Predicaments and Countermeasures of Multimodal Application for English Teaching in Higher Vocational Colleges

Yayun XI, Qian WANG

Abstract


In the intelligent learning era, multimodal data is an important carrier to accurately depict learners learning situations. Studying the teaching of multimodal learning analytics is helpful to restore original teaching process, reveal teaching rules, and help learners grow. This paper reviews the current situation of multimodal learning analytics at home and abroad, and points out that multimodal application for English teaching in higher vocational colleges currently faces difficulties such as the weighting and proportion of multiple data sources, the protection of ethical privacy, and the acquisition of platform data. With the learners needs based on a questionnaire survey, the research believes that a multi-modal and data-driven English teaching system should be built, a reasonable learning ability evaluation system should be created, and the characteristics of the development of English teaching in higher vocational education should also be integrated, so as to promote the empowerment of education big data technology, and high-quality development of intelligent education project and higher vocational education.


Keywords


Multimodal data; Multimodal learning analytics; Intelligent education; Higher vocational education; English teaching

Full Text:

PDF

References


Johns, T. (1991). Should you be persuaded: Two samples of data driven learning materials. In T. Johns & P. King (Eds.), Classroom Concordancing (pp. 2). Birmingham: ELR.

Kress, G., & Van Leeuwen, T. (1996). Reading images: The grammar of visual design. London: Routledge.

Ma, Y. F., Yue, T. Y., & Di, X. (2020). The reform of classroom teaching in vocational education: A study of deep learning supported by multimodal data. Communication of Vocational Education, 2020(12), 17-25.

Peng, H. C., & Jiang, Y. Q. (2022). Multimodal data-enhanced research in education sciences: Development trajectory and challenges. Chinese Journal of Distance Education, 2022(09), 19-26;33;78.

Scherer, S., Worsley, M., & Morency, L. P. (2012). 1st International Workshop on multimodal learning analytics: Extended abstract. In Proceedings of the 14th ACM international conference on multimodal interaction (pp. 353-356). New York: ACM.

Wang, Q. (2021). Exploring the teaching reform of higher vocational education based on the cognitive characteristics of higher vocational students. Xue Zhou Kan Magazine, 2021(27), 3-4.

Wang, Y. Y., & Zheng, Y. H. (2022). Multimodal data fusion: The core driving force to solve the key problems of intelligent education. Modern Distance Education Research, 34(02), 93-102.

Zhang, Z. H., He, M., & Han, Z. (2014). Construction and application of College English Multimodal-Corpus. Shandong Foreign Language Teaching, 35(03), 50-55.




DOI: http://dx.doi.org/10.3968/13459

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Canadian Social Science

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Reminder

  • How to do online submission to another Journal?
  • If you have already registered in Journal A, then how can you submit another article to Journal B? It takes two steps to make it happen:

1. Register yourself in Journal B as an Author

  • Find the journal you want to submit to in CATEGORIES, click on “VIEW JOURNAL”, “Online Submissions”, “GO TO LOGIN” and “Edit My Profile”. Check “Author” on the “Edit Profile” page, then “Save”.

2. Submission

Online Submissionhttp://cscanada.org/index.php/css/submission/wizard

  • Go to “User Home”, and click on “Author” under the name of Journal B. You may start a New Submission by clicking on “CLICK HERE”.
  • We only use four mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases: [email protected]; [email protected]; [email protected]; [email protected]

 Articles published in Canadian Social Science are licensed under Creative Commons Attribution 4.0 (CC-BY).

 

Canadian Social Science Editorial Office

Address: 1020 Bouvier Street, Suite 400, Quebec City, Quebec, G2K 0K9, Canada.
Telephone: 1-514-558 6138 
Website: Http://www.cscanada.net; Http://www.cscanada.org 
E-mail:[email protected]; [email protected]

Copyright © Canadian Academy of Oriental and Occidental Culture