participants in both groups significantly improved listening and reading skills. On the post-listening test, however, the experimental group showed more improvements. Their listening proficiency level improved from intermediate to advanced level after engaging in chat with the chatbot. Limitations and implications for theory and practice are discussed at the end.

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참고문헌

  1. J. Khan & S. Shrivastava. (2016). English language as a medium of communication in India. New Man International Journal of Multidisciplinary Studies, 3(10), 12-15.
  2. J. Jeon. (2010). Issues for English tests and assessments: A view from Korea. In Y. I. Moon, & B. Spolsky (Eds.) Language assessment in Asia: local, regional or global (pp. 55-82). Seoul: Asia TEFL.
  3. T. Y. Kim. (2009). The dynamics of L2 self and L2 learning motivation: A qualitative case study of Korean ESL students. English Teaching, 64(3), 49-70.
  4. J. Jeon & J. Paek. (2008). Developing framework to evaluate the process and performance of government English language policies. Seoul: Korean Ministry of Education, Science, and Technology.
  5. J. I. Han & N. Y. Kim. (2016). The effects of post-task CMC activities and task types on Korean EFL learners' oral performance. STEM Journal, 17(2), 109-135.
  6. S. W. Kang. (2009, April 1). Koreans ranked bottom in English proficiency test. The Korea Times.
  7. L. Fryer & R. Carpenter. (2006). Bots as language learning tools. Language Learning & Technology, 10(3), 8-14.
  8. D. Graddol. (1997). The future of English? London: British Council.
  9. N. Y. Kim. (2017). Effects of different voice-chat conditions on EFL learners' topic negotiation according to proficiency levels. Modern English Education, 18(1), 49-74. https://doi.org/10.18095/meeso.2017.18.1.03
  10. . A. Shawar & E. Atwell. (2007). Chatbots: Are they really useful? LDV Forum, 22(1), 29-49.
  11. Y. F. Wang & S. Petrina. (2013). Using learning analytics to understand the design of an intelligent language tutor? Chatbot Lucy. International Journal of Advanced Computer Science and Applications, 4(11), 124-131.
  12. Z. W. Hong, Y. M. Huang, M. Hsu & W. W. Shen. (2016). Authoring robot-assisted instructional materials for improving learning performance and motivation in EFL classrooms. Educational Technology & Society, 19(1), 337-349.
  13. C. W. Liao. (2010). TOEIC listening and reading test scale anchoring study. Princeton, NJ: Educational Testing Service.
  14. H. Shah, K. Warwick, J. Vallverdu & D. Wu. (2016). Can machines talk? Comparison of Eliza with modern dialogue systems. Computers in Human Behavior, 58, 278-295. https://doi.org/10.1016/j.chb.2016.01.004
  15. L. Floridi, M. Taddeo & M. Turilli. (2009). Turing's imitation game: Still an impossible challenge for all machines and some judges? An evaluation of the 2008 Loebner Contest. Minds and Machines, 19(1), 145-150. https://doi.org/10.1007/s11023-008-9130-6
  16. N. Y. Kim. (2016). Effects of different voice-chat conditions on Korean EFL learners' speaking ability, oral interaction, and affective factors. Unpublished doctoral dissertation, Ewha Womans University, Korea.
  17. S. Lee, H. Noh, J. Lee, K. Lee, G. Gary, S. Sagong & M. Kim. (2011). On the effectiveness of robot-assisted language learning. ReCALL, 23(1), 25-58. https://doi.org/10.1017/S0958344010000273
  18. J. R. Movellan, M. Eckhardt, M. Virnes & A. Rodriguez. (2009). Sociable robot improves toddler vocabulary skills. In M. Scheutz, F. Michaud, P. J. Hinds, & B. Scassellati (Eds.), Proceedings of the 4th ACM/IEEE Human Robot Interaction (pp. 307-308). New York: ACM.
  19. J. Johnson. (2003). Children, robotics and education. Artificial Life and Robotics, 7(1-2), 16-21. https://doi.org/10.1007/BF02480880
  20. J. Han. (2012). Emerging technologies? Robot assisted language learning. Language Learning & Technology, 16(3), 1-9.
  21. S. Papert. (1993). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books.
  22. J. Zakos & L. Capper. (2008). CLIVE - An artificially intelligent chat robot for conversational language practice. In J. Darzentas, G. Vouros, S. Vosinakis, & A. Arnellos (Eds.) Proceedings of 5th Hellenic Conference on Artificial Intelligence (pp. 437-442). Berlin: Springer.
  23. N. Y. Kim. (2018). Effect of text chat on EFL writing fluency, accuracy, and complexity by interlocutors. Foreign Languages Education, 25(1), 27-54. https://doi.org/10.15334/FLE.2018.25.1.27