Student Performance Measurement on Psychometric Parameters
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| Title: | Student Performance Measurement on Psychometric Parameters |
|---|---|
| Language: | English |
| Authors: | Burman, Iti (ORCID |
| 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 |
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