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Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia

Learning analytics is the process of assessing, evaluating, and measuring student performance and the effectiveness of the teaching and learning process. This study investigates the relationship between three dimensions of learning analytics (summative, real-time, and predictive) and learning demog...

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Main Authors: Che Nawi, Nur Raihan, Omar, Muhd Khaizer, Sharef, Nurfadhlina Mohd, Azmi Murad, Masrah Azrifah, Mansor, Evi Indriasari, Nasharuddin, Nurul Amelina, Samian, Normalia, Arshad, Noreen Izza, Shahbodin, Faaizah, Marhaban, Mohammad Hamiruce
Format: Article
Language:English
Published: Human Resource Management Academic Research Society 2023
Online Access:http://eprints.utem.edu.my/id/eprint/27346/2/0047723122023.PDF
http://eprints.utem.edu.my/id/eprint/27346/
https://hrmars.com/papers_submitted/16961/correlation-between-students-expectations-and-demographic-characteristics-toward-features-of-learning-analytics-system-in-malaysia.pdf
http://dx.doi.org/10.6007/IJARPED/v12-i2/16961
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spelling my.utem.eprints.273462024-07-04T11:06:27Z http://eprints.utem.edu.my/id/eprint/27346/ Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia Che Nawi, Nur Raihan Omar, Muhd Khaizer Sharef, Nurfadhlina Mohd Azmi Murad, Masrah Azrifah Mansor, Evi Indriasari Nasharuddin, Nurul Amelina Samian, Normalia Arshad, Noreen Izza Shahbodin, Faaizah Marhaban, Mohammad Hamiruce Learning analytics is the process of assessing, evaluating, and measuring student performance and the effectiveness of the teaching and learning process. This study investigates the relationship between three dimensions of learning analytics (summative, real-time, and predictive) and learning demographic characteristics (age, gender, categories of students, current semester, field of study, credit hours are taken in the current semester and CGPA). Questionnaires were distributed to 350 students enrolled in various programs at a public university in Malaysia. The study found that demographic profiles of the respondents which include age, gender, types of students, credit hours taken, concern for achievement, learning preferences, and learning motivation significantly contributed to learning analytic features. Additionally, the study revealed a strong and positive direction of learning analytic features: summative, real-time, and predictive based on the Pearson Correlation report. To comprehensively enhance the learning experience, the study recommends an extensive study related to learner profiling that considers intrinsic and extrinsic value such as assistive technology, learning performance, and motivation. The implications for other stakeholders such as teachers, learners, curriculum developers, and policymakers can be significant, as they can use learner profiling information to develop personalized learning plans, provide targeted support, design effective learning materials, and make informed education policy and funding decisions. A comprehensive understating of learner profiling and learning analytics can have far-reaching implications for various stakeholders in the education system, potentially leading to more personalized, effective, and equitable learning experiences for all learners. Human Resource Management Academic Research Society 2023-05 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27346/2/0047723122023.PDF Che Nawi, Nur Raihan and Omar, Muhd Khaizer and Sharef, Nurfadhlina Mohd and Azmi Murad, Masrah Azrifah and Mansor, Evi Indriasari and Nasharuddin, Nurul Amelina and Samian, Normalia and Arshad, Noreen Izza and Shahbodin, Faaizah and Marhaban, Mohammad Hamiruce (2023) Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia. International Journal of Academic Research in Progressive Education and Development, 12 (2). pp. 1073-1096. ISSN 2226-6348 https://hrmars.com/papers_submitted/16961/correlation-between-students-expectations-and-demographic-characteristics-toward-features-of-learning-analytics-system-in-malaysia.pdf http://dx.doi.org/10.6007/IJARPED/v12-i2/16961
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Learning analytics is the process of assessing, evaluating, and measuring student performance and the effectiveness of the teaching and learning process. This study investigates the relationship between three dimensions of learning analytics (summative, real-time, and predictive) and learning demographic characteristics (age, gender, categories of students, current semester, field of study, credit hours are taken in the current semester and CGPA). Questionnaires were distributed to 350 students enrolled in various programs at a public university in Malaysia. The study found that demographic profiles of the respondents which include age, gender, types of students, credit hours taken, concern for achievement, learning preferences, and learning motivation significantly contributed to learning analytic features. Additionally, the study revealed a strong and positive direction of learning analytic features: summative, real-time, and predictive based on the Pearson Correlation report. To comprehensively enhance the learning experience, the study recommends an extensive study related to learner profiling that considers intrinsic and extrinsic value such as assistive technology, learning performance, and motivation. The implications for other stakeholders such as teachers, learners, curriculum developers, and policymakers can be significant, as they can use learner profiling information to develop personalized learning plans, provide targeted support, design effective learning materials, and make informed education policy and funding decisions. A comprehensive understating of learner profiling and learning analytics can have far-reaching implications for various stakeholders in the education system, potentially leading to more personalized, effective, and equitable learning experiences for all learners.
format Article
author Che Nawi, Nur Raihan
Omar, Muhd Khaizer
Sharef, Nurfadhlina Mohd
Azmi Murad, Masrah Azrifah
Mansor, Evi Indriasari
Nasharuddin, Nurul Amelina
Samian, Normalia
Arshad, Noreen Izza
Shahbodin, Faaizah
Marhaban, Mohammad Hamiruce
spellingShingle Che Nawi, Nur Raihan
Omar, Muhd Khaizer
Sharef, Nurfadhlina Mohd
Azmi Murad, Masrah Azrifah
Mansor, Evi Indriasari
Nasharuddin, Nurul Amelina
Samian, Normalia
Arshad, Noreen Izza
Shahbodin, Faaizah
Marhaban, Mohammad Hamiruce
Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia
author_facet Che Nawi, Nur Raihan
Omar, Muhd Khaizer
Sharef, Nurfadhlina Mohd
Azmi Murad, Masrah Azrifah
Mansor, Evi Indriasari
Nasharuddin, Nurul Amelina
Samian, Normalia
Arshad, Noreen Izza
Shahbodin, Faaizah
Marhaban, Mohammad Hamiruce
author_sort Che Nawi, Nur Raihan
title Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia
title_short Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia
title_full Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia
title_fullStr Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia
title_full_unstemmed Correlation between students expectations and demographic characteristics toward features of learning analytics system in Malaysia
title_sort correlation between students expectations and demographic characteristics toward features of learning analytics system in malaysia
publisher Human Resource Management Academic Research Society
publishDate 2023
url http://eprints.utem.edu.my/id/eprint/27346/2/0047723122023.PDF
http://eprints.utem.edu.my/id/eprint/27346/
https://hrmars.com/papers_submitted/16961/correlation-between-students-expectations-and-demographic-characteristics-toward-features-of-learning-analytics-system-in-malaysia.pdf
http://dx.doi.org/10.6007/IJARPED/v12-i2/16961
_version_ 1804070313779003392
score 13.211869

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