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An English-language Multimedia Teaching Model Based on Krashen\u2019s Theory ARTICLE

, Hohai University

iJET Volume 13, Number 8, ISSN 1863-0383 Publisher: International Association of Online Engineering, Kassel, Germany


Traditional English teaching practice often centers on the teacher and implements the teaching mode of \u201cexemplifying by the teacher-answering by students-evaluating by the teacher\u201d. This inflexible teaching mode fails to fully exert student\u2019s subjective function; at the same time, due to the lack of necessary guidance and help from teachers, students are more likely to suffer from learning burnout and low self-confidence. With this regard, an English multimedia teaching mode was proposed in this study based on Krashen\u2019s \u201cLanguage Input Theory\u201d. The theory is characterized by emphasizing the analysis of English language learning from the perspectives of \u201cacquisition\u201d and \u201clearning\u201d, advocating \u201cunderstanding\u201d of knowledge and using student-centered teaching methods. In this study, Krashen\u2019s theory was combined with interactive learning methods and multimedia information technology to form an English teaching mode focused on \u201cteacher-student\u201d, \u201cstudent-student\u201d and \u201cstudent-computer\u201d interactions and build an \u201cin class- after class\u201d and \u201conline-offline\u201d English learning environment. This mode was practically applied in the teaching of \u201cCollege English\u201d at Hohai University in Jiangsu Province, China. The results show that the English multimedia teaching mode based on Krashen\u2019s theory is more effective than the traditional teaching mode in improving students\u2019 interest and self-confidence in learning.


Yuan, F. (2018). An English-language Multimedia Teaching Model Based on Krashen\u2019s Theory. International Journal of Emerging Technologies in Learning (iJET), 13(8), 198-209. Kassel, Germany: International Association of Online Engineering. Retrieved September 18, 2018 from .