| With the development of modern information technology, the transmission and expression of information have become a process with various modes being involved.As a result, multimodal discourse analysis (MDA) has become a common concern of scholars both at home and abroad. However, current studies mainly focus on static texts while studies on dynamic discourse are relatively scarce. Besides, most studies focus on qualitative analysis of multimodal discourse while ignoring the quantitative analysis, especially corpus based quantitative analysis.On the other hand, the development of internet has also initiated the emergence of a new phenomenon in distance education called Massive Open Learning Courses(MOOCs),which has brought great changes to higher education. The growing interest in MOOCs also provides great opportunities for language education.However, there are few studies concerning the discourse of MOOCs.In this thesis, the author takes MOOCs as a typical dynamic discourse and conducts both qualitative and quantitative analysis. Through these analyses, the author tries to answer the following questions: What features can be presented from the distribution of different semiotic modes? How do the multimodalities in MOOCs achieve the three meta-functions? What are the relations between different semiotic modes?To answer these questions,the author proposes a new model of MDA that is applicable to the analysis of MOOCs based on Systemic and functional grammar,Kress and van Leeuwen's visual grammar,Lim's and Zhang Delu's theoretical framework of MDA. Besides, the author also builds a multimodal corpus of MOOCs with MDA annotation tool-ELAN.This thesis enriches and develops the theory of multimodal discourse analysis,and is innovative in the research subject and methodology. Besides,the research results are also meaningful for the design of language MOOCs and multimodal teaching both in English MOOCs and traditional English teaching. |
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