Experience of using ICT Tools for Monitoring the Psychological Component of the Quality of Teacher's Activity of the Higher Education Institutions

Bondarchuk, Olena; Balakhtar, Valentyna; Balakhtar, Kateryna S.; Kyrichuk, Valeriy O.; Yakubovska, Nataliia O.; Ostapov, Serhii E.; Grubi, Tamara

doi:10.5220/0010924700003364

Cited by 2 publications

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“…On the other hand, in the 1990s, the expansion of college enrollment raised concerns about the declining quality of college students. It can be said that it is an important subject that restricts the quality of personnel training in higher education [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Higher Education Course Evaluation Based on Deep Learning Model

Zheng

2022

Wireless Communications and Mobile Computing

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Higher education has completed a revolutionary transition stage from traditional elite education to mass quality education, and the improvement of higher education quality has increasingly become the focus of social attention. Courses are the most basic unit of university teaching, and the quality of courses directly affects the quality of personnel training. The expansion of higher education has resulted in insufficient teaching resources and a decline in the quality of courses. Improving quality is the eternal theme of higher education reform. How to formulate scientific curriculum quality standards and objectively evaluate curriculum quality is the most concerned issue of the society. Therefore, in-depth analysis of the factors that affect the quality of the curriculum and the establishment of the curriculum quality evaluation system and method has certain practical significance for improving the quality of the curriculum. This work combines the evaluation of higher education courses with deep learning models and proposes a network MSACNN for quality evaluation of higher education courses. This work proposes to use an attention-based multiscale network to explicitly learn the relationship between the qualities of various higher education courses. By using parallel networks with different convolution kernels, it combines different scale features at the same spatial location to better learn the relationship between the quality features of higher education courses. This work conducts sufficient experiments on the higher education curriculum quality dataset, and the experimental results demonstrate that the multiscale network based on the attention mechanism exhibits superior performance. MSACNN surpasses other machine learning methods in both precision and recall metrics.

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Section: Introductionmentioning

confidence: 99%

Higher Education Course Evaluation Based on Deep Learning Model

Zheng

2022

Wireless Communications and Mobile Computing

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show abstract

“…The article highlighted the results of empirical research of value, cognitive and behavioural components and individual-psychological and organizational-professional factors of creativity of foreign language teachers. According to the results of ANOVA, there were established statistically significant differences in the manifestations of creativity of foreign language teachers depending on their gender, age and organizational and professional The focus of the article "Experience of using ICT tools for monitoring the psychological component of the quality of teacher's activity of the higher education institutions" [32] by Olena I. Bondarchuk (figure 83), Valentyna V. Balakhtar, Kateryna S. Balakhtar, Valeriy O. Kyrichuk, Nataliia O. Yakubovska, Serhii E. Ostapov and Tamara V. Grubi is on the quality of education as a multifaceted category, and the monitoring of the quality of education -as a purposeful and specially organized system of studying, assessment, analysis of data on the state of education of students. Emphasis is on the psychological component of monitoring the quality of education, which involves creating a positive socio-psychological atmosphere for participants in the educational process, both students and teachers.…”

Section: Session C: Psychological Safety In the Digital Educational E...mentioning

confidence: 99%