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1860797953717829632
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INTELEK Repository
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COMPUTING
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Online Access
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https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2024-08-28 15:38:29
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Restricted Document
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15070
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UniSZA
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4763-01-FH05-FIK-21-51589.pdf
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Mukta Goyal
Rajalakshmi Krishnamurthi and Divakar Yadav
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oai_dc
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https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15070
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15070 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15070 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Book Chapter application/pdf Adobe Acrobat Pro DC 20 Paper Capture Plug-in with ClearScan 1.7 Mukta Goyal Rajalakshmi Krishnamurthi and Divakar Yadav 2024-08-28 15:38:29 COMPUTING 260 COMPUTING 4763-01-FH05-FIK-21-51589.pdf UniSZA Private Access CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model The student centred learning is one of the e-learning service factors in universities and schools that have been improved with added values. Now, students can access the e-learning platform on a cloud server with their mobile devices. Several ways and practices in e-learning today include learning management systems (LMS), blended learning, microlearning, mobile learning, open learning, selflearning, and virtual learning. Microlearning refers to the micro perspective in learning contact, education, and exercise. Student engagement is one of the key indicators of a successful implementation of e-learning. Those studies were carried out based on the educational data mining technique, which is widely used in analysing the various patterns of online learning behaviour and predicting learning outcomes. Another popular technique that uses a similar approach but with different focus is learning analytics. © The Institution of Engineering and Technology 2021. Institution of Engineering & Technology (IET) United Kingdom Institution of Engineering & Technology (IET) 53-78 E-learning Methodologies: Fundamentals, technologies and applications
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| spellingShingle |
CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model
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| subject |
COMPUTING
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| summary |
The student centred learning is one of the e-learning service factors in universities and schools that have been improved with added values. Now, students can access the e-learning platform on a cloud server with their mobile devices. Several ways and practices in e-learning today include learning management systems (LMS), blended learning, microlearning, mobile learning, open learning, selflearning, and virtual learning. Microlearning refers to the micro perspective in learning contact, education, and exercise. Student engagement is one of the key indicators of a successful implementation of e-learning. Those studies were carried out based on the educational data mining technique, which is widely used in analysing the various patterns of online learning behaviour and predicting learning outcomes. Another popular technique that uses a similar approach but with different focus is learning analytics. © The Institution of Engineering and Technology 2021.
|
| title |
CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model
|
| title_full |
CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model
|
| title_fullStr |
CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model
|
| title_full_unstemmed |
CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model
|
| title_short |
CHAPTER 3 : Predicting students’ behavioural engagement in microlearning using learning analytics model
|
| title_sort |
chapter 3 : predicting students’ behavioural engagement in microlearning using learning analytics model
|