Video learning analytics: Investigating behavioral patterns and learner clusters in video-based online learning.
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| Title: | Video learning analytics: Investigating behavioral patterns and learner clusters in video-based online learning. |
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| Authors: | Yoon, Meehyun1 (AUTHOR) myoon1@ewha.ac.kr, Lee, Jungeun2 (AUTHOR) jungeunjoan.lee@gmail.com, Jo, Il-Hyun1 (AUTHOR) ijo@ewha.ac.kr |
| Source: | Internet & Higher Education. Jun2021, Vol. 50, pN.PAG-N.PAG. 1p. |
| Subject Terms: | *Online education, *Information-seeking behavior, *Instructional systems design, *Digital learning, Videos, Social interaction |
| Abstract: | Video-based online learning is becoming commonplace in higher education settings. Prior studies have suggested design principles and instructional strategies to boost video-based learning. However, little research has been done on different learner characteristics, such as how learners behave, what behavioral patterns they exhibit, and how different they are from each other. To fill this research gap in student-video interaction, we employed learning analytics to obtain useful insights into students' learning in the context of video-based online learning. From 11 log behaviors represented by log data from 72 college students, four behavioral patterns were identified while students learned from videos: browsing, social interaction, information seeking, and environment configuration. Based on the behavioral patterns observed, participants were classified into two clusters. Participants in the active learner cluster exhibited frequent use of social interaction, information seeking, and environment configuration, while participants in the passive learner cluster exhibited only frequent browsing. We found that active learners exhibited higher learning achievement than passive learners. • An understanding of learner behavioral patterns is critical to improving video-based learning environments. • We employed learning analytics to obtain insights into students' behavioral patterns in video-based learning. • We identified four behavioral patterns: browsing, social interaction, information seeking, and environment configuration. • The active learner cluster engaged in social activities, information seeking, and environment configuration. • The passive learner cluster only engaged in browsing. • We found that active learners demonstrated better achievement than the passive learners. [ABSTRACT FROM AUTHOR] |
| Copyright of Internet & Higher Education is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 150875402 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Video learning analytics: Investigating behavioral patterns and learner clusters in video-based online learning. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yoon%2C+Meehyun%22">Yoon, Meehyun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> myoon1@ewha.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Lee%2C+Jungeun%22">Lee, Jungeun</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jungeunjoan.lee@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Jo%2C+Il-Hyun%22">Jo, Il-Hyun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ijo@ewha.ac.kr</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Internet+%26+Higher+Education%22">Internet & Higher Education</searchLink>. Jun2021, Vol. 50, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Online+education%22">Online education</searchLink><br />*<searchLink fieldCode="DE" term="%22Information-seeking+behavior%22">Information-seeking behavior</searchLink><br />*<searchLink fieldCode="DE" term="%22Instructional+systems+design%22">Instructional systems design</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+learning%22">Digital learning</searchLink><br /><searchLink fieldCode="DE" term="%22Videos%22">Videos</searchLink><br /><searchLink fieldCode="DE" term="%22Social+interaction%22">Social interaction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Video-based online learning is becoming commonplace in higher education settings. Prior studies have suggested design principles and instructional strategies to boost video-based learning. However, little research has been done on different learner characteristics, such as how learners behave, what behavioral patterns they exhibit, and how different they are from each other. To fill this research gap in student-video interaction, we employed learning analytics to obtain useful insights into students' learning in the context of video-based online learning. From 11 log behaviors represented by log data from 72 college students, four behavioral patterns were identified while students learned from videos: browsing, social interaction, information seeking, and environment configuration. Based on the behavioral patterns observed, participants were classified into two clusters. Participants in the active learner cluster exhibited frequent use of social interaction, information seeking, and environment configuration, while participants in the passive learner cluster exhibited only frequent browsing. We found that active learners exhibited higher learning achievement than passive learners. • An understanding of learner behavioral patterns is critical to improving video-based learning environments. • We employed learning analytics to obtain insights into students' behavioral patterns in video-based learning. • We identified four behavioral patterns: browsing, social interaction, information seeking, and environment configuration. • The active learner cluster engaged in social activities, information seeking, and environment configuration. • The passive learner cluster only engaged in browsing. • We found that active learners demonstrated better achievement than the passive learners. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Internet & Higher Education is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=150875402 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.iheduc.2021.100806 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Online education Type: general – SubjectFull: Information-seeking behavior Type: general – SubjectFull: Instructional systems design Type: general – SubjectFull: Digital learning Type: general – SubjectFull: Videos Type: general – SubjectFull: Social interaction Type: general Titles: – TitleFull: Video learning analytics: Investigating behavioral patterns and learner clusters in video-based online learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yoon, Meehyun – PersonEntity: Name: NameFull: Lee, Jungeun – PersonEntity: Name: NameFull: Jo, Il-Hyun IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 10967516 Numbering: – Type: volume Value: 50 Titles: – TitleFull: Internet & Higher Education Type: main |
| ResultId | 1 |
