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Exploring the New Practice of Higher Education Academic Advising Based on Educational Data Analysis Technology

Published: 18 November 2022 Publication History

Abstract

In the era of big data, the use of big data analysis technology in the educational field can change traditional and backward educational concepts and ways of thinking. Universities have more real and valuable data information in the process of development, which can provide powerful data support for educational development. At present, talent training in colleges and universities mainly aims at cultivating all-round development talents with strong professional abilities and high comprehensive quality. Therefore, higher education academic advising for the all-round development of college students is particularly important. This paper scientifically explains the meaning and current situation of higher education academic advising, and uses data analysis technology to process the educational data of a certain class of students in the School of Information and Software Engineering, University of Electronic Science and Technology of China, and designs a set of academic advising models that can be promoted in science and engineering colleges, including dynamic evaluation sub-models of professional ability, English ability, comprehensive quality, ideological quality, and physical and mental quality. Through the implementation of the models, Explore and practice the problem of higher education academic advising based on the organic combination of big data technology and education professional direction.

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ICEMT '22: Proceedings of the 6th International Conference on Education and Multimedia Technology
July 2022
482 pages
ISBN:9781450396455
DOI:10.1145/3551708
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 November 2022

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Author Tags

  1. Academic advising
  2. Data analysis technology
  3. Higher education

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