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Intelligent Platform for Educational Resources of Computer Basic Courses in the Digital Education Environment

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DOI: 10.23977/acss.2023.071002 | Downloads: 12 | Views: 444

Author(s)

Weibin Wang 1

Affiliation(s)

1 School of Information Engineering, Xi'an Fanyi University, Xi'an, Shaanxi, China

Corresponding Author

Weibin Wang

ABSTRACT

Computer science is a highly practical professional foundation course, and its teaching purpose is to equip students with basic computer application skills and prepare them for future work. Due to the lack of clear goals in current computer foundation courses, teachers mainly adopt an "indoctrination" teaching method that only emphasizes theory and not practice, resulting in students becoming accustomed to "contact based" learning without applying theory to practice. Therefore, it is necessary to choose a scientific and reasonable teaching strategy based on the specific purpose of computer teaching and students' actual mastery, so that students can proficiently master and apply this knowledge in practice. On this basis, this article first described the main problems in the teaching of computer basic courses and the impact of digital learning environment on contemporary education models, thereby highlighting the necessity of building a computer basic course resource platform. After that, this article discussed a cloud service platform for computer basic course education resources. Finally, through experimental analysis and survey questionnaires, it was proven that the response time of the designed system was shorter than that of traditional systems; the accuracy of the system was superior to traditional systems, and 66.23% of respondents were satisfied with the system.

KEYWORDS

Computer Foundation Course, Intelligent Platform for Educational Resources, Digital Education Environment, Cloud Service Resources

CITE THIS PAPER

Weibin Wang, Intelligent Platform for Educational Resources of Computer Basic Courses in the Digital Education Environment. Advances in Computer, Signals and Systems (2023) Vol. 7: 10-17. DOI: http://dx.doi.org/10.23977/acss.2023.071002.

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