research-article

ViVo: Video-Augmented Dictionary for Vocabulary Learning

Authors:

Yuanchun ShiAuthors Info & Claims

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

Pages 5568 - 5579

https://doi.org/10.1145/3025453.3025779

Published: 02 May 2017 Publication History

Abstract

Research on Computer-Assisted Language Learning (CALL) has shown that the use of multimedia materials such as images and videos can facilitate interpretation and memorization of new words and phrases by providing richer cues than text alone. We present ViVo, a novel video-augmented dictionary that provides an inexpensive, convenient, and scalable way to exploit huge online video resources for vocabulary learning. ViVo automatically generates short video clips from existing movies with the target word highlighted in the subtitles. In particular, we apply a word sense disambiguation algorithm to identify the appropriate movie scenes with adequate contextual information for learning. We analyze the challenges and feasibility of this approach and describe our interaction design. A user study showed that learners were able to retain nearly 30% more new words with ViVo than with a standard bilingual dictionary days after learning. They preferred our video-augmented dictionary for its benefits in memorization and enjoyable learning experience.

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References

[1]

Akinnaso, F. N. On the differences between spoken and written language. Language and speech 25, 2 (1982), 97--125.

[2]

Amemiya, S., Hasegawa, K., Kaneko, K., Miyakoda, H., and Tsukahara, W. Long-term memory of foreign-word learning by short movies for ipods. In Advanced Learning Technologies, 2007. ICALT 2007. Seventh IEEE International Conference on, IEEE (2007), 561--563.

[3]

Bhingardive, S., Singh, D., V, R., Redkar, H., and Bhattacharyya, P. Unsupervised most frequent sense detection using word embeddings. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, ACL (2015), 1238--1243.

[4]

Cai, C. J., Guo, P. J., Glass, J. R., and Miller, R. C. Wait-learning: Leveraging wait time for second language education. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI '15, ACM (2015), 3701--3710.

Digital Library

[5]

Dang, T.-D., Chen, G.-D., Dang, G., Li, L.-Y., et al. Rolo: A dictionary interface that minimizes extraneous cognitive load of lookup and supports incidental and incremental learning of vocabulary. Computers & Education 61 (2013), 251--260.

Digital Library

[6]

Dearman, D., and Truong, K. Evaluating the implicit acquisition of second language vocabulary using a live wallpaper. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2012), 1391--1400.

Digital Library

[7]

DeVito, J. A. Levels of abstraction in spoken and written language. Journal of Communication 17, 4 (1967), 354--361.

[8]

Ebbinghaus, H. Memory: A contribution to experimental psychology. No. 3. University Microfilms, 1913.

[9]

Edge, D., Cheng, K.-Y., and Whitney, M. Spatialease: Learning language through body motion. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '13, ACM (2013), 469--472.

Digital Library

[10]

Edge, D., Searle, E., Chiu, K., Zhao, J., and Landay, J. A. Micromandarin: Mobile language learning in context. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '11, ACM (2011), 3169--3178.

Digital Library

[11]

Fast, E., Chen, B., and Bernstein, M. S. Empath: Understanding topic signals in large-scale text. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, ACM (2016), 4647--4657.

Digital Library

[12]

Han, C.-H., Yang, C.-L., and Wang, H.-C. Supporting second language reading with picture note-taking. In CHI '14 Extended Abstracts on Human Factors in Computing Systems, CHI EA '14, ACM (2014), 2245--2250.

Digital Library

[13]

Harris, Z. S. Distributional structure. Word 10, 2--3 (1954), 146--162.

[14]

Kayama, T., Kaneko, K., Miyakoda, H., and Ishikawa, M. Effective materials for abstract words in foreign vocabulary learning. In Wireless, Mobile and Ubiquitous Technologies in Education (WMUTE), 2010 6th IEEE International Conference on, IEEE (2010), 207--209.

Digital Library

[15]

Kovacs, G., and Miller, R. C. Smart subtitles for vocabulary learning. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '14, ACM (2014), 853--862.

Digital Library

[16]

Lesk, M. Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. In Proceedings of the 5th annual international conference on Systems documentation, ACM (1986), 24--26.

Digital Library

[17]

Manning, C. D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S. J., and McClosky, D. The Stanford CoreNLP natural language processing toolkit. In Association for Computational Linguistics (ACL) System Demonstrations (2014), 55--60.

[18]

Matthiesen, S. J. Essential Words for the TOEFL. Barron's Educational Series, 2014.

[19]

Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., and Dean, J. Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems (2013), 3111--3119.

Digital Library

[20]

Miyakoda, H., Kaneko, K.-i., and Ishikawa, M. Effective learning material for mobile devices. JLCL 26, 1 (2011), 39--51.

[21]

Paivio, A. Dual coding theory: Retrospect and current status. Canadian Journal of Psychology/Revue canadienne de psychologie 45, 3 (1991), 255.

[22]

Raine, P. Incidental learning of vocabulary through authentic subtitled videos. JALT-The Japan Association for Language Teaching (2012).

