Are online behavioural characteristics effective predictors of intrinsic motivation and user engagement in the online learning environment?
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| Title: | Are online behavioural characteristics effective predictors of intrinsic motivation and user engagement in the online learning environment? |
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| Authors: | Sun, Jerry Chih-Yuan1 jerrysun@nycu.edu.tw, Lin, Che-Tsun2, Chang, Wen-Li3 |
| Source: | Australasian Journal of Educational Technology. 2025, Vol. 41 Issue 6, p36-51. 16p. |
| Subject Terms: | *Intrinsic motivation, *Student engagement, *Instructional systems design, *Online education, *Digital learning, *Evaluation methodology, Data mining |
| Abstract: | This study aimed to investigate the predicted relationship among online behavioural characteristics, intrinsic motivation and user engagement. An online learning platform was used to collect data on the online reading time and the number of test attempts of 161 graduate students, as well as their post-learning motivation and user engagement levels. The data were processed based on the e-learning motivation and user engagement scales. The data structure was validated using structural equation modelling. The findings showed that online reading time positively predicts anxiety and negatively affects focused attention. A higher number of test attempts negatively affects effort expectancy, perceived usability, novelty, felt involvement and endurability, leading to reduced user interaction quality. The findings suggest designing online courses with multiple smaller units, each with controlled learning time. Implications for practice or policy: • Educators can integrate motivation and engagement measures with learning logs to better align instructional support with learners' psychological and behavioural patterns. • Instructional designers can apply learning analytics evidence to optimise platform features that strengthen learner motivation and sustained engagement. • Course designers should limit excessive online text reading and adopt multimodal materials to reduce anxiety and attention loss. • Assessment designers may need to limit repeated test attempts, as frequent retries are linked to lower perceived ease of use and adaptability. [ABSTRACT FROM AUTHOR] |
| Copyright of Australasian Journal of Educational Technology is the property of Australasian Journal of Educational Technology (AJET) 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 | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 190924775 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Are online behavioural characteristics effective predictors of intrinsic motivation and user engagement in the online learning environment? – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Sun%2C+Jerry+Chih-Yuan%22">Sun, Jerry Chih-Yuan</searchLink><relatesTo>1</relatesTo><i> jerrysun@nycu.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Lin%2C+Che-Tsun%22">Lin, Che-Tsun</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Chang%2C+Wen-Li%22">Chang, Wen-Li</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Australasian+Journal+of+Educational+Technology%22">Australasian Journal of Educational Technology</searchLink>. 2025, Vol. 41 Issue 6, p36-51. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Intrinsic+motivation%22">Intrinsic motivation</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+engagement%22">Student engagement</searchLink><br />*<searchLink fieldCode="DE" term="%22Instructional+systems+design%22">Instructional systems design</searchLink><br />*<searchLink fieldCode="DE" term="%22Online+education%22">Online education</searchLink><br />*<searchLink fieldCode="DE" term="%22Digital+learning%22">Digital learning</searchLink><br />*<searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study aimed to investigate the predicted relationship among online behavioural characteristics, intrinsic motivation and user engagement. An online learning platform was used to collect data on the online reading time and the number of test attempts of 161 graduate students, as well as their post-learning motivation and user engagement levels. The data were processed based on the e-learning motivation and user engagement scales. The data structure was validated using structural equation modelling. The findings showed that online reading time positively predicts anxiety and negatively affects focused attention. A higher number of test attempts negatively affects effort expectancy, perceived usability, novelty, felt involvement and endurability, leading to reduced user interaction quality. The findings suggest designing online courses with multiple smaller units, each with controlled learning time. Implications for practice or policy: • Educators can integrate motivation and engagement measures with learning logs to better align instructional support with learners' psychological and behavioural patterns. • Instructional designers can apply learning analytics evidence to optimise platform features that strengthen learner motivation and sustained engagement. • Course designers should limit excessive online text reading and adopt multimodal materials to reduce anxiety and attention loss. • Assessment designers may need to limit repeated test attempts, as frequent retries are linked to lower perceived ease of use and adaptability. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Australasian Journal of Educational Technology is the property of Australasian Journal of Educational Technology (AJET) 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=190924775 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 36 Subjects: – SubjectFull: Intrinsic motivation Type: general – SubjectFull: Student engagement Type: general – SubjectFull: Instructional systems design Type: general – SubjectFull: Online education Type: general – SubjectFull: Digital learning Type: general – SubjectFull: Evaluation methodology Type: general – SubjectFull: Data mining Type: general Titles: – TitleFull: Are online behavioural characteristics effective predictors of intrinsic motivation and user engagement in the online learning environment? Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Sun, Jerry Chih-Yuan – PersonEntity: Name: NameFull: Lin, Che-Tsun – PersonEntity: Name: NameFull: Chang, Wen-Li IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 14493098 Numbering: – Type: volume Value: 41 – Type: issue Value: 6 Titles: – TitleFull: Australasian Journal of Educational Technology Type: main |
| ResultId | 1 |
