A Research on Online Teaching Behavior of Chinese Local University Teachers Based on Cluster Analysis

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Title: A Research on Online Teaching Behavior of Chinese Local University Teachers Based on Cluster Analysis
Language: English
Authors: Liu, Bing, Luo, Xiaobing, Lu, Shui-lin
Source: International Journal of Distance Education Technologies. 2023 21(2).
Availability: IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/
Peer Reviewed: Y
Page Count: 20
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, College Faculty, Web Based Instruction, Teacher Behavior, Online Courses, Teacher Student Relationship, Academic Achievement, Educational Planning, Teacher Effectiveness, Course Evaluation, Grading
Geographic Terms: China
DOI: 10.4018/IJDET.320801
ISSN: 1539-3100
1539-3119
Abstract: COVID-19 boosted online teaching and yielded a significant amount of valuable data, yet utilizing it for education is a challenge. This study employed the K-means clustering method to analyze the online teaching behavior data of 1147 courses from a local university in East China. As a result, five types of courses with distinct teaching behaviors were identified: resource preparation (4.1%), online classroom interaction (3.6%), task evaluation (9.2%), active interaction (15.5%), and inactive interaction (67.6%). By examining the relationship between these course types and academic performance, the authors discovered no significant difference in the academic performance of students in the three course groups (i.e., resource preparation, online classroom interaction, and task evaluation) and students in the inactive interaction course group. However, there was a significant disparity in academic performance between students in active interaction courses and students in inactive interaction courses. These findings can assist teachers in planning online teaching activities more effectively and improving teaching outcomes.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1395571
Database: ERIC
FullText Text:
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  Data: A Research on Online Teaching Behavior of Chinese Local University Teachers Based on Cluster Analysis
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  Data: IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22College+Faculty%22">College Faculty</searchLink><br /><searchLink fieldCode="DE" term="%22Web+Based+Instruction%22">Web Based Instruction</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Behavior%22">Teacher Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22Online+Courses%22">Online Courses</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Student+Relationship%22">Teacher Student Relationship</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Planning%22">Educational Planning</searchLink><br /><searchLink fieldCode="DE" term="%22Teacher+Effectiveness%22">Teacher Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Course+Evaluation%22">Course Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Grading%22">Grading</searchLink>
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  Data: 10.4018/IJDET.320801
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  Data: 1539-3100<br />1539-3119
– Name: Abstract
  Label: Abstract
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  Data: COVID-19 boosted online teaching and yielded a significant amount of valuable data, yet utilizing it for education is a challenge. This study employed the K-means clustering method to analyze the online teaching behavior data of 1147 courses from a local university in East China. As a result, five types of courses with distinct teaching behaviors were identified: resource preparation (4.1%), online classroom interaction (3.6%), task evaluation (9.2%), active interaction (15.5%), and inactive interaction (67.6%). By examining the relationship between these course types and academic performance, the authors discovered no significant difference in the academic performance of students in the three course groups (i.e., resource preparation, online classroom interaction, and task evaluation) and students in the inactive interaction course group. However, there was a significant disparity in academic performance between students in active interaction courses and students in inactive interaction courses. These findings can assist teachers in planning online teaching activities more effectively and improving teaching outcomes.
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  Data: As Provided
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  Data: 2023
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  Label: Accession Number
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  Data: EJ1395571
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1395571
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        Value: 10.4018/IJDET.320801
    Languages:
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      Pagination:
        PageCount: 20
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: College Faculty
        Type: general
      – SubjectFull: Web Based Instruction
        Type: general
      – SubjectFull: Teacher Behavior
        Type: general
      – SubjectFull: Online Courses
        Type: general
      – SubjectFull: Teacher Student Relationship
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Educational Planning
        Type: general
      – SubjectFull: Teacher Effectiveness
        Type: general
      – SubjectFull: Course Evaluation
        Type: general
      – SubjectFull: Grading
        Type: general
      – SubjectFull: China
        Type: general
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      – TitleFull: A Research on Online Teaching Behavior of Chinese Local University Teachers Based on Cluster Analysis
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            NameFull: Lu, Shui-lin
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