Sasipa Boonyubol
ABSTRACT
In recent years, massive open online courses (MOOCs) have been rapidly growing with learners from both English and non-English speaking countries. Nowadays, many MOOC developers provide transcripts in multiple languages to attract a broader range of learners. However, providing transcripts is ineffective for visually impaired learners and tends to divert learners' attention away from the overall content of the video lecture. Thus, aside from offering English transcripts, Japanese lecture videos in the Tokyo TechIntroduction to Electrical and Electronic Engineering MOOC were automatically dubbed into English with a computer-generated voice. To understand the effect of English-automatically dubbed videos on learners, the learners' interactions, video completion rate, and course completions were compared to the original course in Japanese. The results show that English automatically dubbed videos have an overall high learner engagement when compared to Japanese videos with English transcripts. Survey results on learners' satisfaction towards the English dubbed videos also showed higher positive responses. These results show the effectiveness of dubbing Japanese lectures into English using text-to-speech technology which has signification for MOOCs offered in various languages.
Supplemental Material
- Sasipa BOONYUBOL, Do Ngoc KHANH, Toru NAGAHAMA, and Jeffrey S. CROSS. 2021. W-04 Improving International Learners' Engagement in Japanese Online Engineering Courses by Adding Automatically English Dubbed Videos. JSEE Annual Conference International Session Proceedings, Vol. 2021 (2021), 18--23. https://doi.org/10.20549/jseeen.2021.0_18Google Scholar
- Xiaoyin CHE, Sheng LUO, Haojin YANG, and Christoph MEINEL. 2017. Automatic Lecture Subtitle Generation and How It Helps. In 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT). 34--38. https://doi.org/10.1109/ICALT.2017.11Google Scholar
- Marcello FEDERICO, Robert ENYEDI, Roberto BARRA-CHICOTE, Ritwik GIRI, Umut ISIK, Arvindh KRISHNASWAMY, and Hassan SAWAF. 2020. From Speech-to-Speech Translation to Automatic Dubbing. https://doi.org/10.48550/ARXIV.2001.06785Google Scholar
- Kate S. HONE and Ghada R. El Said. 2016. Exploring the factors affecting MOOC retention: A survey study. Computers & Education, Vol. 98 (2016), 157--168. https://doi.org/10.1016/j.compedu.2016.03.016Google ScholarDigital Library
- May Kristine JONSON CARLON, Anie Day DC. ASA, Nopphon KEERATIVORANAN, TORU Nagahama, and Jeffrey S. CROSS. 2021. Topic Modeling in MOOCs: What Was to Be Discussed, What the Instructor Discussed, and What the Learners Discussed. In 2021 IEEE International Conference on Engineering, Technology Education (TALE). 849--853. https://doi.org/10.1109/TALE52509.2021.9678621Google Scholar
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Index Terms
- Comparing MOOC Learners Engagement with Japanese Videos and Text to Speech Generated English Videos
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