ObjectiveFew research efforts have substantially introduced relevant studies on Chinese students’ adaptability in relation to the ineffectiveness of blended learning mode in College English. This study is guided by social cognitive theory, and related literature has been reviewed concerning adaptability. In this study, we aim to examine the involved relationships among contextual factors, self-efficacy, motivation, and adaptability to blended learning mode among non-English majored Chinese learners in the College English course.MethodsThe quantitative research method was employed in this study, and 595 respondents were eventually collected to enable the data analysis. The structural equation modeling (SEM) approach was used to analyze the data.Results(1) The non-English majored learners’ adaptability to blended learning mode in College English was at a low level with a mean value of 2.26, indicating that students still suffer difficulties from class conducted in blended learning; (2) the fit indices were at the level of good fit, and it suggested the structural model had an overall good fit to the data as shown: x2/df = 2.496, RMESA = 0.050, GFI = 0.956, AGFI = 0.936, NFI = 0.968, RFI = 0.959, IFI = 0.980, TLI = 0.975, CFI = 0.980; (3) adaptability was positively related to contextual factors, self-efficacy, and motivation (p < 0.001); (4) contextual factors exerted an indirect effect on the adaptability not only through the separate mediating role of self-efficacy and motivation, but through the chain mediating role of self-efficacy and motivation (p < 0.01).ImplicationsThis study theoretically extends previous studies on adaptability by investigating the affecting factors in the framework of social cognitive theory. More practically important is that this study sheds light on the impact mechanism of positive and enjoyable environment, self-efficacy and motivation on non-English majored learners’ adaptability to blended learning mode in English course, which would provide a vital insight for administrators and College English instructors to reconsider the role of learners’ responses in the mixed mode to improve their English achievement more effectively, as well as to enhance and promote their user experience of the offered blended learning service.

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The advancement of artificial intelligence technology is highly dependent on advancements in computer technology. The former created the technology for the latter. In the near future, we believe computer artificial intelligence technology will be further developed and better serve people. In other words, the data or note producer will edit the bridge segments with prominent contradictions in each program and broadcast them through the network with the titles that people are interested in, which has gotten a lot of attention and comments. This paper investigates a new fuzzy evaluation model by starting with the current situation. This paper investigates fuzzy algorithm-based artificial intelligence machine translation. The order of machine translation follows the trend in the figure, whereas the distribution of HEMTM machine translation is more concentrated under the HEMTM model. The average reliability ratio of the data mining algorithm is 0.97, the average reliability ratio of the decision tree algorithm is 0.84, the average reliability ratio of the machine learning algorithm is 0.71, and the average reliability ratio of the fuzzy algorithm is 1.34 when the vocabulary index is 15. The proportion of fuzzy algorithms in this paper is the highest of the four algorithms. It can be transformed into the contraction of frequency-domain coefficients in artificial intelligence machine translation using a fuzzy algorithm, greatly simplifying the operation. However, it will cause the ringing effect of fuzzy algorithm boundary in machine translation because it cannot well express the singular information of signals such as boundary. The extent of this effect is determined by the artificial intelligence machine translation breadth.

The success of blended learning depends on many factors. Among these, adaptability, though acknowledged as an important issue in blended learning, warrants further study, together with its influencing factors. This study aimed to explore non-English majored learners’ adaptability to blended learning in College English from the perspective of English teachers. Semi-structured interviews with 16 English instructors from 5 universities were conducted, and the interview transcripts were qualitatively analyzed. The results showed that the non-English majored learners were not perceived to have fully adapted themselves to the new mode of College English and their adaptability was highly affected by agentive factors and contextual factors. The findings emphasize the key role of learners’ adaptability in blended learning environments. Additionally, this study further provides a vital insight for administrators and instructors to reconsider the role of learners’ responses to the blended learning mode and apply this understanding to improve achievement in English courses.