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Extracting the Relationships Among Students Based on Accessing Pattern of Digital Learning Attributes

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Title: Extracting the Relationships Among Students Based on Accessing Pattern of Digital Learning Attributes
Language: English
Authors: Muhuri, Samya (ORCID 0000-0003-3426-3741), Mukhopadhyay, Debajyoti (ORCID 0000-0002-8071-4091)
Source: IEEE Transactions on Learning Technologies. Dec 2022 15(6):747-756.
Availability: Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076
Peer Reviewed: Y
Page Count: 10
Publication Date: 2022
Document Type: Journal Articles
Reports - Research
Descriptors: Students, Online Courses, Social Networks, Interpersonal Relationship, Peer Relationship, Learning Processes, Behavior Patterns, Educational Technology, Digital Literacy, Educational Resources
DOI: 10.1109/TLT.2022.3166537
ISSN: 1939-1382
Abstract: A paradigm shift can be expected in the education sector, especially after the COVID-19 pandemic. E-learning systems are being adopted by all the stakeholders as physical meetings are not feasible. Different online learning attributes, such as video conferencing tools, coding platforms, online learning frameworks, digital books, and online videos, are available, which are enhancing the traditional learning methodology. Now, the main challenge for the educationists is to identify how these attributes are utilized by the learners. In this article, we have represented any online class as a social network where students are connected through learning platforms. We have mined the network based on several network measuring parameters to recognize the maneuvering pattern of these digital resources or attributes by the students. We have also proposed a community detection method that would form different groups among the students based on their comfortable learning patterns. As a case study, we have scrutinized the accessing patterns of different digital learning resources by some particular students. The experimental results show the significant relationship between the digital resource accessing patterns of the students with their immediate performance in the test. The satisfactory inquisitive results of our approach would definitely inspire the researchers of interdisciplinary areas to probe further in this domain.
Abstractor: As Provided
Entry Date: 2022
Accession Number: EJ1359997
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Muhuri%2C+Samya%22">Muhuri, Samya</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3426-3741">0000-0003-3426-3741</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mukhopadhyay%2C+Debajyoti%22">Mukhopadhyay, Debajyoti</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8071-4091">0000-0002-8071-4091</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22IEEE+Transactions+on+Learning+Technologies%22"><i>IEEE Transactions on Learning Technologies</i></searchLink>. Dec 2022 15(6):747-756.
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  Data: Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076
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  Data: 10.1109/TLT.2022.3166537
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  Data: A paradigm shift can be expected in the education sector, especially after the COVID-19 pandemic. E-learning systems are being adopted by all the stakeholders as physical meetings are not feasible. Different online learning attributes, such as video conferencing tools, coding platforms, online learning frameworks, digital books, and online videos, are available, which are enhancing the traditional learning methodology. Now, the main challenge for the educationists is to identify how these attributes are utilized by the learners. In this article, we have represented any online class as a social network where students are connected through learning platforms. We have mined the network based on several network measuring parameters to recognize the maneuvering pattern of these digital resources or attributes by the students. We have also proposed a community detection method that would form different groups among the students based on their comfortable learning patterns. As a case study, we have scrutinized the accessing patterns of different digital learning resources by some particular students. The experimental results show the significant relationship between the digital resource accessing patterns of the students with their immediate performance in the test. The satisfactory inquisitive results of our approach would definitely inspire the researchers of interdisciplinary areas to probe further in this domain.
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      – SubjectFull: Social Networks
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