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Analysis on the Quality of Distance and Digital Learning Service (DDLS) Based on Bibliometrics

Published: 15 December 2023 Publication History

Abstract

Quality is the core pursuit of distance and digital learning (DDLS). DDLS is usually more difficult to monitor and ensure its quality than on-site learning services, for its feature of “Separation of time and space”. In this paper, the public portal of the Ministry of Education, and State Administration of Market Supervision of China, the official website of the China Consumers Association, and some well-known complaint platforms and head social platforms have been selected as the typical data sources of public and private sectors, quality problems of DDLS extracted from the mentioned channels are analyzed and compared. The results show that the DDLS quality problems are mainly manifested in three aspects: (1) DDLS resources; (2) DDLS process; (3) DDLS effectiveness. Qualification & quality, and cost problem are the focuses that learners are most concerned about among them.

References

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  1. Analysis on the Quality of Distance and Digital Learning Service (DDLS) Based on Bibliometrics

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    ICEME '23: Proceedings of the 2023 14th International Conference on E-business, Management and Economics
    July 2023
    507 pages
    ISBN:9798400708022
    DOI:10.1145/3616712
    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 the author(s) 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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    Publication History

    Published: 15 December 2023

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    Author Tags

    1. digital learning
    2. distance learning
    3. quality analysis

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