E-learning, assessment competency, and academic performance: A structural equation modeling approach

E-learning practices and the competency in assessment should facilitate one’s academic performance. The main purpose of this study is to explore the degree of influence of e-learning practices and competency in assessment on academic achievement of students. This study is a quantitative approach usi...

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Main Authors: Nor Hasnida Chemdghazali, Zahari Suppian, Hishamuddin Ahmad, Syaza Hazwani Zaini, Tajul Rosli Shuib
Format: Article
Language:English
Published: Universitas Negeri Yogyakarta 2024-05-01
Series:Cakrawala Pendidikan: Jurnal Ilmiah Pendidikan
Subjects:
Online Access:http://journal.uny.ac.id/index.php/cp/article/view/63622
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author Nor Hasnida Chemdghazali
Zahari Suppian
Hishamuddin Ahmad
Syaza Hazwani Zaini
Tajul Rosli Shuib
author_facet Nor Hasnida Chemdghazali
Zahari Suppian
Hishamuddin Ahmad
Syaza Hazwani Zaini
Tajul Rosli Shuib
author_sort Nor Hasnida Chemdghazali
collection DOAJ
description E-learning practices and the competency in assessment should facilitate one’s academic performance. The main purpose of this study is to explore the degree of influence of e-learning practices and competency in assessment on academic achievement of students. This study is a quantitative approach using survey method involving the process of data collection through the administration of constructed instruments. The population of the study involves student teachers from the three selected universities in Selangor and Perak. Sample selection is drawn using random sampling technique. A total of 460 student teachers are selected. The questionnaire for e-learning practices is adapted from OLES (Renee, 2011) and the competency in assessment comes from Zahari (2018). The structural equation modeling (SEM) analysis is used to test the hypothesized relationship. The results show that e-learning practices, knowledge in assessment, skills in assessing, and attitude in assessment significantly influence students’ academic achievement. E-learning practices emerge as the strongest predictor of student achievement, with a significant standardized regression coefficient of 0.39. This is followed by skills in assessing (0.27), knowledge in assessment (0.09), and lastly attitude in assessment (0.08). The core findings of the study have some implications for higher education and practice, measurement and theory development, and future research.
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issn 0216-1370
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language English
publishDate 2024-05-01
publisher Universitas Negeri Yogyakarta
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series Cakrawala Pendidikan: Jurnal Ilmiah Pendidikan
spelling doaj-art-dc432ec7afbc4a0f964cc6cc19b4727f2025-08-20T02:38:18ZengUniversitas Negeri YogyakartaCakrawala Pendidikan: Jurnal Ilmiah Pendidikan0216-13702442-86202024-05-0143228829510.21831/cp.v43i2.6362219902E-learning, assessment competency, and academic performance: A structural equation modeling approachNor Hasnida Chemdghazali0Zahari Suppian1Hishamuddin Ahmad2Syaza Hazwani Zaini3Tajul Rosli Shuib4Universiti Pendidikan Sultan IdrisUniversiti Pendidikan Sultan IdrisUniversiti Pendidikan Sultan IdrisUniversiti Pendidikan Sultan IdrisUniversiti Pendidikan Sultan IdrisE-learning practices and the competency in assessment should facilitate one’s academic performance. The main purpose of this study is to explore the degree of influence of e-learning practices and competency in assessment on academic achievement of students. This study is a quantitative approach using survey method involving the process of data collection through the administration of constructed instruments. The population of the study involves student teachers from the three selected universities in Selangor and Perak. Sample selection is drawn using random sampling technique. A total of 460 student teachers are selected. The questionnaire for e-learning practices is adapted from OLES (Renee, 2011) and the competency in assessment comes from Zahari (2018). The structural equation modeling (SEM) analysis is used to test the hypothesized relationship. The results show that e-learning practices, knowledge in assessment, skills in assessing, and attitude in assessment significantly influence students’ academic achievement. E-learning practices emerge as the strongest predictor of student achievement, with a significant standardized regression coefficient of 0.39. This is followed by skills in assessing (0.27), knowledge in assessment (0.09), and lastly attitude in assessment (0.08). The core findings of the study have some implications for higher education and practice, measurement and theory development, and future research.http://journal.uny.ac.id/index.php/cp/article/view/63622e-learningassessment competencyacademic performancestructural equation model
spellingShingle Nor Hasnida Chemdghazali
Zahari Suppian
Hishamuddin Ahmad
Syaza Hazwani Zaini
Tajul Rosli Shuib
E-learning, assessment competency, and academic performance: A structural equation modeling approach
Cakrawala Pendidikan: Jurnal Ilmiah Pendidikan
e-learning
assessment competency
academic performance
structural equation model
title E-learning, assessment competency, and academic performance: A structural equation modeling approach
title_full E-learning, assessment competency, and academic performance: A structural equation modeling approach
title_fullStr E-learning, assessment competency, and academic performance: A structural equation modeling approach
title_full_unstemmed E-learning, assessment competency, and academic performance: A structural equation modeling approach
title_short E-learning, assessment competency, and academic performance: A structural equation modeling approach
title_sort e learning assessment competency and academic performance a structural equation modeling approach
topic e-learning
assessment competency
academic performance
structural equation model
url http://journal.uny.ac.id/index.php/cp/article/view/63622
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AT hishamuddinahmad elearningassessmentcompetencyandacademicperformanceastructuralequationmodelingapproach
AT syazahazwanizaini elearningassessmentcompetencyandacademicperformanceastructuralequationmodelingapproach
AT tajulroslishuib elearningassessmentcompetencyandacademicperformanceastructuralequationmodelingapproach