[23]

Sakunkoo, N., and Sakunkoo, P. Gli?ix: Using movie subtitles for language learning. In UIST 2013 Adjunct, ACM (2013).

[24]

Savva, M., Chang, A. X., Manning, C. D., and Hanrahan, P. Transphoner: Automated mnemonic keyword generation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '14, ACM (2014), 3725--3734.

Digital Library

[25]

Secules, T., Herron, C., and Tomasello, M. The effect of video context on foreign language learning. The Modern Language Journal 76, 4 (1992), 480--490.

[26]

Takigiku, Y., Kaneko, K., Ishikawa, M., and Miyakoda, H. Short movie materials based on tessellation for foreign vocabulary learning. In Information Technology Based Higher Education and Training (ITHET), 2010 9th International Conference on, IEEE (2010), 284--291.

Digital Library

[27]

Toutanova, K., Klein, D., Manning, C. D., and Singer, Y. Feature-rich part-of-speech tagging with a cyclic dependency network. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology-Volume 1, Association for Computational Linguistics (2003), 173--180.

Digital Library

[28]

Xu, B., Gao, G., Fussell, S. R., and Cosley, D. Improving machine translation by showing two outputs. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2014), 3743--3746.

Digital Library

[29]

Yeh, Y., and Wang, C.-w. Effects of multimedia vocabulary annotations and learning styles on vocabulary learning. Calico Journal (2003), 131--144.

[30]

Yu, M. New Oriental GRE Vocabulary Selection. Qunyan Press, 2005.

[31]

Zhou, J., Dai, X., and Wang, P. Foreign language learning based on video scenes. In Education Technology and Computer (ICETC), 2010 2nd International Conference on, vol. 2, IEEE (2010), V2--350.

Cited By

Fukushima SSakamoto KNakamura Y(2024)NariTan: Enhancing Second Language Vocabulary Learning Through Non-Human Avatar Embodiment in Immersive Virtual RealityMultimodal Technologies and Interaction10.3390/mti81000938:10(93)Online publication date: 18-Oct-2024
https://doi.org/10.3390/mti8100093
Chen QLiu SHuang KWang XMa XZhu JPeng Z(2024)RetAssist: Facilitating Vocabulary Learners with Generative Images in Story Retelling PracticesProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661581(2019-2036)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661581
Draxler FHaller LSchmidt AChuang L(2022)Auto-Generating Multimedia Language Learning Material for Children with Off-the-Shelf AIProceedings of Mensch und Computer 202210.1145/3543758.3543777(96-105)Online publication date: 4-Sep-2022
https://dl.acm.org/doi/10.1145/3543758.3543777
Show More Cited By

Index Terms

ViVo: Video-Augmented Dictionary for Vocabulary Learning
1. Human-centered computing
  1. Human computer interaction (HCI)

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cover image ACM Conferences

CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

May 2017

7138 pages

ISBN:9781450346559

DOI:10.1145/3025453

General Chairs:
Gloria Mark
University of California Irvine
,
Susan Fussell
Cornell University
,
Program Chairs:
Cliff Lampe
University of Michigan
,
m.c. schraefel
University of Southampton
,
Juan Pablo Hourcade
University of Iowa
,
Caroline Appert
Université Paris-Sud
,
Daniel Wigdor
University of Toronto

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Published: 02 May 2017

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Tsinghua University Research Funding
National Key Research and Development Plan
NExT Search Centre by the Singapore National Research Foundation
Natural Science Foundation of China

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CHI '17

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CHI '17: CHI Conference on Human Factors in Computing Systems

May 6 - 11, 2017

Colorado, Denver, USA

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CHI '17 Paper Acceptance Rate 600 of 2,400 submissions, 25%;

Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Fukushima SSakamoto KNakamura Y(2024)NariTan: Enhancing Second Language Vocabulary Learning Through Non-Human Avatar Embodiment in Immersive Virtual RealityMultimodal Technologies and Interaction10.3390/mti81000938:10(93)Online publication date: 18-Oct-2024
https://doi.org/10.3390/mti8100093
Chen QLiu SHuang KWang XMa XZhu JPeng Z(2024)RetAssist: Facilitating Vocabulary Learners with Generative Images in Story Retelling PracticesProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661581(2019-2036)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661581
Draxler FHaller LSchmidt AChuang L(2022)Auto-Generating Multimedia Language Learning Material for Children with Off-the-Shelf AIProceedings of Mensch und Computer 202210.1145/3543758.3543777(96-105)Online publication date: 4-Sep-2022
https://dl.acm.org/doi/10.1145/3543758.3543777
Fukushima S(2019)EmoTan: enhanced flashcards for second language vocabulary learning with emotional binaural narrationResearch and Practice in Technology Enhanced Learning10.1186/s41039-019-0109-014:1Online publication date: 8-Nov-2019
https://doi.org/10.1186/s41039-019-0109-0

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