Search

Due to the increasingly serious problems of environmental pollution and resource waste, promoting the green and low-carbon transformation of education has become a new trend. Online foreign language education is a new mode of green transformation development relying on digital technology. Based on the new background of green technology, this paper focuses on the evaluation of online foreign language teaching satisfaction and the key influencing factors. The entropy weight method was used to construct the evaluation index of online foreign language teaching satisfaction, the multiple linear regression model and confirmatory factor analysis model were used to systematically analyze the main factors affecting the satisfaction, and the questionnaire was used to investigate the data of online foreign language courses such as American Literature, American Culture, College English, Comprehensive English, and History of Foreign Literature. The results show that: (1) college students have a high degree of satisfaction with online foreign language teaching, and the satisfaction index based on entropy weight method is above level 2. (2) Through the multiple linear regression model, the four dimensions of teaching involvement, teaching communication, teaching skills and teaching effect all have a significant impact on the satisfaction of online foreign language teaching. (3) Based on the confirmatory factor model, online foreign language teaching satisfaction is affected by multiple latent and explicit variables, and the effect direction is generally positive. Finally, the paper puts forward specific strategies to improve the effect of green and low-carbon digital technology on foreign language education. [ABSTRACT FROM AUTHOR]

Under the background of environmental pollution and energy depletion, online teaching is the key means to reduce the waste of resources and achieve the sustainable goal of education. This paper constructs a fuzzy comprehensive evaluation model to scientifically estimate the satisfaction of online teaching mode and introduces a multiple linear regression model and structural equation model respectively to empirically analyze the factors affecting satisfaction. The results show that: (1) Online teaching in colleges and universities has achieved remarkable results, and students' satisfaction is at a good level. According to the fuzzy comprehensive evaluation method, the comprehensive satisfaction scores for the dimensions of teacher questioning, flipped classroom, platform resources, student learning, and teacher engagement are in the range [80, 90]. (2) Teaching platform resources, student discussion and online skills are the key factors of online teaching satisfaction. According to the results of multiple linear regression analysis, the factors A11, B21, and C21 are significant at the 1% level in terms of significance level, with p-values of 0.008, 0.010, and 0.004, respectively. (3) The influence paths of teaching knowledge, teaching interaction and teaching platform on teaching satisfaction are different. According to the calculation results of structural equation model, teaching knowledge and teaching interaction have a positive impact on teaching satisfaction, and the regression coefficients for both are 0.123 and 0.930, respectively, while the regression coefficient of teaching platform on teaching satisfaction is -0.168, which has a negative impact. Finally, it is necessary for universities to build a three-dimensional element of a "teacher-student platform" to continuously optimize the path of online teaching satisfaction. [ABSTRACT FROM AUTHOR]