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Student Performance Measurement on Psychometric Parameters

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Title: Student Performance Measurement on Psychometric Parameters
Language: English
Authors: Burman, Iti (ORCID 0000-0002-9598-1467), Som, Subhranil, Hossain, Syed Akhter, Sharma, Mayank
Source: International Journal of Information and Communication Technology Education. 2020 16(4):68-85.
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: 18
Publication Date: 2020
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Student Evaluation, Psychometrics, Academic Achievement, Psychological Patterns, Student Motivation, Personality Traits, Learning Strategies, Demography, Scores, Socioeconomic Background, Undergraduate Students, Construct Validity, Test Reliability, Grades (Scholastic)
DOI: 10.4018/IJICTE.2020100105
ISSN: 1550-1876
Abstract: Educational data mining provides various advantages to the education systems in many ways. It enhances the teaching process, the learning process, the scholastic performance of students, career selection, employability, and more. The differences in attitude of students' behavior lead to difference in their academic performance. The article covers the non-intellectual parameters of students to enhance their academic performance. The study tests the relationship between psychometric constructs of students and their academic correlate. The models for enhancing intellectual performance which involves various non-intellectual parameters are analyzed using structural equation modeling. It is observed that the values of the models were retrieved near to fit values. The results entail that the models will be beneficial for students in improving their academic performance by revising their psychological parameters.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1268104
Database: ERIC
FullText Text:
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  Data: Student Performance Measurement on Psychometric Parameters
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  Data: <searchLink fieldCode="AR" term="%22Burman%2C+Iti%22">Burman, Iti</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9598-1467">0000-0002-9598-1467</externalLink>)<br /><searchLink fieldCode="AR" term="%22Som%2C+Subhranil%22">Som, Subhranil</searchLink><br /><searchLink fieldCode="AR" term="%22Hossain%2C+Syed+Akhter%22">Hossain, Syed Akhter</searchLink><br /><searchLink fieldCode="AR" term="%22Sharma%2C+Mayank%22">Sharma, Mayank</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Information+and+Communication+Technology+Education%22"><i>International Journal of Information and Communication Technology Education</i></searchLink>. 2020 16(4):68-85.
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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: Y
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  Data: 18
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="DE" term="%22Student+Evaluation%22">Student Evaluation</searchLink><br /><searchLink fieldCode="DE" term="%22Psychometrics%22">Psychometrics</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+Patterns%22">Psychological Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Motivation%22">Student Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Personality+Traits%22">Personality Traits</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Strategies%22">Learning Strategies</searchLink><br /><searchLink fieldCode="DE" term="%22Demography%22">Demography</searchLink><br /><searchLink fieldCode="DE" term="%22Scores%22">Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+Background%22">Socioeconomic Background</searchLink><br /><searchLink fieldCode="DE" term="%22Undergraduate+Students%22">Undergraduate Students</searchLink><br /><searchLink fieldCode="DE" term="%22Construct+Validity%22">Construct Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Reliability%22">Test Reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Grades+%28Scholastic%29%22">Grades (Scholastic)</searchLink>
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  Data: 10.4018/IJICTE.2020100105
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  Data: 1550-1876
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Educational data mining provides various advantages to the education systems in many ways. It enhances the teaching process, the learning process, the scholastic performance of students, career selection, employability, and more. The differences in attitude of students' behavior lead to difference in their academic performance. The article covers the non-intellectual parameters of students to enhance their academic performance. The study tests the relationship between psychometric constructs of students and their academic correlate. The models for enhancing intellectual performance which involves various non-intellectual parameters are analyzed using structural equation modeling. It is observed that the values of the models were retrieved near to fit values. The results entail that the models will be beneficial for students in improving their academic performance by revising their psychological parameters.
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  Data: 2020
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  Data: EJ1268104
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1268104
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        Value: 10.4018/IJICTE.2020100105
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 68
    Subjects:
      – SubjectFull: Student Evaluation
        Type: general
      – SubjectFull: Psychometrics
        Type: general
      – SubjectFull: Academic Achievement
        Type: general
      – SubjectFull: Psychological Patterns
        Type: general
      – SubjectFull: Student Motivation
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      – SubjectFull: Personality Traits
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      – SubjectFull: Learning Strategies
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      – SubjectFull: Demography
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      – SubjectFull: Scores
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      – SubjectFull: Socioeconomic Background
        Type: general
      – SubjectFull: Undergraduate Students
        Type: general
      – SubjectFull: Construct Validity
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      – SubjectFull: Test Reliability
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      – SubjectFull: Grades (Scholastic)
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    Titles:
      – TitleFull: Student Performance Measurement on Psychometric Parameters
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            NameFull: Som, Subhranil
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            NameFull: Hossain, Syed Akhter
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            NameFull: Sharma, Mayank
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            – TitleFull: International Journal of Information and Communication Technology Education
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