An Empirical Study On Constructing The Demand System Of Digital Teaching Content Resources For Science Classes And The Factors Influencing Satisfaction With Use

In 2017,the Science Curriculum Standard for compulsory Education Primary Schools was released,and the science curriculum aimed at the cultivation of scientific literacy was promoted as the basic curriculum.However,science teaching is faced with some problems,such as weak teachers,poor foundation of professional ability,unable to develop effectively and so on.From the perspective of the development trend of informationization,digitization and visualization of school education,the author thinks that equipping the school classroom with the tool of "digital teaching content resources for science classes" can obviously alleviate the above problems in science teaching.This study attempts to focus on "the construction of the content demand system of digital teaching content resources in science courses and the research on the Factors influencing Satisfaction with their use".The purpose is to fit in with the current reform of science courses.Based on the perspective of front-line science teachers and students,this research focuses on the induction,experimental design and pilot of the potential demand of science digital teaching content resources.The classical KANO model is used to investigate and qualitatively analyze the demand structure of digital teaching content resources of science teachers and students.Our study also tries to analyze,summary and explain the differences of demand structure between teachers and students.Secondly,on the basis of the qualitative demand system structure of science digital teaching content resources,taking teachers as the key object,using KANO model and ACSI satisfaction theory model to construct the hypothesis,this study attempts to test and verify the influence mechanism of glamorous content resource type,expected content resource type and necessary content resource type on teachers' usage satisfaction.At the same time,it further verifies the rationality and reliability of the above qualitative content resource requirement architecture.Thirdly,taking ACSI model and TAM model as the theoretical hypothesis model,based on theoretical analysis and practical cognition,we extract the external factors that affect teachers' satisfaction with the use of science digital teaching content resources and construct external variables.Through the construction of structural equation model,we test and confirm the significance of the relevant factors of teachers' satisfaction with the use of science digital teaching content resources.Finally,based on the results of the empirical research on the demand structure of science digital teaching content resources and teachers' use satisfaction,the research provides countermeasures and suggestions for the development and application of science digital teaching content resources at the practical level.This study mainly uses the KANO questionnaire tool survey method and structural equation model(SEM)method,as well as the combination of in-depth interview method and participatory observation method to carry out the subject research.In the research of similar topics,the research has remarkable practical characteristics.Through the joint application of KANO model and SEM method,the effective unity of qualitative and quantitative research is realized.It not only discovers and puts forward the demand structure of science course digital teaching content resources,but also verifies the rationality and reliability of the demand structure of science course digital teaching content resources.And our study also puts forward the hypothesis and verifies the key factors that affect the satisfaction of the practical application of science digital teaching content resources.The research and conclusion of this topic has a certain theoretical guiding significance and high practical significance in promoting the development of the construction and application of national science digital teaching content resources and promoting the optimization and upgrading of scientific quality education.