Analysis And Research On Teaching Language Of MOOC Video Based On Knowledge Classification

With the popularization and rapid development of the Internet and information technology,the scale of MOOC continues to expand and its influence continues to rise.It is highly concerned by the government and schools.As a new type of teaching method,MOOC has a strong impact on traditional teaching,prompting teachers to change their concepts and actively participate in the wave of MOOC development.In order to ensure the quality of MOOCs,teachers need to change their inherent teaching concepts and design excellent MOOCs based on the characteristics of MOOC learning.So far,the country has launched more than 3000 national high-quality online open courses as models of MOOC course design.By analyzing the regular characteristics of these high-quality courses,it can provide the majority of MOOC teachers with certain thinking and reference,and optimize the MOOC design Improve the quality and influence of MOOC.This research is based on the theory of knowledge classification and the teacher’s language of instruction as a foothold.The teacher’s language in the MOOC video is divided into teaching spoken language and teaching screen language for research,and explores the presentation of teaching spoken language and teaching screen language in different types of knowledge.Features and laws.First of all,it sorts out and analyzes typical teaching language coding systems,transforms them according to the characteristics of MOOC videos,and builds a MOOC video teaching language coding system based on knowledge classification.On this basis,relying on the two high-quality MOOC platforms of Xuetang Online and China University MOOC,four high-quality courses are selected from the "computer" national boutique online open courses,and a suitable amount of MOOC videos are selected as research samples.The selected MOOC videos are divided into multiple segments according to the knowledge points,and the knowledge type of each knowledge point is determined as the basis for the coding of the teaching language.Then,coding and analyzing the dimensions of teaching oral language and teaching screen language are carried out on the knowledge point fragments of each type of knowledge,and the statistical characteristics of the two types of knowledge teaching videos and the characteristics of teaching language conversion are compared.The research results show that declarative knowledge accounts for a larger proportion,and the teaching time of procedural knowledge is longer;the oral teaching of declarative knowledge presents a chain structure of "instructions-telling-explaining-questioning",and the oral teaching of procedural knowledge is presented in "Narration" is the core central structure;in terms of teaching visual language,the proportion of each teaching visual language in the two types of knowledge is balanced;in the teaching visual language of declarative knowledge,the conversion of diagrams and sentences with prominent clues is frequent,and words and The conversion of relational cues is frequent;the teaching screen language of procedural knowledge is divided into two parts: diagrams and sentences.Diagrams and prominent cues are frequently converted,and sentences and words are frequently converted to relational cues.Finally,according to the analysis results,a strategy to promote the design of MOOC video instruction language is proposed from two aspects of teaching oral language and teaching image language,and strive to provide reference and reference for the optimization design of the current MOOC video instruction language.