Teaching the Culture of Quality from the Ground Up: Novice-tailored Quality Improvement for Scratch Programmers

Tilevich, Eli; Hall, Simin; Techapalokul, Peeratham

doi:10.18260/1-2--35283

Cited by 1 publication

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References 28 publications

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“…Developed countries generally regard pre-school education as an important starting point and foundation for elite training, therefore they have laid great emphasis on it, and the teaching quality of preschool education and the faculty level of developed countries are improving constantly [1][2][3][4][5][6][7]. In China, preschool education is receiving more attention than ever before, and the government has successively issued a few important documents [8][9][10][11][12] such as the Professional Standards for Kindergarten Teachers, the Opinions of the State Council on the Current Development of Preschool Education, and the Guidelines for Kindergarten Education, etc. Although these documents have provided a policy basis for the development of preschool education, in terms of teaching quality assurance system and mode, there is still much room for improvement, and there's an urgent need to build a normative teaching quality evaluation system so as to give objective and scientific evaluation to the teaching quality of preschool teachers.…”

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confidence: 99%

A Teaching Quality Evaluation Model for Preschool Teachers Based on Deep Learning

Wang

Liu

2021

Int. J. Emerg. Technol. Learn.

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Developed countries regard preschool education as an important starting point and foundation for elite training. In recent years, preschool education has also attracted a growing attention in developing countries like China. Considering the significance of the teaching quality of preschool teachers to lifelong academic achievement, this paper designs a teaching quality evaluation model for preschool teachers based on deep learning. Firstly, a progressive system with a hierarchical structure was developed for the relevant evaluation indices. Then, the fuzzy comprehensive evaluation of each index layer and evaluation criterion was determined by the principle of fuzzy relationship synthesis. Finally, an evaluation prediction model was established based on extreme gradient boosting (XGBoost) algorithm and technology services’ ResNet (TS-ResNet), and proved effective and accurate through experiments. The research results provide a reference for the application of the proposed model in other evaluation prediction scenarios.

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